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Background:
Systematic Review

The Effect of Sex on the Therapeutic Efficiency of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials

by
Xingyu Zhong
†,
Jianxuan Sun
†,
Na Zeng
,
Yifan Xiong
,
Ye An
,
Shaogang Wang
* and
Qidong Xia
*
Department and Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1095 Jiefang Avenue, Wuhan 430030, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2024, 16(2), 382; https://doi.org/10.3390/cancers16020382
Submission received: 8 December 2023 / Revised: 11 January 2024 / Accepted: 13 January 2024 / Published: 16 January 2024
(This article belongs to the Special Issue Sex Differences in Cancer)
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Abstract

:

Simple Summary

Sex is an important variable that can affect immunity, both in the cellular and humoral sense. This may result from differences in genes, hormones, the environment, and commensal microbiome composition. Although some researchers have investigated the relationship between the efficacy of immunotherapy and sex, their conclusions are contradictory. Based on immune checkpoint inhibitors (ICI) in cancer, we conducted an updated systematic review and meta-analysis to explore whether sex has an impact on the efficacy of immunotherapy. A total of 103 articles of randomized controlled trials were retrieved from the bibliographic database. The results show that both male and female patients treated with ICI showed a lower risk of death than control subjects, with females achieving smaller gains (p = 0.02). And in the PD-1 subgroup, male patients showed a better response to ICI (p = 0.0073). We found that sex is a factor affecting the efficacy of ICI, and that males were more likely to benefit from ICI treatment.

Abstract

Background: Sex is an important factor influencing the immune system, and the distribution of tumors, including their types and subtypes, is characterized by sexual dichotomy. The aim of this study was to investigate whether there is an association between sex and the treatment effect of immune checkpoint inhibitors (ICI). Methods: Four bibliographic databases were searched. Studies of randomized controlled trials (RCTs) assessing the efficacy of ICI were identified and used, and the primary endpoint was the difference in efficacy of ICI between males and females, presented as overall survival (OS), progression-free survival (PFS) and recurrence-free survival (RFS). The study calculated the pooled HRs and 95% CIs for OS, PFS and RFS for males and females using a random effects model or a fixed effects model, and thereby assessed the effect of sex on the efficacy of ICI treatment. This study is registered with PROSPERO (CRD42022370939). Results: A total of 103 articles, including a total of 63,755 patients with cancer, were retrieved from the bibliographic database, of which approximately 70% were males. In studies with OS as the outcome, the combined hazard ratio (HR) was 0.77 (95% CI 0.74–0.79) for male patients treated with ICI and 0.81 (95% CI 0.78–0.85) for female patients compared to controls, respectively. The difference in efficacy between males and females was significant. Conclusions: ICI therapy, under suitable conditions for its use, has a positive impact on survival in various types of tumors, and male patients benefit more than females. It may be necessary to develop different tumor immunotherapy strategies for patients of different sexes.

1. Introduction

Intersexual differences often manifest as differences in sex chromosomes and hormone levels between men and women, and this difference often leads to distinct immune responses between males and females. According to reports, females show stronger immune responses in most cases compared to males [1,2]. This distinction is evident in the observation that women are more susceptible to autoimmune diseases, while being less susceptible to infectious diseases [3,4]. Regarding cancer, males generally have a higher risk of developing cancer compared to females [5]. Additionally, certain cancer types, such as lung cancer, demonstrate a higher mortality rate among males. Various factors can contribute to this disparity, including distinct lifestyles between males and females. Moreover, it is crucial to acknowledge the differences in the immune systems of males and females as an influencing factor.
Immunotherapy, represented by immune checkpoint inhibitors (ICI), has introduced a novel approach to cancer treatment. ICI primarily encompass anti-PD-1 antibodies, anti-PD-L1 antibodies and anti-CTLA-4 antibodies. These agents function by impeding the PD-1-PD-L1 or the CTLA-4 signaling pathway between tumor cells and immune cells, thereby inhibiting immune evasion by tumors [6]. The fundamental objective of ICI therapy is to bolster the body’s immune response, resulting in reduced harm to normal tissues compared to conventional chemotherapy, as well as improved therapeutic efficacy in certain cases [7].
Despite the considerable advantages of ICI treatment in antitumor therapy, a majority of patients do not respond favorably to it [8]. Therefore, it is imperative to investigate the factors influencing the efficacy of ICI therapy. Additionally, considering that females generally exhibit superior immune strength compared to males in the absence of intervention, the impact of ICI therapy in enhancing antitumor immune responses may be relatively less pronounced in females than in males. This difference in response between males and females may contribute to variations in the efficacy of ICI therapy. However, previous studies have inadequately considered the influence of sex differences on ICI efficacy, and the limited availability of data regarding female patients may lead to erroneous conclusions, as most studies have been predominantly conducted on males. Fortunately, there has been a recent increase in the number of clinical trials investigating ICI therapies, which have provided supplementary data on relevant sex differences. Therefore, in this study, we conducted a systematic review and meta-analysis of randomized controlled clinical studies to evaluate the impact of sex on the efficacy of ICI therapy.

2. Materials and Methods

2.1. Selection Criteria

The inclusion and exclusion criteria were as follows: (1) the type of studies were phase II/III clinical trials and RCTs; (2) the subjects were treated with PD-1, PD-L1 or CTLA-4, or combinations of them; (3) the outcome of interest was HR for survival outcome, including overall survival (OS), progression-free survival (PFS) and recurrence-free survival (RFS); (4) the studies included only the most recent patient dataset reported in different articles; (5) studies without data analyzed according to sex were excluded; (6) studies with no full text or lacking valuable data, including numbers of patients (categorized by sex), treatment phase, treatment of controls, interventions and HR of survival outcomes, were excluded.

2.2. Search Strategy

This study was conducted according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 reporting guidelines (Supplementary Materials Table S1) [9]. Four bibliographic databases, namely PubMed (Medline), EMBASE, Cochrane Library and Web of Science, were searched for studies assessing the relationship between sex and ICI treatment outcomes, from initiation to 28 November 2023. Conference abstracts were also included. The databases were searched using keywords such as “Immune Checkpoint Inhibitors”, “PD-1 “, “PD-L1”, “CTLA-4”, “Neoplasms” and “Cancers”. Detailed search strategies in the different databases are described in Supplementary Materials Tables S2–S5. Two reviewers, Z.X. and S.J., searched abstracts during the screening procedure and selected them according to the search criteria. Differences regarding inclusion or exclusion were resolved by consensus by the third author (Z. N.), and the Endnote application (version X9) was used to remove duplicates and apply inclusion criteria. The PRISMA flowchart in Figure 1 was used to describe the literature search process. This systematic review and meta-analysis study is registered with PROSPERO (CRD42022370939).

2.3. Data Extraction

This research used a designed data extraction form to extract information from the included studies. The data extraction form consists of bibliographic information and background information. The bibliographic information includes the name of the author, year of publication, journal name and title. The background information contains the region of the study conducted, age, number of male/female patients and order of treatment (whether it was first-line or not). In addition, the background information also includes tumor type, type of ICI, and mean follow-up time. The detailed characteristics of the articles included in this study are shown in Table 1. The outcomes of interest were the survival outcomes of patients, including OS, PFS and RFS, males and females separately.

2.4. Literature Quality Assessment

All of the included studies used the modified Jadad scale [113] to evaluate the quality of trials in four dimensions (Supplementary Materials Table S6). A study with a total score of 1–3 was considered as low-quality literature, and 4–7 as high-quality literature. Two researchers, X. Y. F. and Z. N., performed the risk of bias and literature quality assessment, and discrepancies were resolved by consensus with the third researcher, A. Y.

2.5. Data Synthesis and Statistical Analysis

In this study, the effectiveness of ICI in patients with cancer was evaluated using a random effects (RE) model or a fixed effects (FE) model [114], on the basis of different survival outcome (OS, PFS and RFS) classifications. Then, the relationship between ICI and survival outcomes was further evaluated in patients of different sexes, and 95% CIs were calculated to assess the relationship between sex and ICI treatment effects. The heterogeneity between studies was also analyzed using the standard Cochrane chi-square χ2 (Cochrane’s Q) test with a significance level of α = 0.10, as well as the I2 test [115]. The I2 test describes the percentage of variation between studies, and an I2 statistic of ≥50% indicates considerable heterogeneity [116]. Subgroup analysis stratified by parameters such as tumor types and category of ICI was performed to identify potential sources of heterogeneity. The study also performed a meta-regression, using parameters such as age and follow-up duration, which could be potential confounding factors across the studies. Begg’s [117] and Egger’s [118] tests were used to identify publication bias. Using contour-enhanced funnel plots, other causes of publication bias were identified by examining the symmetry of the funnel plots. Finally, the study carried out sensitivity analysis and cumulative meta-analysis by incrementally adding or omitting included studies, and also applied trim-and-fill methods to assess the effect of publication bias [119]. This study used the “meta” package [120] and the “metagen” command [121] of R software version 4.2.0 for data processing and statistical analysis. All p values were two-sided, and p < 0.05 was considered a significant difference.

3. Results

This study retrieved 66,582 publications from electronic databases and other sources. However, after applying the inclusion and exclusion criteria (shown in Figure 1), 66,479 articles were excluded, and 103 articles were included in this systematic review and meta-analysis study. Of the 66,479 excluded articles, 30,971 duplicates were removed using the automated tool in the Endnote application, and 5973 were removed using manual identification by reviewers. Furthermore, after reading the titles and abstracts, 26,055 articles were removed, and 581 articles were excluded for lack of full text or raw data. After reading the full text, 1505 case reports, 458 retrospective studies and 323 non-RCT prospective studies were excluded. Ultimately, 188 articles were removed for not including ICI intervention, and another 425 articles were removed for lacking sex subgroup analyses.

3.1. Characteristics of Included Studies and Patients

The characteristics of the 103 articles included in this study are shown in Table 1. All 103 articles were analyses of data from phase 2/3 clinical studies, and the outcomes of interest included OS, PFS and RFS in patients treated with ICI, which corresponded to 77, 33 and 12 articles, respectively. All but 21 studies were conducted in a single country, and the remaining studies involved multiple countries with a cumulative scope of Europe, North America, Asia, Africa and Oceania (Figure 2). There were 63,755 cancer patients, and the number of patients in each study ranged from 61 to 1764. There were 76 studies that included follow-up information, with an average follow-up time ranging from 5 months to 7 years (Table 1).
In these studies, the average age of the patients was over 60 years, and the proportion of male patients was approximately 70%. A review of the literature found that more than sixty percent of the studies revealed that males showed better outcomes after ICI treatment, but nearly forty percent still provided the contrary conclusion. Meanwhile, anti-PD-1 and anti-PD-L1 antibodies were the most commonly used ICI treatment, and lung cancer emerged as the most preferred ICI treatment candidate among all tumor types.

3.2. Quality Assessment of the Included Studies

The Jadad assessment criteria were used to assess the quality of RCT studies in this study, as shown in Supplementary Materials Table S6. All of the experiments were conducted via random assignment. The use of the Jadad criteria indicated that all of the articles included in this study were of high or moderate quality.

3.3. Effect of Sex on OS after ICI Treatment

Of all the trials with OS as an outcome, 41 used anti-PD-1 therapy, 20 used anti-PD-L1 therapy, 8 used anti-CTLA-4 antibodies and the other 10 used a combination of anti-PD-1/PD-L1 and anti-CTLA-4 therapy.
Among male patients, those treated with ICI showed a lower risk of death than those in the control group (pooled overall survival HR 0.77, 95% CI 0.74–0.79) (Figure 3). The cumulative meta-analysis in Figure S1A and sensitivity analysis in Figure S1B showed a relatively stable result. This study used Egger’s test to identify publication bias. Both Egger’s test (t = −3.16 and p-value = 0.0022) and Begg’s test (z = −3.06, p-value = 0.0022) results indicated significant publication bias.
Similarly, female patients treated with ICI also benefited, but with smaller gains compared to male patients (pooled overall survival HR 0.81, 95% CI 0.78–0.85) (Figure 3). The cumulative meta-analysis in Figure S2A and sensitivity analysis in Figure S2B showed a relatively stable result. This study used Egger’s test to identify publication bias. Both Egger’s test (t = −0.37, p-value = 0.716) and Begg’s test (z = −1.07, p-value = 0.283) results indicated no significant publication bias.
Overall, a certain amount of heterogeneity existed between studies (I2 = 35%, p < 0.01). Comparing the differences between men and women on the effect of ICI treatment in terms of improvement in OS was more pronounced in male patients with ICI treatment (p = 0.02). An interactional HR analysis of men and women showed that the ICI intervention group exhibited a lower risk of death than the control group (HR 0.78, 95% CI 0.76–0.80) (Figure S3).
A subgroup analysis was performed according to different tumor types and ICI drug types (Figure 4). Notably, in the PD-1 subgroup, male patients showed a better response to ICI treatment than female patients. However, in other drug types, this difference was not statistically significant. It is also noteworthy that the combination treatment modality of PD-1 with CTLA-4 was not significantly distinct between males and females. The difference in efficacy between sexes was also not significant in different tumor types. Additionally, we performed regression analyses on variables such as age and follow-up time, and the results showed that they were not associated with ICI efficacy in both males and females (Figure S4).

3.4. Effect of Sex on PFS and RFS after ICI Treatment

Besides OS, 33 and 12 studies used PFS and RFS as the survival outcome, respectively (Figures S5 and S6). We found ICI treatment improved survival outcomes of patients with cancer compared to controls, both in male patients (PFS: HR 0.63, 95% CI 0.58–0.69; RFS: HR 0.76, 95% CI 0.70–0.82) and female patients (PFS: HR 0.71, 95% CI 0.64–0.80; RFS: HR 0.74, 95% CI 0.67–0.82). The cumulative meta-analysis in Figures S7A,B and S8A,B and sensitivity analysis in Figures S7C,D and S8C,D showed relatively stable results. In contrast to OS, there was no significant difference between males and females in the efficacy of ICI treatment in terms of PFS (p = 0.10) and RFS (p = 0.79). In an interactional analysis of the sexes, ICI treatment improved the quality of survival of cancer patients more than controls (PFS: HR 0.66, 95% CI 0.62–0.71; RFS: HR 0.75, 95% CI 0.71–0.80), but there was higher heterogeneity between articles (PFS: I2 = 66%, p < 0.01; RFS: I2 = 45%, p < 0.01). Regression analysis for age and follow-up time showed absolutely no significant results (Figures S9 and S10).

4. Discussion

To the best of our knowledge, this study represents the most recent and comprehensive investigation into the impact of sex on ICI treatment outcomes. Fabio Conforti et al. [122] conducted the first meta-analysis of sex and ICI treatment effects in 2018, and found that males benefited more from ICI treatment than females. However, another study conducted by Fang Yang et al. [123] in 2020 came to a different conclusion, where there was no significant difference in the effect of ICI treatment between males and females. In a subsequent study, Li-Ting Lai et al. [19] also found no difference in results between the sexes. These conflicting findings impede a comprehensive understanding of the association between sex and ICI therapy. Nevertheless, it is worth noting that these studies only incorporated results from 20, 32 and 39 studies, respectively, consequently limiting the reliability of the conclusions drawn. Fortunately, with the abundance of recent clinical trials focusing on ICI drugs, we obtained more up-to-date trial data and incorporated them into our study for an updated meta-analysis. Hence, in this study, we analyzed 103 randomized controlled studies covering 66,582 study subjects.
The results of this study suggest that ICI therapy is an effective intervention with better efficacy than control treatment (conventional chemotherapy) for a wide range of tumor types. Among the results, males are more likely to benefit from ICI therapy than females, especially for anti-PD-1 types, as demonstrated by males exhibiting a lower risk of death (namely a better OS outcome). The results of this study are consistent with those of Fabio Conforti et al. [122].
The global increase in the burden of tumors poses a serious challenge to the health care system. Epidemiological analyses of tumors have identified sex differences as one of the factors influencing tumor incidence and mortality [124,125]; therefore, attempts have been made to explore the intrinsic associations between sex and tumors from different perspectives. Some researchers have analyzed these associations from a genetic aspect, starting from germline DNA or sex-dependent somatic mutations, in order to find possible oncogenic factors [126]. Also, differences in hormonal and immune systems between the sexes are thought to be closely related to tumor development. Many key immune-related genes are located on the X chromosome, thus innately determining that females have a stronger immune system to deal with the tumor challenge [1,127]. In addition, behavioral factors that differ between males and females in later life should also be included in assessments of the impact of tumors.
Immunotherapy that utilizes the body’s own immune system against cancer cells is an emerging field in oncology treatment. In particular, ICI therapies developed to address the immune escape mechanism of tumors are being used on a large scale in clinical practice. However, ICI therapy is not effective for all tumor patients, and requires consideration of the patient’s own condition. As a result of the influence of sex on the differences between the immune systems of males and females, it is readily thought that this may be an influential factor in the efficacy of ICI. As mentioned earlier, different studies on the relationship between sex and ICI efficacy have yielded conflicting results, leading to a lack of uniform understanding of whether it affects ICI efficacy.
Based on the results of our study on OS outcomes, males were more able to benefit from ICI treatment than females. This finding can be explained in terms of the following aspects. Firstly, since females tend to show stronger antitumor immunity than males [128], enhancing the immune system response via ICI therapy is less pronounced in females, which in turn manifests as a weaker response to ICI therapy than males. A recent study confirmed in mice that females show a stronger antitumor immune effect than males, and after treatment with ICI, male T-cell responses grew stronger, with a change that was greater than in females [129]. Secondly, there are differences between the sexes in the expressions of ICI-related receptors, such as PD-1 [130,131]. PD-1 is an immunosuppressive molecule. It has been shown that female tumor patients have higher serum and CD4+ T-cell membrane levels of PD-1 than males. Even though some studies have found sex differences in the efficacy of ICI in patients with equally high PD-1 expression [132], the effect of receptor expression differences between males and females can still not be excluded. It is worth noting that Xiangnan Guan et al. [133] recently identified androgen receptor (AR) as an essential element affecting the reactivity of prostate cancer patients to ICI therapy, and revealed the mechanism by which AR modulates antitumor immunity by regulating IFNγ activity. Combined PD-1 blockade and AR inhibition may result in better tumor suppression [133]. AR signaling has previously been identified as an important contributor to prostate cancer development, and AR blockade therapies have been widely used as an essential component of prostate cancer-targeted therapies [134]. The new study seems to provide a new insight into AR-targeted therapy from an immunological perspective, which is a win–win event for both prostate cancer treatment and tumor immunotherapy. Meanwhile, ChaoYang et al. [135] found that androgen receptor expression may be a potential factor contributing to sex differences in tumors. Through in vivo experiments and analysis of human samples, AR signaling was suggested to affect the activity of tumor-infiltrating CD8+ T cells, resulting in men exhibiting lower antitumor immune activity. When silencing the expression of the AR gene, the activity of CD8+ T cells was restored in male mice without similar changes in females. This result suggests that the level of AR is an important contributor to sex differences in antitumor immunity. Consistently, Hyunwoo Kwon et al. [136] also suggested that AR modulates the immune activity of CD8+ T cells in the tumor microenvironment, and leads to differences in tumor characteristics between males and females. Together, these studies uncover AR as a sex-differentiated tumor regulator that modulates antitumor immune activity. Also, the differences between sexes in tumor mutation burden [137], as well as exposure factors that differ later in life, lead to a stronger tumor mutation threat in males, which indirectly affects the therapeutic efficacy of ICI [138]. Meanwhile, a number of recent studies have focused on the effects of pregnancy on antitumor immunity. There have been reported promotive effects of pregnancy on regulatory immunity [139], and similar effects may persist long after pregnancy [140]. Fetal–maternal microchimerism and immune memory for shared cancer trophoblast antigens may be potential mechanisms of the effect [141]. In addition, we speculate that differences in the microbial environment between males and females may be an influential factor to be considered [142,143], although more adequate evidence is still needed to demonstrate the relationship between the two.
Different ICI drugs may influence the efficacy of treatment between the sexes. The effect of PD-1 treatment shows a more significant sex disparity than other treatment modalities. This finding differs from the findings of Yingcheng Wu et al. [144] and Antonino Grassadonia et al. [145], who found that CTLA-4 showed greater gender differences in efficacy than PD-1. This may be influenced by both tumor type and heterogeneity between articles, thus more targeted clinical studies on different ICI drug types may be necessary. In general, the various types of ICI drugs are almost universally more favorable to male patients in terms of their treatment efficacy. For tumor types, lung and gastrointestinal tumors have the highest number of RCT studies, which may be related to their high prevalence. An additional factor worth considering is that not all types of tumors respond well to ICI treatment. For example, ICI tends to be the best immunotherapy modality in lung cancer [146], whereas the benefits in uroepithelial tumors need to be further identified [147]. There does not seem to be a significant male–female difference in the therapeutic effect of ICI between different tumor types, a result that is consistent with the findings of Antonino Grassadonia et al. [143], but differs from that of Yingcheng Wu et al. [144]. In this case, the influence of differences in the tumor types themselves as well as quality variations of the studies should be considered. Variations in the number of studies may also contribute to biased results, thus more trials may be needed in the future to explore the benefits of ICI immunotherapy in different tumor types.
Consistently in terms of OS, ICI drugs had a favorable effect on the quality of survival in terms of the PFS and RFS of patients, but they did not seem to show a distinguishing effect between males and females. The effect of heterogeneity between articles needs to be taken into account for this, and due to the small number of studies, larger studies may be required to verify the reliability of the findings.
The major strength of this study is the inclusion of the most recent and comprehensive set of relevant clinical trials. In this research, we obtained 103 articles based on the results of RCT studies through an extensive literature search and a subsequent rigorous screening process, which provided a strong guarantee of the quality of the results. Also, the low publication bias among the included articles is another strength of this study. Meanwhile, during the subgroup analysis, we made a detailed classification of tumor types and treatment modalities separately, thus enabling more targeted study results and avoiding mutual interference between different tumor types or treatment modalities.
This study has various limitations. Firstly, our analysis was performed based on the results of previous studies rather than the raw data of the patients. The data for some important factors are inaccessible, such as receptor expression, posing difficulties for more comprehensive causal analyses. Meanwhile, we only performed subgroup analysis for different tumor types and treatment modalities. Despite these two being the most influential factors of interest to us, the possibility that the presence of other factors interfered with the difference in ICI treatment effect between sexes cannot be excluded. Moreover, we did not consider the effects of specific patterns of ICI use in our analysis, such as dosage and duration of treatment. For this reason, along with regional or ethnic differences in the populations enrolled in the studies, the heterogeneity that exists between their results is noteworthy. And, similar to other studies, the smaller numbers of female patients may have affected the accuracy of the results. The low number of female cases may be a result of the fact that there are fewer female tumors than male tumors originally [148], and most studies did not strictly require a female case size at the time of recruitment.

5. Conclusions

This systematic review and meta-analysis, comprising 103 randomized controlled trials, conclusively demonstrate a disparity in the sensitivity to ICI therapy between males and females. Specifically, our findings indicate that males tend to derive greater benefits from ICI treatment compared to females. This significant observation holds crucial implications for the field of oncology, considering the integral role of ICI therapy in cancer treatment and its positive impact on patient survival. However, in light of the differential response between male and female patients, it is imperative to consider sex differences when administering ICI therapy. Consequently, there may be a need to reconsider and tailor treatment regimens specifically for female patients. In this case, the different types of drugs or tumors is also one of the factors to be considered. Meanwhile, considering the lack of available clinical data on female ICI treatment, more female study subjects are needed to be included in subsequent studies to better guide the clinical application of ICI.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers16020382/s1. Figure S1: Cumulative meta-analysis and Sensitivity analysis for HR of males, with OS as the outcome; Figure S2: Cumulative meta-analysis and Sensitivity analysis for HR of females, with OS as the outcome; Figure S3: Subgroup analysis of hazard ratios for death in tumor patients stratified by tumor type and ICI drug type, by sex, with OS as the outcome; Figure S4: Meta-regression for HR of males and females, with OS as the outcome; Figure S5: Hazard ratios for death in the intervention and control groups in males (A) and females (B), with PFS as the outcome; Figure S6: Hazard ratios for death in the intervention and control groups in males (A) and females (B), with RFS as the outcome; Figure S7: Cumulative meta-analysis and Sensitivity analysis for HR with PFS as the outcome; Figure S8: Cumulative meta-analysis and Sensitivity analysis for HR with RFS as the outcome; Figure S9: Meta-regression for HR of males and females, with PFS as the outcome; Figure S10: Meta-regression for HR of males and females, with RFS as the outcome; Table S1: PRISMA 2020 Checklist; Table S2: Details of Search Strategy to Retrieve the Studies using PubMed (Medline). Date of Search: 11/28/2023; Table S3: Details of Search Strategy to Retrieve the Studies using Embase. Date of Search: 11/28/2023; Table S4: Details of Search Strategy to Retrieve the Studies using Cochrane. Date of Search: 11/28/2023; Table S5: Details of Search Strategy to Retrieve the Studies using Web of Science. Date of Search: 11/28/2023; Table S6: Jadad quality score of included studies.

Author Contributions

Conceptualization, X.Z. and J.S.; methodology, X.Z., J.S. and N.Z.; validation, X.Z., N.Z. and Q.X.; formal analysis, X.Z., J.S. and N.Z.; investigation, N.Z., Y.X. and Y.A.; writing—original draft preparation, X.Z. and J.S.; writing—review and editing, S.W. and Q.X.; visualization, X.Z. and Y.A.; supervision, S.W. and Q.X.; project administration, S.W. and Q.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

We would acknowledge Jia Hu’s help in improving the language quality of the manuscript. Abstract graphic was created with BioRender software (https://biorender.com/ accessed on 4 November 2023).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ortona, E.; Pierdominici, M.; Rider, V. Editorial: Sex Hormones and Gender Differences in Immune Responses. Front. Immunol. 2019, 10, 1076. [Google Scholar] [CrossRef] [PubMed]
  2. Ruggieri, A.; Anticoli, S.; D’Ambrosio, A.; Giordani, L.; Viora, M. The influence of sex and gender on immunity, infection and vaccination. Ann. Dell’istituto Super. Sanita 2016, 52, 198–204. [Google Scholar] [CrossRef]
  3. Jacobson, D.L.; Gange, S.J.; Rose, N.R.; Graham, N.M. Epidemiology and estimated population burden of selected autoimmune diseases in the United States. Clin. Immunol. Immunopathol. 1997, 84, 223–243. [Google Scholar] [CrossRef] [PubMed]
  4. vom Steeg, L.G.; Klein, S.L. SeXX Matters in Infectious Disease Pathogenesis. PLoS Pathog. 2016, 12, e1005374. [Google Scholar] [CrossRef] [PubMed]
  5. Cook, M.B.; Dawsey, S.M.; Freedman, N.D.; Inskip, P.D.; Wichner, S.M.; Quraishi, S.M.; Devesa, S.S.; McGlynn, K.A. Sex disparities in cancer incidence by period and age. Cancer Epidemiol. Biomark. Prev. 2009, 18, 1174–1182. [Google Scholar] [CrossRef]
  6. He, X.; Xu, C. Immune checkpoint signaling and cancer immunotherapy. Cell Res. 2020, 30, 660–669. [Google Scholar] [CrossRef]
  7. Tan, S.; Li, D.; Zhu, X. Cancer immunotherapy: Pros, cons and beyond. Biomed. Pharmacother. 2020, 124, 109821. [Google Scholar] [CrossRef]
  8. Marin-Acevedo, J.A.; Kimbrough, E.O.; Lou, Y. Next generation of immune checkpoint inhibitors and beyond. J. Hematol. Oncol. 2021, 14, 45. [Google Scholar] [CrossRef]
  9. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Rev. Esp. Cardiol. 2021, 74, 790–799. [Google Scholar] [CrossRef]
  10. Chen, L.T.; Satoh, T.; Ryu, M.H.; Chao, Y.; Kato, K.; Chung, H.C.; Chen, J.S.; Muro, K.; Kang, W.K.; Yeh, K.H.; et al. A phase 3 study of nivolumab in previously treated advanced gastric or gastroesophageal junction cancer (ATTRACTION-2): 2-year update data. Gastric Cancer 2020, 23, 510–519. [Google Scholar] [CrossRef]
  11. Eggermont, A.M.M.; Chiarion-Sileni, V.; Grob, J.J.; Dummer, R.; Wolchok, J.D.; Schmidt, H.; Hamid, O.; Robert, C.; Ascierto, P.A.; Richards, J.M.; et al. Adjuvant ipilimumab versus placebo after complete resection of stage III melanoma: Long-term follow-up results of the European Organisation for Research and Treatment of Cancer 18071 double-blind phase 3 randomised trial. Eur. J. Cancer 2019, 119, 1–10. [Google Scholar] [CrossRef] [PubMed]
  12. Reck, M.; Ciuleanu, T.E.; Cobo, M.; Schenker, M.; Zurawski, B.; Menezes, J.; Richardet, E.; Bennouna, J.; Felip, E.; Juan-Vidal, O.; et al. First-line nivolumab plus ipilimumab with two cycles of chemotherapy versus chemotherapy alone (four cycles) in advanced non-small-cell lung cancer: CheckMate 9LA 2-year update. ESMO Open 2021, 6, 100273. [Google Scholar] [CrossRef] [PubMed]
  13. Takahashi, M.; Kato, K.; Okada, M.; Chin, K.; Kadowaki, S.; Hamamoto, Y.; Doki, Y.; Kubota, Y.; Kawakami, H.; Ogata, T.; et al. Nivolumab versus chemotherapy in Japanese patients with advanced esophageal squamous cell carcinoma: A subgroup analysis of a multicenter, randomized, open-label, phase 3 trial (ATTRACTION-3). Esophagus 2021, 18, 90–99. [Google Scholar] [CrossRef] [PubMed]
  14. Hayashi, H.; Sugawara, S.; Fukuda, Y.; Fujimoto, D.; Miura, S.; Ota, K.; Ozawa, Y.; Hara, S.; Tanizaki, J.; Azuma, K.; et al. A Randomized Phase II Study Comparing Nivolumab with Carboplatin-Pemetrexed for EGFR-Mutated NSCLC with Resistance to EGFR Tyrosine Kinase Inhibitors (WJOG8515L). Clin. Cancer Res. 2022, 28, 893–902. [Google Scholar] [CrossRef] [PubMed]
  15. Kojima, T.; Shah, M.A.; Muro, K.; Francois, E.; Adenis, A.; Hsu, C.H.; Doi, T.; Moriwaki, T.; Kim, S.B.; Lee, S.H.; et al. Randomized Phase III KEYNOTE-181 Study of Pembrolizumab versus Chemotherapy in Advanced Esophageal Cancer. J. Clin. Oncol. 2020, 38, 4138–4148. [Google Scholar] [CrossRef] [PubMed]
  16. Felip, E.; Altorki, N.; Zhou, C.; Csoszi, T.; Vynnychenko, I.; Goloborodko, O.; Luft, A.; Akopov, A.; Martinez-Marti, A.; Kenmotsu, H.; et al. Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB-IIIA non-small-cell lung cancer (IMpower010): A randomised, multicentre, open-label, phase 3 trial. Lancet 2021, 398, 1344–1357. [Google Scholar] [CrossRef]
  17. Nishio, M.; Barlesi, F.; West, H.; Ball, S.; Bordoni, R.; Cobo, M.; Longeras, P.D.; Goldschmidt, J., Jr.; Novello, S.; Orlandi, F.; et al. Atezolizumab Plus Chemotherapy for First-Line Treatment of Nonsquamous NSCLC: Results From the Randomized Phase 3 IMpower132 Trial. J. Thorac. Oncol. 2021, 16, 653–664. [Google Scholar] [CrossRef]
  18. Lee, N.Y.; Ferris, R.L.; Psyrri, A.; Haddad, R.I.; Tahara, M.; Bourhis, J.; Harrington, K.; Chang, P.M.H.; Lin, J.C.; Razaq, M.A.; et al. Avelumab plus standard-of-care chemoradiotherapy versus chemoradiotherapy alone in patients with locally advanced squamous cell carcinoma of the head and neck: A randomised, double-blind, placebo-controlled, multicentre, phase 3 trial. Lancet Oncol. 2021, 22, 450–462. [Google Scholar] [CrossRef]
  19. Park, K.; Özgüroğlu, M.; Vansteenkiste, J.; Spigel, D.; Yang, J.C.H.; Ishii, H.; Garassino, M.; de Marinis, F.; Szczesna, A.; Polychronis, A.; et al. Avelumab versus Docetaxel in Patients with Platinum-Treated Advanced NSCLC: 2-Year Follow-Up From the JAVELIN Lung 200 Phase 3 Trial. J. Thorac. Oncol. 2021, 16, 1369–1378. [Google Scholar] [CrossRef]
  20. Zhou, C.; Chen, G.; Huang, Y.; Zhou, J.; Lin, L.; Feng, J.; Wang, Z.; Shu, Y.; Shi, J.; Hu, Y.; et al. Camrelizumab plus carboplatin and pemetrexed versus chemotherapy alone in chemotherapy-naive patients with advanced non-squamous non-small-cell lung cancer (CameL): A randomised, open-label, multicentre, phase 3 trial. Lancet. Respir. Med. 2021, 9, 305–314. [Google Scholar] [CrossRef]
  21. Spigel, D.R.; Vicente, D.; Ciuleanu, T.E.; Gettinger, S.; Peters, S.; Horn, L.; Audigier-Valette, C.; Pardo Aranda, N.; Juan-Vidal, O.; Cheng, Y.; et al. Second-line nivolumab in relapsed small-cell lung cancer: CheckMate 331(☆). Ann. Oncol. 2021, 32, 631–641. [Google Scholar] [CrossRef]
  22. Zhou, C.; Wang, Z.; Sun, Y.; Cao, L.; Ma, Z.; Wu, R.; Yu, Y.; Yao, W.; Chang, J.; Chen, J.; et al. Sugemalimab versus placebo, in combination with platinum-based chemotherapy, as first-line treatment of metastatic non-small-cell lung cancer (GEMSTONE-302): Interim and final analyses of a double-blind, randomised, phase 3 clinical trial. Lancet Oncol. 2022, 23, 220–233. [Google Scholar] [CrossRef] [PubMed]
  23. Hodi, F.S.; O’Day, S.J.; McDermott, D.F.; Weber, R.W.; Sosman, J.A.; Haanen, J.B.; Gonzalez, R.; Robert, C.; Schadendorf, D.; Hassel, J.C.; et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 2010, 363, 711–723. [Google Scholar] [CrossRef] [PubMed]
  24. Ribas, A.; Kefford, R.; Marshall, M.A.; Punt, C.J.; Haanen, J.B.; Marmol, M.; Garbe, C.; Gogas, H.; Schachter, J.; Linette, G.; et al. Phase III randomized clinical trial comparing tremelimumab with standard-of-care chemotherapy in patients with advanced melanoma. J. Clin. Oncol. 2013, 31, 616–622. [Google Scholar] [CrossRef] [PubMed]
  25. Robert, C.; Thomas, L.; Bondarenko, I.; O’Day, S.; Weber, J.; Garbe, C.; Lebbe, C.; Baurain, J.F.; Testori, A.; Grob, J.J.; et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N. Engl. J. Med. 2011, 364, 2517–2526. [Google Scholar] [CrossRef] [PubMed]
  26. Govindan, R.; Szczesna, A.; Ahn, M.J.; Schneider, C.P.; Gonzalez Mella, P.F.; Barlesi, F.; Han, B.; Ganea, D.E.; Von Pawel, J.; Vladimirov, V.; et al. Phase III Trial of Ipilimumab Combined with Paclitaxel and Carboplatin in Advanced Squamous Non-Small-Cell Lung Cancer. J. Clin. Oncol. 2017, 35, 3449–3457. [Google Scholar] [CrossRef]
  27. Reck, M.; Luft, A.; Szczesna, A.; Havel, L.; Kim, S.W.; Akerley, W.; Pietanza, M.C.; Wu, Y.L.; Zielinski, C.; Thomas, M.; et al. Phase III Randomized Trial of Ipilimumab Plus Etoposide and Platinum versus Placebo Plus Etoposide and Platinum in Extensive-Stage Small-Cell Lung Cancer. J. Clin. Oncol. 2016, 34, 3740–3748. [Google Scholar] [CrossRef] [PubMed]
  28. Brahmer, J.; Reckamp, K.L.; Baas, P.; Crinò, L.; Eberhardt, W.E.; Poddubskaya, E.; Antonia, S.; Pluzanski, A.; Vokes, E.E.; Holgado, E.; et al. Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2015, 373, 123–135. [Google Scholar] [CrossRef]
  29. Motzer, R.J.; Escudier, B.; McDermott, D.F.; George, S.; Hammers, H.J.; Srinivas, S.; Tykodi, S.S.; Sosman, J.A.; Procopio, G.; Plimack, E.R.; et al. Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N. Engl. J. Med. 2015, 373, 1803–1813. [Google Scholar] [CrossRef]
  30. Borghaei, H.; Paz-Ares, L.; Horn, L.; Spigel, D.R.; Steins, M.; Ready, N.E.; Chow, L.Q.; Vokes, E.E.; Felip, E.; Holgado, E.; et al. Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2015, 373, 1627–1639. [Google Scholar] [CrossRef]
  31. Larkin, J.; Minor, D.; D’Angelo, S.; Neyns, B.; Smylie, M.; Miller, W.H., Jr.; Gutzmer, R.; Linette, G.; Chmielowski, B.; Lao, C.D.; et al. Overall Survival in Patients with Advanced Melanoma Who Received Nivolumab versus Investigator’s Choice Chemotherapy in CheckMate 037: A Randomized, Controlled, Open-Label Phase III Trial. J. Clin. Oncol. 2018, 36, 383–390. [Google Scholar] [CrossRef] [PubMed]
  32. Robert, C.; Long, G.V.; Brady, B.; Dutriaux, C.; Maio, M.; Mortier, L.; Hassel, J.C.; Rutkowski, P.; McNeil, C.; Kalinka-Warzocha, E.; et al. Nivolumab in previously untreated melanoma without BRAF mutation. N. Engl. J. Med. 2015, 372, 320–330. [Google Scholar] [CrossRef] [PubMed]
  33. Maio, M.; Scherpereel, A.; Calabrò, L.; Aerts, J.; Perez, S.C.; Bearz, A.; Nackaerts, K.; Fennell, D.A.; Kowalski, D.; Tsao, A.S.; et al. Tremelimumab as second-line or third-line treatment in relapsed malignant mesothelioma (DETERMINE): A multicentre, international, randomised, double-blind, placebo-controlled phase 2b trial. Lancet Oncol. 2017, 18, 1261–1273. [Google Scholar] [CrossRef] [PubMed]
  34. Herbst, R.S.; Baas, P.; Kim, D.W.; Felip, E.; Pérez-Gracia, J.L.; Han, J.Y.; Molina, J.; Kim, J.H.; Arvis, C.D.; Ahn, M.J.; et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): A randomised controlled trial. Lancet 2016, 387, 1540–1550. [Google Scholar] [CrossRef]
  35. Herbst, R.S.; Garon, E.B.; Kim, D.W.; Cho, B.C.; Gervais, R.; Perez-Gracia, J.L.; Han, J.Y.; Majem, M.; Forster, M.D.; Monnet, I.; et al. Five Year Survival Update from KEYNOTE-010: Pembrolizumab versus Docetaxel for Previously Treated, Programmed Death-Ligand 1-Positive Advanced NSCLC. J. Thorac. Oncol. 2021, 16, 1718–1732. [Google Scholar] [CrossRef] [PubMed]
  36. Fehrenbacher, L.; von Pawel, J.; Park, K.; Rittmeyer, A.; Gandara, D.R.; Ponce Aix, S.; Han, J.Y.; Gadgeel, S.M.; Hida, T.; Cortinovis, D.L.; et al. Updated Efficacy Analysis Including Secondary Population Results for OAK: A Randomized Phase III Study of Atezolizumab versus Docetaxel in Patients with Previously Treated Advanced Non-Small Cell Lung Cancer. J. Thorac. Oncol. 2018, 13, 1156–1170. [Google Scholar] [CrossRef]
  37. Carbone, D.P.; Reck, M.; Paz-Ares, L.; Creelan, B.; Horn, L.; Steins, M.; Felip, E.; van den Heuvel, M.M.; Ciuleanu, T.E.; Badin, F.; et al. First-Line Nivolumab in Stage IV or Recurrent Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2017, 376, 2415–2426. [Google Scholar] [CrossRef]
  38. Ferris, R.L.; Blumenschein, G., Jr.; Fayette, J.; Guigay, J.; Colevas, A.D.; Licitra, L.; Harrington, K.; Kasper, S.; Vokes, E.E.; Even, C.; et al. Nivolumab for Recurrent Squamous-Cell Carcinoma of the Head and Neck. N. Engl. J. Med. 2016, 375, 1856–1867. [Google Scholar] [CrossRef]
  39. Antonia, S.J.; Villegas, A.; Daniel, D.; Vicente, D.; Murakami, S.; Hui, R.; Kurata, T.; Chiappori, A.; Lee, K.H.; de Wit, M.; et al. Overall Survival with Durvalumab after Chemoradiotherapy in Stage III NSCLC. N. Engl. J. Med. 2018, 379, 2342–2350. [Google Scholar] [CrossRef]
  40. Ferrucci, P.F.; Di Giacomo, A.M.; Del Vecchio, M.; Atkinson, V.; Schmidt, H.; Schachter, J.; Queirolo, P.; Long, G.V.; Stephens, R.; Svane, I.M.; et al. KEYNOTE-022 part 3: A randomized, double-blind, phase 2 study of pembrolizumab, dabrafenib, and trametinib in BRAF-mutant melanoma. J. Immunother. Cancer 2020, 8, e001806. [Google Scholar] [CrossRef]
  41. Reck, M.; Rodríguez-Abreu, D.; Robinson, A.G.; Hui, R.; Csőszi, T.; Fülöp, A.; Gottfried, M.; Peled, N.; Tafreshi, A.; Cuffe, S.; et al. Updated Analysis of KEYNOTE-024: Pembrolizumab versus Platinum-Based Chemotherapy for Advanced Non-Small-Cell Lung Cancer with PD-L1 Tumor Proportion Score of 50% or Greater. J. Clin. Oncol. 2019, 37, 537–546. [Google Scholar] [CrossRef]
  42. Mok, T.S.K.; Wu, Y.L.; Kudaba, I.; Kowalski, D.M.; Cho, B.C.; Turna, H.Z.; Castro, G., Jr.; Srimuninnimit, V.; Laktionov, K.K.; Bondarenko, I.; et al. Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer (KEYNOTE-042): A randomised, open-label, controlled, phase 3 trial. Lancet 2019, 393, 1819–1830. [Google Scholar] [CrossRef] [PubMed]
  43. Motzer, R.J.; Choueiri, T.K.; McDermott, D.F.; Powles, T.; Vano, Y.A.; Gupta, S.; Yao, J.; Han, C.; Ammar, R.; Papillon-Cavanagh, S.; et al. Biomarker analysis from CheckMate 214: Nivolumab plus ipilimumab versus sunitinib in renal cell carcinoma. J. Immunother. Cancer 2022, 10, e004316. [Google Scholar] [CrossRef] [PubMed]
  44. Cohen, E.E.W.; Soulières, D.; Le Tourneau, C.; Dinis, J.; Licitra, L.; Ahn, M.J.; Soria, A.; Machiels, J.P.; Mach, N.; Mehra, R.; et al. Pembrolizumab versus methotrexate, docetaxel, or cetuximab for recurrent or metastatic head-and-neck squamous cell carcinoma (KEYNOTE-040): A randomised, open-label, phase 3 study. Lancet 2019, 393, 156–167. [Google Scholar] [CrossRef]
  45. Bellmunt, J.; de Wit, R.; Vaughn, D.J.; Fradet, Y.; Lee, J.L.; Fong, L.; Vogelzang, N.J.; Climent, M.A.; Petrylak, D.P.; Choueiri, T.K.; et al. Pembrolizumab as Second-Line Therapy for Advanced Urothelial Carcinoma. N. Engl. J. Med. 2017, 376, 1015–1026. [Google Scholar] [CrossRef]
  46. Burtness, B.; Harrington, K.J.; Greil, R.; Soulières, D.; Tahara, M.; de Castro, G., Jr.; Psyrri, A.; Basté, N.; Neupane, P.; Bratland, Å.; et al. Pembrolizumab alone or with chemotherapy versus cetuximab with chemotherapy for recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-048): A randomised, open-label, phase 3 study. Lancet 2019, 394, 1915–1928. [Google Scholar] [CrossRef] [PubMed]
  47. Eggermont, A.M.M.; Blank, C.U.; Mandala, M.; Long, G.V.; Atkinson, V.G.; Dalle, S.; Haydon, A.M.; Meshcheryakov, A.; Khattak, A.; Carlino, M.S.; et al. Adjuvant pembrolizumab versus placebo in resected stage III melanoma (EORTC 1325-MG/KEYNOTE-054): Distant metastasis-free survival results from a double-blind, randomised, controlled, phase 3 trial. Lancet Oncol. 2021, 22, 643–654. [Google Scholar] [CrossRef] [PubMed]
  48. Reck, M.; Mok, T.S.; Nishio, M.; Jotte, R.M.; Cappuzzo, F.; Orlandi, F.; Stroyakovskiy, D.; Nogami, N.; Rodriguez-Abreu, D.; Moro-Sibilot, D.; et al. Atezolizumab plus bevacizumab and chemotherapy in non-small-cell lung cancer (IMpower150): Key subgroup analyses of patients with EGFR mutations or baseline liver metastases in a randomised, open-label phase 3 trial. Lancet Respir. Med. 2019, 7, 387–401. [Google Scholar] [CrossRef]
  49. West, H.; McCleod, M.; Hussein, M.; Morabito, A.; Rittmeyer, A.; Conter, H.J.; Kopp, H.G.; Daniel, D.; McCune, S.; Mekhail, T.; et al. Atezolizumab in combination with carboplatin plus nab-paclitaxel chemotherapy compared with chemotherapy alone as first-line treatment for metastatic non-squamous non-small-cell lung cancer (IMpower130): A multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 2019, 20, 924–937. [Google Scholar] [CrossRef]
  50. Jotte, R.; Cappuzzo, F.; Vynnychenko, I.; Stroyakovskiy, D.; Rodríguez-Abreu, D.; Hussein, M.; Soo, R.; Conter, H.J.; Kozuki, T.; Huang, K.C.; et al. Atezolizumab in Combination with Carboplatin and Nab-Paclitaxel in Advanced Squamous NSCLC (IMpower131): Results from a Randomized Phase III Trial. J. Thorac. Oncol. 2020, 15, 1351–1360. [Google Scholar] [CrossRef]
  51. Fuchs, C.S.; Özgüroğlu, M.; Bang, Y.J.; Di Bartolomeo, M.; Mandala, M.; Ryu, M.H.; Fornaro, L.; Olesinski, T.; Caglevic, C.; Chung, H.C.; et al. Pembrolizumab versus paclitaxel for previously treated PD-L1-positive advanced gastric or gastroesophageal junction cancer: 2-year update of the randomized phase 3 KEYNOTE-061 trial. Gastric Cancer 2022, 25, 197–206. [Google Scholar] [CrossRef] [PubMed]
  52. Barlesi, F.; Vansteenkiste, J.; Spigel, D.; Ishii, H.; Garassino, M.; de Marinis, F.; Özgüroğlu, M.; Szczesna, A.; Polychronis, A.; Uslu, R.; et al. Avelumab versus docetaxel in patients with platinum-treated advanced non-small-cell lung cancer (JAVELIN Lung 200): An open-label, randomised, phase 3 study. Lancet Oncol. 2018, 19, 1468–1479. [Google Scholar] [CrossRef] [PubMed]
  53. Herbst, R.S.; Giaccone, G.; de Marinis, F.; Reinmuth, N.; Vergnenegre, A.; Barrios, C.H.; Morise, M.; Felip, E.; Andric, Z.; Geater, S.; et al. Atezolizumab for first-line treatment of PD-L1-selected patients with NSCLC. N. Engl. J. Med. 2020, 383, 1328–1339. [Google Scholar] [CrossRef]
  54. Bellmunt, J.; Hussain, M.; Gschwend, J.E.; Albers, P.; Oudard, S.; Castellano, D.; Daneshmand, S.; Nishiyama, H.; Majchrowicz, M.; Degaonkar, V.; et al. Adjuvant atezolizumab versus observation in muscle-invasive urothelial carcinoma (IMvigor010): A multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2021, 22, 525–537. [Google Scholar] [CrossRef] [PubMed]
  55. Rizvi, N.A.; Cho, B.C.; Reinmuth, N.; Lee, K.H.; Luft, A.; Ahn, M.J.; van den Heuvel, M.M.; Cobo, M.; Vicente, D.; Smolin, A.; et al. Durvalumab with or without Tremelimumab vs Standard Chemotherapy in First-line Treatment of Metastatic Non-Small Cell Lung Cancer: The MYSTIC Phase 3 Randomized Clinical Trial. JAMA Oncol. 2020, 6, 661–674. [Google Scholar] [CrossRef] [PubMed]
  56. Paz-Ares, L.G.; Ramalingam, S.S.; Ciuleanu, T.E.; Lee, J.S.; Urban, L.; Caro, R.B.; Park, K.; Sakai, H.; Ohe, Y.; Nishio, M.; et al. First-Line Nivolumab Plus Ipilimumab in Advanced NSCLC: 4-Year Outcomes from the Randomized, Open-Label, Phase 3 CheckMate 227 Part 1 Trial. J. Thorac. Oncol. 2022, 17, 289–308. [Google Scholar] [CrossRef] [PubMed]
  57. Kenmotsu, H.; Sugawara, S.; Watanabe, Y.; Saito, H.; Okada, M.; Chen-Yoshikawa, T.F.; Ohe, Y.; Nishio, W.; Nakagawa, S.; Nagao, H. Adjuvant atezolizumab in Japanese patients with resected stage IB-IIIA non-small cell lung cancer (IMpower010). Cancer Sci. 2022, 113, 4327–4338. [Google Scholar] [CrossRef]
  58. Shitara, K.; Van Cutsem, E.; Bang, Y.J.; Fuchs, C.; Wyrwicz, L.; Lee, K.W.; Kudaba, I.; Garrido, M.; Chung, H.C.; Lee, J.; et al. Efficacy and Safety of Pembrolizumab or Pembrolizumab Plus Chemotherapy vs Chemotherapy Alone for Patients with First-line, Advanced Gastric Cancer: The KEYNOTE-062 Phase 3 Randomized Clinical Trial. JAMA Oncol. 2020, 6, 1571–1580. [Google Scholar] [CrossRef]
  59. O’Brien, M.; Paz-Ares, L.; Marreaud, S.; Dafni, U.; Oselin, K.; Havel, L.; Esteban, E.; Isla, D.; Martinez-Marti, A.; Faehling, M.; et al. Pembrolizumab versus placebo as adjuvant therapy for completely resected stage IB-IIIA non-small-cell lung cancer (PEARLS/KEYNOTE-091): An interim analysis of a randomised, triple-blind, phase 3 trial. Lancet Oncol. 2022, 23, 1274–1286. [Google Scholar] [CrossRef]
  60. Grossmann, K.F.; Othus, M.; Patel, S.P.; Tarhini, A.A.; Sondak, V.K.; Knopp, M.V.; Petrella, T.M.; Truong, T.G.; Khushalani, N.I.; Cohen, J.V.; et al. Adjuvant Pembrolizumab versus IFNα2b or Ipilimumab in Resected High-Risk Melanoma. Cancer Discov. 2022, 12, 644–653. [Google Scholar] [CrossRef]
  61. Powles, T.; van der Heijden, M.S.; Castellano, D.; Galsky, M.D.; Loriot, Y.; Petrylak, D.P.; Ogawa, O.; Park, S.H.; Lee, J.L.; De Giorgi, U.; et al. Durvalumab alone and durvalumab plus tremelimumab versus chemotherapy in previously untreated patients with unresectable, locally advanced or metastatic urothelial carcinoma (DANUBE): A randomised, open-label, multicentre, phase 3 trial. Lancet Oncol. 2020, 21, 1574–1588. [Google Scholar] [CrossRef]
  62. Livingstone, E.; Zimmer, L.; Hassel, J.C.; Fluck, M.; Eigentler, T.K.; Loquai, C.; Haferkamp, S.; Gutzmer, R.; Meier, F.; Mohr, P.; et al. Adjuvant nivolumab plus ipilimumab or nivolumab alone versus placebo in patients with resected stage IV melanoma with no evidence of disease (IMMUNED): Final results of a randomised, double-blind, phase 2 trial. Lancet 2022, 400, 1117–1129. [Google Scholar] [CrossRef] [PubMed]
  63. Owonikoko, T.K.; Park, K.; Govindan, R.; Ready, N.; Reck, M.; Peters, S.; Dakhil, S.R.; Navarro, A.; Rodríguez-Cid, J.; Schenker, M.; et al. Nivolumab and Ipilimumab as Maintenance Therapy in Extensive-Disease Small-Cell Lung Cancer: CheckMate 451. J. Clin. Oncol. 2021, 39, 1349–1359. [Google Scholar] [CrossRef]
  64. Diaz, L.A., Jr.; Shiu, K.K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab versus chemotherapy for microsatellite instability-high or mismatch repair-deficient metastatic colorectal cancer (KEYNOTE-177): Final analysis of a randomised, open-label, phase 3 study. Lancet Oncol. 2022, 23, 659–670. [Google Scholar] [CrossRef] [PubMed]
  65. André, T.; Shiu, K.K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. N. Engl. J. Med. 2020, 383, 2207–2218. [Google Scholar] [CrossRef] [PubMed]
  66. Kato, K.; Cho, B.C.; Takahashi, M.; Okada, M.; Lin, C.Y.; Chin, K.; Kadowaki, S.; Ahn, M.J.; Hamamoto, Y.; Doki, Y.; et al. Nivolumab versus chemotherapy in patients with advanced oesophageal squamous cell carcinoma refractory or intolerant to previous chemotherapy (ATTRACTION-3): A multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 2019, 20, 1506–1517. [Google Scholar] [CrossRef]
  67. Rodríguez-Abreu, D.; Powell, S.F.; Hochmair, M.J.; Gadgeel, S.; Esteban, E.; Felip, E.; Speranza, G.; De Angelis, F.; Dómine, M.; Cheng, S.Y.; et al. Pemetrexed plus platinum with or without pembrolizumab in patients with previously untreated metastatic nonsquamous NSCLC: Protocol-specified final analysis from KEYNOTE-189. Ann. Oncol. 2021, 32, 881–895. [Google Scholar] [CrossRef]
  68. Powles, T.; Park, S.H.; Voog, E.; Caserta, C.; Valderrama, B.P.; Gurney, H.; Kalofonos, H.; Radulović, S.; Demey, W.; Ullén, A.; et al. Avelumab Maintenance Therapy for Advanced or Metastatic Urothelial Carcinoma. N. Engl. J. Med. 2020, 383, 1218–1230. [Google Scholar] [CrossRef]
  69. Moehler, M.; Dvorkin, M.; Boku, N.; Özgüroğlu, M.; Ryu, M.H.; Muntean, A.S.; Lonardi, S.; Nechaeva, M.; Bragagnoli, A.C.; Coşkun, H.S.; et al. Phase III Trial of Avelumab Maintenance after First-Line Induction Chemotherapy versus Continuation of Chemotherapy in Patients with Gastric Cancers: Results from JAVELIN Gastric 100. J. Clin. Oncol. 2021, 39, 966–977. [Google Scholar] [CrossRef]
  70. Bang, Y.J.; Ruiz, E.Y.; Van Cutsem, E.; Lee, K.W.; Wyrwicz, L.; Schenker, M.; Alsina, M.; Ryu, M.H.; Chung, H.C.; Evesque, L.; et al. Phase III, randomised trial of avelumab versus physician’s choice of chemotherapy as third-line treatment of patients with advanced gastric or gastro-oesophageal junction cancer: Primary analysis of JAVELIN Gastric 300. Ann. Oncol. 2018, 29, 2052–2060. [Google Scholar] [CrossRef]
  71. Bajorin, D.F.; Witjes, J.A.; Gschwend, J.E.; Schenker, M.; Valderrama, B.P.; Tomita, Y.; Bamias, A.; Lebret, T.; Shariat, S.F.; Park, S.H.; et al. Adjuvant Nivolumab versus Placebo in Muscle-Invasive Urothelial Carcinoma. N. Engl. J. Med. 2021, 384, 2102–2114. [Google Scholar] [CrossRef] [PubMed]
  72. Choueiri, T.K.; Motzer, R.J.; Rini, B.I.; Haanen, J.; Campbell, M.T.; Venugopal, B.; Kollmannsberger, C.; Gravis-Mescam, G.; Uemura, M.; Lee, J.L.; et al. Updated efficacy results from the JAVELIN Renal 101 trial: First-line avelumab plus axitinib versus sunitinib in patients with advanced renal cell carcinoma. Ann. Oncol. 2020, 31, 1030–1039. [Google Scholar] [CrossRef] [PubMed]
  73. Zhu, X.; Cao, Y.; Liu, W.; Ju, X.; Zhao, X.; Jiang, L.; Ye, Y.; Jin, G.; Zhang, H. Stereotactic body radiotherapy plus pembrolizumab and trametinib versus stereotactic body radiotherapy plus gemcitabine for locally recurrent pancreatic cancer after surgical resection: An open-label, randomised, controlled, phase 2 trial. Lancet Oncol. 2022, 23, e105–e115. [Google Scholar] [CrossRef] [PubMed]
  74. Kelly, R.J.; Ajani, J.A.; Kuzdzal, J.; Zander, T.; Van Cutsem, E.; Piessen, G.; Mendez, G.; Feliciano, J.; Motoyama, S.; Lièvre, A.; et al. Adjuvant Nivolumab in Resected Esophageal or Gastroesophageal Junction Cancer. N. Engl. J. Med. 2021, 384, 1191–1203. [Google Scholar] [CrossRef] [PubMed]
  75. Kang, Y.K.; Chen, L.T.; Ryu, M.H.; Oh, D.Y.; Oh, S.C.; Chung, H.C.; Lee, K.W.; Omori, T.; Shitara, K.; Sakuramoto, S.; et al. Nivolumab plus chemotherapy versus placebo plus chemotherapy in patients with HER2-negative, untreated, unresectable advanced or recurrent gastric or gastro-oesophageal junction cancer (ATTRACTION-4): A randomised, multicentre, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2022, 23, 234–247. [Google Scholar] [CrossRef] [PubMed]
  76. Liu, S.V.; Reck, M.; Mansfield, A.S.; Mok, T.; Scherpereel, A.; Reinmuth, N.; Garassino, M.C.; De Castro Carpeno, J.; Califano, R.; Nishio, M.; et al. Updated Overall Survival and PD-L1 Subgroup Analysis of Patients with Extensive-Stage Small-Cell Lung Cancer Treated with Atezolizumab, Carboplatin, and Etoposide (IMpower133). J. Clin. Oncol. 2021, 39, 619–630. [Google Scholar] [CrossRef]
  77. Paz-Ares, L.; Luft, A.; Vicente, D.; Tafreshi, A.; Gümüş, M.; Mazières, J.; Hermes, B.; Çay Şenler, F.; Csőszi, T.; Fülöp, A.; et al. Pembrolizumab plus Chemotherapy for Squamous Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2018, 379, 2040–2051. [Google Scholar] [CrossRef] [PubMed]
  78. Galsky, M.D.; Arija, J.Á.A.; Bamias, A.; Davis, I.D.; De Santis, M.; Kikuchi, E.; Garcia-Del-Muro, X.; De Giorgi, U.; Mencinger, M.; Izumi, K.; et al. Atezolizumab with or without chemotherapy in metastatic urothelial cancer (IMvigor130): A multicentre, randomised, placebo-controlled phase 3 trial. Lancet 2020, 395, 1547–1557. [Google Scholar] [CrossRef]
  79. Motzer, R.; Alekseev, B.; Rha, S.Y.; Porta, C.; Eto, M.; Powles, T.; Grünwald, V.; Hutson, T.E.; Kopyltsov, E.; Méndez-Vidal, M.J.; et al. Lenvatinib plus Pembrolizumab or Everolimus for Advanced Renal Cell Carcinoma. N. Engl. J. Med. 2021, 384, 1289–1300. [Google Scholar] [CrossRef]
  80. Chen, E.X.; Jonker, D.J.; Loree, J.M.; Kennecke, H.F.; Berry, S.R.; Couture, F.; Ahmad, C.E.; Goffin, J.R.; Kavan, P.; Harb, M.; et al. Effect of Combined Immune Checkpoint Inhibition vs Best Supportive Care Alone in Patients with Advanced Colorectal Cancer: The Canadian Cancer Trials Group CO.26 Study. JAMA Oncol. 2020, 6, 831–838. [Google Scholar] [CrossRef]
  81. Liu, T.; Bai, Y.; Lin, X.; Li, W.; Wang, J.; Zhang, X.; Pan, H.; Bai, C.; Bai, L.; Cheng, Y.; et al. First-line nivolumab plus chemotherapy vs chemotherapy in patients with advanced gastric, gastroesophageal junction, and esophageal adenocarcinoma: CheckMate 649 Chinese subgroup analysis. Int. J. Cancer 2023, 152, 749–760. [Google Scholar] [CrossRef]
  82. Renouf, D.J.; Loree, J.M.; Knox, J.J.; Topham, J.T.; Kavan, P.; Jonker, D.; Welch, S.; Couture, F.; Lemay, F.; Tehfe, M.; et al. The CCTG PA.7 phase II trial of gemcitabine and nab-paclitaxel with or without durvalumab and tremelimumab as initial therapy in metastatic pancreatic ductal adenocarcinoma. Nat. Commun. 2022, 13, 5020. [Google Scholar] [CrossRef]
  83. Peters, S.; Scherpereel, A.; Cornelissen, R.; Oulkhouir, Y.; Greillier, L.; Kaplan, M.A.; Talbot, T.; Monnet, I.; Hiret, S.; Baas, P.; et al. First-line nivolumab plus ipilimumab versus chemotherapy in patients with unresectable malignant pleural mesothelioma: 3-year outcomes from CheckMate 743. Ann. Oncol. 2022, 33, 488–499. [Google Scholar] [CrossRef] [PubMed]
  84. Gutzmer, R.; Stroyakovskiy, D.; Gogas, H.; Robert, C.; Lewis, K.; Protsenko, S.; Pereira, R.P.; Eigentler, T.; Rutkowski, P.; Demidov, L.; et al. Atezolizumab, vemurafenib, and cobimetinib as first-line treatment for unresectable advanced BRAF(V600) mutation-positive melanoma (IMspire150): Primary analysis of the randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 2020, 395, 1835–1844. [Google Scholar] [CrossRef]
  85. Popat, S.; Curioni-Fontecedro, A.; Dafni, U.; Shah, R.; O’Brien, M.; Pope, A.; Fisher, P.; Spicer, J.; Roy, A.; Gilligan, D.; et al. A multicentre randomised phase III trial comparing pembrolizumab versus single-agent chemotherapy for advanced pre-treated malignant pleural mesothelioma: The European Thoracic Oncology Platform (ETOP 9-15) PROMISE-meso trial. Ann. Oncol. 2020, 31, 1734–1745. [Google Scholar] [CrossRef] [PubMed]
  86. Pal, S.K.; Uzzo, R.; Karam, J.A.; Master, V.A.; Donskov, F.; Suarez, C.; Albiges, L.; Rini, B.; Tomita, Y.; Kann, A.G.; et al. Adjuvant atezolizumab versus placebo for patients with renal cell carcinoma at increased risk of recurrence following resection (IMmotion010): A multicentre, randomised, double-blind, phase 3 trial. Lancet 2022, 400, 1103–1116. [Google Scholar] [CrossRef]
  87. Paz-Ares, L.; Chen, Y.; Reinmuth, N.; Hotta, K.; Trukhin, D.; Statsenko, G.; Hochmair, M.J.; Özgüroğlu, M.; Ji, J.H.; Garassino, M.C.; et al. Durvalumab, with or without tremelimumab, plus platinum-etoposide in first-line treatment of extensive-stage small-cell lung cancer: 3-year overall survival update from CASPIAN. ESMO Open 2022, 7, 100408. [Google Scholar] [CrossRef] [PubMed]
  88. Pujol, J.L.; Greillier, L.; Audigier-Valette, C.; Moro-Sibilot, D.; Uwer, L.; Hureaux, J.; Guisier, F.; Carmier, D.; Madelaine, J.; Otto, J.; et al. A Randomized Non-Comparative Phase II Study of Anti-Programmed Cell Death-Ligand 1 Atezolizumab or Chemotherapy as Second-Line Therapy in Patients with Small Cell Lung Cancer: Results From the IFCT-1603 Trial. J. Thorac. Oncol. 2019, 14, 903–913. [Google Scholar] [CrossRef]
  89. Fennell, D.A.; Ewings, S.; Ottensmeier, C.; Califano, R.; Hanna, G.G.; Hill, K.; Danson, S.; Steele, N.; Nye, M.; Johnson, L.; et al. Nivolumab versus placebo in patients with relapsed malignant mesothelioma (CONFIRM): A multicentre, double-blind, randomised, phase 3 trial. Lancet Oncol. 2021, 22, 1530–1540. [Google Scholar] [CrossRef]
  90. Rudin, C.M.; Awad, M.M.; Navarro, A.; Gottfried, M.; Peters, S.; Csőszi, T.; Cheema, P.K.; Rodriguez-Abreu, D.; Wollner, M.; Yang, J.C.; et al. Pembrolizumab or Placebo Plus Etoposide and Platinum as First-Line Therapy for Extensive-Stage Small-Cell Lung Cancer: Randomized, Double-Blind, Phase III KEYNOTE-604 Study. J. Clin. Oncol. 2020, 38, 2369–2379. [Google Scholar] [CrossRef]
  91. Sezer, A.; Kilickap, S.; Gümüş, M.; Bondarenko, I.; Özgüroğlu, M.; Gogishvili, M.; Turk, H.M.; Cicin, I.; Bentsion, D.; Gladkov, O.; et al. Cemiplimab monotherapy for first-line treatment of advanced non-small-cell lung cancer with PD-L1 of at least 50%: A multicentre, open-label, global, phase 3, randomised, controlled trial. Lancet 2021, 397, 592–604. [Google Scholar] [CrossRef] [PubMed]
  92. Huang, J.; Xu, J.; Chen, Y.; Zhuang, W.; Zhang, Y.; Chen, Z.; Chen, J.; Zhang, H.; Niu, Z.; Fan, Q.; et al. Camrelizumab versus investigator’s choice of chemotherapy as second-line therapy for advanced or metastatic oesophageal squamous cell carcinoma (ESCORT): A multicentre, randomised, open-label, phase 3 study. Lancet Oncol. 2020, 21, 832–842. [Google Scholar] [CrossRef] [PubMed]
  93. Sugawara, S.; Lee, J.S.; Kang, J.H.; Kim, H.R.; Inui, N.; Hida, T.; Lee, K.H.; Yoshida, T.; Tanaka, H.; Yang, C.T.; et al. Nivolumab with carboplatin, paclitaxel, and bevacizumab for first-line treatment of advanced nonsquamous non-small-cell lung cancer. Ann. Oncol. 2021, 32, 1137–1147. [Google Scholar] [CrossRef] [PubMed]
  94. Powles, T.; Tomczak, P.; Park, S.H.; Venugopal, B.; Ferguson, T.; Hajek, J.; Gurney, H.; Chang, Y.H.; Lee, J.L.; Sarwar, N.; et al. Pembrolizumab versus placebo as post-nephrectomy adjuvant therapy for clear cell renal cell carcinoma (KEYNOTE-564): 30-month follow-up analysis of a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2022, 23, 1133–1144. [Google Scholar] [CrossRef] [PubMed]
  95. Boyer, M.; Sendur, M.A.N.; Rodriguez-Abreu, D.; Park, K.; Lee, D.H.; Cicin, I.; Yumuk, P.F.; Orlandi, F.J.; Leal, T.A.; Molinier, O.; et al. Pembrolizumab Plus Ipilimumab or Placebo for Metastatic Non-Small-Cell Lung Cancer with PD-L1 Tumor Proportion Score >= 50%: Randomized, Double-Blind Phase III KEYNOTE-598 Study. J. Clin. Oncol. 2021, 39, 2327–2338. [Google Scholar] [CrossRef]
  96. Zhou, C.; Huang, D.; Fan, Y.; Yu, X.; Liu, Y.; Shu, Y.; Ma, Z.; Wang, Z.; Cheng, Y.; Wang, J.; et al. Tislelizumab versus Docetaxel in Patients with Previously Treated Advanced NSCLC (RATIONALE-303): A Phase 3, Open-Label, Randomized Controlled Trial. J. Thorac. Oncol. 2023, 18, 93–105. [Google Scholar] [CrossRef]
  97. Finn, R.S.; Qin, S.; Ikeda, M.; Galle, P.R.; Ducreux, M.; Kim, T.Y.; Kudo, M.; Breder, V.; Merle, P.; Kaseb, A.O.; et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. N. Engl. J. Med. 2020, 382, 1894–1905. [Google Scholar] [CrossRef] [PubMed]
  98. Mai, H.Q.; Chen, Q.Y.; Chen, D.; Hu, C.; Yang, K.; Wen, J.; Li, J.; Shi, Y.R.; Jin, F.; Xu, R.; et al. Toripalimab or placebo plus chemotherapy as first-line treatment in advanced nasopharyngeal carcinoma: A multicenter randomized phase 3 trial. Nat. Med. 2021, 27, 1536–1543. [Google Scholar] [CrossRef]
  99. Wang, J.; Lu, S.; Yu, X.; Hu, Y.; Sun, Y.; Wang, Z.; Zhao, J.; Yu, Y.; Hu, C.; Yang, K.; et al. Tislelizumab Plus Chemotherapy vs Chemotherapy Alone as First-line Treatment for Advanced Squamous Non-Small-Cell Lung Cancer: A Phase 3 Randomized Clinical Trial. JAMA Oncol. 2021, 7, 709–717. [Google Scholar] [CrossRef]
  100. Zhang, L.; Wang, Z.; Fang, J.; Yu, Q.; Han, B.; Cang, S.; Chen, G.; Mei, X.; Yang, Z.; Stefaniak, V.; et al. Final overall survival data of sintilimab plus pemetrexed and platinum as First-Line treatment for locally advanced or metastatic nonsquamous NSCLC in the Phase 3 ORIENT-11 study. Lung Cancer 2022, 171, 56–60. [Google Scholar] [CrossRef]
  101. Yang, Y.; Wang, Z.; Fang, J.; Yu, Q.; Han, B.; Cang, S.; Chen, G.; Mei, X.; Yang, Z.; Ma, R.; et al. Efficacy and Safety of Sintilimab Plus Pemetrexed and Platinum as First-Line Treatment for Locally Advanced or Metastatic Nonsquamous NSCLC: A Randomized, Double-Blind, Phase 3 Study (Oncology pRogram by InnovENT anti-PD-1-11). J. Thorac. Oncol. 2020, 15, 1636–1646. [Google Scholar] [CrossRef] [PubMed]
  102. Luo, H.; Lu, J.; Bai, Y.; Mao, T.; Wang, J.; Fan, Q.; Zhang, Y.; Zhao, K.; Chen, Z.; Gao, S.; et al. Effect of Camrelizumab vs Placebo Added to Chemotherapy on Survival and Progression-Free Survival in Patients with Advanced or Metastatic Esophageal Squamous Cell Carcinoma: The ESCORT-1st Randomized Clinical Trial. JAMA 2021, 326, 916–925. [Google Scholar] [CrossRef] [PubMed]
  103. Wang, J.; Zhou, C.; Yao, W.; Wang, Q.; Min, X.; Chen, G.; Xu, X.; Li, X.; Xu, F.; Fang, Y.; et al. Adebrelimab or placebo plus carboplatin and etoposide as first-line treatment for extensive-stage small-cell lung cancer (CAPSTONE-1): A multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2022, 23, 739–747. [Google Scholar] [CrossRef] [PubMed]
  104. Zhou, Q.; Chen, M.; Jiang, O.; Pan, Y.; Hu, D.; Lin, Q.; Wu, G.; Cui, J.; Chang, J.; Cheng, Y.; et al. Sugemalimab versus placebo after concurrent or sequential chemoradiotherapy in patients with locally advanced, unresectable, stage III non-small-cell lung cancer in China (GEMSTONE-301): Interim results of a randomised, double-blind, multicentre, phase 3 trial. Lancet Oncol. 2022, 23, 209–219. [Google Scholar] [CrossRef] [PubMed]
  105. Lu, S.; Wu, L.; Jian, H.; Chen, Y.; Wang, Q.; Fang, J.; Wang, Z.; Hu, Y.; Sun, M.; Han, L.; et al. Sintilimab plus bevacizumab biosimilar IBI305 and chemotherapy for patients with EGFR-mutated non-squamous non-small-cell lung cancer who progressed on EGFR tyrosine-kinase inhibitor therapy (ORIENT-31): First interim results from a randomised, double-blind, multicentre, phase 3 trial. Lancet Oncol. 2022, 23, 1167–1179. [Google Scholar] [CrossRef]
  106. Wang, Z.X.; Cui, C.; Yao, J.; Zhang, Y.; Li, M.; Feng, J.; Yang, S.; Fan, Y.; Shi, J.; Zhang, X.; et al. Toripalimab plus chemotherapy in treatment-naïve, advanced esophageal squamous cell carcinoma (JUPITER-06): A multi-center phase 3 trial. Cancer Cell 2022, 40, 277–288.e273. [Google Scholar] [CrossRef] [PubMed]
  107. Cheng, Y.; Han, L.; Wu, L.; Chen, J.; Sun, H.; Wen, G.; Ji, Y.; Dvorkin, M.; Shi, J.; Pan, Z.; et al. Effect of First-Line Serplulimab vs Placebo Added to Chemotherapy on Survival in Patients with Extensive-Stage Small Cell Lung Cancer: The ASTRUM-005 Randomized Clinical Trial. JAMA 2022, 328, 1223–1232. [Google Scholar] [CrossRef]
  108. Gogishvili, M.; Melkadze, T.; Makharadze, T.; Giorgadze, D.; Dvorkin, M.; Penkov, K.; Laktionov, K.; Nemsadze, G.; Nechaeva, M.; Rozhkova, I.; et al. Cemiplimab plus chemotherapy versus chemotherapy alone in non-small cell lung cancer: A randomized, controlled, double-blind phase 3 trial. Nat. Med. 2022, 28, 2374–2380. [Google Scholar] [CrossRef]
  109. Eggermont, A.M.M.; Kicinski, M.; Blank, C.U.; Mandala, M.; Long, G.V.; Atkinson, V.; Dalle, S.; Haydon, A.; Khattak, A.; Carlino, M.S.; et al. Association between Immune-Related Adverse Events and Recurrence-Free Survival among Patients with Stage III Melanoma Randomized to Receive Pembrolizumab or Placebo: A Secondary Analysis of a Randomized Clinical Trial. JAMA Oncol. 2020, 6, 519–527. [Google Scholar] [CrossRef]
  110. Finn, R.S.; Ryoo, B.Y.; Merle, P.; Kudo, M.; Bouattour, M.; Lim, H.Y.; Breder, V.; Edeline, J.; Chao, Y.; Ogasawara, S.; et al. Pembrolizumab as Second-Line Therapy in Patients with Advanced Hepatocellular Carcinoma in KEYNOTE-240: A Randomized, Double-Blind, Phase III Trial. J. Clin. Oncol. 2020, 38, 193–202. [Google Scholar] [CrossRef]
  111. Hodi, F.S.; Chesney, J.; Pavlick, A.C.; Robert, C.; Grossmann, K.F.; McDermott, D.F.; Linette, G.P.; Meyer, N.; Giguere, J.K.; Agarwala, S.S.; et al. Combined nivolumab and ipilimumab versus ipilimumab alone in patients with advanced melanoma: 2-year overall survival outcomes in a multicentre, randomised, controlled, phase 2 trial. Lancet Oncol. 2016, 17, 1558–1568. [Google Scholar] [CrossRef] [PubMed]
  112. Rini, B.I.; Plimack, E.R.; Stus, V.; Gafanov, R.; Hawkins, R.; Nosov, D.; Pouliot, F.; Alekseev, B.; Soulières, D.; Melichar, B.; et al. Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N. Engl. J. Med. 2019, 380, 1116–1127. [Google Scholar] [CrossRef] [PubMed]
  113. Oremus, M.; Wolfson, C.; Perrault, A.; Demers, L.; Momoli, F.; Moride, Y. Interrater reliability of the modified Jadad quality scale for systematic reviews of Alzheimer’s disease drug trials. Dement. Geriatr. Cogn. Disord. 2001, 12, 232–236. [Google Scholar] [CrossRef] [PubMed]
  114. DerSimonian, R.; Kacker, R. Random-effects model for meta-analysis of clinical trials: An update. Contemp. Clin. Trials 2007, 28, 105–114. [Google Scholar] [CrossRef] [PubMed]
  115. Higgins, J.P.; Thompson, S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 2002, 21, 1539–1558. [Google Scholar] [CrossRef]
  116. Higgins, J.P.; Thompson, S.G.; Deeks, J.J.; Altman, D.G. Measuring inconsistency in meta-analyses. BMJ (Clin. Res. Ed.) 2003, 327, 557–560. [Google Scholar] [CrossRef]
  117. Begg, C.B.; Mazumdar, M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994, 50, 1088–1101. [Google Scholar] [CrossRef]
  118. Egger, M.; Davey Smith, G.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ (Clin. Res. Ed.) 1997, 315, 629–634. [Google Scholar] [CrossRef]
  119. Duval, S.; Tweedie, R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000, 56, 455–463. [Google Scholar] [CrossRef]
  120. Schwarzer, G. meta: An R package for meta-analysis. R News 2007, 7, 40–45. [Google Scholar]
  121. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2011; pp. 12–21. [Google Scholar]
  122. Conforti, F.; Pala, L.; Bagnardi, V.; De Pas, T.; Martinetti, M.; Viale, G.; Gelber, R.D.; Goldhirsch, A. Cancer immunotherapy efficacy and patients’ sex: A systematic review and meta-analysis. Lancet Oncol. 2018, 19, 737–746. [Google Scholar] [CrossRef] [PubMed]
  123. Yang, F.; Markovic, S.N.; Molina, J.R.; Halfdanarson, T.R.; Pagliaro, L.C.; Chintakuntlawar, A.V.; Li, R.; Wei, J.; Wang, L.; Liu, B.; et al. Association of Sex, Age, and Eastern Cooperative Oncology Group Performance Status with Survival Benefit of Cancer Immunotherapy in Randomized Clinical Trials: A Systematic Review and Meta-analysis. JAMA Netw. Open 2020, 3, e2012534. [Google Scholar] [CrossRef] [PubMed]
  124. Cook, M.B.; McGlynn, K.A.; Devesa, S.S.; Freedman, N.D.; Anderson, W.F. Sex disparities in cancer mortality and survival. Cancer Epidemiol. Biomark. Prev. 2011, 20, 1629–1637. [Google Scholar] [CrossRef] [PubMed]
  125. Straface, E.; Gambardella, L.; Brandani, M.; Malorni, W. Sex differences at cellular level: “cells have a sex”. Handb. Exp. Pharmacol. 2012, 214, 49–65. [Google Scholar] [CrossRef]
  126. Zhu, Y.; Shao, X.; Wang, X.; Liu, L.; Liang, H. Sex disparities in cancer. Cancer Lett. 2019, 466, 35–38. [Google Scholar] [CrossRef]
  127. Pala, L.; De Pas, T.; Catania, C.; Giaccone, G.; Mantovani, A.; Minucci, S.; Viale, G.; Gelber, R.D.; Conforti, F. Sex and cancer immunotherapy: Current understanding and challenges. Cancer Cell 2022, 40, 695–700. [Google Scholar] [CrossRef] [PubMed]
  128. Ray, A.L.; Nofchissey, R.A.; Khan, M.A.; Reidy, M.A.; Lerner, M.R.; Wu, X.; Guo, S.; Hill, S.L.; Weygant, N.; Adams, S.F.; et al. The role of sex in the innate and adaptive immune environment of metastatic colorectal cancer. Br. J. Cancer 2020, 123, 624–632. [Google Scholar] [CrossRef]
  129. Lee, J.; Nicosia, M.; Hong, E.S.; Silver, D.J.; Li, C.; Bayik, D.; Watson, D.C.; Lauko, A.; Kay, K.E.; Wang, S.Z.; et al. Sex-Biased T-cell Exhaustion Drives Differential Immune Responses in Glioblastoma. Cancer Discov. 2023, 13, 2090–2105. [Google Scholar] [CrossRef]
  130. Manson, Q.F.; Ter Hoeve, N.D.; Buerger, H.; Moelans, C.B.; van Diest, P.J. PD-1 and PD-L1 Expression in Male Breast Cancer in Comparison with Female Breast Cancer. Target. Oncol. 2018, 13, 769–777. [Google Scholar] [CrossRef]
  131. Gu, Y.; Tang, Y.Y.; Wan, J.X.; Zou, J.Y.; Lu, C.G.; Zhu, H.S.; Sheng, S.Y.; Wang, Y.F.; Liu, H.C.; Yang, J.; et al. Sex difference in the expression of PD-1 of non-small cell lung cancer. Front. Immunol. 2022, 13, 1026214. [Google Scholar] [CrossRef]
  132. Conforti, F.; Pala, L.; Pagan, E.; Corti, C.; Bagnardi, V.; Queirolo, P.; Catania, C.; De Pas, T.; Giaccone, G. Sex-based differences in response to anti-PD-1 or PD-L1 treatment in patients with non-small-cell lung cancer expressing high PD-L1 levels. A systematic review and meta-analysis of randomized clinical trials. ESMO Open 2021, 6, 100251. [Google Scholar] [CrossRef] [PubMed]
  133. Guan, X.; Polesso, F.; Wang, C.; Sehrawat, A.; Hawkins, R.M.; Murray, S.E.; Thomas, G.V.; Caruso, B.; Thompson, R.F.; Wood, M.A.; et al. Androgen receptor activity in T cells limits checkpoint blockade efficacy. Nature 2022, 606, 791–796. [Google Scholar] [CrossRef] [PubMed]
  134. Dai, C.; Dehm, S.M.; Sharifi, N. Targeting the Androgen Signaling Axis in Prostate Cancer. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2023, 41, 4267–4278. [Google Scholar] [CrossRef]
  135. Yang, C.; Jin, J.; Yang, Y.; Sun, H.; Wu, L.; Shen, M.; Hong, X.; Li, W.; Lu, L.; Cao, D.; et al. Androgen receptor-mediated CD8(+) T cell stemness programs drive sex differences in antitumor immunity. Immunity 2022, 55, 1268–1283.e9. [Google Scholar] [CrossRef] [PubMed]
  136. Kwon, H.; Schafer, J.M.; Song, N.J.; Kaneko, S.; Li, A.; Xiao, T.; Ma, A.; Allen, C.; Das, K.; Zhou, L.; et al. Androgen conspires with the CD8(+) T cell exhaustion program and contributes to sex bias in cancer. Sci. Immunol. 2022, 7, eabq2630. [Google Scholar] [CrossRef] [PubMed]
  137. Gupta, S.; Artomov, M.; Goggins, W.; Daly, M.; Tsao, H. Gender Disparity and Mutation Burden in Metastatic Melanoma. J. Natl. Cancer Inst. 2015, 107, djv221. [Google Scholar] [CrossRef] [PubMed]
  138. Van Allen, E.M.; Miao, D.; Schilling, B.; Shukla, S.A.; Blank, C.; Zimmer, L.; Sucker, A.; Hillen, U.; Foppen, M.H.G.; Goldinger, S.M.; et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 2015, 350, 207–211. [Google Scholar] [CrossRef]
  139. Paolino, M.; Koglgruber, R.; Cronin, S.J.F.; Uribesalgo, I.; Rauscher, E.; Harreiter, J.; Schuster, M.; Bancher-Todesca, D.; Pranjic, B.; Novatchkova, M.; et al. RANK links thymic regulatory T cells to fetal loss and gestational diabetes in pregnancy. Nature 2021, 589, 442–447. [Google Scholar] [CrossRef]
  140. Kieffer, T.E.; Faas, M.M.; Scherjon, S.A.; Prins, J.R. Pregnancy persistently affects memory T cell populations. J. Reprod. Immunol. 2017, 119, 1–8. [Google Scholar] [CrossRef]
  141. Venanzi, F.M.; Bini, M.; Nuccio, A.; De Toma, A.; Lambertini, M.; Ogliari, F.R.; Oresti, S.; Viganò, M.G.; Brioschi, E.; Polignano, M.; et al. Sex dimorphism and cancer immunotherapy: May pregnancy solve the puzzle? Cancer Treat. Rev. 2023, 121, 102648. [Google Scholar] [CrossRef]
  142. Yacouba, A.; Tidjani Alou, M.; Lagier, J.C.; Dubourg, G.; Raoult, D. Urinary microbiota and bladder cancer: A systematic review and a focus on uropathogens. Semin. Cancer Biol. 2022, 86, 875–884. [Google Scholar] [CrossRef] [PubMed]
  143. Thackray, V.G. Sex, Microbes, and Polycystic Ovary Syndrome. Trends Endocrinol. Metab. TEM 2019, 30, 54–65. [Google Scholar] [CrossRef] [PubMed]
  144. Wu, Y.; Ju, Q.; Jia, K.; Yu, J.; Shi, H.; Wu, H.; Jiang, M. Correlation between sex and efficacy of immune checkpoint inhibitors (PD-1 and CTLA-4 inhibitors). Int. J. Cancer 2018, 143, 45–51. [Google Scholar] [CrossRef] [PubMed]
  145. Grassadonia, A.; Sperduti, I.; Vici, P.; Iezzi, L.; Brocco, D.; Gamucci, T.; Pizzuti, L.; Maugeri-Saccà, M.; Marchetti, P.; Cognetti, G.; et al. Effect of Gender on the Outcome of Patients Receiving Immune Checkpoint Inhibitors for Advanced Cancer: A Systematic Review and Meta-Analysis of Phase III Randomized Clinical Trials. J. Clin. Med. 2018, 7, 542. [Google Scholar] [CrossRef]
  146. Lahiri, A.; Maji, A.; Potdar, P.D.; Singh, N.; Parikh, P.; Bisht, B.; Mukherjee, A.; Paul, M.K. Lung cancer immunotherapy: Progress, pitfalls, and promises. Mol. Cancer 2023, 22, 40. [Google Scholar] [CrossRef]
  147. Piombino, C.; Tonni, E.; Oltrecolli, M.; Pirola, M.; Pipitone, S.; Baldessari, C.; Dominici, M.; Sabbatini, R.; Vitale, M.G. Immunotherapy in urothelial cancer: Current status and future directions. Expert Rev. Anticancer. Ther. 2023, 23, 1141–1155. [Google Scholar] [CrossRef]
  148. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef]
Cancers 16 00382 g001
Figure 1. Study selection PRISMA (preferred reporting items for systematic reviews and meta-analyses) flowchart for study selection for the systematic review on the effects of ICI, with data analyzed according to male and female subgroups. ICI, immune checkpoint inhibitors.
Figure 1. Study selection PRISMA (preferred reporting items for systematic reviews and meta-analyses) flowchart for study selection for the systematic review on the effects of ICI, with data analyzed according to male and female subgroups. ICI, immune checkpoint inhibitors.
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Cancers 16 00382 g002
Figure 2. Characteristics of the studies. (A) Regional distribution of included studies and comparison of HR size between males and females (better for males represents a smaller HR for males and vice versa). (B) Male-to-female ratio of study subjects, with the number of males to females being approximately 1:1.6. (C,D) Proportion of study subjects by tumor type (C) and ICI drug type (D) to overall counts.
Figure 2. Characteristics of the studies. (A) Regional distribution of included studies and comparison of HR size between males and females (better for males represents a smaller HR for males and vice versa). (B) Male-to-female ratio of study subjects, with the number of males to females being approximately 1:1.6. (C,D) Proportion of study subjects by tumor type (C) and ICI drug type (D) to overall counts.
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Cancers 16 00382 g003
Figure 3. Hazard ratios for death in the intervention and control groups according to sex, with OS as the outcome. (The references cited in the figure are consistent with Table 1).
Figure 3. Hazard ratios for death in the intervention and control groups according to sex, with OS as the outcome. (The references cited in the figure are consistent with Table 1).
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Cancers 16 00382 g004
Figure 4. Subgroup analysis of hazard ratios for death in tumor patients stratified by tumor type and ICI drug type, by sex, with OS as the outcome.
Figure 4. Subgroup analysis of hazard ratios for death in tumor patients stratified by tumor type and ICI drug type, by sex, with OS as the outcome.
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Table 1. Characteristics of included studies in this systematic review and meta-analysis.
Table 1. Characteristics of included studies in this systematic review and meta-analysis.
PhaseTumor TypeLineTreatment GroupsNumber of PatientsNumber of Men (%)Number of Women (%)Median Age,
Years		Median Follow-Up,
Months		OutcomeOverall HR (95% CI)HR (95% CI) for MenHR (95% CI) for Women
Li-Tzong Chen et al. (2020) [10]3Gastrointestinal cancer>1nivolumab vs. placebo493348 (71%)145 (29%)61.727.3OS0.66 (0.54–0.80)0.60 (0.48–0.76)0.79 (0.55–1.15)
Alexander M M Eggermont et al. (2019) [11]3Melanoma>1ipilimumab vs. placebo951589 (62%)362 (38%)NA82.8OS0.73 (0.60–0.90)0.76 (0.55–1.05)0.69 (0.45–1.07)
NANARFS0.76 (0.64–0.89)0.76 (0.58–0.99)0.76 (0.54–1.07)
M. Reck et al. (2021) [12]3NSCLC1nivolumab + ipilimumab + chemo vs. chemo719504 (70%)215 (30%)NA30.7OS0.73 (0.61–0.87)0.72 (0.59–0.88)0.75 (0.54–1.04)
Masanobu Takahashi et al. (2021) [13]3Gastrointestinal cancer>1nivolumab vs. paclitaxel or docetaxel 274230 (84%)44 (16%)NANAOS0.77 (0.59–1.01)0.79 (0.59–1.06)0.75 (0.37–1.55)
Hidetoshi Hayashi et al. (2022) [14]2NSCLC>1nivolumab vs. pemetrexed + carboplatin10243 (42%)59 (58%)NANAPFS1.92 (1.61–2.29)1.92 (1.01–3.67)1.79 (1.04–3.07)
Takashi Kojima et al. (2020) [15]3Gastrointestinal cancer>1pembrolizumab vs. chemo628544 (87%)84 (13%)NANAPFS0.89 (0.75–1.05)0.89 (0.75–1.07)0.90 (0.57–1.43)
Enriqueta Felip et al. (2021) [16]3NSCLC>1atezolizumab vs. best supportive care after adjuvant cisplatin-based chemo17641178 (67%)586 (33%)NA35.3RFS0.79 (0.64–0.96)0.76 (0.59–0.99)0.80 (0.57–1.13)
Makoto Nishio et al. (2021) [17]3NSCLC1atezolizumab + pemetrexed vs. pemetrexed578384 (66%)194 (34%)63.5 (31–85)NAPFS0.60 (0.49–0.72) 0.64 (0.51–0.79)0.51 (0.36–0.71)
OS0.86 (0.71–1.06)0.93 (0.73–1.18)0.76 (0.54–1.09)
Nancy Y Lee et al. (2021) [18]3HNC>1avelumab + chemo vs. placebo + chemo697575 (82%)122 (18%)NA14.6 (8.5–19.6)PFS1.21 (0.93–1.57)1.21 (0.91–1.61)1.16 (0.58–2.33)
Keunchil Park et al. (2021) [19]3NSCLC2avelumab vs. docetaxel529367 (69%)162 (31%)NANAOS0.87 (0.71–1.05)0.82 (0.65–1.03)1.02 (0.72–1.45)
Caicun Zhou et al. (2021) [20]3NSCLC>1camrelizumab + carboplatin + pemetrexed vs. chemo412295 (72%)117 (28%)NA11.9PFS0.60 (0.45–0.79)0.55 (0.40–0.75)0.78 (0.45–1.37)
D. R. Spigel et al. (2021) [21]3SCLC>1nivolumab vs. chemo569351 (62%)218 (38%)NA15.8OS0.87 (0.73–1.05)0.80 (0.63–1.01)1.03 (0.77–1.38)
Caicun Zhou et al. (2022) [22]3NSCLC1sugemalimab vs. placebo479383 (80%)96 (20%)NA8.6PFS0.48 (0.39–0.60)0.48 (0.38–0.62)0.6090.37–0.99)
F Stephen Hodi et al. (2010) [23]3Melanoma>1A: ipilimumab + gp100 vs. gp100676401 (59%)275 (41%)56.2 (NA)21.0 vs. 27.8 vs. 17.2OS0.68 (NA)0.66 (0.50–0.87)0.72 (0.52–0.99)
B: ipilimumab vs. gp1000.66 (NA)0.54 (0.37–0.77)0.81 (0.55–1.20)
Antoni Ribas et al. (2013) [24]3Melanoma1tremelimumab vs. chemo655372 (57%)283 (43%)56.5 (22–90)NAOS0.88 (NA)0.93 (0.74–1.17)0.81 (0.62–1.06)
Caroline Robert et al. (2011) [25]3Melanoma1lpilimumab + dacarbazine vs. dacarbazine + placebo502301 (60%)201 (40%)56.9 (NA)54OS0.72 (0.59–0.87)0.70 (0.55–0.90)0.86 (0.63–1.17)
Ramaswamy Govindan et al. (2017) [26]3NSCLC1Ipilimumab + paclitaxel + carboplatin vs. paclitaxel + carboplatin + placebo749635 (85%)114 (15%)64 (28–85)12.5 vs. 11.8OS0.91 (0.77–1.07)0.85 (0.71–1.02)1.33 (0.84–2.11)
Martin Reck et al. (2016) [27]3SCLC1Ipilimumab + etoposide + platinum vs. placebo + etoposide + platinum954643 (67%)311 (33%)62.5 (36–85)10.5 vs. 10.2OS0.94 (0.81–1.09)1.07 (0.89–1.28)1.06 (0.81–1.37)
Julie Brahmer et al. (2015) [28]3NSCLC>1nivolumab vs. docetaxel272208 (76%)64 (24%)63 (39–85)11OS0.59 (0.44–0.79)0.57 (0.41–0.78)0.67 (0.36–1.25)
Robert J Motzer et al. (2015) [29]3RCC>1nivolumab vs. everolimus821619 (75%)202 (25%)62 (18–88)14OS0.73 (0.57–0.93)0.73 (0.58–0.92)0.84 (0.57–1.24)
Hossein Borghaei et al. (2015) [30]3NSCLC>1nivolumab vs. docetaxel582319 (55%)263 (45%)62 (21–85)13.2OS0.73 (0.59–0.89)0.73 (0.56–0.96)0.78 (0.58–1.04)
James Larkin et al. (2018) [31]3Melanoma>1nivolumab vs. chemo405261 (64%)144 (36%)60 (23–88)NAOS0.92 (0.71–1.18)0.85 (0.62–1.17)1.07 (0.69–1.65)
Caroline Robert et al. (2015) [32]3Melanoma1nivolumab vs. dacarbazine418246 (59%)172 (41%)65 (18–87)8.9 vs. 6.8OS0.42 (0.25–0.73)0.34 (0.22–0.54)0.56 (0.33–0.95)
Michele Maio et al. (2017) [33]2bOthers>1tremelimumab vs. placebo571434 (76%)137 (24%)66.5 (60–73)NAOS0.92 (0.76–1.12)0.91 (0.73–1.13)1.12 (0.72–1.75)
Roy S Herbst et al. (2016) [34]2/3NSCLC>1pembrolizumab vs. docetaxel1033634 (61%)399 (39%)62.5 (54–70)13.1PFS0.85 (0.73–0.98)0.78 (0.64–0.94)1.02 (0.78–1.32)
Roy S. Herbst et al. (2021) [35]2/3NSCLC>1pembrolizumab vs. docetaxel1033634 (61%)399 (39%)NA67.4OS0.70 (0.61–0.80)0.71 (0.60–0.86)0.66 (0.53–0.84)
Louis Fehrenbacher et al. (2018) [36]3NSCLC>1atezolizumab vs. docetaxel1225467 (38%)758 (62%)63.5 (25–85)28OS0.80 (0.70–0.92)0.81 (0.65–1.01)0.79 (0.66–0.93)
David P Carbone et al. (2017) [37]3NSCLC1nivolumab vs. chemo541332 (61%)209 (39%)64 (29–89)13.5OS1.02 (0.80–1.30)0.97 (0.74–1.26)1.15 (0.79–1.66)
Robert L Ferris et al. (2016) [38]3HNC>1nivolumab vs. chemo361300 (83%)61 (17%)60 (28–83)5.1OS0.70 (0.51–0.96)0.65 (0.48–0.88)0.93 (0.47–1.85)
Scott J Antonia et al. (2018) [39]3NSCLC>1durvalumab vs. placebo713500 (70%)213 (30%)NA25.2OS0.68 (0.54–0.86)0.78 (0.59–1.03)0.46 (0.30–0.73)
Pier Francesco Ferrucci et al. (2020) [40]2Melanoma>1pembrolizumab + dabrafenib + trametinib vs. placebo + dabrafenib + trametinib12069 (58%)51 (43%)56 (18–83)36.6PFS0.53 (0.34–0.83)0.45 (0.25–0.82)0.79 (0.41–1.53)
OS0.64 (0.38–1.06)0.62 (0.31–1.25)0.64 (0.30–1.38)
Martin Reck et al. (2019) [41]3NSCLC1pembrolizumab vs. platinum-based chemo305187 (61%)118 (39%)65.2 (33–90)25.2OS0.63 (0.47–0.86)0.54 (0.36–0.79)0.95 (0.56–1.62)
Tony S K Mok et al. (2019) [42]3NSCLC1pembrolizumab vs. chemo1274902 (71%)372 (29%)63 (57–69)12.8OS0.81 (0.71–0.93)0.80 (0.68–0.94)0.89 (0.68–1.17)
Robert J Motzer et al. (2022) [43]3RCC1nivolumab + ipilimumab vs. sunitinib636477 (75%)159 (25%)62 (21–85)67.7OS0.94 (0.65–1.37)0.81 (0.68–0.97)0.62 (0.45–0.84)
Ezra E W Cohen et al. (2019) [44]3HNC>1pembrolizumab vs. standard of care495412 (83%)83 (17%)60.0 (54–66)7.5OS0.80 (0.65–0.98)0.77 (0.62–0.96)0.94 (0.54–1.63)
Joaquim Bellmunt et al. (2017) [45]3Urothelial carcinoma>1pembrolizumab vs. chemo542402 (74%)140 (26%)66 (26–88)14.1OS0.73 (0.59–0.91)0.73 (0.56–0.94)0.78 (0.49–1.24)
Barbara Burtness et al. (2019) [46]3HNC1A: pembrolizumab vs. cetuximab + chemo601511 (85%)90 (15%)61.3 (54.5–68)11.5 vs. 13.0 vs. 10.7OS0.81 (0.68–0.97)0.80 (0.66–0.97)0.89 (0.56–1.41)
B: pembrolizumab + chemo vs. cetuximab + chemo559466 (83%)93 (17%)0.72 (0.60–0.86)0.72 (0.59–0.89)0.67 (0.42–1.06)
Alexander M M Eggermont et al. (2021) [47]3Melanoma>1pembrolizumab vs. placebo1019628 (62%)391 (38%)NA42.3PFS0.60 (0.49–0.73)0.56 (0.41–0.77)0.68 (0.44–1.05)
Martin Reck et al. (2019) [48] 3NSCLC1atezolizumab + bevacizumab + carboplatin + paclitaxel vs. bevacizumab + carboplatin + paclitaxel800479 (60%)321 (40%)63 (31–90)19.6 vs. 19.7OS0.76 (0.63–0.93)0.73 (0.57–0.93)0.82 (0.61–1.12)
Howard West et al. (2019) [49]3NSCLC1atezolizumab + carboplatin + nabpaclitaxel vs. chemo679400 (59%)279 (41%)64.3 (18–86)18.5 vs. 19.2OS0.80 (0.65–0.99)0.87 (0.66–1.15)0.66 (0.46–0.93)
Robert Jotte et al. (2020) [50]3NSCLC1atezolizumab + carboplatin + nab-paclitaxel vs. carboplatin + nab-paclitaxel683557 (82%)126 (18%)65 (23–83) vs. 65 (38–86)26.8 vs. 24.8OS0.88 (0.73–1.05)0.91 (0.75–1.12)0.68 (0.44–1.04)
PFS0.71 (0.60–0.85)0.71 (0.59–0.85)0.66 (0.45–0.97)
Charles S. Fuchs et al. (2022) [51]3Gastrointestinal cancer>1pembrolizumab vs. paclitaxel395286 (72%)109 (28%)NANAOS0.81 (0.66–1.00)0.87 (0.68–1.11)0.77 (0.50–1.18)
Fabrice Barlesi et al. (2018) [52]3NSCLC>1avelumab vs. docetaxel529367 (69%)162 (31%)63.5 (56–70)18.3OS0.90 (0.73–1.12)0.83 (0.64–1.08)1.08 (0.74–1.59)
Roy S Herbst et al. (2020) [53]3NSCLC1atezolizumab vs. chemo205143 (70%)62 (30%)NANAOS0.59 (0.40–0.89)0.57 (0.35–0.93)0.69 (0.34–1.39)
Joaquim Bellmunt et al. (2021) [54]3Urothelial carcinoma>1atezolizumab vs. observation809638 (79%)171 (21%)NA21.9RFS0.89 (0.74–1.08)0.91 (0.73–1.13)1.00 (0.79–1.29)
Naiyer A Rizvi et al. (2020) [55] 3NSCLC1durvalumab vs. chemo325219 (67%)106 (33%)64.2 (32–85)30.2OS0.76 (0.56–1.02)0.81 (0.59–1.11)0.66 (0.41–1.04)
Luis G Paz-Ares et al. (2022) [56]3NSCLC1nivolumab + ipilimumab vs. chemo1166778 (67%)388 (33%)NA54.8OS0.74 (0.65–0.84)0.67 (0.57–0.78)0.88 (0.70–1.11)
Hirotsugu Kenmotsu et al. (2022) [57]3NSCLC>1atezolizumab vs. best supportive care7458 (78%)16 (22%)64.0 (40–75) vs. 68.0 (37–74)38.3RFS0.52 (0.25–1.08)0.50 (0.21–1.17)0.66 (0.16–2.73)
Kohei Shitara et al. (2020) [58]3Gastrointestinal cancer1A: pembrolizumab vs. chemo506359 (71%)147 (29%)61.7 (20–87)29.4OS0.91 (0.74–1.1)0.88 (0.70–1.11)0.90 (0.63–1.27)
B: pembrolizumab + chemo vs. chemo507374 (74%)133 (26%)62.2 (22–87)OS0.85 (0.7–1.03)0.84 (0.67–1.05)0.89 (0.62–1.29)
Mary O’Brien et al. (2022) [59]3NSCLC>1Pembrolizumab vs. placebo1177804 (68%)373 (32%)65 (59–70)35.6RFS0.76 (0.63–0.91)0.81 (0.65–1.01)0.73 (0.54–1.00)
Kenneth F Grossmann et al. (2022) [60]3Melanoma>1pembrolizumab vs. standard of care1201678 (56%)523 (44%)53 (20, 82) vs. 54 (18, 86)47.5OS0.82 (0.62–1.07)0.7 (0.43–1.15)0.87 (0.63–1.21)
RFS0.76 (0.64–0.91)0.75 (0.55–1.03)0.76 (0.62–0.93)
Thomas Powles et al. (2020) [61]3Urothelial carcinoma1durvalumab + tremelimumab vs. chemo686530 (77%)156 (23%)68 (60–73)41.2OS0.85 (0.72–1.02)0.84 (0.69–1.02)0.90 (0.63–1.30)
Elisabeth Livingstone et al. (2022) [62]2Melanoma>1A: nivolumab + ipilimumab vs. placebo10864 (59%)44 (41%)55.0 (46.0–65.0)49.2RFS0.25 (0.13–0.48)0.33 (0.17–0.66)0.17 (0.07–0.44)
B: nivolumab vs. placebo11164 (58%)47 (42%)55.0 (46.0–65.1)49.2RFS0.60 (0.36–1.00)0.80 (0.45–1.41)0.43 (0.21–0.87)
Taofeek K Owonikoko et al. (2021) [63]3SCLC>1A: chemo + nivolumab + ipilimumab 554355 (64%)199 (36%)NANAOS0.92 (0.76–1.12)0.99 (0.78–1.27)0.82 (0.58–1.14)
B: chemo +nivolumab vs. chemo + placebo555352 (63%)203 (37%)OS0.83 (0.63–1.01)0.89 (0.70–1.14)0.75 (0.54–1.04)
Luis A Diaz Jr. et al. (2022) [64]3Gastrointestinal cancer1pembrolizumab vs. mFOLFOX6307153 (50%)154 (50%)63 (50–73)NAOS0.74 (0.53–1.03)0.61 (0.38–0.99)0.88 (0.55–1.41)
Thierry André et al. (2020) [65] 3Gastrointestinal cancer1pembrolizumab vs. chemo307153 (50%)154 (50%)63 (24–93)32.4PFS0.60 (0.45–0.80)0.59 (0.38–0.90)0.58 (0.39–0.87)
Ken Kato et al. (2019) [66]3Gastrointestinal cancer2nivolumab vs. chemo419364 (87%)55 (13%)65.5 (57–72)10.5 vs. 8.0OS0.77 (0.62–0.95)0.79 (0.63–0.99)0.72 (0.38–1.36)
D Rodríguez-Abreu et al. (2021) [67]3NSCLC1pemetrexed + platinum + pembrolizumab vs. pemetrexed + platinum616363 (59%)253 (41%)64.5 (34–84)31OS0.56 (0.46–0.69) 0.74 (0.56–0.96) 0.41 (0.30–0.56)
PFS0.49 (0.41–0.59)0.58 (0.46–0.74)0.39 (0.29–0.52)
Thomas Powles et al. (2020) [68] 3Urothelial carcinoma>1avelumab + best support care vs. best support care700541 (77%)159 (23%)68.5 (32–90)NAOS0.69 (0.56–0.86)0.64 (0.50–0.83)0.89 (0.56–1.41)
PFS0.62 (0.52–0.75)0.60 (0.49–0.74)0.69 (0.47–1.01)
Markus Moehler et al. (2021) [69]3Gastrointestinal cancer1avelumab vs. chemo499331 (66%)168 (34%)NANAOS0.90 (0.74–1.11)0.83 (0.64–1.07)1.06 (0.76–1.49)
Y-J Bang et al. (2018) [70]3Gastrointestinal cancer>1avelumab vs. chemo371267 (72%)104 (28%)60 (18–86)10.6OS1.1 (0.90–1.40)0.99 (0.75–1.32)1.54 (0.99–2.38)
D.F. Bajorin et al. (2021) [71]3Urothelial carcinoma>1nivolumab vs. placebo709540 (76%)169 (24%)NANARFS0.70 (0.57–0.86)0.68 (0.54–0.87)0.76 (0.50–1.16)
T. K. Choueiri et al. (2020) [72]3RCC1avelumab + axitinib vs. sunitinib886660 (74%)226 (26%)NANAPFS 0.688 (0.574–0.825) 0.647 (0.524–0.798) 0.862 (0.604–1.229)
OS0.796 (0.616- 1.027)0.797 (0.594–1.071)0.814 (0.486–1.364)
Xiaofei Zhu et al. (2022) [73]2Gastrointestinal cancer>1stereotactic body radiotherapy + pembrolizumab + trametinib vs. SBRT + gemcitabine170105 (62%)65 (38%)NA13.1OS; PFSOS: 0.69 (0.51–0.95); PFS: 0.60 (0.44–0.81)OS: 0.62 (0.42–0.92); PFS: 0.52 (0.35–0.77)OS: 0.86 (0.52–1.40); PFS: 0.76 (0.47–1.24)
R.J. Kelly et al. (2021) [74]3Gastrointestinal cancer>1nivolumab vs. placebo532671 (126%)123 (23%)NA24.4RFS0.70 (0.58–0.86)0.73 (0.59–0.91)0.59 (0.35–1.00)
Yoon-Koo Kang et al. (2022) [75]2/3Gastrointestinal cancer>1nivolumab + chemo vs. placebo + chemo724523 (72%)201 (28%)NA11.6PFS0.68 (0.51–0.90) 0.70 (0.54–0.90)0.72 (0.48–1.10)
OS0.90 (0.75–1.08)0.87 (0.70–1.07)0.99 (0.70–1.39)
Stephen V. Liu et al. (2021) [76]1/3SCLC1carboplatin + etoposide (CP/ET) + atezolizumab vs. CP/ET + placebo403261 (65%)142 (35%)NANAOS0.76 (0.60–0.95)0.83 (0.63–1.10)0.64 (0.43–0.94)
Luis Paz-Ares et al. (2018) [77]3NSCLC1pembrolizumab + chemo vs. placebo + chemo559455 (81%)104 (19%)65 (29–88)7.8OS0.64 (0.49–0.85)0.69 (0.51–0.94)0.42 (0.22–0.81)
Matthew D Galsky et al. (2020) [78]3Urothelial carcinoma>1atezolizumab + chemo vs. chemo1213636 (52%)215 (18%)69 (62–75) vs. 67 (61–73)11.8OS0.84 (0.69–1.00)0.83 (0.67–1.02)0.88 (0.61–1.26)
PFS0.81 (0.69–0.94)0.83 (0.69–0.99)0.75 (0.55–1.02)
R. Motzer et al. (2021) [79]3RCC>1lenvatinib + pembrolizumab vs. sunitinib712530 (74%)209 (26%)NANAPFS0.39 (0.32–0.49)0.38 (0.30–0.49)0.42 (0.27–0.66)
Eric X. Chen et al. (2020) [80]2Gastrointestinal cancer>1tremelimumab + durvalumab + BSC vs. BSC180121 (67%)59 (33%)65 (36–87)15.2OS0.72 (0.54–0.97)0.79 (0.57–1.10)0.55 (0.32–0.95)
Tianshu Liu et al. (2022) [81]3Gastrointestinal cancer1nivolumab + chemo vs. chemo156105 (67%)51 (33%)60.5 (23–85)14.0 vs. 9.9OS0.54 (0.37–0.79)0.52 (0.33–0.83)0.68 (0.30–1.11)
Daniel J. Renouf et al. (2022) [82]2Gastrointestinal cancer>1gemcitabine + nab-paclitaxel + durvalumab + tremelimumab vs. gemcitabine + nab-paclitaxe18093 (52%)87 (48%)64.3 (29–84)28.5OS0.94 (0.71–1.25)1.00 (0.66–1.64)0.84 (0.57–1.26)
S. Peters et al. (2022) [83]3Others 1nivolumab + ipilimumab vs. chemo605467 (77%)138 (23%)69 (62–75)43.1OS0.75 (0.63–0.90)0.73 (0.60–0.90)0.82 (0.56–1.20)
Ralf Gutzmer et al. (2020) [84]3Melanoma1atezolizumab + vemurafenib + cobimetinib vs. placebo + vemurafenib + cobimetinib514299 (58%)215 (42%)54.0 (44.8–64.0) vs. 53.5 (43.0–63.8)18.9PFS0.77 (0.62–0.96)0.75 (0.56–1.01)0.81 (0.58–1.13)
S. Popat et al. (2020) [85]3Others>1pembrolizumab vs. chemo144118 (82%)26 (18%)NANAOS1.11 (0.73–1.66)1.16 (0.74–1.82)0.91 (0.34–2.45)
Sumanta Kumar Pal et al. (2022) [86]3RCC>1atezolizumab vs. placebo778565 (73%)213 (27%)60 (52–69)45RFS0.93 (0.75–1.15)1.08 (0.84–1.39)0.61 (0.40–0.94)
L. Paz-Ares et al. (2022) [87]3SCLC1A: durvalumab + EP vs. EP537374 (70%)163 (30%)NA39.4OS0.71 (0.60–0.86)0.76 (0.62–0.95)0.60 (0.42–0.84)
B: durvalumab + tremelimumab + EP vs. EP537386 (72%)151 (28%)NA39.4OS0.81 (0.67–0.97)0.81 (0.65–1.00)0.74 (0.52–1.05)
Jean-Louis Pujol et al. (2019) [88]2SCLC2atezolizumab vs. chemo7343 (59%)30 (41%)64.7 (51.1–85.5)13.7OS0.84 (0.45–1.58)0.82 (0.36–1.91)0.74 (0.26–2.07)
Dean A. Fennell et al. (2021) [89]3Others>1nivolumab vs. placebo332253 (76%)79 (24%)NA11.6PFS0.67 (0.53–0.85) 0.65 (0.49–0.86) 0.69 (0.42–1.14)
OS0.69 (0.52–0.91)0.63 (0.46–0.87)0.96 (0.51–1.79)
Charles M Rudin et al. (2020) [90]3SCLC1pembrolizumab + EP vs. placebo + EP453294 (65%)159 (35%)64.5 (24–83)NAPFS0.73 (0.60–0.88)0.66 (0.52–0.84)0.76 (0.54–1.06)
OS0.80 (0.64–0.98)0.76 (0.59–0.98)0.88 (0.61–1.26)
Ahmet Sezer et al. (2021) [91]3NSCLC1cemiplimab vs. platinum-doublet chemo463479 (103%)84 (18%)NANAOS 0.57 (0.42–0.77) 0.50 (0.36–0.69) 1.11 (0.49–2.52)
PFS0.54 (0.43–0.68)0.50 (0.40–0.64)0.79 (0.43–1.46)
Jing Huang et al. (2020) [92]3Gastrointestinal cancer2camrelizumab vs. chemo448400 (89%)48 (11%)60 (54–65)8.3 vs. 6.2OS0.71 (0.57–0.87)0.75 (0.60–0.93)0.45 (0.21–0.93)
S. Sugawara et al. (2021) [93]3NSCLC1nivolumab + carboplatin, paclitaxel and bevacizumab vs. chemo + carboplatin, paclitaxel and bevacizumab550411 (75%)139 (25%)NANAPFS0.57 (0.46–0.72)0.53 (0.41–0.69)0.72 (0.45–1.15)
Thomas Powles et al. (2022) [94]3RCC>1pembrolizumab vs. placebo994706 (71%)288 (29%)NA30.1RFS0.63 (0.50–0.80)0.60 (0.45–0.80)0.73 (0.48–1.13)
Michael Boyer et al. (2021) [95]3NSCLC>1ipilimumab vs. saline placebo568393 (69%)174 (31%)NANAOS1.08 (0.85–1.37) 0.97 (0.73–1.29) 1.29 (0.84–1.99)
PFS1.06 (0.86–1.30)1.02 (0.80–1.29)1.15 (0.78–1.69)
Caicun Zhou et al. (2022) [96] 3NSCLC>1tislelizumab vs. docetaxel805622 (77%)183 (23%)NA16OS0.66 (0.56–0.79)0.61 (0.50–0.74)0.95 (0.65–1.38)
Richard S. Finn et al. (2020) [97]3Gastrointestinalcancer>1atezolizumab + bevacizumab vs. sorafenib501414 (83%)87 (17%)NANAOS0.60 (0.44–0.82)0.66 (0.47–0.92)0.35 (0.15–0.81)
PFS0.59 (0.47–0.75)0.59 (0.45–0.77)0.60 (0.34–1.06)
Hai-Qiang Mai et al. (2021) [98]3Others1toripalimab + GP vs. placebo + GP289240 (83%)49 (17%)48 (19–72)NAPFS0.51 (0.356–0.728)0.54 (0.360–0.806)0.41 (0.187–0.889)
Jie Wang et al. (2021) [99]3NSCLC>1A: tislelizumab + PC vs. PC241 218 (90%)23 (10%)62 (34–74)NAPFS0.52 (0.37–0.74) 0.53 (0.37–0.76)0.53 (0.17–1.61)
B: tislelizumab + nab-PC vs. PC240223 (93%)17 (7%)0.48 (0.34–0.68)0.50 (0.35–0.71)0.36 (0.09–1.47)
Li Zhang et al. (2022) [100]3NSCLC1sintilimab + chemo vs. placebo + chemo397303 (76%)94 (24%)NA30.8OS0.65 (0.50–0.85)0.57 (0.43–0.77)0.99 (0.56–1.77)
Yunpeng Yang et al. (2020) [101]3NSCLC1sintilimab + chemo vs. placebo + chemo397303 (76%)94 (24%)61 (30, 75)8.9PFS0.482 (0.362–0.643)0.443 (0.320–0.612)0.603 (0.332–1.098)
Huiyan Luo et al. (2021) [102]3Gastrointestinal cancer>1camrelizumab + chemo vs. placebo + chemo596523 (88%)73 (12%)NA10.8OS0.70 (0.56–0.88)0.69 (0.55–0.88)0.87 (0.42–1.81)
Jie Wang et al. (2022) [103]3SCLC1adebrelimab + chemo vs. placebo + chemo462372 (81%)90 (19%)62 (56–66)13.5OS0.72 (0.58–0.90)0.72 (0.57–0.92)0.62 (0.37–1.05)
Qing Zhou et al. (2022) [104]3NSCLC>1sugemalimab vs. placebo381351 (92%)30 (8%)NANAPFS0.64 (0.48–0.85)0.61 (0.45–0.82)1.40 (0.55–3.57)
Shun Lu et al. (2022) [105]3NSCLC>1sintilimab + bevacizumab biosimilar IBI305 + pemetrexed + cisplatin vs. pemetrexed + cisplatin299123 (41%)176 (59%)NANAPFS0.46 (0.34–0.64)0.67 (0.41–1.09)0.44 (0.30–0.66)
Zi-Xian Wang et al. (2022) [106]3Gastrointestinal cancer>1toripalimab + TP vs. placebo + TP514437 (85%)77 (15%)NANAPFS0.57 (0.45–0.72) 0.51 (0.40–0.66)0.96 (0.53–1.75)
OS0.59 (0.43–0.80)0.50 (0.36–0.70)1.40 (0.60–3.28)
Ying Cheng et al. (2022) [107]3SCLC1serplulimab + chemo vs. placebo + chemo585481 (82%)104 (18%)61.112.3OS0.63 (0.49–0.82)0.64 (0.48–0.84)0.57 (0.30–1.06)
Miranda Gogishvili et al. (2022) [108]3NSCLC1cemiplimab + chemo vs. placebo + chemo312268 (86%)44 (14%)63.0 (57–68)16.3 vs. 16.7OS0.71 (0.53–0.93)0.55 (0.41–0.74)2.11 (0.89–5.03)
PFS0.56 (0.44–0.70)0.48 (0.37–0.61)0.90 (0.50–1.62)
Alexander M. M. Eggermont et al. (2020) [109]3Melanoma>1pembrolizumab vs. placebo1019628 (62%)391 (38%)54 (19–88)36.6RFS0.56 (0.47–0.68)0.55 (0.40–0.74)0.60 (0.40–0.90)
Richard S. Finn et al. (2020) [110] 3Gastrointestinal cancer>1pembrolizumab + BSC vs. placebo + BSC413338 (82%)75 (18%)13.8NAOS0.78 (0.61–1.00)0.76 (0.58–1.00)0.80 (0.44–1.47)
PFS0.72 (0.57–0.90)0.74 (0.57–0.95)0.59 (0.33–1.06)
F. Stephen Hodi et al. (2016) [111]2Melanoma>1nivolumab and ipilimumab vs. ipilimumab14295 (67%)47 (33%)6524.5OS0.74 (0.43–1.26)0.65 (0.33–1.26)0.89 (0.36–2.19)
Brian I. Rini et al. (2019) [112]3RCC>1pembrolizumab + axitinib vs. sunitinib861628 (73%)233 (27%)61.512.8OS0.53 (0.38–0.74)0.54 (0.37–0.80)0.45 (0.25–0.83)
PFS0.69 (0.57–0.84)0.77 (0.61–0.97)0.54 (0.37–0.81)
BSC: best supportive care; EP: carboplatin or cisplatin + etoposide; TP: paclitaxel + cisplatin.
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MDPI and ACS Style

Zhong, X.; Sun, J.; Zeng, N.; Xiong, Y.; An, Y.; Wang, S.; Xia, Q. The Effect of Sex on the Therapeutic Efficiency of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials. Cancers 2024, 16, 382. https://doi.org/10.3390/cancers16020382

AMA Style

Zhong X, Sun J, Zeng N, Xiong Y, An Y, Wang S, Xia Q. The Effect of Sex on the Therapeutic Efficiency of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials. Cancers. 2024; 16(2):382. https://doi.org/10.3390/cancers16020382

Chicago/Turabian Style

Zhong, Xingyu, Jianxuan Sun, Na Zeng, Yifan Xiong, Ye An, Shaogang Wang, and Qidong Xia. 2024. "The Effect of Sex on the Therapeutic Efficiency of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials" Cancers 16, no. 2: 382. https://doi.org/10.3390/cancers16020382

APA Style

Zhong, X., Sun, J., Zeng, N., Xiong, Y., An, Y., Wang, S., & Xia, Q. (2024). The Effect of Sex on the Therapeutic Efficiency of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials. Cancers, 16(2), 382. https://doi.org/10.3390/cancers16020382

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