Sleep Quality and Its Determinants Among Patients with Metastatic Cancer Treated with Immune Checkpoint Inhibitors: A Two-Center Cross-Sectional Study
by
,
Betul Aktepe
1,
Tugce Ulasli
2,
Pinar Ezgi Dama
2,
Ilkay Tugba Unek
2,
Aziz Karaoglu
2,
Mehmet Hamid Boztas
3,
Suayib Yalcin
4 and
Oktay Halit Aktepe
2,* 1
Department of Psychiatry, Urla State Hospital, Ministry of Health, Izmir 35430, Turkey
2
Department of Medical Oncology, Dokuz Eylul University, Izmir 35330, Turkey
3
Department of Psychiatry, Bolu Abant Izzet Baysal University, Bolu 14030, Turkey
4
Department of Medical Oncology, Hacettepe University Cancer Institute, Ankara 06230, Turkey
*
Author to whom correspondence should be addressed.
Medicina 2025, 61(12), 2131; https://doi.org/10.3390/medicina61122131 (registering DOI)
Submission received: 24 October 2025
/
Revised: 24 November 2025
/
Accepted: 27 November 2025
/
Published: 28 November 2025
(This article belongs to the Section Oncology)
Abstract
Background and Objectives: Sleep disturbance (SD) is common among cancer patients and may be influenced by immune-related mechanisms during immune checkpoint inhibitor (ICI) therapy. This study evaluated the prevalence and predictors of SD in patients receiving ICIs. Materials and Methods: This retrospective, two-center study included 187 patients with advanced or metastatic cancers. Sleep quality was assessed at three months using the Pittsburgh Sleep Quality Index (PSQI). Patients were categorized as having no SD (PSQI ≤ 5) or SD (PSQI > 5). Logistic regression analyses identified predictors of SD. Results: Clinically relevant SD was observed in 97 patients (51.9%), with a mean PSQI score of 7.54 ± 5.39. The most affected PSQI components were SD (1.33 ± 1.05) and daytime dysfunction (1.21 ± 1.04). In univariate analyses, Eastern Cooperative Oncology Group (ECOG) performance status ≥ 1 (Odds ratio [OR]: 3.29, 95% confidence interval [CI] 1.77–6.08, p < 0.001), second-line or beyond therapy (OR: 3.76, 95% CI 1.92–7.34, p < 0.001), ≥ 2 metastatic sites (OR: 2.69, 95% CI 1.47–4.92, p = 0.001), and ≥6 ICI cycles (OR: 1.85, 95% CI 1.04–3.32, p = 0.036) were associated with SD. In multivariate analysis, ECOG ≥ 1 (OR: 2.33, 95% CI 1.17–4.62, p = 0.015), second-line or beyond therapy (OR: 2.43, 95% CI 1.14–5.16, p = 0.021), and ≥ 2 metastatic sites (OR: 2.10, 95% CI 1.06–4.16, p = 0.032) remained independent predictors. Conclusions: Over half of patients treated with ICIs experienced SD. Poor performance status, advanced disease burden, and later-line therapy independently predicted impaired sleep, supporting the routine assessment of sleep during ICIs.
1. Introduction
Sleep is a fundamental component of human physiology, playing a critical role in cellular recovery, immune system regulation, and optimal psychological and cognitive performance [1]. Among cancer patients, sleep disturbances (SDs) are highly prevalent and have been linked to fatigue, cognitive decline, and poorer survival outcomes [2]. The causes of SD in oncology are multifactorial, involving tumor-related symptoms, treatment toxicities, psychological distress, and altered circadian rhythms [3]. SD has been linked to impaired immune regulation and enhanced inflammatory responses, which may in turn promote tumor progression [1,4].
Immune checkpoint inhibitors (ICIs), including agents targeting programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) pathways, have transformed the treatment landscape of several cancers [5]. Despite their survival benefits, ICIs have distinct toxicity profiles, known as immune-related adverse events (irAEs), which can involve multiple organ systems and disrupt sleep regulation [6]. Proinflammatory cytokines such as interleukin (IL)-6 and tumor necrosis factor-alpha (TNF-α) can influence immune checkpoint activity and sleep regulation, indicating a mechanistic link through shared neuroimmune and inflammatory pathways that shape tumor immunity and sleep physiology [7].
The Pittsburgh Sleep Quality Index (PSQI) is a validated and widely used tool for evaluating subjective sleep quality in cancer care [8,9]. Despite its clinical relevance, SD among patients receiving ICIs remains frequently unrecognized and inadequately managed. Emerging evidence suggests that SD may impair quality of life and influence treatment adherence, immune regulation, and possibly long-term survival outcomes [10]. Given these potential implications, our study aimed to determine the prevalence and predictors of SD in cancer patients treated with ICIs, using the PSQI as a standardized assessment tool.
2. Materials and Methods
2.1. Patients and Study Design
This cross-sectional, two-center study included patients aged 18 years or older with histologically confirmed advanced or metastatic malignancies who received ICIs at the Departments of Medical Oncology of Bolu Abant Izzet Baysal University and Dokuz Eylül University between October 2022 and October 2025. Eligible systemic therapies included agents targeting PD-1 or PD-L1, such as nivolumab, pembrolizumab, or atezolizumab, either as monotherapy or in combination with other standard systemic treatments. Only patients who completed at least three cycles of ICIs were included in the analysis, while those with incomplete clinical or PSQI data or who discontinued treatment earlier were excluded. Additionally, the study included only individuals with an Eastern Cooperative Oncology Group (ECOG) performance status of 0–2. To minimize potential confounding factors, patients with primary sleep disorders unrelated to malignancy or anticancer therapy (such as obstructive sleep apnea, restless legs syndrome, or narcolepsy) and those with uncontrolled psychiatric or neurological disorders that could impair sleep quality (including severe depression, bipolar disorder, or epilepsy) were not considered eligible.
2.2. Sleep Quality Assessment
Sleep quality was evaluated using the PSQI, a widely validated self-report tool that assesses seven domains of sleep over the preceding month. The PSQI consists of seven component scores, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, SDs, use of sleep medication, and daytime dysfunction. Each component is scored from 0 (no difficulty) to 3 (severe difficulty). The scores are summed to obtain a global score between 0 and 21, with values > 5 considered indicative of clinically significant SD. Therefore, we used this threshold to define clinically relevant SD in this study.
2.3. Statistical Analysis
Descriptive statistics summarized baseline characteristics. Continuous variables were expressed as mean ± standard deviation (Sd) or median with interquartile range (IQR); categorical variables as frequencies and percentages. Logistic regression models were used to identify predictors of SD. Variables with p ≤ 0.20 in univariate analyses were entered into multivariable models. Odds ratios (OR) with 95% confidence intervals (CI) were reported. A two-sided p-value < 0.05 was considered statistically significant. All analyses were performed using the Statistical Package for the Social Sciences, Version 27.0 (IBM Corp., Armonk, NY, USA).
3. Results
3.1. Patients’ Clinical Characteristics
A total of 187 patients who received ICIs were included in the analysis. Demographic and clinical features for both the overall cohort and the PSQI-based groups are presented in Table 1. The median age of the cohort was 60 years, with 93 patients (49.7%) aged < 60 years and 94 (50.3%) aged ≥ 60 years. The majority of participants were male (72.7%, n = 136), and most had an ECOG performance status of 1–2 (61%). The most common primary cancer type was non–small cell lung cancer (NSCLC) in 105 patients (56.1%), followed by renal cell carcinoma (RCC) in 27 (14.4%), melanoma in 20 (10.7%), and other malignancies in 35 (18.7%). Bone, lung, liver, and adrenal metastases were present in 43.3%, 28.3%, 20.9%, and 13.4% of patients, respectively. Hypertension (HT) was the most common comorbidity (26.2%), followed by diabetes mellitus (DM, 10.2%) and cardiovascular disease (CVD, 11.8%). Most patients (69.5%) received ICIs as second-line or later therapy, while 30.5% were treated in the first-line setting. Anti-PD-1-based regimens constituted the majority of treatments (82.9%), followed by anti-PD-L1 (13.4%) and anti-CTLA-4/combination regimens (3.7%).
The median number of ICI cycles at the time of sleep assessment was 6 (IQR: 4–9). When stratified according to sleep quality, 97 patients (51.9%) were classified as having SD (PSQI > 5), and 90 (48.1%) as having good sleep quality (PSQI ≤ 5). SD was more frequent among patients aged ≥ 60 years than those aged <60 years, although the difference was not statistically significant (p = 0.068). The proportion of male patients was slightly higher in the non–SD group compared with the SD group (p = 0.068). SD was more frequent in the ECOG 1–2 group than in the ECOG 0 group (p < 0.001). Primary cancer type and comorbidities did not differ significantly between groups (p > 0.05 for all). SD was more frequent among those receiving ICIs as second-line or beyond therapy compared with those treated in the first-line setting (p < 0.001). SD was significantly more frequent among patients receiving ICIs as second-line or beyond therapy and among those who had completed six or more treatment cycles at the time of PSQI assessment (p < 0.001 and p = 0.036, respectively). No significant difference was observed in the distribution of anti-PD-1, anti-PD-L1, or anti-CTLA-4/combination regimens between the groups (p = 0.641).
3.2. Sleep Quality Components and Predictors of SD
The mean PSQI component scores and predictors of SD are summarized in Table 2 and Table 3. Among the seven PSQI subdomains, SD (mean 1.33 ± 1.05) and daytime dysfunction (1.21 ± 1.04) were the most impaired, followed by sleep duration (1.19 ± 0.99). The lowest mean score was observed for the use of sleep medication (0.36 ± 0.74). The overall mean PSQI global score was 7.54 ± 5.39, indicating that the majority of patients experienced clinically relevant sleep impairment during ICI therapy.
Univariate and multivariate logistic regression analyses were conducted to identify factors associated with SD. In the univariate model, poorer performance status (ECOG ≥ 1) (OR: 3.29, 95% CI 1.77–6.08, p < 0.001), treatment with ICIs in second- or later-line settings (OR: 3.76, 95% CI 1.92–7.34, p < 0.001), having two or more metastatic sites (OR: 2.69, 95% CI 1.47–4.92, p = 0.001), and receiving ≥ 6 cycles of ICI (OR: 1.85, 95% CI 1.04–3.32, p = 0.036) were significantly associated with SD. In the multivariate model, SD was independently predicted by ECOG ≥ 1 (OR: 2.33, 95% CI 1.17–4.62, p = 0.015), second-line or beyond therapy (OR: 2.43, 95% CI 1.14–5.16, p = 0.021), and the presence of ≥ 2 metastatic sites (OR: 2.10, 95% CI 1.06–4.16, p = 0.032).
4. Discussion
In this cross-sectional study, we assessed PSQI-defined sleep quality in a cohort mainly comprising NSCLC, RCC, and melanoma patients receiving ICIs, with evaluations conducted after a median of six treatment cycles, and found that nearly 52% of patients had clinically meaningful SD, highlighting a substantial sleep burden and the need for routine assessment during ICI therapy. Our results are consistent with previous reports that sleep problems are common among cancer patients, with prevalence estimates ranging from 25 to 59% [11].
In cancer, insomnia is recognized as a common symptom contributing to poor quality of life and poor functioning [12]. Although sleep problems are common in oncology, they have been little studied in the context of ICIs [13]. For example, a recent pilot study in patients receiving first-line ICIs reported clinically significant insomnia in 58% of participants, with no link between insomnia severity and the number of ICI infusions [13]. In contrast, our study evaluated overall sleep quality using the PSQI in a cohort primarily composed of second-line or later-line ICI recipients who had previously received systemic therapies and likely accumulated greater symptom burden and treatment-related toxicities. These differences in both patient population and assessment method may account for the observed association between prolonged ICI exposure (≥ 6 cycles) and poorer sleep quality, which was not evident in the first-line pilot study. Li et al. reported in a prospective cohort of advanced NSCLC patients receiving sintilimab, camrelizumab, or tislelizumab that SD was an independent predictor of worse progression-free and overall survival, underlining the prognostic importance of early sleep assessment [10]. Furthermore, meta-analytic data by Kiss et al. showed an insomnia incidence of 8.3% in ICI-treated patients. Collectively, these findings emphasize that routine early follow-up with standardized tools, such as the PSQI, may facilitate timely supportive interventions.
Recent evidence highlights the potential role of chronomodulation in oncology. A systematic review of 18 randomized controlled trials involving 2547 patients demonstrated that chronomodulated chemotherapy reduced treatment-related toxicities in the majority of studies, while maintaining comparable antitumor efficacy and, in some cases, improving outcomes [14]. In the ICI setting, earlier administration of immunochemotherapy was significantly correlated with improved survival outcomes in NSCLC [15]. Additionally, Strøm et al. performed a longitudinal study to identify how sleep and circadian rest–activity rhythms evolve in NSCLC patients receiving ICIs, and they demonstrated that while sleep quality improved modestly during treatment, persistent circadian disruption remained and was closely associated with higher levels of fatigue, depression, and perceived stress [16]. However, we did not have the opportunity to record the exact time of ICIs’ infusions, but the high rate of SD may still be linked to circadian disruption caused by treatment schedules.
The biological mechanisms linking immune checkpoint inhibition to SD are complex and likely bidirectional. ICIs enhance T-cell activation and increase the release of proinflammatory cytokines, particularly IL-1β, IL-6, and TNF-α [17], which are established regulators of sleep–wake homeostasis and have been shown to modulate slow-wave sleep and circadian rhythm stability [18]. Elevated systemic inflammation may therefore establish a proinflammatory milieu that interferes with both sleep continuity and restorative sleep quality [19,20]. In addition, endocrine irAEs, well-recognized toxicities of ICIs, disturb hormonal homeostasis and can promote circadian misalignment, fatigue, and insomnia-like symptoms [6,21]. Treatment of such adverse effects often involves high-dose corticosteroids, which are well known to disrupt circadian cortisol rhythms and provoke insomnia [11]. Taken together, these mechanisms indicate that SD may serve as a marker of immune imbalance during ICI therapy, influencing both well-being and treatment outcomes.
The present study has several strengths. First, it represents one of the largest two-center cohorts to date evaluating sleep quality in patients receiving ICIs, thereby enhancing the generalizability of the findings. Second, sleep quality was assessed using the well-validated PSQI, which allows a comprehensive and standardized evaluation across multiple sleep domains. Third, the inclusion of key clinical factors, including ECOG performance status, treatment line, metastatic burden, and the total number of ICI cycles, enabled robust multivariate modeling to identify independent predictors of SD.
This study has several limitations. First, sleep quality was assessed only once, approximately three months after the initiation of ICI therapy, and no baseline pre-treatment sleep data were available. Therefore, it was not possible to determine whether SD was pre-existing or developed after ICI exposure, nor to evaluate temporal changes in sleep quality. As a result, the present findings should be interpreted as reflecting short-term sleep status during ongoing ICI therapy. Second, although patients with uncontrolled psychiatric or neurological disorders were excluded to reduce major confounding, milder psychological symptoms common in cancer populations may still have influenced subjective sleep reports but were not systematically assessed in this retrospective dataset. Third, other factors that could affect sleep quality, including pain severity, concomitant medications such as corticosteroids, and supportive care interventions, were not consistently documented. Finally, the cross-sectional design limits causal inference; future prospective studies with repeated assessments at multiple timepoints are needed to better characterize the evolution and long-term impact of ICIs on sleep.
5. Conclusions
Our results underscore the importance of proactively monitoring sleep in patients undergoing prolonged ICI therapy. Therefore, oncologists and supportive care teams should integrate standardized sleep assessments, such as the PSQI or validated insomnia questionnaires, into the routine follow-up of patients treated with ICIs. Optimizing sleep and circadian regulation may enhance the effectiveness of ICIs, contributing to improved treatment outcomes, reduced symptom burden, and better quality of life in cancer patients.
Author Contributions
Conceptualization, B.A., O.H.A., M.H.B. and S.Y.; methodology, B.A., O.H.A., P.E.D., A.K. and S.Y.; software, B.A., O.H.A., T.U., I.T.U. and M.H.B.; validation, P.E.D., T.U., I.T.U. and S.Y.; formal analysis, A.K.; investigation, B.A., O.H.A., P.E.D., T.U. and M.H.B.; resources, A.K. and S.Y.; data curation, P.E.D. and T.U.; writing—original draft preparation, B.A., O.H.A., P.E.D., T.U., M.H.B. and I.T.U.; writing—review and editing, A.K. and S.Y.; visualization, B.A., O.H.A., T.U., I.T.U. and A.K.; supervision, M.H.B. and S.Y.; project administration, B.A., O.H.A. and M.H.B.; funding acquisition, B.A. and O.H.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was approved by the Clinical Research Ethic Commission of Bolu Abant Izzet Baysal University (approval date: 11 October 2022, decision no: 2022/261) and performed according to the latest version of the Declaration of Helsinki.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author due to privacy and ethical restrictions related to patient confidentiality.
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| CI | Confidence interval |
| CTLA-4 | Cytotoxic T-lymphocyte-associated protein 4 |
| CVD | Cardiovascular disease |
| DM | Diabetes mellitus |
| ECOG | Eastern Cooperative Oncology Group |
| HT | Hypertension |
| ICI | Immune checkpoint inhibitor |
| IQR | Interquartile range |
| IL | Interleukin |
| irAE | Immune-related adverse event |
| NSCLC | Non-small cell lung cancer |
| OR | Odds ratio |
| PD-1 | Programmed cell death protein 1 |
| PD-L1 | Programmed death-ligand 1 |
| PSQI | Pittsburgh Sleep Quality Index |
| RCC | Renal cell carcinoma |
| SD | Sleep disturbances |
| Sd | Standard deviation |
| TNF-α | tumor necrosis factor-alpha |
References
- Irwin, M.R. Sleep and Inflammation: Partners in Sickness and in Health. Nat. Rev. Immunol. 2019, 19, 702–715. [Google Scholar] [CrossRef] [PubMed]
- Amidi, A.; Wu, L.M. Circadian Disruption and Cancer- and Treatment-Related Symptoms. Front. Oncol. 2022, 12, 1009064. [Google Scholar] [CrossRef] [PubMed]
- Palesh, O.; Peppone, L.; Innominato, P.F.; Janelsins, M.; Jeong, M.; Sprod, L.; Savard, J.; Rotatori, M.; Kesler, S.; Telli, M.; et al. Prevalence, Putative Mechanisms, and Current Management of Sleep Problems during Chemotherapy for Cancer. Nat. Sci. Sleep. 2012, 4, 151–162. [Google Scholar] [CrossRef] [PubMed]
- Calvo-Schimmel, A.; Kober, K.M.; Paul, S.M.; Cooper, B.A.; Harris, C.; Shin, J.; Hammer, M.J.; Conley, Y.P.; Dokiparthi, V.; Olshen, A.; et al. Sleep Disturbance Is Associated with Perturbations in Immune-Inflammatory Pathways in Oncology Outpatients Undergoing Chemotherapy. Sleep. Med. 2023, 101, 305–315. [Google Scholar] [CrossRef]
- Sun, Q.; Hong, Z.; Zhang, C.; Wang, L.; Han, Z.; Ma, D. Immune Checkpoint Therapy for Solid Tumours: Clinical Dilemmas and Future Trends. Signal Transduct. Target. Ther. 2023, 8, 320. [Google Scholar] [CrossRef]
- Balachandran, D.D.; Bashoura, L.; Sheshadri, A.; Manzullo, E.; Faiz, S.A. The Impact of Immunotherapy on Sleep and Circadian Rhythms in Patients with Cancer. Front. Oncol. 2023, 13, 1295267. [Google Scholar] [CrossRef]
- Cohen, M.; Shamay, Y.; Czamanski-Cohen, J.; Shulman, K.; Keren Rosenberg, S.; Abu-Amna, M.; Turgeman, I.; Merkin Livshits, L.; Birenboim, R.; Dines, M.; et al. Linkage between Psychological Factors and Response to Immune Checkpoint Inhibitor Therapy: A Preliminary Study. Cells 2023, 12, 2471. [Google Scholar] [CrossRef]
- Buysse, D.J.; Reynolds, C.F.; Monk, T.H.; Berman, S.R.; Kupfer, D.J. The Pittsburgh Sleep Quality Index: A New Instrument for Psychiatric Practice and Research. Psychiatry Res. 1989, 28, 193–213. [Google Scholar] [CrossRef]
- Sohrabi, M.; Gholami, A.; Hassanzadeh, P.; Hatami, S.; Ajdarkosh, H.; Zamani, F.; Doustmohammadian, A. Examining the Factor Structure of the Pittsburgh Sleep Quality Index and Its Determinants among GI Cancer Patients. BMC Cancer 2024, 24, 1577. [Google Scholar] [CrossRef]
- Li, N.; Xue, D.; Zhao, X.; Li, L.; Men, K.; Yang, J.; Jiang, H.; Meng, Q.; Zhang, S. Sleep Disturbance as a Poor Prognostic Predictor in Patients with Advanced Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors: A Prospective Study. J. Psychosom. Res. 2024, 186, 111892. [Google Scholar] [CrossRef]
- Pinucci, I.; Maraone, A.; Tarsitani, L.; Pasquini, M. Insomnia among Cancer Patients in the Real World: Optimising Treatments and Tailored Therapies. Int. J. Environ. Res. Public Health 2023, 20, 3785. [Google Scholar] [CrossRef]
- Kiss, I.; Kuhn, M.; Hrusak, K.; Buchler, B.; Boublikova, L.; Buchler, T. Insomnia in Patients Treated with Checkpoint Inhibitors for Cancer: A Meta-Analysis. Front. Oncol. 2022, 12, 946307. [Google Scholar] [CrossRef]
- Sillah, A.; Peters, U.; Watson, N.F.; Tykodi, S.S.; Hall, E.T.; Silverman, A.; Malen, R.C.; Thompson, J.A.; Lee, S.M.; Bhatia, S.; et al. Associating Sleep Problems with Advanced Cancer Diagnosis, and Immune Checkpoint Treatment Outcomes: A Pilot Study. Support. Care Cancer 2022, 30, 3829–3838. [Google Scholar] [CrossRef]
- Printezi, M.I.; Kilgallen, A.B.; Bond, M.J.G.; Štibler, U.; Putker, M.; Teske, A.J.; Cramer, M.J.; Punt, C.J.A.; Sluijter, J.P.G.; Huitema, A.D.R.; et al. Toxicity and Efficacy of Chronomodulated Chemotherapy: A Systematic Review. Lancet Oncol. 2022, 23, e129–e143. [Google Scholar] [CrossRef]
- Huang, Z.; Karaboué, A.; Zeng, L.; Lecoeuvre, A.; Zhang, L.; Li, X.-M.; Qin, H.; Danino, G.; Yang, F.; Malin, M.-S.; et al. Overall Survival According to Time-of-Day of Combined Immuno-Chemotherapy for Advanced Non-Small Cell Lung Cancer: A Bicentric Bicontinental Study. EBioMedicine 2025, 113, 105607. [Google Scholar] [CrossRef]
- Strøm, L.; Zachariae, R.; Wu, L.M.; Meldgaard, P.; Ancoli-Israel, S.; Lekander, M.; Mroczek, D.; Amidi, A. Longitudinal Investigation of Sleep and Circadian Rest-Activity Rhythms in Non-Small Cell Lung Cancer Patients during Immunotherapy and Associations with Fatigue, Depression, and Perceived Stress. Sleep. Med. 2025, 134, 106740. [Google Scholar] [CrossRef] [PubMed]
- Wang, M.; Zhai, X.; Li, J.; Guan, J.; Xu, S.; Li, Y.; Zhu, H. The Role of Cytokines in Predicting the Response and Adverse Events Related to Immune Checkpoint Inhibitors. Front. Immunol. 2021, 12, 670391. [Google Scholar] [CrossRef] [PubMed]
- Krueger, J.M.; Clinton, J.M.; Winters, B.D.; Zielinski, M.R.; Taishi, P.; Jewett, K.A.; Davis, C.J. Involvement of Cytokines in Slow Wave Sleep. Prog. Brain Res. 2011, 193, 39–47. [Google Scholar] [PubMed]
- Irwin, M.R.; Olmstead, R.; Carroll, J.E. Sleep Disturbance, Sleep Duration, and Inflammation: A Systematic Review and Meta-Analysis of Cohort Studies and Experimental Sleep Deprivation. Biol. Psychiatry 2016, 80, 40–52. [Google Scholar] [CrossRef]
- Besedovsky, L.; Lange, T.; Haack, M. The Sleep-Immune Crosstalk in Health and Disease. Physiol. Rev. 2019, 99, 1325–1380. [Google Scholar] [CrossRef]
- Cardona, Z.; Sosman, J.A.; Chandra, S.; Huang, W. Endocrine Side Effects of Immune Checkpoint Inhibitors. Front. Endocrinol. 2023, 14, 1157805. [Google Scholar] [CrossRef]
Table 1.
Baseline clinical and demographic characteristics of patients stratified according to SD status (PSQI-based).
Table 1.
Baseline clinical and demographic characteristics of patients stratified according to SD status (PSQI-based).
| Characteristics | All Patients (n = 187) | No SD Group (n = 90, 48.1%) | SD Group (n = 97, 51.9%) | p Value |
|---|---|---|---|---|
| Age (years) | 0.068 | |||
| <60 | 93 (49.7%) | 51 (56.7%) | 42 (43.3%) | |
| ≥60 | 94 (50.3%) | 39 (43.3%) | 55 (56.7%) | |
| Gender | 0.068 | |||
| Male | 136 (72.7%) | 71 (78.9%) | 65 (67%) | |
| Female | 51 (27.3%) | 19 (21.1%) | 32 (33%) | |
| ECOG performance status | <0.001 | |||
| 0 | 73 (39%) | 48 (53.3%) | 25 (25.8%) | |
| 1–2 | 114 (61%) | 42 (46.7%) | 72 (74.2%) | |
| Primary cancer type | 0.818 | |||
| NSCLC | 105 (56.1%) | 50 (55.6%) | 55 (56.7%) | |
| RCC | 27 (14.4%) | 14 (15.6%) | 13 (13.4%) | |
| Melanoma | 20 (10.7%) | 11 (12.2%) | 9 (9.3%) | |
| Others | 35 (18.7%) | 15 (16.7%) | 20 (20.6%) | |
| Metastatic sites | ||||
| Lung | 53 (28.3%) | 25 (27.8%) | 28 (28.9%) | 0.869 |
| Liver | 39 (20.9%) | 17 (18.9%) | 22 (22.7%) | 0.524 |
| Bone | 81 (43.3%) | 36 (40%) | 45 (46.4%) | 0.378 |
| Adrenal | 25 (13.4%) | 11 (12.2%) | 14 (14.4%) | 0.657 |
| Comorbidities | ||||
| HT | 49 (26.2%) | 25 (27.8%) | 24 (24.7%) | 0.637 |
| DM | 19 (10.2%) | 11 (12.2%) | 8 (8.2%) | 0.369 |
| CVD | 22 (11.8%) | 11 (12.2%) | 11 (11.3%) | 0.852 |
| Line of ICI | <0.001 | |||
| First-line | 57 (30.5%) | 40 (40.7%) | 17 (31.2%) | |
| Second-line or beyond | 130 (69.5%) | 50 (59.3%) | 80 (68.8%) | |
| ICI cycle at SD assessment | 0.036 | |||
| <6 cycles | 89 (47.6%) | 50 (55.6%) | 39 (40.2%) | |
| ≥6 cycles | 98 (52.4%) | 40 (44.4%) | 58 (59.8%) | |
| Regimen type | 0.641 | |||
| Anti-PD-1 | 155 (82.9%) | 77 (85.6%) | 78 (80.4%) | |
| Anti-PD-L1 | 25 (13.4%) | 10 (11.1%) | 15 (15.5%) | |
| Anti-CTLA-4/combination | 7 (3.7%) | 3 (3.3%) | 4 (4.1%) |
Abbreviations: CVD: cardiovascular disease; DM: diabetes mellitus; ECOG: Eastern Cooperative Oncology Group; HT: hypertension; ICI: immune checkpoint inhibitor; NSCLC: non–small cell lung cancer; PD-1: programmed cell death protein 1; PD-L1: programmed death-ligand 1; PSQI: Pittsburgh Sleep Quality Index; RCC: renal cell carcinoma; SD: sleep disturbance.
Table 2.
Mean scores of the seven PSQI components and the global PSQI score among patients receiving ICIs.
Table 2.
Mean scores of the seven PSQI components and the global PSQI score among patients receiving ICIs.
| Variable | Mean | Sd |
|---|---|---|
| Subjective sleep quality | 1.12 | 0.99 |
| Sleep latency | 1.02 | 1.08 |
| Sleep duration | 1.19 | 0.99 |
| Habitual sleep efficiency | 1.12 | 1.03 |
| Sleep disturbances | 1.33 | 1.05 |
| Use of sleeping medication | 0.36 | 0.74 |
| Daytime dysfunction | 1.21 | 1.04 |
| Total PSQI | 7.54 | 5.39 |
Abbreviations: PSQI: Pittsburgh Sleep Quality Index; Sd: standard deviation.
Table 3.
Univariate and multivariate logistic regression analyses for factors associated with SD in patients receiving ICIs.
Table 3.
Univariate and multivariate logistic regression analyses for factors associated with SD in patients receiving ICIs.
| Variable | Univariate OR (95% CI) | p | Multivariate OR (95% CI) | p |
|---|---|---|---|---|
| Female sex | 1.84 (0.95–3.55) | 0.070 | 1.44 (0.70–2.98) | 0.316 |
| Age ≥ 60 years | 1.71 (0.96–3.05) | 0.069 | 0.81 (0.39–1.65) | 0.569 |
| ECOG ≥ 1 | 3.29 (1.77–6.08) | <0.001 | 2.33 (1.17–4.62) | 0.015 |
| Second-line or beyond therapy | 3.76 (1.92–7.34) | <0.001 | 2.43 (1.14–5.16) | 0.021 |
| ≥2 metastatic sites | 2.69 (1.47–4.92) | 0.001 | 2.10 (1.06–4.16) | 0.032 |
| Number of ICI cycles ≥ 6 | 1.85 (1.04–3.32) | 0.036 | 1.64 (0.86–3.13) | 0.133 |
Abbreviations: OR: odds ratio; CI: confidence interval; ECOG: Eastern Cooperative Oncology Group.
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MDPI and ACS Style
Aktepe, B.; Ulasli, T.; Dama, P.E.; Unek, I.T.; Karaoglu, A.; Boztas, M.H.; Yalcin, S.; Aktepe, O.H. Sleep Quality and Its Determinants Among Patients with Metastatic Cancer Treated with Immune Checkpoint Inhibitors: A Two-Center Cross-Sectional Study. Medicina 2025, 61, 2131. https://doi.org/10.3390/medicina61122131
AMA Style
Aktepe B, Ulasli T, Dama PE, Unek IT, Karaoglu A, Boztas MH, Yalcin S, Aktepe OH. Sleep Quality and Its Determinants Among Patients with Metastatic Cancer Treated with Immune Checkpoint Inhibitors: A Two-Center Cross-Sectional Study. Medicina. 2025; 61(12):2131. https://doi.org/10.3390/medicina61122131
Chicago/Turabian StyleAktepe, Betul, Tugce Ulasli, Pinar Ezgi Dama, Ilkay Tugba Unek, Aziz Karaoglu, Mehmet Hamid Boztas, Suayib Yalcin, and Oktay Halit Aktepe. 2025. "Sleep Quality and Its Determinants Among Patients with Metastatic Cancer Treated with Immune Checkpoint Inhibitors: A Two-Center Cross-Sectional Study" Medicina 61, no. 12: 2131. https://doi.org/10.3390/medicina61122131
APA StyleAktepe, B., Ulasli, T., Dama, P. E., Unek, I. T., Karaoglu, A., Boztas, M. H., Yalcin, S., & Aktepe, O. H. (2025). Sleep Quality and Its Determinants Among Patients with Metastatic Cancer Treated with Immune Checkpoint Inhibitors: A Two-Center Cross-Sectional Study. Medicina, 61(12), 2131. https://doi.org/10.3390/medicina61122131
