Search Results (1,084)

Background/Objectives: The global health crisis of the COVID-19 pandemic in 2020 severely impacted healthcare systems, particularly affecting cancer patients, including those with lung cancer. Understanding the pandemic’s effects on lung cancer diagnosis is important for providing guidelines for future similar crises. Methods: A comprehensive search was conducted using the SCOPUS and PubMed databases, including keywords such as ‘COVID-19 pandemic,’ ‘lung cancer,’ ‘diagnosis,’ and ‘screening.’ In the initial screening phase, studies were selected based on their title and abstract, followed by the removal of duplicates. A second round of full-text screening was then performed using predefined inclusion and exclusion criteria. Specific checklists were applied to ensure methodological quality. Results: Out of 564 articles, 78 met the inclusion criteria and were grouped according to changes in lung cancer incidence, screening and diagnostic procedures, and staging during the COVID-19 pandemic compared to pre-pandemic. Multiple studies reported an average decline of 20% in newly diagnosed lung cancer cases, alongside significant decreases in screenings, follow-ups, and diagnostic procedures. In contrast, only two studies reported an increase in lung cancer incidence, and three studies reported increases in screening or diagnostic activity. Eight studies reported a shift toward more advanced-stage diagnoses and fewer early-stage detections, while four studies observed a decrease in advanced-stage lung cancer during the pandemic compared to pre-pandemic years. Conclusions: Studies show that overall, the COVID-19 pandemic disrupted lung cancer diagnosis in many countries, highlighting the need for stronger healthcare systems that can support crisis response and equitable care. Full article

Background/Objectives: Intraoperative molecular imaging (IMI) enables real-time visualization of tumor biology during surgery using fluorescent probes and near-infrared imaging systems. As lung cancer screening increases detection of small and nonpalpable pulmonary nodules, conventional localization and margin assessment techniques remain limited, particularly during minimally invasive surgery. This review summarizes the technical foundations, imaging agents, clinical applications, and future directions of IMI in thoracic oncology. Methods: We performed a narrative review to synthesize current evidence regarding the technical foundations, molecular imaging agents, clinical applications, and future directions of intraoperative molecular imaging in thoracic oncology. Given the multidisciplinary scope of the field, a narrative approach was selected to integrate mechanistic, translational, and clinical evidence rather than to answer a single narrowly defined clinical question. Results: IMI generates dynamic intraoperative contrast based on preferential probe accumulation or activation within malignant tissue. Current approaches include non-specific fluorophores such as indocyanine green, activatable probes targeting tumor-associated proteases or acidic microenvironments, and receptor-targeted agents such as pafolacianine. Across prospective studies and multicenter trials, IMI improved localization of nonpalpable lesions, identified occult synchronous malignancies, and enhanced intraoperative margin assessment, frequently altering surgical management. Phase 2 and 3 studies of folate receptor-targeted imaging demonstrated clinically significant findings in a substantial proportion of patients, including lesions not detected by conventional imaging or palpation. However, performance remains dependent on tumor biology, target expression, lesion depth, and optical constraints. Conclusions: IMI represents an emerging transition from anatomy-guided toward biology-informed thoracic surgery by providing real-time molecular information during resection. Current evidence supports its role as a complementary intraoperative technology that augments conventional imaging and surgical techniques, particularly for small, peripheral, and nonpalpable lesions. Full article

Background: Lung cancer carries a high psychosocial burden. Tobacco use, the stigma attached to the disease, and coping strategies are thought to interact and shape psychological outcomes, yet they have rarely been examined together. This review aimed to synthesise the evidence on the relationship between tobacco use, lung cancer stigma, and coping, and how these factors interact and influence patients’ psychological outcomes. Methods: Following the PRISMA 2020 guideline, PubMed/MEDLINE and Dialnet were searched (window 2014–April 2026) for empirical studies conducted in adults with lung cancer that addressed stigma, coping, or relevant psychological outcomes (e.g., anxiety, depression, distress, or quality of life). Study selection and data extraction were performed independently by two reviewers, with discrepancies resolved by consensus and, where needed, by a third reviewer. Methodological quality was appraised with design-specific tools (JBI for cross-sectional and cohort studies, CASP for qualitative studies, and COSMIN-oriented criteria for the psychometric study). Given the clinical and methodological heterogeneity, a structured narrative synthesis was conducted following the SWiM guideline. The protocol was registered in the Open Science Framework. Results: Twenty-four studies were included. Stigma was prevalent and consistently associated with depression, anxiety, distress, and poorer quality of life, with longitudinal evidence indicating that stigma precedes and predicts distress. Internalised stigma (guilt, shame, self-blame) was the facet most strongly linked to depression and anxiety. Smoking history graded stigma intensity (current > former > never smokers) but did not determine it, since clinically significant stigma also affected never-smokers. Adaptive coping (e.g., fighting spirit, positive reappraisal) and social support were consistently associated with better psychological adjustment and quality of life, while maladaptive coping (e.g., helplessness, avoidance, anxious preoccupation) was associated with worse outcomes; cross-sectional evidence further indicated that coping modes mediated the relationship between stigma and quality of life and that social support and self-compassion attenuated the impact of stigma on distress. Conclusions: Internalised stigma is a central, modifiable psychosocial stressor in lung cancer that affects smokers and never-smokers alike. Systematic screening for stigma, coping, and social support, together with non-stigmatising care, is warranted. Full article

Blood-based biomarkers have emerged as promising, minimally invasive tools for the diagnosis, prognostic stratification, and treatment monitoring of non-small cell lung cancer (NSCLC), including markers of tumor burden, tumor dissemination, immune signaling, and post-transcriptional regulation. However, evidence across biomarker classes remains fragmented. This study aimed to synthesize published evidence on major blood-based biomarkers relevant to diagnosis, prognosis, treatment stratification, and monitoring in NSCLC. PubMed was searched for systematic reviews and meta-analyses of blood-based biomarkers in NSCLC. Of 356 screened records, 82 underwent full-text review, and 57 systematic reviews/meta-analyses were included. Biomarkers were grouped into four categories: circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), cytokines/soluble immune proteins, and non-coding RNAs (ncRNAs). Reported pooled effect estimates were extracted by biomarker class and evidence domain, and the methodological quality of included reviews was assessed using AMSTAR 2. Evidence was unevenly distributed across biomarker classes and evidence domains. Circulating ncRNAs were mainly represented in diagnostic and prognostic evidence; selected diagnostic ncRNAs, including miR-145, miR-25, and circRNAs, showed reported AUCs ranging from 0.83 to 0.85. ctDNA was represented across diagnostic, prognostic, treatment-stratification, and dynamic monitoring evidence, with ctDNA positivity associated with poorer survival or recurrence outcomes and ctDNA clearance or decline associated with improved outcomes. CTC evidence was primarily prognostic, with CTC positivity associated with worse overall survival and disease-free survival. Soluble immune biomarker evidence was also primarily prognostic, with elevated soluble PD-L1 and IL-6 associated with adverse survival outcomes and limited exploratory monitoring evidence for exosomal PD-L1. Overall, the evidence suggested distinct but complementary roles across biomarker classes, although direct head-to-head comparisons were lacking. Blood-based biomarkers show potential to support diagnosis, prognosis, and longitudinal monitoring in NSCLC, but their reported utility differs by biomarker class and clinical context. In the available review-level evidence, ncRNAs were mainly represented in diagnostic and prognostic evidence, while ctDNA was represented across diagnostic, prognostic, treatment-stratification, and dynamic monitoring evidence. CTCs were mainly represented in prognostic evidence, and soluble immune biomarkers were primarily represented in prognostic evidence, with limited exploratory evidence for dynamic monitoring. Further assay standardization, prospective validation, and direct comparative studies are needed before these biomarkers can be routinely integrated into clinical practice. Full article

Unc-51-like kinase 3 (ULK3) is a key member of the ULK serine/threonine kinase family. Aberrant ULK3 expression has been increasingly linked to tumorigenesis and malignant progression in multiple cancer types. However, the precise role of ULK3 in tumor initiation and progression remains incompletely understood. Leveraging integrated multi-omics data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), we systematically characterized the expression of ULK3 at both the transcript and protein levels across 33 cancer types. We also evaluated genomic alterations, prognostic significance, alternative splicing, pathway enrichment, tumor stemness, immune infiltration, and immunotherapy-related biomarkers. In parallel, we investigated the function of ULK3 in prostate cancer PC-3 cells using cellular localization analysis, wound-healing assays, and MTT assays. We further applied Connectivity Map (CMap) screening and molecular docking to identify candidate ULK3 activators. ULK3 was significantly upregulated in 13 cancer types, including Bladder Urothelial Carcinoma, Breast Invasive Carcinoma, and Lung Adenocarcinoma. In contrast, ULK3 was downregulated in Cholangiocarcinoma and Head and Neck Squamous Cell Carcinoma. High ULK3 expression was associated with poor overall survival in Adrenocortical Carcinoma, Kidney Renal Clear Cell Carcinoma, and Skin Cutaneous Melanoma. Copy number amplification contributed to ULK3 overexpression. A recurrent A206V missense mutation was detected in the protein kinase (Pkinase) domain. Genes co-expressed with ULK3 were enriched in RNA splicing, methylation, oxidative phosphorylation, and energy metabolism. ULK3 expression showed positive correlations with tumor stemness indices and m1A/m5C/m6A RNA modification regulators. From an immunological perspective, high ULK3 expression was associated with lower Immune Score, increased M2 macrophage infiltration, and co-expression of PD-L1, CTLA4, and LAG3 in most cancers. ULK3 expression was also correlated with Tumor Mutational Burden in Kidney Renal Clear Cell Carcinoma and Rectum Adenocarcinoma. In addition, ULK3 expression was associated with Microsatellite Instability in Brain Lower Grade Glioma, Lung Adenocarcinoma, and Uterine Corpus Endometrial Carcinoma. ULK3 overexpression promoted proliferation and migration in PC-3 cells. Cephaeline was screened as a putative ULK3 activator. Overall, ULK3 expression and amplification were associated with poor clinical outcomes, tumor stemness, immunosuppression, and RNA dysregulation. These findings highlight the potential value of ULK3 as a pan-cancer diagnostic and prognostic biomarker and as a predictor of immunotherapy response, particularly in prostate cancer. Full article

Cancer remains a growing public health concern in South Africa, particularly in underserved communities where disparities in awareness and access to care contribute to delayed diagnosis. This study evaluated the impact of a culturally tailored educational intervention based on an adapted Cancer-Community Awareness Access Research and Education (c-CARE) module in Johannesburg and iLembe districts. A pilot study using a quasi-experimental pre–post design was conducted to assess changes in knowledge and attitudes among 210 traditional health practitioners, community health workers, and faith-based leaders. Structured surveys measured awareness of multiple myeloma, prostate, lung, breast, and cervical cancers. Data were captured in REDCap and analyzed using SPSS version 30. Significant improvements in knowledge were observed across all cancers. Awareness of lung cancer increased from 74.3% to 96.7%, multiple myeloma from 26.7% to 96.7%, prostate cancer from 52.5% to 98.3%, breast cancer from 93.4% to 98.7%, and cervical cancer from 84.8% to 96.0%. Participants demonstrated improved understanding of screening modalities and risk factors, including tobacco-related harms. Despite these gains, screening-related fears remained evident. These findings demonstrate that contextually adapted, community-based training can strengthen cancer literacy and support early detection strategies in underserved settings. Full article

Marine medicinal algae represent a valuable reservoir of bioactive metabolites for anticancer drug discovery, yet the efficient identification of target-relevant compounds from chemically complex marine matrices remains challenging. In this study, an integrated cathepsin B-oriented strategy was developed to discover, prioritize, isolate, and validate antitumor metabolites from the brown alga Sargassum polycystum. Affinity ultrafiltration LC-MS was first applied to screen CTSB-binding constituents from the crude extract, followed by molecular docking, molecular dynamics simulation, and gray relational analysis for multidimensional candidate prioritization. Seven CTSB-binding metabolites were characterized, including chlorogenic acid, caffeic acid, cynarin, loliolide, taxifolin, senkyunolide H, and dihydroactinidiolide, with binding degrees of 73.99–85.61% at 2.5 U/mL CTSB. Molecular docking showed predicted binding affinities ranging from −6.3 to −9.4 kcal/mol, compared with −10.2 kcal/mol for the positive control CA-074Me. Integrated computational and biological evaluation identified caffeic acid, cynarin, and taxifolin as the top-ranked candidates. Preparative recovery was then achieved using counter-current chromatography combined with semi-preparative HPLC, and the isolated compounds were structurally identified by LC-MS/MS and NMR. Cellular assays in NCI-H1975 cells suggested that these metabolites reduced CTSB-associated enzymatic activity and intracellular CTSB-related fluorescence signals to different extents, with phenolic acid-type compounds exhibiting comparatively stronger effects. At the extract level, S. polycystum dose-dependently suppressed NCI-H1975 xenograft tumor growth, with inhibition rates of 48.78%, 36.58%, and 22.86% in the high-, middle-, and low-dose groups, respectively, without evident hepatorenal histopathological toxicity. This effect was associated with reduced CTSB, Ki-67, and Bcl-2 staining, increased Bax staining, enhanced apoptosis, and ultrastructural alterations in tumor tissues. Overall, this study provides a practical CTSB-oriented workflow for discovering antitumor metabolites from marine medicinal algae and supports further investigation of S. polycystum as a potential source of anti-NSCLC candidates. Full article

Background/Objectives: Postoperative intensive care unit (ICU) disposition after anatomical lung resection is usually planned preoperatively, but the final care pathway may be substantially influenced by intraoperative events. We evaluated actual postoperative ICU admission among patients with a documented preoperative ICU monitoring recommendation and compared preoperative-only and perioperative triage approaches. Methods: In this retrospective single-centre cohort study, 1060 adults undergoing elective anatomical lung resection for non-small cell lung cancer (NSCLC) between January 2019 and December 2025 were screened; 159 patients with a documented preoperative ICU monitoring recommendation constituted the analytical cohort. A clinically pre-specified primary perioperative model incorporating operative duration, intraoperative complication, chronic obstructive pulmonary disease (COPD), and pre-existing arrhythmia was compared with a preoperative-only model and with an exploratory perioperative ICU triage score. Results: Actual postoperative ICU admission occurred in 45 patients (28.3%). Operative duration (adjusted odds ratio [OR] 1.012 per minute; 95% confidence interval [CI], 1.005–1.018; p < 0.001) and intraoperative complication (adjusted OR 15.002; 95% CI, 3.738–60.210; p < 0.001) were significantly associated with actual postoperative ICU admission. The primary perioperative model achieved an AUC of 0.802 (95% CI, 0.717–0.876), compared with 0.759 for the exploratory perioperative triage score and 0.665 for the preoperative-only model. Conclusions: Fewer than one-third of patients with a documented preoperative ICU monitoring recommendation underwent actual postoperative ICU admission. In this selected cohort, perioperative reassessment incorporating intraoperative information showed higher apparent discriminative performance than the preoperative-only approach while the exploratory score showed intermediate, hypothesis-generating performance. Because the outcome reflected observed institutional ICU disposition rather than independently adjudicated ICU-level care requirement, prospective multicentre validation using predefined ICU admission criteria is required before clinical implementation. Full article

Background/Objectives: Celiac disease (CD) is common, but its cancer-risk profile remains incompletely defined. Estimates vary because of referral patterns, diagnostic era, outcome definitions, and surveillance around diagnosis. We evaluated cancer-category-specific associations in a matched cohort of clinically recognized CD. Methods: We used longitudinal electronic health record (EHR) data from Clalit Health Services for a propensity-matched cohort. Adults with EHR-coded CD were matched to controls on demographic, socioeconomic, comorbidity, and inflammatory variables. Pre-index invasive malignancies and non-invasive neoplasms were excluded. Dated EHR-coded invasive oncology outcomes were analyzed using Cox models. A restricted dated-event cohort, lag analyses, competing-risk modeling, hemoglobin adjustment, and age-at-index strata assessed robustness. Results: The primary matched cohort included 8143 individuals: 1006 with CD and 7137 controls, contributing 49,330.5 person-years. CD was associated with increased hazard of an EHR-coded invasive oncology outcome (hazard ratio [HR] 1.61, 95% confidence interval [CI] 1.47–1.77; $p<0.001$). Strongest signals were hematological malignancy codes (HR 1.99), lymphoma codes (HR 1.90), and gastrointestinal (GI) cancer codes (HR 2.71). Associations persisted after one-year and two-year lags. In the dated-event sensitivity cohort (161 CD; 1610 controls), CD remained associated with invasive cancer (HR 1.68, 95% CI 1.31–2.14), with the strongest signals for lymphoma (HR 2.81) and GI cancer (HR 2.25). The association was essentially unchanged under competing-risk modeling (Fine–Gray subdistribution HR 1.69) and after hemoglobin adjustment (HR 1.61), and was present in both age strata. Neither breast nor lung cancer was associated. Lymphoma codes included peripheral T-cell lymphomas recorded at intra-abdominal and extranodal sites, the pattern most consistent with enteropathy-associated T-cell lymphoma (EATL). Conclusions: In clinically recognized CD, cancer hazard was elevated and category-specific, concentrated in hematological, lymphoid, and GI codes with a gut-oriented T-cell lymphoma signal. The findings support targeted clinical vigilance, not expanded screening, and describe relative associations that require registry-linked confirmation. Full article

Background/Objectives: Blood-based biomarkers may improve risk stratification of indeterminate pulmonary nodules detected on low-dose computed tomography (LDCT). We evaluated the diagnostic performance and independent predictive value of an aptamer-based blood assay, AptoDetect™-Lung, in a high-risk Korean screening population. Methods: This multicenter prospective cohort study enrolled adults with Lung Imaging Reporting and Data System (Lung-RADS) category 3 or 4 pulmonary nodules identified on LDCT across ten tertiary hospitals in South Korea between June 2023 and December 2024. Analyses focused on a predefined high-risk subgroup meeting Korean screening criteria (age 54–74 years and ≥30 pack-years of smoking). Baseline serum AptoDetect™-Lung scores were measured. Associations with lung cancer diagnosis were assessed using univariate and multivariable logistic regression, adjusting for clinical and radiologic variables. Diagnostic performance was evaluated using receiver operating characteristic analysis. Results: Among 1084 participants with histopathologic confirmation, 319 met high-risk criteria, of whom 260 (81.5%) were diagnosed with lung cancer. In this subgroup, the AptoDetect™-Lung score was independently associated with malignancy after adjustment (adjusted odds ratio of 1.14 per unit; 95% confidence interval of 1.02–1.27; p = 0.020). Discriminative performance was higher in the high-risk subgroup than in the overall cohort (area under the curve [AUC] of 0.639 vs. 0.570; p = 0.025). Performance was higher for squamous cell carcinoma and small-cell lung cancer than for adenocarcinoma. A multivariable model incorporating biomarker score, Lung-RADS category, age, and family history achieved an AUC of 0.710. Conclusions: An aptamer-based blood biomarker may provide modest adjunctive value for risk stratification in high-risk individuals. Full article

Background/Objectives: Robotic-assisted bronchoscopy has emerged as an advanced technique for the evaluation of peripheral pulmonary lesions, offering improved navigation and targeting accuracy. While several studies investigating other diagnostic modalities have identified factors associated with higher diagnostic yield, such determinants remain poorly defined for shape-sensing robotic-assisted bronchoscopy (ssRAB). This study therefore aimed to identify predictors of diagnostic yield in robotic bronchoscopy. Methods: This retrospective single-center study included all consecutive patients who underwent ssRAB (ION^TM system, Intuitive Surgical, Sunnyvale, CA, USA) between August 2024 and March 2026. Lung nodules undergoing marker placement only or procedures performed without cone-beam CT (CBCT) guidance were excluded. Collected variables included demographic characteristics, lesion size, lesion density (solid, part-solid, ground-glass), biopsy modality, and number of biopsy samples obtained. Diagnostic yield was defined as a definitive pathological diagnosis of the target lesion. Predictors of diagnostic success were assessed using univariable logistic regression. Results: In total, 111 pulmonary nodules were included in the analysis. The overall diagnostic yield was 88.3% (98/111). The mean patient age was 64.94 ± 7.9 years, with a predominance of female patients (58.4%). No significant associations were observed between diagnostic yield and lesion size (odds ratio [OR] 1.014 per mm; p = 0.764), lesion density (p = 0.892), or biopsy instrument (p = 0.835). However, an increased number of biopsy samples showed a positive association with diagnostic yield, showing a statistical trend (OR 1.22 per additional sample; p = 0.084). Conclusions: Robotic-assisted bronchoscopy provides a high diagnostic yield for peripheral pulmonary lesions. The number of biopsy samples appears to be the most relevant modifiable factor influencing diagnostic success, underscoring the importance of adequate tissue acquisition. In contrast, lesion characteristics and biopsy modality did not significantly affect outcomes in this cohort. Full article

Background: The coronavirus disease 2019 (COVID-19) pandemic significantly disrupted cancer screening, diagnosis, and care. This phase of the Hungarian Cancer Epidemiology (HUN-CANCER-EPI) study evaluated trends in cancer incidence and mortality in Hungary during the pre-COVID (2011–2019), COVID (2020–2021), and post-COVID (2022–2023) periods. Methods: Nationwide data from the Hungarian National Health Insurance Fund database were analysed. Age- and sex-adjusted incidence and mortality trends from 2011 to 2019 were modeled using Poisson regression. Changes from trends in 2020–2023 were compared to pre-COVID projections with 95% confidence intervals. Results: From 2011 to 2019, age-standardised cancer incidence declined by 1.9% (95% CI: 1.3% to 2.4%) annually in males and by 1.0% (95% CI: 0.6% to 1.4%) in females. During 2020–2021, incidence dropped sharply below the expected: in 2020 (−12.8% in males and −11.8% in females) and in 2021 (−11.7% and −7.9%, respectively). The largest declines affected prostate, melanoma, and kidney cancer. Rapidly progressing tumors like pancreatic and esophageal showed smaller decreases. By 2023, partial incidence rebounds were observed for prostate cancer, kidney cancer, and melanoma, likely reflecting the recovery of pandemic-delayed diagnoses. Lung and liver cancers showed no rebound. The steepest drops were in males aged 70+, with incomplete recovery. Mortality stayed near expected levels overall, with some exceptions, like melanoma, where the rebound in incidence coincided with increased mortality rates in 2023, which may reflect delayed diagnosis, although this cannot be directly confirmed. Conclusions: The pandemic had lasting, cancer-type-specific impacts on incidence patterns, particularly affecting screening-dependent, slow-growing tumors. Mortality remained largely stable overall during the available follow-up, highlighting the need for targeted recovery strategies and strengthened healthcare system resilience. Full article

Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis, biological heterogeneity, and persistent challenges in staging and treatment selection. This narrative review summarizes current and emerging applications of AI across lung cancer screening and early detection, imaging-based staging and prognostication, tissue and liquid biopsy-based tumor characterization, treatment planning, surgical and intraoperative guidance, and drug discovery. In imaging, deep learning models have demonstrated high performance in pulmonary nodule detection, risk stratification, and prediction of molecular alterations, while also showing promise in improving screening efficiency and reducing interpretive variability. In pathology and liquid biopsy domains, AI enables prediction of driver mutations, immunotherapy response, and survival outcomes directly from histopathology slides, circulating tumor DNA, and other blood-based biomarkers, facilitating minimally invasive precision oncology approaches. In treatment planning and delivery, AI systems are being developed to support clinical decision-making, surgical planning (through advanced image segmentation and delineation of operative anatomy), and intraoperative navigation through robotic and computer vision-enabled platforms. Despite these advances, significant barriers remain, including limited real-world validation, algorithmic biases, workflow integration issues, and unresolved ethical and legal concerns. Future progress will depend on the development of transparent, clinically validated, and generalizable AI systems that augment rather than replace the expertise of clinical providers and healthcare teams. Active engagement from pulmonologists, oncologists, radiologists, and thoracic surgeons will be essential in guiding safe implementation and ensuring that AI-driven innovations translate into meaningful improvements in patient outcomes. Full article

Background/Objectives: Immunotherapy has emerged as an important field of research in non-small-cell lung cancer (NSCLC) and has demonstrated promising results in clinical practice. In recent years, multiple studies have been conducted, increasing the amount of available data. Therefore, the aim of this systematic review is to assess the combination of perioperative immunotherapy with chemotherapy compared to chemotherapy only in patients with resectable NSCLC in terms of survival, pathological response, and adverse events. Methods: The clinical databases PubMed, Cochrane Library, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) were systematically searched, up to March 2026. A two-step selection process served as the screening for eligibility, in which the assessment was based on pre-defined inclusion and exclusion criteria. This process was visualized via a PRISMA diagram. For each included study, the risk of bias was assessed with the help of the Cochrane Risk of Bias 2.0 tool and the Newcastle Ottawa Scale. A narrative synthesis was performed due to heterogeneity. Data were extracted into tables. Results: A total of 16 studies, involving 4646 patients in total, met the eligibility criteria, and their data on study population, intervention, comparison, and outcome were extracted into tabular form. Survival and pathological response rates are continuously higher in patients treated with immunochemotherapy. Findings on adverse events differed across the individual studies, though the results indicate an increased risk of treatment-related adverse events (TRAEs) in patients undergoing the combined treatment approach. Discussion/Conclusions: Chemoimmunotherapy leads to superior clinical outcomes in terms of survival and pathological response rates, though the trend towards a higher incidence and severity of TRAEs warrants further research. The interpretation of findings is limited by differences in study characteristics, mechanism of conduct, and endpoints between the individual studies. Full article

Background/Objectives: Given rising lung cancer incidence and limited data on pulmonologist-performed ultrasound-guided transthoracic core biopsy (US-TTCB), in this study, we evaluated diagnostic yield and safety for pleural or pulmonary lung masses, using Clavien–Dindo classification to standardize complication reporting. Methods: We retrospectively reviewed single-center pulmonologist-performed US-TTCB using a MEDONE biopsy gun with a 16 G/18 G Tru-Cut needle between January 2019 and December 2025. The primary endpoints were diagnostic yield, defined as specific malignant or benign histology, and complication rate. Non-diagnostic results were assessed using available clinical/imaging follow-up. Univariate analyses screened candidate correlates, and a prespecified computer tomography (CT)-completed subanalysis (n = 67) used multivariable logistic regression and receiver operating characteristic (ROC) analysis to assess CT lesion size discrimination. Results: Diagnostic yield was 84.2% (202/240); complications occurred in 12.1% (29/240), including one Clavien–Dindo Grade III event (0.4%). In the CT-completed subset (n = 67), diagnostic yield was independently associated with CT lesion size (aOR 1.03/mm, 95% CI 1.00–1.05; p = 0.022) and Chronic Obstructive Pulmonary Disease (COPD) (aOR 2.30, 95% CI 1.06–4.96; p = 0.034); CT lesion size showed an area under the curve (AUC) of 0.717 for predicting yield. Diagnostic yield remained stable over time (84.2% in first vs. second half; p = 1.00), with no association between case order and yield (OR 0.999; p = 0.64). Conclusions: US-TTCB of pleural/pulmonary masses achieved a high diagnostic yield with minimal major complications. Large CT dimension and COPD were associated with higher diagnostic success, and CT size provided fair discrimination for predicting yield; findings should be interpreted in the context of the retrospective single-center design and the restricted CT-completed subset. Full article