A Systematic Review and Meta-Analysis of the Impact of Tumour Mutation Burden on Survival Outcomes in Solid Tumours.
메타분석
2/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
5278 patients across 28 studies were analysed.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Standardising TMB assessment and refining relevant thresholds are essential for optimising its role in precision oncology. [TRIAL REGISTRATION] PROSPERO Registration Number: CRD42024608809.
OpenAlex 토픽 ·
Cancer Genomics and Diagnostics
Pancreatic and Hepatic Oncology Research
Lung Cancer Treatments and Mutations
[BACKGROUND] Tumour mutation burden (TMB) is an emerging pan-cancer biomarker with predictive value for immune checkpoint inhibitor (ICI) outcomes, yet evidence is inconsistent due to methodological v
- HR 0.56
- 연구 설계 systematic review
APA
Aijia Meng, Alexander Yuile, et al. (2026). A Systematic Review and Meta-Analysis of the Impact of Tumour Mutation Burden on Survival Outcomes in Solid Tumours.. Cancer medicine, 15(5), e71888. https://doi.org/10.1002/cam4.71888
MLA
Aijia Meng, et al.. "A Systematic Review and Meta-Analysis of the Impact of Tumour Mutation Burden on Survival Outcomes in Solid Tumours.." Cancer medicine, vol. 15, no. 5, 2026, pp. e71888.
PMID
42041198 ↗
Abstract 한글 요약
[BACKGROUND] Tumour mutation burden (TMB) is an emerging pan-cancer biomarker with predictive value for immune checkpoint inhibitor (ICI) outcomes, yet evidence is inconsistent due to methodological variability and cut-off thresholds. This systematic review and meta-analysis evaluated the impact of TMB on overall survival (OS) and progression-free survival (PFS) across solid tumours in ICI-treated cohorts and its predictive relevance in non-ICI-treated cohorts.
[METHODS] Following PRISMA 2020 guidelines, we searched PubMed, Scopus, ScienceDirect and Cochrane for studies published between 2010 and 2024 reporting hazard ratios (HRs) and 95% confidence intervals (CIs) for OS and PFS in high- versus low-TMB cohorts. High and low TMB were defined by study-specific cut-offs, and ultra-high TMB was defined as the top 20% of cohort-specific values. Study quality was assessed with the Newcastle-Ottawa Scale; heterogeneity with I; publication bias with funnel plots/Egger's test; and robustness by leave-one-out analysis.
[RESULTS] 5278 patients across 28 studies were analysed. High TMB, defined by cohort-specific cut-offs, was significantly associated with improved OS and PFS, particularly in non-small cell lung cancer (OS: HR = 0.56), selected gastrointestinal cancers (OS: HR = 0.36), and advanced/recurrent tumours (OS: HR = 0.52). Benefits were greatest in ICI-treated patients, especially with combined anti-PD-L1/PD-1 and anti-CTLA-4 therapy (OS: HR = 0.47; PFS: HR = 0.50). Chemotherapy-treated cohorts also showed better outcomes, but less consistently (OS: HR = 0.60; PFS: HR = 0.55). Ultra-high TMB had better OS than the universal 10 mut/Mb cut-off (HR = 0.44 vs. 0.58). Non-beneficial associations were observed in glioma and penile squamous cell carcinoma, highlighting disease-specific variability. Sequencing platforms and cut-off definitions remained sources of heterogeneity.
[CONCLUSION] TMB demonstrates prognostic relevance and predictive utility in a histology- and treatment-context-dependent manner, with the most consistent associations in selected ICI-treated tumours. Associations in non-ICI-treated cohorts were weaker and inconsistent, indicating putative predictive value. Standardising TMB assessment and refining relevant thresholds are essential for optimising its role in precision oncology.
[TRIAL REGISTRATION] PROSPERO Registration Number: CRD42024608809.
[METHODS] Following PRISMA 2020 guidelines, we searched PubMed, Scopus, ScienceDirect and Cochrane for studies published between 2010 and 2024 reporting hazard ratios (HRs) and 95% confidence intervals (CIs) for OS and PFS in high- versus low-TMB cohorts. High and low TMB were defined by study-specific cut-offs, and ultra-high TMB was defined as the top 20% of cohort-specific values. Study quality was assessed with the Newcastle-Ottawa Scale; heterogeneity with I; publication bias with funnel plots/Egger's test; and robustness by leave-one-out analysis.
[RESULTS] 5278 patients across 28 studies were analysed. High TMB, defined by cohort-specific cut-offs, was significantly associated with improved OS and PFS, particularly in non-small cell lung cancer (OS: HR = 0.56), selected gastrointestinal cancers (OS: HR = 0.36), and advanced/recurrent tumours (OS: HR = 0.52). Benefits were greatest in ICI-treated patients, especially with combined anti-PD-L1/PD-1 and anti-CTLA-4 therapy (OS: HR = 0.47; PFS: HR = 0.50). Chemotherapy-treated cohorts also showed better outcomes, but less consistently (OS: HR = 0.60; PFS: HR = 0.55). Ultra-high TMB had better OS than the universal 10 mut/Mb cut-off (HR = 0.44 vs. 0.58). Non-beneficial associations were observed in glioma and penile squamous cell carcinoma, highlighting disease-specific variability. Sequencing platforms and cut-off definitions remained sources of heterogeneity.
[CONCLUSION] TMB demonstrates prognostic relevance and predictive utility in a histology- and treatment-context-dependent manner, with the most consistent associations in selected ICI-treated tumours. Associations in non-ICI-treated cohorts were weaker and inconsistent, indicating putative predictive value. Standardising TMB assessment and refining relevant thresholds are essential for optimising its role in precision oncology.
[TRIAL REGISTRATION] PROSPERO Registration Number: CRD42024608809.
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