A Systematic Review and Meta-Analysis of the Impact of Tumour Mutation Burden on Survival Outcomes in Solid Tumours
Bibliographic record
Abstract
ABSTRACT 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 2 ; 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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".