Evidence map›Paper›PMID 39777634›Full record

ArticleTargeted oncology2025

Tumour Mutational Burden and Immune Checkpoint Inhibitor Response in Non-small Cell Lung Cancer: A Continuous Modelling Approach.

Michael J Sorich, Arkady T Manning-Bennett, Lee X Li, Adel Shahnam, Ganessan Kichenadasse, Christos S Karapetis, Ahmad Y Abuhelwa, Ross A McKinnon, Andrew Rowland, Ashley M Hopkins

Abstract read
In one paragraph

Article in Targeted oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Michael J Sorich *College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia. michael.sorich@flinders.edu.au.ORCID http://orcid.org/0000-0003-1999-866X
Arkady T Manning-Bennett *College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.ORCID http://orcid.org/0000-0002-6592-5675
Lee X LiCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Adel ShahnamDepartment of Medical Oncology, Peter McCallum Cancer Centre, Melbourne, VIC, Australia.
Ganessan KichenadasseCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Christos S KarapetisCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Ahmad Y AbuhelwaDepartment of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates.
Ross A McKinnonCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Andrew RowlandCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Ashley M HopkinsCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.

Funding

National Health and Medical Research Council GNT2013565
6 · The paper itself

Abstract

backgroundTumour mutational burden (TMB) is an established biomarker for patients treated with immune checkpoint inhibitors (ICIs). The optimal TMB cut-off is uncertain. It is also uncertain whether there is a sharp TMB threshold or a more graduated change in clinical outcomes as TMB increases.

objectiveWe aimed to determine the relationship between TMB and ICI treatment outcomes using alternative statistical approaches in patients with non-small cell lung cancer.

methodsTumour mutational burden was evaluated as a prognostic and predictive biomarker in advanced non-small cell lung cancer utilising data from two real-world cohorts of ICI use (n = 968) and three randomised controlled trials evaluating ICIs (n = 1588). The non-linear relationship between continuous TMB and response/survival/efficacy outcomes was evaluated using statistical methods that do not require specifying a TMB cut-off.

resultsMedian TMB for all cohorts was seven mutations/megabase, excluding MYSTIC, where the median was 13 mutations/megabase. Progressively higher TMB was significantly associated with a progressively higher objective response rate and progression-free survival in ICI-treated patients in Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets [MSK-IMPACT] (objective response rate: p < 0.001, progression-free survival: p < 0.001), Strata Clinical Molecular Database [SCMD] (progression-free survival: p = 0.023) and OAK/POPLAR (objective response rate: p = 0.017, progression-free survival: p < 0.001) This relationship was not apparent for patients treated with chemotherapy. There was no obvious TMB threshold for ICI response. The relationship between TMB and overall survival was more complex and heterogeneous.

conclusionsUsing a single cut-off to analyse a continuous biomarker may hide important information. Methods that provide more nuance to the underlying relationship between TMB and outcomes enable readers to judge for themselves the value and limitations of TMB cut-offs proposed for clinical practice.

Indexed as

Carcinoma, Non-Small-Cell LungImmune Checkpoint InhibitorsLung NeoplasmsAgedFemaleHumansMaleMiddle AgedMutationImmune Checkpoint Inhibitors

Identifiers

PMID39777634
PMCPMC11933204

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.