Blood-based tumor mutational burden as a biomarker for atezolizumab in non-small cell lung cancer: the phase 2 B-F1RST trial
Bibliographic record
Abstract
Tumor mutational burden (TMB) in circulating tumor DNA (ctDNA) has shown promise in predicting benefit from PD-L1/PD-1 inhibitors in retrospective studies. Aiming to assess blood TMB (bTMB) prospectively, we conducted B-F1RST ( NCT02848651 ), an open-label, phase 2 trial that evaluated bTMB as a predictive biomarker for first-line atezolizumab monotherapy in locally advanced or metastatic stage IIIB-IVB non-small cell lung cancer (n = 152). The co-primary endpoints were investigator-assessed objective response rate (ORR) per RECIST version 1.1 and investigator-assessed progression-free survival (PFS) between high and low bTMB subgroups at the pre-defined bTMB ≥ 16 (14.5 mutations per megabase) cutoff. Secondary endpoints included investigator-assessed PFS, overall survival (OS) and duration of response at various bTMB cutoffs, as well as safety. Investigator-assessed PFS in the bTMB ≥ 16 versus bTMB < 16 groups was not statistically significant. However, bTMB ≥ 16 was associated with higher ORR, and ORR improved as bTMB cutoffs increased. No new safety signals were seen. In exploratory analyses, patients with maximum somatic allele frequency (MSAF) < 1% had higher ORR than patients with MSAF ≥ 1%. However, further analysis showed that this effect was driven by better baseline prognostics rather than by MSAF itself. At 36.5-month follow-up, an exploratory analysis of OS found that bTMB ≥ 16 was associated with longer OS than bTMB < 16. Further study and assay optimization will be required to develop bTMB as a predictive, standalone biomarker of immunotherapy or for use in conjunction with other biomarkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".