A phase 1b study evaluating the safety and preliminary efficacy of berzosertib in combination with gemcitabine in patients with advanced non-small cell lung cancer
Bibliographic record
Abstract
OBJECTIVES: Berzosertib (formerly M6620, VX-970) is an intravenous, highly potent and selective, first-in-class ataxia telangiectasia and Rad3-related (ATR) protein kinase inhibitor. We assessed the safety, tolerability, preliminary efficacy, and pharmacokinetics (PK) of berzosertib plus gemcitabine in an expansion cohort of patients with advanced non-small cell lung cancer (NSCLC). The association of efficacy with TP53 status and other tumor markers was also explored. MATERIALS AND METHODS: (days 1 and 8) at the recommended phase 2 dose established in the dose escalation part of the study. RESULTS: Thirty-eight patients received at least one dose of study treatment. The most common treatment-emergent adverse events were fatigue (55.3%), anemia (52.6%), and nausea (39.5%). Gemcitabine had no apparent effect on the PK of berzosertib. The objective response rate (ORR) was 10.5% (4/38, 90% confidence interval [CI]: 3.7-22.5%). In the exploratory analysis, the ORR was 30.0% (3/10, 90% CI: 9.0-61.0%) in patients with high loss of heterozygosity (LOH) and 11.0% (1/9, 90% CI: 1.0-43.0%) in patients with low LOH. The ORR was 33.0% (2/6, 90% CI: 6.0-73.0%) in patients with high tumor mutational burden (TMB), 12.5% (2/16, 90% CI: 2.0-34.0%) in patients with intermediate TMB, and 0% (0/3, 90% CI: 0.0-53.6%) in patients with low TMB. CONCLUSIONS: Berzosertib plus gemcitabine was well tolerated in patients with advanced, pre-treated NSCLC. Based on the observed clinical efficacy, future clinical trials should involve genomically selected patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".