Impact of Tumor Response and Response Duration on Survival Among Participants Receiving Pembrolizumab Plus Chemotherapy as First-Line Therapy for Non-Small-Cell Lung Cancer
Bibliographic record
Abstract
INTRODUCTION: Response Evaluation Criteria in Solid Tumors (RECIST) is the primary tool for assessing tumor response in solid tumors. Immunotherapy elicits unique response patterns, and assessment of their contribution to overall survival (OS) is of interest. We evaluated tumor size changes (TSC) for association with OS, evaluated whether deeper response had greater association with OS than the 30% RECIST cutoff, and quantified the contribution of objective response rate (ORR) and duration of response (DOR) to OS benefit using data from KEYNOTE-189 and KEYNOTE-407 examining first-line pembrolizumab plus chemotherapy in metastatic non-small-cell lung cancer (NSCLC). METHODS: Associations between early TSC (percentage change from baseline in sum of target lesion diameters) and OS were evaluated using recursive partitioning analyses, C-index, and time-varying receiver operating characteristic curve. Deeper response and OS associations were assessed in sensitivity analyses. Contribution of TSC, ORR, and DOR to the OS benefit of pembrolizumab plus chemotherapy (versus chemotherapy) was quantified with a proportion of treatment effect analysis. Data cutoff was May 2019. RESULTS: In total, 1175 participants were included (KEYNOTE-189, n = 616; KEYNOTE-407, n = 559). At week 12, -30% TSC had a greater association with OS than other cutoffs, which was similar to week 12 ORR. Deeper response did not have greater association with OS than the 30% RECIST cutoff. For pembrolizumab plus chemotherapy versus chemotherapy in KEYNOTE-189, the proportion of treatment effect on OS benefit for DOR coupled with ORR was higher than ORR alone (0.57 versus 0.36) or an alternative TSC cutoff (0.57 versus 0.08 for -10%, 0.09 for -20%, and 0.20 for -30%), with similar results in KEYNOTE-407 for DOR and ORR versus ORR alone (0.92 versus 0.61) or an alternative TSC cutoff (0.92 versus 0.36, 0.43, and 0.40, respectively). CONCLUSIONS: These ad hoc exploratory analyses suggest that RECIST remains a valid assessment for metastatic NSCLC treated with immunotherapy plus chemotherapy. Early responses per RECIST criteria predicted improved OS. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02578680, NCT02775435.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".