Abstract CT097: Associations between percent residual viable tumor (%RVT) and efficacy with perioperative nivolumab (NIVO) for resectable NSCLC in CheckMate 77T
Bibliographic record
Abstract
Abstract Background: In CheckMate 816, lower %RVT in primary tumor (PT) and lymph node (LN) after neoadjuvant (neoadj) NIVO + chemo correlated with improved EFS in patients (pts) with resectable NSCLC. To further evaluate %RVT as a surrogate for EFS, we report an exploratory analysis of efficacy with adjuvant (adj) NIVO after neoadj treatment (tx) by LN involvement, nodal (N) status, and %RVT in PT and LN in CheckMate 77T. Methods: Pts with resectable stage IIA-IIIB NSCLC were randomized to neoadj NIVO + chemo Q3W (up to 4 cycles [cyc]) followed by adj NIVO Q4W (up to 13 cyc) or neoadj placebo (PBO) + chemo Q3W (up to 4 cyc) followed by adj PBO Q4W (up to 13 cyc). Primary endpoint: EFS per BICR. This analysis, which included pts with pathologically evaluable samples who had definitive surgery and ≥ 1 adj tx dose, assessed EFS by LN involvement, N status, %RVT in PT and LN, and associations between %RVT and EFS per time-dependent ROC curve analysis. Results: BL characteristics were similar between tx arms (NIVO, 123; PBO, 134; median f/u, 33.3 mo). NIVO improved EFS v PBO regardless of LN involvement or N status (Table). A higher proportion of pts treated with NIVO had 0% RVT in PT and/or LN v PBO (52% v 20%). In pts with LN involvement, 2-y EFS rates with NIVO were higher in pts with 0% RVT in both PT and LN (90%) or 0% RVT in PT or LN (85%) v > 0% RVT in both PT and LN (76%). Area under the ROC curve for %RVT-PT in pts with PT-only disease was 0.83. 2-y EFS rates with NIVO were 94%, 77%, and 50% in pts with 0-5%, > 5-80%, and > 80% RVT-PT, respectively; similar results were seen in all pts with pathologically evaluable samples whether they received adj tx or not. Conclusions: In this exploratory analysis, NIVO improved EFS v PBO, particularly in pts with LN involvement and regardless of N status. %RVT also associated with EFS in a continuous manner, supporting %RVT as a surrogate for EFS and highlighting its prognostic value in pts who receive perioperative NIVO. Citation Format: Julie Stein Deutsch, Ashley Cimino-Mathews, Elizabeth Thompson, Edward Gabrielson, Peter Illei, Jaroslaw Jedrych, Ezra Baraban, Alex S. Baras, Mariano Provencio Pulla, Tina Cascone, Jonathan D. Spicer, Mark M. Awad, Fumihiro Tanaka, Jie He, Shun Lu, Cinthya Coronado Erdmann, Vipul Devas, Sumeena Bhatia, Janis M. Taube. Associations between percent residual viable tumor (%RVT) and efficacy with perioperative nivolumab (NIVO) for resectable NSCLC in CheckMate 77T [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr CT097.
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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) | 0.000 | 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 | 0.000 |
| 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".