CheckMate 77 T: A phase 3 trial of neoadjuvant nivolumab (NIVO) + chemotherapy (chemo) followed by adjuvant NIVO in resectable early-stage non-small cell lung cancer (NSCLC)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Although surgery for early NSCLC is potentially curative, 5-year overall survival (OS) rates for patients (pts) with stage IIA–IIIB NSCLC are historically < 50%, representing a population of high unmet need. Conventional neoadjuvant or adjuvant chemo provides a 5% absolute improvement in OS at 5 years. A rational approach to improve survival in these pts is to eradicate micrometastatic disease and potentially induce anti-tumor immunity to minimize the risk of relapse with peri-operative regimens including NIVO, a fully human anti-programmed cell death 1 antibody. Early phase trials indicate the potential of NIVO-based regimens to deepen pathological responses and extend survival in this setting (Reuss JE et al, ASCO 2019. Abstract 8524; Cascone T et al, ASCO 2019. Abstract 8504; Provencio M et al, WCLC2019. Abstract OA13.05). Phase 2 single-arm NADIM trial (NCT03081689) demonstrated a major pathological response (MPR) rate of 83% with neoadjuvant NIVO + chemo followed by adjuvant NIVO in pts with resectable stage IIIA NSCLC (Provencio M et al, WCLC2019. Abstract OA13.05). These results require validation in a large randomized controlled study. CheckMate 77 T (NCT04025879), a phase 3, randomized, double-blind trial, evaluates neoadjuvant NIVO + chemo followed by adjuvant NIVO in resectable early stage NSCLC.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 it