AZUR-2, a phase III, open-label, randomized study of perioperative dostarlimab monotherapy vs standard of care in previously untreated patients with T4N0 or stage III dMMR/MSI-H resectable colon cancer.
Bibliographic record
Abstract
TPS240 Background: Emerging evidence suggests neoadjuvant therapy may benefit patients (pts) with advanced colon cancer. Neoadjuvant immunotherapy has shown promising efficacy for early-stage mismatch repair deficient (dMMR) colon cancer [1,2]. Evidence from other immunogenic tumors suggests that a perioperative approach with immunotherapy may further improve survival outcomes [3,4]. Dostarlimab (anti-PD-1) has shown a favorable benefit:risk profile in previously untreated dMMR locally advanced rectal cancer [5] and in advanced dMMR/microsatellite instability-high (MSI-H) solid tumors [6]. AZUR-2 (NCT05855200) will evaluate the efficacy and safety of perioperative dostarlimab monotherapy vs standard of care (SOC) in pts with previously untreated T4N0 or Stage III dMMR/MSI-H resectable colon adenocarcinoma. Methods: AZUR-2 is a global, multicenter, randomized, open-label Phase III study. Approximately 711 pts will be enrolled. Key eligibility criteria include age ≥18 years, no prior therapy or surgery for colon cancer, ECOG PS 0–1, and no symptomatic bowel obstruction. Central prescreening is available at sites without local dMMR/MSI-H testing (not required if dMMR/MSI-H already determined). Pts stratified by clinical tumor/node (TN) staging will be randomized 2:1 to receive dostarlimab pre- and post-surgery, or surgery followed by SOC (adjuvant FOLFOX/CAPEOX for 3–6 months or watch and wait approach per physician’s discretion). Primary endpoint is event-free survival (EFS) (events: recurrence based on radiological assessment by blinded independent central review or pathological assessment of new lesions, disease progression precluding surgery, treatment (tx)-related toxicity precluding surgery, or death). Secondary endpoints include pathological response, OS, and safety. Disease assessments will consist of CT scans of chest, abdomen, and pelvis. Pts will undergo safety follow-up at end of tx and at 30 and 90 days after last dose. Efficacy will be assessed in all pts randomized (intent-to-treat) and safety in all pts who receive surgery or ≥1 dose of study tx. A stratified log-rank test will be used for primary analysis. The primary analysis for EFS with >90% power will be conducted after all pts have been followed for ≥3 years. An interim EFS analysis will be conducted ~12 months earlier. Exploratory endpoints include pt-reported outcomes to evaluate health-related quality of life. References: [1] Chalabi M, et al. Nat Med 2020;26:566–76. [2] Chalabi M, et al. Ann Oncol 2022;33(suppl 7):S808–69. [3] Patel S, et al. NEJM 2023;388:813–23. [4] Wakelee H, et al. NEJM 2023;389:491–503. [5] Cercek A, et al. NEJM 2022;386:2363–76. [6] Andre T, et al. JCO 2022;40(16 suppl):2587. Funding:GSK (219606). Editorial support provided by Fishawack Health, funded by GSK. Clinical trial information: NCT05855200 .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".