Neoadjuvant durvalumab (D) + chemotherapy (CT) + novel anticancer agents and adjuvant D ± novel agents in resectable non-small-cell lung cancer (NSCLC): Updated outcomes from NeoCOAST-2.
Bibliographic record
Abstract
8046 Background: Perioperative CT + immune checkpoint inhibitor therapy has improved outcomes in resectable NSCLC but most patients (pts) still do not experience pathological complete response (pCR) and long-term benefit. We report final pCR rates, ongoing circulating tumor DNA (ctDNA) findings, and updated safety data from Arms 1/2/4 of NeoCOAST-2 (NCT05061550), a phase 2 platform study evaluating neoadjuvant and adjuvant D ± novel agent-based combinations in pts with untreated Stage IIA–IIIB resectable NSCLC. Methods: Pts were stratified by PD-L1 expression (<1% vs ≥1%) and randomized to neoadjuvant D + platinum-doublet CT + oleclumab (anti-CD73 monoclonal antibody [mAb]) then adjuvant D + oleclumab (Arm 1), neoadjuvant D + platinum-doublet CT + monalizumab (anti-NKG2A mAb) then adjuvant D + monalizumab (Arm 2), or neoadjuvant D + single-agent platinum CT + Dato-DXd (TROP2-directed antibody-drug conjugate [ADC]) then adjuvant D (Arm 4). Neoadjuvant therapy was given Q3W for 4 cycles. Adjuvant therapy was given for up to 1 year or until disease progression. Primary endpoints were pCR rate by blinded independent pathology review and safety and tolerability. Key secondary endpoints included major pathological response (mPR) rate, ctDNA clearance, and feasibility of surgery. Results: As of Dec 19 2024, 202 pts were randomized (Arms 1/2/4, N=76/72/54). Among dosed pts with confirmed NSCLC, pCR and mPR rates were numerically higher in Arm 4 vs Arms 1/2 overall and in pts with a PD-L1 TPS <1% or ≥1% (Table). Rates of ctDNA clearance in the neoadjuvant period were higher in Arm 4 vs Arms 1/2, and higher in pts with pCR vs non-pCR and with mPR vs non-mPR across arms. Among dosed pts, 69/74 (93.2%) pts in Arm 1, 66/71 (93.0%) pts in Arm 2, and 51/54 (94.4%) pts in Arm 4 underwent surgery; overall, grade ≥3 treatment-related adverse events occurred in 36.5%, 40.8%, and 20.4% of pts, respectively. Conclusions: All arms show that novel perioperative combinations may improve pCR rates and maintain tolerability and feasibility of surgery in resectable NSCLC. The final analysis of pCR and mPR rates in Arm 4 is the first for an ADC in this setting and confirms the encouraging efficacy and manageable safety profile of D + CT + Dato-DXd. Presurgical ctDNA clearance is associated with pathological responses. Clinical trial information: NCT05061550 . Arm 1 Arm 2 Arm 4 Overall, n (%) [95% CI]pCRmPR n=74 15 (20.3) [11.8–31.2] 31 (41.9) [30.5–53.9] n=70 18 (25.7) [16.0–37.6] 35 (50.0) [37.8–62.2] n=54 19 (35.2) [22.7–49.4] 34 (63.0) [48.7–75.7] PD-L1 TPS <1%, n (%)pCRmPR n=25 4 (16.0) 10 (40.0) n=28 5 (17.9) 10 (35.7) n=16 5 (31.3) 10 (62.5) PD-L1 TPS ≥1%, n (%)pCRmPR n=49 11 (22.4) 21 (42.9) n=42 13 (31.0) 25 (59.5) n=38 14 (36.8) 24 (63.2)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".