180O IMpassion132 double-blind randomised phase III trial of chemotherapy (CT) ± atezolizumab (atezo) for early-relapsing unresectable locally advanced or metastatic triple-negative breast cancer (aTNBC)
Bibliographic record
Abstract
Immune checkpoint inhibitors (ICIs) improve efficacy of first-line CT for some patients (pts) with aTNBC but data in early relapse are limited. IMpassion132 (NCT03371017) enrolled pts with aTNBC relapsing <12 mo after the last of any anthracycline- and taxane-containing (neo)adjuvant CT or primary TNBC surgery. PD-L1 status was centrally assessed by SP142 before randomisation. Initially pts were enrolled irrespective of PD-L1 status. In Aug 2019 the protocol was amended to enrich for PD-L1+ (tumour immune cell ≥1%) aTNBC. Stratification factors were investigator-selected CT (capecitabine 1000 mg/m2 bid d1–14 q21d [X] or carboplatin AUC2 + gemcitabine 1000 mg/m2 d1 & 8 q21d [CG]), visceral (lung and/or liver) metastases and (until Aug 2019) PD-L1 status. Pts were randomised 1:1 to placebo or atezo 1200 mg q21d with chosen CT until progression or unacceptable toxicity. Crossover was not allowed. The primary endpoint was overall survival (OS), tested hierarchically first in PD-L1+ pts then, if positive, in the modified intent-to-treat (mITT*) population. Secondary endpoints included progression-free survival (PFS), objective response rate (ORR) and safety. Among 354 PD-L1+ pts (of 595 pts enrolled), 68% had a disease-free interval <6 mo and 73% received CG. The primary objective was not met (Table); subgroup results were consistent. PFS was similar across treatment arms and populations (median ∼4 mo). ORRs were 28% with placebo + CT vs 40% with atezo + CT. Adverse events (predominantly haematological) were broadly similar between arms and as expected with atezo + CG or X in early-relapsing aTNBC.Table: 180OFinal OS analysis (prespecified after ∼247 deaths in the PD-L1+ population); median follow-up 9 monthsOS (95% CI)PD-L1+mITT*Placebo + CT (n=177)Atezo + CT (n=177)Placebo + CT (n=192)Atezo + CT (n=188)Events, n (%)128 (72)124 (70)160 (83)158 (84)Stratified hazard ratio0.93 (0.73–1.20); p=0.590.94 (0.76–1.18)Median, mo11.2 (9.0–13.3)12.1 (10.1–15.1)9.8 (8.4–12.0)10.4 (8.9–12.9)12-mo rate, %48 (40–55)50 (43–58)42 (35–50)46 (39–54)18-mo rate, %32 (25–40)34 (26–41)26 (19–32)27 (20–34)*All-comer pts randomised before Aug 2019. Open table in a new tab *All-comer pts randomised before Aug 2019. Pts with early-relapsing aTNBC have a dismal prognosis that is not improved with atezo.A biology-based definition of intrinsic resistance to ICIs in aTNBC is urgently needed to optimally treat these pts and design next-generation (combination) clinical trials.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".