Atezolizumab (atezo) therapy for locally advanced/metastatic urinary tract carcinoma (mUTC) in patients (pts) with poor performance status (PS): Analysis of the prospective global SAUL study.
Bibliographic record
Abstract
5035 Background: Pts with PS > 1 have a poor prognosis and are often excluded from clinical trials. The single-arm SAUL study (NCT02928406) evaluated atezo in a ‘real-world’ population. Overall, safety and efficacy were consistent with prior trials. However, ECOG PS 2 pts had worse overall survival (OS) but fewer adverse events (AEs) than ECOG PS 0/1 pts [Sternberg, 2019], likely reflecting shorter treatment duration and warranting exploration. Methods: Pts with mUTC received atezo 1200 mg q3w until loss of clinical benefit or unacceptable toxicity. The primary endpoint was safety. Post hoc analyses compared baseline factors, AEs and efficacy in pts with ECOG PS 2 vs 0/1. In this analysis, AE incidences were restricted to the first 45 days of atezo to adjust for differing treatment exposure. Results: None of the baseline factors explored was significantly associated with worse OS or disease control rate (DCR) in ECOG PS 2 pts. However, pts with visceral metastases and ECOG PS 2 had particularly poor outcomes. Safety appeared similar between subgroups. Conclusions: ECOG PS 2 pts have a dismal prognosis. The higher proportion with poor prognostic factors despite similar age in ECOG PS 2 vs 0/1 pts may suggest that poor PS was related to disease rather than comorbidities. Risk/benefit should be considered especially carefully when treating pts with ECOG PS 2 due to high-burden/visceral disease. Clinical trial information: NCT02928406 . [Table: see text]
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".