Impact of pure versus mixed metastatic urothelial carcinoma (mUC) histology on response with immune checkpoint inhibitors (ICIs).
Bibliographic record
Abstract
479 Background: PD1/PD-L1 inhibitors have been evaluated in trials enrolling patients (pts) with pure urothelial or mixed urothelial histology containing non-urothelial components. However, any differential impact of pure vs. mixed urothelial histology on ICI benefit is unclear. We conducted a retrospective study to evaluate the impact of pure vs. mixed urothelial carcinoma histology on outcomes with ICIs in pts with metastatic urothelial carcinoma (mUC). Methods: We obtained data from 120 pts with mUC from a single institution (DFCI) who received ICI therapy. Demographic, clinical variables and outcomes (overall response rate [ORR], overall survival [OS]) were collected. Histology was reviewed at DFCI for all pts and recorded as pure urothelial if only urothelial carcinoma was seen or mixed urothelial if components of any other histology were observed in addition to urothelial. A Cox regression analysis was done to study the association of prognostic variables and histology with objective response. Results: Data was obtained from 120 pts, of whom 110 (91.7%) received a single agent PD1/PD-L1 inhibitor (pembrolizumab=58, atezolizumab=52, nivolumab=4, nivolumab + ipilimumab=3, nivolumab + vaccine=2, durvalumab+tremelimumab=1). The median age was 66, 70.8% were male and 72.5% had received prior chemotherapy. 79 (65.8%) tumors originated from the bladder, 39 (32.5%) from the upper tract, 2 (1.67%) had unknown site of origin. 91 (76.6%) had pure urothelial and 28 (23.3%) had mixed urothelial histology. On univariable analysis, pure vs. mixed urothelial histology was not associated with response (HR 1.52 [95% CI 0.59-3.98, p=0.39]). On multivariable analysis, upper tract vs. bladder primary (HR 3.06 [95% CI 1.10-8.49], p=0.032) and higher blood neutrophil to lymphocyte ratio (HR 0.35 [95% CI 0.17-0.72], p=0.004) were associated with lower response rate. Conclusions: In this hypothesis-generating study, pure vs. mixed urothelial carcinoma histology did not appear to significantly impact response to ICI therapy for mUC. The impact of proportion of non-urothelial histology, pure non-urothelial histology and site of primary on response warrants further study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".