Identification of characteristics predictive of long-term survival with durvalumab or durvalumab plus tremelimumab in metastatic urothelial carcinoma
Bibliographic record
Abstract
BACKGROUND: This retrospective analysis of data from clinical trials in metastatic urothelial carcinoma (mUC) was conducted to determine baseline patient characteristics associated with long-term survival (LTS) following treatment with immune checkpoint inhibitors. METHODS: Data for this analysis were from patients with platinum-refractory mUC who received durvalumab or durvalumab plus tremelimumab in phase 1/2 studies. The primary outcome measure was LTS. Patients were categorised as overall survival (OS) ≥ 2 years (from first dose) or OS < 2 years. A univariable analysis assessed independent associations with LTS and multivariable logistic regression was employed including each variable with P ≤ 0.05 as covariates. RESULTS: Among 360 patients, 88 (24.4%) had OS ≥ 2 years and 272 (75.6%) had OS < 2 years. In univariable analysis, several baseline characteristics and laboratory measurements were associated with LTS including sex, ECOG PS, PD-L1 expression, prior surgery, time from initial diagnosis, lymph node-only involvement, visceral disease, haemoglobin level, absolute neutrophil count, neutrophil-lymphocyte ratio and lactate dehydrogenase level. In multivariable analysis, LTS was significantly associated with ECOG PS, PD-L1 expression, haemoglobin level and absolute neutrophil count. CONCLUSIONS: Several baseline clinical characteristics and laboratory measurements were associated with LTS for patients with platinum-refractory mUC treated with durvalumab or durvalumab plus tremelimumab.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".