Nomogram to assess benefit of new over historical agents as salvage therapy for metastatic urothelial carcinoma (mUC) in non-randomized trials: Effect of atezolizumab on 12-month survival.
Bibliographic record
Abstract
346 Background: Early surrogate endpoints of benefit in mUC phase 2 salvage therapy trials are necessary to identify promising drugs, particularly for checkpoint inhibitors where response and progression-free survival are inadequate. We developed a nomogram using prognostic variables from phase 2 trials of historical agents to estimate 12 month survival to which observed survival in single arm trials could be compared. Methods: Data were obtained from phase II trials of salvage therapy for mUC for survival and 5 prognostic factors: hemoglobin, performance status, liver metastasis, treatment-free interval and albumin. Patients (pts) were randomly allotted to discovery:validation (DIS:VAL) datasets in a 2:1 ratio. A nomogram was developed for estimating 12-month survival. Calibration plots were constructed in the VAL dataset by plotting estimated vs. observed 12-mo survival and data bootstrapped to assess performance. The nomogram was applied to external nonrandomized salvage therapy data: 1) retrospective pemetrexed data or 2) trials of atezolizumab: PCD4989g and IMvigor210. Results: Data were available from 340 pts receiving sunitinib (n = 77), everolimus (n = 45), docetaxel + vandetanib or placebo (n = 109), pazopanib (n = 42), paclitaxel (n = 36) and docetaxel (n = 31). Calibration and prognostic ability of the model was acceptable (c-index = 0.634, 95% CI = 0.596-0.652). Observed 12-month survival for pts on pemetrexed (n = 127, 23.5% [95% CI: 16.2%-31.7%]) were similar to nomogram-predicted survival (19% [95% CI: 16.5-21.5], P> 0.05), while observed result with atezolizumab (n = 403, 39.0% [95% CI: 34.1-43.9]) exceeded predicted result (24.6% [95% CI: 23.4-25.8], P< 0.001). Conclusions: Atezolizumab was associated with a significantly longer 12-mo survival compared to nomogram-predicted survival while pemetrexed was not. This nomogram incorporates baseline prognostic factors to provide expected 12-mo survival of phase 2 patient cohorts with which to compare observed survival, thereby providing a useful tool to quantify benefit in phase II studies while controlling for the impact of clinical variables.
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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 | 0.071 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".