Validated five-factor prognostic model for survival of patients (pts) with metastatic urothelial carcinoma (mUC) receiving different post-platinum PD-L1 inhibitors.
Bibliographic record
Abstract
476 Background: A prognostic model for overall survival (OS) of mUC was previously reported in the setting of post-platinum atezolizumab (Pond GR, GU ASCO 2018). This model was limited by employing only atezolizumab treated pts, small size of the validation dataset and unclear applicability to other PD-1/L1 inhibitors. Hence, we constructed a robust prognostic model utilizing the combined atezolizumab cohort as the discovery dataset and used a validation dataset comprised of post-platinum avelumab-treated pts. Methods: The discovery dataset consisted of pt level data from 2 phase I/II trials (IMvigor210 and PCD4989g) evaluating atezolizumab (n = 405). Pts enrolled on a phase I/II trial that received post-platinum avelumab (n = 242) comprised the validation dataset (EMR 100070-001). Cox regression analyses evaluated the association of candidate prognostic factors with OS. Factors were dichotomized and laboratory values were normalized by logarithmic transformation. Stepwise selection was employed to propose an optimal model using the discovery dataset. Discrimination (via c-statistic) and calibration were assessed in the avelumab dataset following the validation procedure by Royston and Altman (2013). Results: The 5 factors included in the optimal prognostic model in the discovery dataset were ECOG-PS (1 vs. 0; HR 1.80; 95% CI [1.36-2.36]), presence/absence of liver metastasis (HR 1.55; 95% CI [1.20-2.00]), number of platelets (HR 2.22; 95% CI [1.54-3.18]), neutrophil-lymphocyte ratio (NLR; HR 1.94; 95% CI [1.57-2.40]) and lactate dehydrogenase (LDH; HR 1.60; 95% CI [1.28-1.99]). The c-statistic for prediction of survival was 0.692 and 0.671 in the discovery and validation datasets, respectively. Acceptable or good calibration of expected 1-year survival was observed. Conclusions: A 5-factor externally validated prognostic model for OS is proposed employing a large dataset of 647 pts overall in the setting of post-platinum PD-L1 inhibitors for mUC. This model may assist in prognostic stratification and interpreting nonrandomized trials of post-platinum PD1/L1 inhibitors.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".