External Validation of a Prognostic Model of Overall Survival in Men With Chemotherapy-Naïve Metastatic Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
PURPOSE We have previously developed and externally validated a prognostic model of overall survival (OS) in men with metastatic, castration-resistant prostate cancer (mCRPC) treated with docetaxel. We sought to externally validate this model in a broader group of men with docetaxel-naïve mCRPC and in specific subgroups (White, Black, Asian patients, different age groups, and specific treatments) and to classify patients into validated two and three prognostic risk groupings on the basis of the model. METHODS Data from 8,083 docetaxel-naïve mCRPC men randomly assigned on seven phase III trials were used to validate the prognostic model of OS. We assessed the predictive performance of the model by computing the time-dependent area under the receiver operating characteristic curve (tAUC) and validated the two-risk (low and high) and three-risk prognostic groups (low, intermediate, and high). RESULTS The tAUC was 0.74 (95% CI, 0.73 to 0.75), and when adjusting for the first-line androgen receptor (AR) inhibitor trial status, the tAUC was 0.75 (95% CI, 0.74 to 0.76). Similar results were observed by the different racial, age, and treatment subgroups. In patients enrolled on first-line AR inhibitor trials, the median OS (months) in the low-, intermediate-, and high-prognostic risk groups were 43.3 (95% CI, 40.7 to 45.8), 27.7 (95% CI, 25.8 to 31.3), and 15.4 (95% CI, 14.0 to 17.9), respectively. Compared with the low-risk prognostic group, the hazard ratios for the high- and intermediate-risk groups were 4.3 (95% CI, 3.6 to 5.1; P < .0001) and 1.9 (95% CI, 1.7 to 2.1; P < .0001). CONCLUSION This prognostic model for OS in docetaxel-naïve men with mCRPC has been validated using data from seven trials and yields similar results overall and across race, age, and different treatment classes. The prognostic risk groups are robust and can be used to identify groups of patients for enrichment designs and for stratification in randomized clinical trials. [Media: see text]
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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".