Prediction of Survival following First-Line Chemotherapy in Men with Castration-Resistant Metastatic Prostate Cancer
Bibliographic record
Abstract
PURPOSE: We sought to evaluate predictors of overall survival following progression after systemic chemotherapy in men with metastatic castration-resistant prostate cancer. EXPERIMENTAL DESIGN: For our study population, we used the TAX327 multicenter randomized phase III trial comparing administration of docetaxel and prednisone every 3 weeks, weekly administration of docetaxel and prednisone, and administration of mitoxantrone and prednisone every 3 weeks. Progression was defined as the earliest of prostate-specific antigen (PSA), tumor, or pain progression. We analyzed predictors of postprogression survival according to both prechemotherapy and postchemotherapy variables with adjustment for potential confounders. RESULTS: Among 1,006 men, 640 had evaluable information on protocol-defined progression leading to further therapy. Median postprogression survival was 14.5 months. In the multivariable analysis, several pretreatment factors were associated with postprogression survival: pain, performance status, alkaline phosphatase, number of sites of metastatic disease, liver metastases, hemoglobin, PSA, and time since diagnosis. In addition, we found that the number of progression factors (PSA, pain, and tumor size), the duration of first-line chemotherapy, and whether progression occurred during chemotherapy independently predicted postprogression survival. We found evidence for the benefit of continuation of chemotherapy beyond progression only for men who had isolated worsening of pain. A nomogram was constructed and internally validated with a concordance index of 0.70. CONCLUSIONS: An internally validated model to predict postchemotherapy survival was developed. Evaluation of men in the postdocetaxel setting should consider the type of progression, duration of therapy, and known pretreatment prognostic factors. Definitions of progression in castration-resistant prostate cancer that include pain should also consider composite measures of tumor or PSA progression. External validation is planned.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".