A Contemporary Prognostic Nomogram for Men with Hormone-Refractory Metastatic Prostate Cancer: A TAX327 Study Analysis
Bibliographic record
Abstract
PURPOSE: To develop a prognostic model and nomogram using baseline clinical variables to predict death among men with metastatic hormone-refractory prostate cancer (HRPC). EXPERIMENTAL DESIGN: TAX327 was a clinical trial that randomized 1,006 men with metastatic HRPC to receive every three week or weekly docetaxel or mitoxantrone, each with prednisone. We developed a multivariate Cox model and nomogram to predict survival at 1, 2, and 5 years. RESULTS: Ten independent prognostic factors other than treatment group were identified in multivariate analysis: (a) presence of liver metastases [hazard ratio (HR), 1.66; P = 0.019], (b) number of metastatic sites (HR, 1.63 if > or =2 sites; P = 0.001), (c) clinically significant pain (HR, 1.48; P < 0.0001), (d) Karnofsky performance status (HR, 1.39 if < or =70; P = 0.016), (e) type of progression (HR, 1.37 for measurable disease progression and 1.29 for bone scan progression; P = 0.005 and 0.01, respectively), (f) pretreatment prostate-specific antigen (PSA) doubling time (HR, 1.19 if <55 days; P = 0.066), (g) PSA (HR, 1.17 per log rise; P < 0.0001), (h) tumor grade (HR, 1.18 for high grade; P = 0.069), (i) alkaline phosphatase (HR, 1.27 per log rise; P < 0.0001), and (j) hemoglobin (HR, 1.11 per unit decline; P = 0.004). A nomogram was developed based on this multivariate model and validated internally using bootstrap methods, with a concordance index of 0.69. CONCLUSIONS: This multivariate model identified several new independent prognostic factors in men with metastatic HRPC, including PSA doubling time, and led to the successful development of a clinically applicable nomogram. External prospective validation may support the wider use of this prognostic baseline model for men with HRPC treated with chemotherapy.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".