Differential treatment outcomes in <i>BRCA1/2</i>‐, <i>CDK12</i>‐, and <i>ATM</i>‐mutated metastatic castration‐resistant prostate cancer
Bibliographic record
Abstract
BACKGROUND: DNA damage repair mutations (DDRm) are common in patients with metastatic castration-resistant prostate cancer (mCRPC). The optimal standard therapy for this population is not well described. METHODS: A multi-institutional, retrospective study of patients with mCRPC and DDRm was conducted. Patient data, including systemic therapies and responses, were collected. The decline in prostate-specific antigen ≥ 50% from baseline (PSA50) and overall survival (OS) from the treatment start were compared by mutation and treatment type. A multivariable Cox proportional hazards model for OS was created that controlled for DDRm, first-line treatment received for mCRPC, and clinical factors. RESULTS: The most common DDRm observed among 149 men with mCRPC were BRCA1/2 (44%), CDK12 (32%), and ATM (15%). The majority received first-line abiraterone (40%) or enzalutamide (30%). The PSA50 rate with first-line abiraterone was lower for CDK12 (52%) than BRCA1/2 (89%; P = .02). After first-line abiraterone or enzalutamide, the median OS was longest with second-line carboplatin-chemotherapy (38 months) in comparison with abiraterone or enzalutamide (33 months), docetaxel (17 months), or cabazitaxel (11 months; P = .02). PSA50 responses to carboplatin-based chemotherapy were higher for BRCA1/2 (79%) than ATM (14%; P = .02) or CDK12 (38%; P = .08). In a multivariable analysis, neither the specific DDRm type nor the first-line treatment was associated with improved OS. CONCLUSIONS: Responses to standard therapies were generally superior in patients with BRCA1/2 mutations and inferior in patients with ATM or CDK12 mutations. The DDRm type did not independently predict OS. After progression on first-line abiraterone or enzalutamide, carboplatin-based chemotherapy was associated with the longest OS. These findings may inform treatment discussions and clinical trial design and require prospective validation.
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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 | 0.002 |
| 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".