Predictors of germline DNA damage repair gene mutations (gDDRm) in patients (pts) with metastatic castration-resistant prostate cancer (CRPC).
Bibliographic record
Abstract
159 Background: gDDRm are present in 6-12% of pts with CRPC and have implications for prognosis, treatment outcomes and familial screening. This study's aim was to identify clinical/pathologic characteristics associated with a higher risk of a pt harboring a gDDRm. Methods: 631 consecutive pts with metastatic prostate cancer were screened for germline mutations in 22 DNA repair genes (including ATM, BRCA1/2, MSH2/6, FANC/ERCC members). Clinical/pathologic characteristics (age at diagnosis, visceral metastases (mets) at time of CRPC, Gleason score, intraductal/cribriform histology (I/C) at diagnosis, family history (FHx) of prostate, breast, ovarian, or pancreatic cancer, time from androgen deprivation therapy initiation to CRPC) were compared between gDDRm+ and gDDRm- cases. A multivariate logistic model of gDDRm status was constructed using purposeful selection of covariates where clinical judgement was employed in addition to statistical significance. A weighted scoring system was created by multiplying each risk factor (RF) by its estimated β coefficient. A pt’s total score was calculated by the sum of each weighted RF. Results: gDDRm+ were identified in 38/631 pts (6.0%, BRCA2 = 28, ATM = 4, BRCA1 = 2, PALB2 = 2, MSH2 = 1, ERCC3 = 1). 29 gDDRm+ and 128 gDDRm- cases with complete clinical/pathologic information were included in the model. Multivariate modeling revealed that visceral mets, FHx and I/C were statistically significantly associated with gDDRm+; age ≤ 65 was included in the model because it was considered clinically relevant (Table). Based on the model results, the weights of each RF are: visceral mets (2), FHx (1), I/C (2), age ≤ 65 (1). Using a total score cut-off ≥ 1, the model achieves a sensitivity, specificity, positive predictive value, and negative predictive value of 97%, 31%, 24%, and 98%, respectively. Conclusions: In this cohort, visceral mets, FHx and I/C were independently associated with a higher risk of harboring a gDDRm. The predictive model may aid in selecting pts for gDDRm screening. Model validation is required. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".