Estimating high-risk castration resistant prostate cancer (CRPC) using electronic health records.
Bibliographic record
Abstract
INTRODUCTION: Canadian guidelines define castration-resistant prostate cancer (CRPC) at high risk of developing metastases using PSA doubling time (PSADT) < 8 months, whereby men may be offered more frequent bone scans/imaging. We evaluated PSA data from nonmetastatic (M0) prostate cancer patients treated at urology and oncology clinics across the United States (US) to describe the proportion and characteristics of patients who met CRPC and high-risk criteria. MATERIALS AND METHODS: We identified M0 prostate cancer patients aged = 18 years receiving androgen deprivation therapy (ADT) in 2011 from electronic health records (EHR), covering 129 urology and 64 oncology practices across the US. We estimated the proportion of prostate cancer patients with evidence of CRPC (consecutive rising PSAs) and subsets that may be at high risk (using several PSA and PSADT cut-points). RESULTS: Among 3121 M0 prostate cancer patients actively treated with ADT, 1188 (38%) had evidence of CRPC. Of these, 712 (60%) qualified as high risk in 2011 based on PSADT < 8 months (equivalent to = 8 months in these data). Men = 65 years were more likely to have evidence of CRPC than younger men, although younger men were more likely to have evidence of high-risk disease. CRPC was more common among men receiving ADT in the oncology setting than the urology setting (48% versus 37%). CONCLUSIONS: In this large EHR study with patient-level PSA data, 38% of men with M0 prostate cancer treated with ADT had CRPC. Approximately 60% of M0 CRPC patients may experience a PSADT of < 8 months. These findings require validation in a Canadian patient population.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".