Clinical Utility of CLIA-Grade AR-V7 Testing in Patients With Metastatic Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
Purpose A splice variant of the androgen receptor, AR-V7, confers resistance to AR-targeted therapies (ATTs) but not taxane chemotherapies in patients with metastatic castration-resistant prostate cancer. Since August 2015, a clinical-grade assay to detect AR-V7 messenger RNA expression in circulating tumors cells (CTCs) has been available to providers through a Clinical Laboratory Improvement Amendments–certified laboratory at Johns Hopkins University. Methods We contacted ordering providers of the first 150 consecutive tests by using a questionnaire-based survey to determine how the results of AR-V7 testing were used to influence clinical practice. Results In all, 142 (95%) of 150 questionnaires were completed by 38 providers from 29 sites across the United States and Canada. AR-V7 test results were reported either as CTC– (28%), CTC+/AR-V7– (30%), or CTC+/AR-V7+ (42%). Prevalence of AR-V7 detection increased with prior exposure to ATTs (abiraterone and enzalutamide naïve, 22%; after abiraterone or enzalutamide, 35%; after abiraterone and enzalutamide, 43%). Overall, management was affected by AR-V7 testing in 53% of the patients and even more often with CTC+/AR-V7+ results. AR-V7+ patients were commonly switched from ATT to taxane chemotherapy (43%) or were offered a clinical trial (43%); management remained unchanged in only 14% of these patients. Overall, patients who had a change in management on the basis of AR-V7 testing were significantly more likely to achieve a physician-reported 50% decline in prostate-specific antigen response on next-line therapy than those who did not change treatment (54% v 31%; P = .015). Conclusion Providers used AR-V7 testing to influence clinical decision making more often than not. Physicians reported that men with AR-V7+ results had the most treatment changes, and such men were preferentially managed with taxane therapy or offered a clinical trial, which may have improved outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".