Factors Affecting Genomic Testing in Prostate Cancer: Results From the Decision-Making, Experience, and Confidence In Determining Genomic Evaluation (DECIDE) Survey
Bibliographic record
Abstract
PURPOSE: Genomic testing for prostate cancer (PCa) clinical management and hereditary cancer assessment has grown in clinical impact; however, challenges remain regarding optimal implementation and end-user confidence. The Decision-making, Experience, and Confidence In Determining Genomic Evaluation (DECIDE) survey was designed to collect information regarding utility and understanding of genomic testing from PCa health care providers, researchers, and stakeholders. METHODS: The DECIDE survey was administered online from October 2022 to January 2023 with 18 multiple-response questions. Survey domains included self-confidence with ordering and interpreting germline and somatic genomic tests, process of testing and use of results, decision-making factors, and barriers to testing. Data were summarized by evaluating counts and percentages of responses, and the results were presented by descriptive statistics. RESULTS: One hundred twenty-two participants completed the survey. The majority were medical oncologists (70%) and at academic medical centers (89%). Self-confidence was high in knowing indications for genomic testing (82% respondents) but lower in interpretation of results, especially from circulating tumor DNA (52%). Confidence varied in interpreting pathogenic variants (65% high confidence), variants of unknown significance (47%), and incidental findings from genomic tests (35%). Common barriers to testing were difficulty obtaining tissue (71%) and cost (35%). Testing utility was sometimes limited by inability to obtain the recommended treatment (33%). Most of the respondents (55%) agreed that lack of education and training of health care professionals regarding genomic testing is impeding clinical translation. CONCLUSION: The DECIDE survey provided critical insights into challenges with genomic testing, from provider confidence in interpretating results to testing and practice barriers. The results inform next steps to further educate PCa providers and to collectively improve testing and result reporting for enhanced implementation of PCa genomic testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".