Patient perspectives on testing for clonal hematopoiesis of indeterminate potential
Bibliographic record
Abstract
Clonal hematopoiesis of indeterminate potential (CHIP), an emerging biomarker for personalized risk-directed interventions, is increased in cancer survivors. However, little is known about patient preferences for CHIP testing. We surveyed participants in a prospective cohort study of young women with breast cancer (BC). The emailed survey included an introduction to CHIP and a vignette eliciting participants' preferences for CHIP testing, considering sequentially: population-based 10-year risk of BC recurrence, hematologic malignancy, and heart disease; increased CHIP-associated risks; current CHIP management; dedicated CHIP clinic; and hypothetical CHIP treatment. Preference changes were evaluated using the McNemar test. The survey response rate was 82.2% (528/642). Median age at time of survey was 46 years and median time from diagnosis was 108 months. Only 5.9% had prior knowledge of CHIP. After vignette presentation, most survivors (87.1%) recommended CHIP testing for the vignette patient. Presented next with CHIP-independent, population-based risks, 11.1% shifted their preference from testing to not testing. After receiving information about CHIP-associated risks, an additional 10.1% shifted their preference to testing. Preference for testing increased if vignette patient was offered a CHIP clinic or hypothetical CHIP treatment, with 7.2% and 14.1% switching preferences toward testing, respectively. Finally, 75.8% of participants desired CHIP testing for themselves. Among participants, 28.2% reported that learning about CHIP caused at least moderate anxiety. Most young survivors favored CHIP testing, with preferences influenced by risk presentation and potential management strategies. Our findings highlight the importance of risk communication and psychosocial support when considering biomarkers for future risk in cancer survivors. This trial has been registered at www.clinicaltrials.gov as #NCT01468246.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".