The Clinical Utility of a 7-Gene Biosignature on Radiation Therapy Decision Making in Patients with Ductal Carcinoma In Situ Following Breast-Conserving Surgery: An Updated Analysis of the DCISionRT® PREDICT Study
Bibliographic record
Abstract
BACKGROUND: Breast-conserving surgery (BCS) followed by adjuvant radiotherapy (RT) is a standard treatment for ductal carcinoma in situ (DCIS). A low-risk patient subset that does not benefit from RT has not yet been clearly identified. The DCISionRT test provides a clinically validated decision score (DS), which is prognostic of 10-year in-breast recurrence rates (invasive and non-invasive) and is also predictive of RT benefit. This analysis presents final outcomes from the PREDICT prospective registry trial aiming to determine how often the DCISionRT test changes radiation treatment recommendations. METHODS: Overall, 2496 patients were enrolled from February 2018 to January 2022 at 63 academic and community practice sites and received DCISionRT as part of their care plan. Treating physicians reported their treatment recommendations pre- and post-test as well as the patient's preference. The primary endpoint was to identify the percentage of patients where testing led to a change in RT recommendation. The impact of the test on RT treatment recommendation was physician specialty, treatment settings, individual clinical/pathological features and RTOG 9804 like criteria. Multivariate logisitc regression analysis was used to estimate the odds ratio (ORs) for factors associated with the post-test RT recommendations. RESULTS: RT recommendation changed 38% of women, resulting in a 20% decrease in the overall recommendation of RT (p < 0.001). Of those women initially recommended no RT (n = 583), 31% were recommended RT post-test. The recommendation for RT post-test increased with increasing DS, from 29% to 66% to 91% for DS <2, DS 2-4, and DS >4, respectively. On multivariable analysis, DS had the strongest influence on final RT recommendation (odds ratio 22.2, 95% confidence interval 16.3-30.7), which was eightfold greater than clinicopathologic features. Furthermore, there was an overall change in the recommendation to receive RT in 42% of those patients meeting RTOG 9804-like low-risk criteria. CONCLUSIONS: The test results provided information that changes treatment recommendations both for and against RT use in large population of women with DCIS treated in a variety of clinical settings. Overall, clinicians changed their recommendations to include or omit RT for 38% of women based on the test results. Based on published clinical validations and the results from current study, DCISionRT may aid in preventing the over- and undertreatment of clinicopathological 'low-risk' and 'high-risk' DCIS patients. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03448926 ( https://clinicaltrials.gov/study/NCT03448926 ).
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".