Adherence to Guidelines in Requesting Oncotype DX in a Publicly Funded Health Care System
Bibliographic record
Abstract
Background: Oncotype DX [ODX (Genomic Health, Redwood City, CA, U.S.A.)] is an approved prognostic tool for women with node-negative, hormone receptor–positive, her2-negative breast cancer. Because of cost, optimal use of this test is crucial, especially in a publicly funded health care system. We evaluated adherence with our provincial guidelines for ODX requests, the management of patients with an intermediate recurrence score (RS), and the cost impact of ODX. Methods: This retrospective study included 201 consecutive patients with an ODX request from two university institutions in Quebec between May 2012 and December 2014. Concordance with provincial guidelines was estimated, with its 95% confidence interval (CI). For patients with an intermediate RS, factors influencing the final treatment decision were assessed. The cost impact of ODX was derived from the proportion of patients for whom chemotherapy was not recommended. Results: In 93.0% of patients (95% CI: 89.5% to 96.6%), ODX was ordered according to guidelines. The concordance was similar in both institutions (92.7%; 95% CI: 88.1% to 97.3%; and 93.6%; 95% CI: 88.2% to 99.0%). In 112 (55.7%), 78 (38.8%), and 9 (4.5%) patients, the RS suggested low, intermediate, and high risk respectively. In the intermediate-risk group, most patients (n = 58, 74.4%) did not receive chemotherapy, mainly because of patient preference and the absence of a clear proven benefit. Savings of CA$100,000 for the study period (2.5 years) were estimated to be associated with ODX use. Conclusions: In our experience, the use of ODX was concordant with published recommendations and had a positive cost impact.
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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 | 0.012 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".