Oncologists' Selection of Genetic and Molecular Testing in the Evolving Landscape of Stage II Colorectal Cancer.
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Bibliographic record
Abstract
PurposeLittle is known about the roles of genetic and molecular testing and Lynch syndrome screening in the formulation of predictive and prognostic assessments for patients with stage II colorectal cancer (CRC).MethodsFrom 2012 to 2013, we surveyed medical oncologists in the Cancer Care Outcomes Research and Surveillance Consortium and evaluated oncologists' selection of microsatellite instability (MSI) and/or immunohistochemistry (IHC) for mismatch repair (MMR) proteins, germline testing for MMR genes, BRAF and KRAS mutation analysis, and Oncotype DX in stage II CRC. Physicians were randomly assigned to receive one of three vignettes that varied by strength of CRC family history. We used multivariable logistic regression to identify physician and practice characteristics associated with test selection.ResultsAmong 327 oncologists, MSI and/or IHC for MMR proteins were most frequently selected (n = 205; 64%), with 82% versus 53% choosing MSI/IHC testing in patients with strong versus no CRC family history, respectively (adjusted odds ratio [OR], 3.87; 95% CI, 2.07 to 7.22). KRAS and Oncotype DX testing were chosen by 24% and 38% of oncologists, respectively. Graduates of non-US and Canadian medical schools and physicians compensated by fee-for-service or on the basis of productivity were more likely to choose KRAS testing versus those receiving salaries not on the basis of productivity (OR, 2.16; 95% CI, 1.17 to 3.99; and OR, 1.94; 95% CI, 1.02 to 3.66, respectively). Fee-for-service or productivity-based salaries were also associated with increased odds of Oncotype DX testing (OR, 2.04; 95% CI, 1.17 to 3.55).ConclusionAmong surveyed oncologists, we found undertesting and overtesting related to genetic and molecular testing and Lynch syndrome screening for patients with stage II CRC,highlighting the need for improved implementation, targeted education, and evaluation of organizational and financial arrangements to promote the appropriate use of such tests.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it