Impact of Reflex <i>EGFR</i>/<i>ALK</i> Testing on Time to Treatment of Patients With Advanced Nonsquamous Non–Small-Cell Lung Cancer
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Bibliographic record
Abstract
PURPOSE: Optimal first-line systemic therapy for patients with advanced nonsquamous (nonsq) non-small-cell lung cancer (NSCLC) requires confirmation of EGFR/ ALK status, which can delay treatment. We evaluated the impact of reflex testing, defined as pathologists initiating EGFR/ ALK testing at the time of diagnosis of nonsq NSCLC, on time to treatment (TTT). METHODS: We conducted a retrospective review of patients with nonsq NSCLC with medical oncology consultation at Sunnybrook Odette Cancer Centre between March 18, 2010 and April 30, 2014. Data were compared during routine and reflex testing. TTT was defined as the interval between the first medical oncology visit with advanced NSCLC and the initiation of systemic therapy. RESULTS: A total of 306 patients were included (n = 232 for routine testing, n = 74 for reflex testing). There was a trend to improvement in median TTT with reflex testing (36 days [interquartile range {IQR}, 16 to 71 days v 26 days [IQR, 8 to 41 days], P = .071). Omitting patients with intentional delays in systemic therapy for low-volume disease, poor performance status, comorbidity management, and/or radiation therapy, median TTT improved (34 days [IQR, 15 to 67 days] v 22 days [IQR, 8 to 42 days], P = .049). Time to optimal first-line systemic therapy according to published guidelines improved (median, 36 days [IQR, 16 to 91 days] v 24 days [IQR, 8 to 43 days], P = .036). There was no impact on receipt of any first-line systemic therapy (55% v 59%, P = .66). The quality of biomarker testing improved, with fewer unsuccessful tests ( EGFR, 14% v 4%, P = .039; and ALK, 17% v 3%, P = .037). CONCLUSION: Reflex testing of EGFR/ ALK improved the time to optimal systemic therapy and the quality of biomarker testing for patients with advanced nonsq NSCLC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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