A Prospective, Multi-Center Clinical Utility Study Demonstrates That the 40-Gene Expression Profile (40-GEP) Test Impacts Clinical Management for Medicare-Eligible Patients with High-Risk Cutaneous Squamous Cell Carcinoma (cSCC)
Bibliographic record
Abstract
The incidence and mortality rates of cutaneous squamous cell carcinoma (cSCC) in the Medicare population are rapidly increasing. The current national guidelines are broad and the available staging systems for stratification are inadequate to accurately guide patient management. A prognostic 40-gene expression profile (40-GEP) test has demonstrated both analytical and clinical validity for assessment of metastatic risk of high-risk cSCC patients independent of traditional clinicopathologic factors. Real-world data have shown that clinicians can identify appropriate patients for 40-GEP testing and use this personalized, molecular risk stratification tool to guide risk-aligned clinical planning and patient management. The data herein focuses on 59 Medicare-eligible patients (≥65 years of age) enrolled within a multicenter, prospective Clinical Utility and Health Outcomes Study (UTILISE) conducted to demonstrate patterns of 40-GEP test utilization, distribution of results across clinicopathologic variables, and impact on clinician recommendations for clinical management of high-risk cSCC patients. Of patients under study, more than 80% of clinicians reported that the 40-GEP had a positive impact toward managing their high-risk SCC patient, 42% stated, a 40-GEP test result was the single most influential factor in determining management plans and 24% made changes to their treatment plan in after receiving the 40-GEP result‑ a clinical actionability rate comparable to those of currently covered molecular tests for cancer patients. This analysis demonstrates the positive impact the 40-GEP is having on clinicians’ assessment of risk for their high-risk cSCC patients, which, in line with guidelines, is driving risk-aligned changes in treatment plans.
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How this classification was reachedexpand
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".