Abstract
Introduction: Eighty-eight percent of patients who receive a sentinel lymph node biopsy (SLNB) receive a negative result. Current guidelines suggest avoiding SLNB if the risk of positivity is <5%. A low threshold for performing SLNB indicates worry about missing positive nodes but results in many unnecessary biopsies. The integrated 31-gene expression profile (i31-GEP) test combines the 31-GEP with Breslow thickness, age, ulceration, and mitotic rate using a validated neural network algorithm to identify patients with <5% risk by reporting a precise, individualized likelihood score. Using logistic regression, a separate GEP (8 genes plus Breslow thickness and age; CP-GEP) also aims to identify patients who can forego SLNB by binning patients into low-and high-risk categories. This study compared the i31-GEP for SLNB with the CP-GEP to identify patients who can safely forego SLNB. Methods: This study evaluated the genes, gene pathways, and relative contribution of the two gene signatures relative to clinical and pathologic factors and further analyzed patients with T1b-T2 tumors from previously published studies in U.S. cohorts for the i31-GEP (n=763) and CP-GEP (n=153). A ratio of true-to-false-negative i31-GEP for SLNB and CP-GEP test results was compared to the guideline-established ratio of 19 negatives to one missed positive (19:1) if foregoing SLNB using a 5% risk threshold. Results: The i31-GEP had a 30:1 true-to-false-negative ratio, compared to 15:1 using CP-GEP. In T1b tumors, the i31-GEP ratio increased to 35:1 compared to 14:1 using CP-GEP. Limitations: Retrospective design, which could lead to bias. Patients included in both analyses were primarily from institutional surgical centers, and referral bias may not make the result generalizable. Conclusion: Only the i31-GEP provided benefit over guideline-established care for identifying patients with low risk of SLN positivity.
| Original language | English |
|---|---|
| Pages (from-to) | 464-471 |
| Number of pages | 8 |
| Journal | SKIN: Journal of Cutaneous Medicine |
| Volume | 6 |
| Issue number | 6 |
| DOIs | |
| State | Published - 1 Nov 2022 |
| Externally published | Yes |
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