ONCOmmunity

Optimizing treatment approaches for patients with cutaneous melanoma by integrating clinical and pathologic features with the 31-gene expression profile test.

By: Abel Jarell, Brian R Gastman, Larry D Dillon, Eddy C Hsueh, Sebastian Podlipnik, Kyle R Covington, Robert W Cook, Christine N Bailey, Ann P Quick, Brian J Martin, Sarah J Kurley, Matthew Goldberg, Susana Puig

Northeast Dermatology Associates, PC, Portsmouth, NH.
2022-01-24; doi: 10.1016/j.jaad.2022.06.1202

Abstract

Background

Many patients with low-stage cutaneous melanoma will experience tumor recurrence, metastasis, or death, and many higher-staged patients will not.

Objective

Develop an algorithm by integrating the 31-gene expression profile test with clinicopathologic data for an optimized, personalized risk of recurrence (i31-ROR) or death and use i31-ROR in conjunction with a previously validated algorithm for precise sentinel lymph node positivity risk estimates (i31-SLNB) for optimized treatment plan decisions.

Methods

Cox regression models for ROR were developed (n=1581) and independently validated (n=523) on a cohort with stage I-III melanoma. Using NCCN cut-points, i31-ROR performance was evaluated using the midpoint survival rates between patients with stage IIA and IIB disease as a risk threshold.

Results

Patients with a low-risk i31-ROR result had significantly higher 5-year recurrence-free (91% vs. 45%, P<.001), distant metastasis-free (95% vs. 53%, P<.001), and melanoma-specific survival (98% vs. 73%, P<.001) than patients with a high-risk i31-ROR result. A combined i31-SLNB/ROR analysis identified 44% of patients who could forego SLNB while maintaining high survival rates (>98%) or were re-stratified as being at a higher or lower risk of recurrence or death.

Limitations

Multi-center, retrospective study.

Conclusion

Integrating clinicopathologic features with the 31-GEP optimizes patient risk-stratification compared to clinicopathologic features alone.