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

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 (+1 others)
2022 Journal of American Academy of Dermatology  
Many patients with low-stage cutaneous melanoma will experience tumor recurrence, metastasis, or death, and many higher-staged patients will not. 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. Cox
more » ... ression 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. 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. Multi-center, retrospective study. Integrating clinicopathologic features with the 31-GEP optimizes patient risk-stratification compared to clinicopathologic features alone.
doi:10.1016/j.jaad.2022.06.1202 pmid:35810840 fatcat:pvk5dqsycndmrb2bg5aquoxjdq