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

TAKE-HOME MESSAGE

• An algorithm using the 31-gene expression profile (31-GEP) test to identify the risk of sentinel lymph node (SLN) positivity (i31-SLNB) in patients with melanoma was previously published. In this study, the 31-GEP test was used to predict the risk of recurrence (i31-ROR), distant metastasis, and melanoma-specific death. The 31-GEP score was a significant predictor of recurrence-free survival (RFS), distant metastasis-free survival (DMFS), and melanoma-specific survival (MSS). Data from patients with i31-SLNB risk of positive node >5% were subsequently analyzed using the i31-ROR model. Patients with a negative SLN but high-risk i31-ROR had lower 5-year RFS, DMFS, and MSS than those with a negative SLN and a low-risk i31-ROR.
• The 31-GEP test may aid in identifying patients with high-risk melanoma previously missed by current prognostication criteria and holds the potential to improve patient outcomes.

–  Katherine M. Stiff, MD

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Shannon C. Trotter DO

Staging for cutaneous melanoma (CM) directs next steps in treatment and management. However, staging can miss early CM patients that go on to recur, metastasize, or die from their disease or late stage patients that do not. The integrated or i31-gene expression profile (GEP) test can help identify the outliers that staging does not capture. With the addition of clinicopathologic features, the i31-GEP results are uniquely personalized to the patient. 

The i31-GEP test helps answer two clinically relevant questions. First, what is the likelihood of a positive sentinel lymph node biopsy (i31-SLNB)? Second, what is the risk of recurrence (i31-ROR)? The i31-GEP test provides ROR, distant metastasis free survival melanoma specific survival (MSS), and risk prediction estimates. Of note, AJCC only provides MSS. The i31-GEP test empowers the clinician to have an individual risk assessment for the patient.

It is likely that the greatest impact on clinical decision making from the i31-GEP test may center on SLNB conversations. For example, if a CM patient does not meet current NCCN criteria for a SLNB but has an i31-SLNB result of 8.3%, the dermatologist may refer the patient for SLNB. On the other hand, if a CM patient meets NCCN criteria for a SLNB but has an i31-SLNB of 2.2%, the dermatologist may still refer to SLNB based on current guidelines, but a decision to forego the procedure with more confidence may occur.

Overall, the i31-GEP is a complementary tool for CM that can help reconcile AJCC gaps in staging and SLNB patient selection. However, more research is needed on the optimal way to integrate the i31-GEP test into current guidelines and treatment approaches to the patient.  

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.

Journal of the American Academy of Dermatology

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

J Am Acad Dermatol 2022 Jul 07;[EPub Ahead of Print], A Jarell, BR Gastman, LD Dillon, EC Hsueh, S Podlipnik, KR Covington, RW Cook, CN Bailey, AP Quick, BJ Martin, SJ Kurley, M Goldberg, S Puig 

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Benjamin Hidalgo-Matlock
Skin Care Physicians of Costa Rica

Clinica Victoria en San Pedro: 4000-1054
Momentum Escazu: 2101-9574

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