Evidence map›Paper›PMID 42337205›Full record

ArticleDermatology and therapy2026

Comparing the i31-SLNB and the MIA Nomogram for Sentinel Lymph Node Biopsy Positivity Prediction in Cutaneous Melanoma: A Prospective Cohort Analysis.

Rohit Sharma, Rajan P Kulkarni, Richard Essner, Andrew Ward, Andrew H Lewis, Shireen Guide, J Michael Guenther

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Article in Dermatology and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Rohit SharmaMarshfield Clinic Health System, Marshfield, WI, USA.
Rajan P KulkarniOregon Health & Science University, Portland, OR, USA.
Richard EssnerSaint Johns Cancer Institute, Santa Monica, CA, USA.
Andrew WardUniversity of Tennessee Medical Center, Knoxville, TN, USA.
Andrew H LewisCastle Biosciences, Inc., Friendswood, TX, USA.
Shireen GuideMission Dermatology Center, Santa Margarita, CA, USA.
J Michael GuentherSt. Elizabeth Physicians, 20 Medical Village Drive, Edgewood, KY, 41017, USA. Joseph.Guenther@stelizabeth.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSentinel lymph node biopsy (SLNB) for cutaneous melanoma (CM) provides essential prognostic information and is a component of the American Joint Committee on Cancer (AJCC) staging; however, up to 88% of SLNBs performed are negative. This means most patients who undergo the procedure do not benefit but are exposed to additional costs and surgery-associated morbidities. Improved tools are needed to identify patients at low risk of sentinel lymph node (SLN) positivity for whom the procedure is unnecessary and can be avoided. Here, we compared the sentinel lymph node positivity predictive accuracy of the integrated 31-gene expression profile (GEP) for sentinel lymph node biopsy (i31-SLNB) and the Melanoma Institute Australia (MIA) nomogram in patients with CM enrolled in the prospective DECIDE study who underwent SLNB.

methodsData from patients with T1-T4 tumors and i31-SLNB test results from a prospective, multicenter study were evaluated. Area under the curve (AUC) was used to compare the discriminative performance of the i31-SLNB and MIA nomogram in predicting SLN positivity. Observed SLN positivity rates in patients with conflicting risk predictions were examined.

resultsThe analysis included 912 patients, of whom 430 were SLN-assessed. The i31-SLNB predicted < 5% risk of SLN positivity more often than the MIA nomogram and observed positivity was below 5% for the i31-SLNB (2.6%, negative predictive value [NPV] = 97.4%, 95% CI 94.2-100.0%) but not the MIA nomogram (5.8%, NPV = 94.2%, 95% CI 88.1-98.7%). The AUC for the i31-SLNB was 0.74, significantly higher than that of the MIA nomogram (0.61; p = 0.001), demonstrating better discriminative performance. At 5% and 10% risk thresholds, when the tools conflicted in their risk predictions, the i31-SLNB was accurate, with observed SLN positivity rates of 1.9% and 2.8% below each threshold and 11.5% and 25.8% above each threshold.

conclusionsThe i31-SLNB more accurately stratifies patients under consideration for SLNB into groups based on risk of SLN positivity than the clinicopathologic-only MIA nomogram.

Indexed as

31-gene expression profileCutaneous melanomaSentinel lymph node biopsy

Identifiers

PMID42337205
PMCPMC13493683

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.