ArticleAnnals of surgical oncology2024
Using Nomograms Wisely: Predicting Sentinel Node Positivity in Melanoma.
Article in Annals of surgical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Development and validation of a nomogram prediction model for thyroid dysfunction in patients with type 2 diabetes mellitus.Scientific reports · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFour externally validated sentinel node biopsy (SNB) prediction nomograms exist for malignant melanoma that each incorporate different clinical and histopathologic variables, which can result in substantially different risk estimations for the same patient. We demonstrate this variability by using hypothetical melanoma cases.
methodsWe compared the MSKCC and MIA calculators. Using a random number generator, 300 hypothetical thin melanoma "patients" were created with varying age, tumor thickness, Clark level, location on the body, ulceration, melanoma subtype, mitosis, and lymphovascular invasion (LVI). The chi-square test was used to detect statistically significant differences in risk estimations between nomograms. Multivariate linear regression was used to determine the most relevant contributing pathologic features in cases where the predictions diverged by > 10%.
resultsOf 300 randomly generated cases, 164 were deleted as their clinical scenarios were unlikely. The MSKCC nomogram generally calculated a lower risk than the MIA (p < 0.001). The highest risk score attained for any "patient" using MSKCC calculator was 15% achieved in one of 136 patients (0.7%), whereas using the MIA nomogram, 58 of 136 patients (43%, p < 0.001) had predicted risk >15%. Regression analysis on patients with >10% difference between nomograms revealed LVI (26, p < 0.001), mitosis (14, p < 0.001), and melanoma subtype (8, p < 0.001) were the factors with high coefficients within MIA that were not present in MSKCC.
conclusionsNomograms are useful tools when predicting SNB risk but provide risk outputs that are quite sensitive to included predictors.
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