Nomograms versus artificial intelligence platforms: which one can better predict sentinel node positivity in melanoma
Eduardo Bertolli1, Sara B Micheletti2, Veridiana P de Camargo2
1Surgical Oncology.
Melanoma Research
|June 4, 2025
Summary
Artificial intelligence (AI) platforms show promise in predicting sentinel lymph node biopsy (SNB) positivity for melanoma patients, outperforming traditional nomograms in a recent study. Further AI development could enhance melanoma treatment decisions.
Area of Science:
- Oncology
- Medical Informatics
- Predictive Analytics
Background:
- Nomograms are standard tools in oncology for clinical decision-making, including sentinel lymph node biopsy (SNB) for melanoma.
- Artificial intelligence (AI) is emerging as a powerful tool for medical predictions.
Purpose of the Study:
- To compare the predictive accuracy of nomograms and AI platforms for SNB positivity in melanoma patients.
- To evaluate the real-world performance of established nomograms and AI tools.
Main Methods:
- Retrospective analysis of 62 melanoma patients who underwent SNB (2020-2024).
- Utilized three open-access nomograms and three public AI platforms to predict SNB positivity.
- Assessed predictive accuracy using clinical and pathological data, including logistic regression and ROC curves.
Main Results:
- No concordance was found among nomograms or AI platforms (P < 0.001).
- The Memorial Sloan Kettering Cancer Center (MSKCC) nomogram and ChatGPT showed statistical significance for SNB positivity (P=0.04 and P=0.02, respectively).
- ChatGPT predictions yielded an Area Under the Curve (AUC) of 0.702, improved to 0.715 when integrated with MSKCC predictions.
Conclusions:
- AI platforms, particularly ChatGPT, demonstrated superior predictive performance for SNB positivity compared to nomograms in this cohort.
- Future enhancements in AI platforms may improve nomogram validation and lead to more accurate predictive models for melanoma management.
