Risk Prediction Models for Melanoma: A Systematic Review on the Heterogeneity in Model Development and Validation

Isabelle Kaiser, Annette B. Pfahlberg, Wolfgang Uter, Markus V. Heppt, Marit B. Veierød and Olaf Gefeller
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Isabelle Kaiser: Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
Annette B. Pfahlberg: Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
Wolfgang Uter: Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
Markus V. Heppt: Department of Dermatology, University Hospital Erlangen, 91054 Erlangen, Germany
Marit B. Veierød: Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, 0317 Oslo, Norway
Olaf Gefeller: Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany

IJERPH, 2020, vol. 17, issue 21, 1-24

Abstract: The rising incidence of cutaneous melanoma over the past few decades has prompted substantial efforts to develop risk prediction models identifying people at high risk of developing melanoma to facilitate targeted screening programs. We review these models, regarding study characteristics, differences in risk factor selection and assessment, evaluation, and validation methods. Our systematic literature search revealed 40 studies comprising 46 different risk prediction models eligible for the review. Altogether, 35 different risk factors were part of the models with nevi being the most common one ( n = 35, 78%); little consistency in other risk factors was observed. Results of an internal validation were reported for less than half of the studies ( n = 18, 45%), and only 6 performed external validation. In terms of model performance, 29 studies assessed the discriminative ability of their models; other performance measures, e.g., regarding calibration or clinical usefulness, were rarely reported. Due to the substantial heterogeneity in risk factor selection and assessment as well as methodologic aspects of model development, direct comparisons between models are hardly possible. Uniform methodologic standards for the development and validation of risk prediction models for melanoma and reporting standards for the accompanying publications are necessary and need to be obligatory for that reason.

Keywords: melanoma; risk prediction; statistical models; validation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:21:p:7919-:d:436278

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