Predictive accuracy of risk prediction models for recurrence, metastasis and survival for early-stage cutaneous melanoma: a systematic review.

To identify prognostic models for melanoma survival, recurrence and metastasis among American Joint Committee on Cancer stage I and II patients postsurgery; and evaluate model performance, including overall survival (OS) prediction. Systematic review and narrative synthesis. Searched MEDLINE, Embase, CINAHL, Cochrane Library, Science Citation Index and grey literature sources including cancer and guideline websites from 2000 to September 2021. Included studies on risk prediction models for stage I and II melanoma in adults ≥18 years. Outcomes included OS, recurrence, metastases and model performance. No language or country of publication restrictions were applied. Two pairs of reviewers independently screened studies, extracted data and assessed the risk of bias using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist and the Prediction study Risk of Bias Assessment Tool. Heterogeneous predictors prevented statistical synthesis. From 28 967 records, 15 studies reporting 20 models were included; 8 (stage I), 2 (stage II), 7 (stages I-II) and 7 (stages not reported), but were clearly applicable to early stages. Clinicopathological predictors per model ranged from 3-10. The most common were: ulceration, Breslow thickness/depth, sociodemographic status and site. Where reported, discriminatory values were ≥0.7. Calibration measures showed good matches between predicted and observed rates. None of the studies assessed clinical usefulness of the models. Risk of bias was high in eight models, unclear in nine and low in three. Seven models were internally and externally cross-validated, six models were externally validated and eight models were internally validated. All models are effective in their predictive performance, however the low quality of the evidence raises concern as to whether current follow-up recommendations following surgical treatment is adequate. Future models should incorporate biomarkers for improved accuracy. CRD42018086784.

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© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: TPK, RPWK, MA, AB, VK, DCoughlan, CR, CHE, FB and FP have no conflicts of interest to declare. DCraig: December 2018 to present, member of the HD&DR Research-led prioritisation committee. LV was a member of the NIHR Clinical Evaluation and Trial Panel from 2015 to 2018. LV and DCraig are both part funded by the NIHR Applied Research Collaboration for the North East and North Cumbria. PL is Chief Scientific Officer for AMLo Biosciences, holds shares in AMLo and is named as an inventor on patents for biomarkers this area. RE received personal fees from AMLo Biosciences, outside the submitted work, he also was previously Chief Medical Officer for AMLo Biosciences but gave up this position in January 2021. He is named as an inventor on patents owned by AMLo Biosciences for biomarkers this area.