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

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

Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement

Transparent and accurate reporting is essential to evaluate the validity and applicability of risk prediction models. Our aim was to evaluate the reporting quality of studies developing and validating risk prediction models for melanoma according to the TRIPOD (Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis) checklist. We included studies that were identified by a recent systematic review and updated the literature search to ensure that our TRIPOD rating included all relevant studies. Six reviewers assessed compliance with all 37 TRIPOD components for each study using the published “TRIPOD Adherence Assessment Form”. We further examined a potential temporal effect of the reporting quality. Altogether 42 studies were assessed including 35 studies reporting the development of a prediction model and seven studies reporting both development and validation. The median adherence to TRIPOD was 57% (range 29% to 78%). Study components that were least likely to be fully reported were related to model specification, title and abstract. Although the reporting quality has slightly increased over the past 35 years, there is still much room for improvement. Adherence to reporting guidelines such as TRIPOD in the publication of study results must be adopted as a matter of course to achieve a sufficient level of reporting quality necessary to foster the use of the prediction models in applications

Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies

Rising incidences of cutaneous melanoma have fueled the development of statistical models that predict individual melanoma risk. Our aim was to assess the validity of published prediction models for incident cutaneous melanoma using a standardized procedure based on PROBAST (Prediction model Risk Of Bias ASsessment Tool). We included studies that were identified by a recent systematic review and updated the literature search to ensure that our PROBAST rating included all relevant studies. Six reviewers assessed the risk of bias (ROB) for each study using the published “PROBAST Assessment Form” that consists of four domains and an overall ROB rating. We further examined a temporal effect regarding changes in overall and domain-specific ROB rating distributions. Altogether, 42 studies were assessed, of which the vast majority (n = 34; 81%) was rated as having high ROB. Only one study was judged as having low ROB. The main reasons for high ROB ratings were the use of hospital controls in case-control studies and the omission of any validation of prediction models. However, our temporal analysis results showed a significant reduction in the number of studies with high ROB for the domain “analysis”. Nevertheless, the evidence base of high-quality studies that can be used to draw conclusions on the prediction of incident cutaneous melanoma is currently much weaker than the high number of studies on this topic would suggest

Distinct antibody clones detect PD-1 checkpoint expression and block PD-L1 interactions on live murine melanoma cells

Abstract Monoclonal antibodies (abs) targeting the programmed cell death 1 (PD-1) immune checkpoint pathway have revolutionized tumor therapy. Because T-cell-directed PD-1 blockade boosts tumor immunity, anti-PD-1 abs have been developed for examining T-cell-PD-1 functions. More recently, PD-1 expression has also been reported directly on cancer cells of various etiology, including in melanoma. Nevertheless, there is a paucity of studies validating anti-PD-1 ab clone utility in specific assay types for characterizing tumor cell-intrinsic PD-1. Here, we demonstrate reactivity of several anti-murine PD-1 ab clones and recombinant PD-L1 with live B16-F10 melanoma cells and YUMM lines using multiple independent methodologies, positive and negative PD-1-specific controls, including PD-1-overexpressing and PD-1 knockout cells. Flow cytometric analyses with two separate anti-PD-1 ab clones, 29F.1A12 and RMP1-30, revealed PD-1 surface protein expression on live murine melanoma cells, which was corroborated by marked enrichment in PD-1 gene (Pdcd1) expression. Immunoblotting, immunoprecipitation, and mass spectrometric sequencing confirmed PD-1 protein expression by B16-F10 cells. Recombinant PD-L1 also recognized melanoma cell-expressed PD-1, the blockade of which by 29F.1A12 fully abrogated PD-1:PD-L1 binding. Together, our data provides multiple lines of evidence establishing PD-1 expression by live murine melanoma cells and validates ab clones and assay systems for tumor cell-directed PD-1 pathway investigations