Positive predictive value metrics for multicancer detection tests
Cette étude définit des valeurs prédictives positives pour les tests de détection multicancers puis examine leurs propriétés qualitatives et quantitatives
Introduction : Multicancer detection (MCD) tests generally target selected cancer sites, but may also have some detection ability at other sites; they additionally typically give a predicted cancer signal origin (CSO) for positive tests. Positive predictive value (PPV) is a widely used metric assessing performance of single-cancer screening tests. The aim here was to define PPVs in a number of ways in the MCD context, create a prototypical MCD test, and show the qualitative and quantitative properties of these PPV metrics.
Methods : PPVs were defined based on which subjects were included in the numerator and denominator. PPVALL, PPVT, and PPVCSO each have as denominator all subjects with positive screens, and as numerators all subjects with any cancer diagnosis, diagnosis at any targeted site, and diagnosis at the predicted CSO site, respectively. Predicted CSO site-specific PPVs were defined similarly, except with denominator subjects with a given cancer site as predicted CSO. MCD performance data taken from a case-control study and population incidence rates were used to determine sensitivity, specificity, CSO accuracy, and cancer prevalence values of a prototypical MCD test for which PPV were calculated. A range of sensitivity rates for nontargeted cancer sites were assessed.
Results : PPVALL increased and PPVT decreased as sensitivity for nontargeted sites increased. Predicted site-specific PPVs depended primarily on cancer site CSO accuracy, not on site population prevalence.
Conclusions : PPVs can be defined in multiple ways for MCD tests. Their usefulness depends on the clinical context. Companies offering MCD tests can consider discussing the clinical usefulness of various PPVs with clinicians to decide what metrics to include on test reports.
Journal of Medical Screening , résumé, 2026