Fig 1.
Schematic of multi-stage screening process starting with machine-learning derived algorithm.
Table 1.
Percentage of cases and controls reporting symptoms or statuses within the 24-month period prior to diagnosis.
Fig 2.
Model parameters obtained in each time window (0–24,1–24,…,20–24 months) prior to diagnosis.
a) AUC (%) b) Sensitivity (%) c) Specificity (%).
Fig 3.
AUC, sensitivity and specificity of the models with % of the population recommended for biomarker (Stage 2) testing.
Table 2.
Parameters of the optimal logistic regression models envisioned in the context of the hypothetical multi-stage screening model*: England 2017.