Work

Supplementary Methods from Estimating the Opportunity for Early Detection of Ovarian Cancer Using Individual-Patient Data from a Large Randomized Controlled Trial

Year: 2025

Type: supplementary-materials

Abstract: Supplementary Methods describe the model selection process using approximate leave-one-out cross-validation, posterior predictive checks comparing predicted and observed cancer incidence, and the estimation of empirical screening sensitivities from the fitted natural history model.

DOI: 10.1158/1055-9965.30517277

Authors: Marc D. Ryser, Shannon T. Holloway, Raphaël Morsomme, Andy Ryan, Sophia Apostolidou, Aleksandra Gentry-Maharaj, Kemal Caglar Gogebakan, Jane Lange, Jason Xu, Usha Menon, Ruth Etzioni

Language: English

Topic: Ovarian cancer diagnosis and treatment

Subfield: Reproductive Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

OpenAlex ID: W4415786214

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