Improving identification of symptomatic cancer at primary care clinics: A predictive modeling analysis in Botswana.

ABSTRACT: In resource-limited settings, augmenting primary care provider (PCP)-based referrals with data-derived algorithms could direct scarce resources towards those patients most likely to have a cancer diagnosis and benefit from early treatment. Using data from Botswana, we compared accuracy of predictions of probable cancer using different approaches for identifying symptomatic cancer at primary clinics. We followed cancer suspects until they entered specialized care for cancer treatment (following pathologically confirmed diagnosis), exited from the study following noncancer diagnosis, or died. Routine symptom and demographic data included baseline cancer probability assessed by the primary care provider (low, intermediate, high), age, sex, performance status, baseline cancer probability by st

SUBMITTER: Molebatsi K 

PROVIDER: S-EPMC10286759 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature