Ontology highlight
ABSTRACT: Background
To inform healthcare professionals, payers and health technology organisations of estimated survival benefits of new treatments, statistical methods can be used to model the projected clinical benefits versus costs of new interventions. This is particularly relevant for new treatments where data describing all progression events are incomplete and long-term survival outcomes are not yet established. In patients with the fast-growing B-cell cancer, diffuse large B-cell lymphoma (DLBCL), heterogeneous clinical efficacy outcomes are observed with the presence of both 'cured' (long-term survivors [LTS]) and 'non-cured' patients. Mixture cure rate models represent an alternative approach to traditional standard parametric survival models as they capture this heterogeneity. Th
SUBMITTER: Felizzi F
PROVIDER: S-EPMC9928994 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature