A survival regression with cure fraction applied to cervical cancer

• Published in: Computational statistics Vol. 38; no. 1; pp. 403 - 418
• Main Authors: Cancho, Vicente G., Bedia, Elizbeth C., Cordeiro, Gauss M., Prataviera, Fábio, Ortega, Edwin M. M., Santo, Ana P. J. E.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-03-2023; Springer Nature B.V
• Subjects: Algorithms; Cancer; Cervical cancer; Economic Theory/Quantitative Economics/Mathematical Methods; Likelihood ratio; Mathematics and Statistics; Original Paper; Poisson distribution; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Statistical analysis; Statistics; Survival; Cure rate model; Proportional hazards; EM algorithm; Generalized Poisson distribution
• ISSN: 0943-4062; 1613-9658
• DOI: 10.1007/s00180-022-01233-4

A new survival model is proposed in the presence of surviving fractions and unobserved dispersion. It is obtained by considering several latent factors (or risks) that generated the observed lifetime which follows a generalized Poisson distribution, and it includes as a special case, the promotion time cure model. We explore maximum likelihood tools for inference issues by aid of the expectation maximization algorithm for estimating the parameters while model discrimination problem is treated by the aid of the likelihood ratio test. The new regression is applied to cervical cancer data to evaluate covariates effects in the cured fraction and non-cured group.