A multistate survival model of the natural history of cancer using data from screened and unscreened population.
Markov model
cancer screening
lead time
misclassification
prostate cancer
sojourn time
time-varying hazard
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
20 07 2021
20 07 2021
Historique:
revised:
01
02
2021
received:
10
03
2020
accepted:
06
04
2021
pubmed:
6
5
2021
medline:
30
6
2021
entrez:
5
5
2021
Statut:
ppublish
Résumé
One of the main aims of models using cancer screening data is to determine the time between the onset of preclinical screen-detectable cancer and the onset of the clinical state of the cancer. This time is called the sojourn time. One problem in using screening data is that an individual can be observed in preclinical phase or clinically diagnosed but not both. Multistate survival models provide a method of modeling the natural history of cancer. The natural history model allows for the calculation of the sojourn time. We developed a continuous-time Markov model and the corresponding likelihood function. The model allows for the use of interval-censored, left-truncated and right-censored data. The model uses data of clinically diagnosed cancers from both screened and nonscreened individuals. Parameters of age-varying hazards and age-varying misclassification are estimated simultaneously. The mean sojourn time is calculated from a micro-simulation using model parameters. The model is applied to data from a prostate screening trial. The simulation study showed that the model parameters could be estimated accurately.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3791-3807Informations de copyright
© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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