期刊
CANCER EPIDEMIOLOGY
卷 53, 期 -, 页码 72-80出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.canep.2018.01.013
关键词
Net survival; Cure models; Probability of being cured; Time-to-cure
资金
- Institut National du Cancer (INCa) [2014-087]
- Fondation ARC pour la recherche sur le cancer [PDF20151203665]
- French Government (Agence Nationale de la Recherche, Investissements d'Avenir) [ANR-11-LABX-0021]
Background: Cure models have been adapted to net survival context to provide important indicators from population-based cancer data, such as the cure fraction and the time-to-cure. However existing methods for computing time-to-cure suffer from some limitations. Methods: Cure models in net survival framework were briefly overviewed and a new definition of time-to-cure was introduced as the time TTC at which P(t), the estimated covariate-specific probability of being cured at a given time t after diagnosis, reaches 0.95. We applied flexible parametric cure models to data of four cancer sites provided by the French network of cancer registries (FRANCIM). Then estimates of the time-to-cure by TTC and by two existing methods were derived and compared. Cure fractions and probabilities P(t) were also computed. Results: Depending on the age group, TTC ranged from to 8 to 10 years for colorectal and pancreatic cancer and was nearly 12 years for breast cancer. In thyroid cancer patients under 55 years at diagnosis, TTC was strikingly 0: the probability of being cured was> 0.95 just after diagnosis. This is an interesting result regarding the health insurance premiums of these patients. The estimated values of time-to-cure from the three approaches were close for colorectal cancer only. Conclusions: We propose a new approach, based on estimated covariate-specific probability of being cured, to estimate time-to-cure. Compared to two existing methods, the new approach seems to be more intuitive and natural and less sensitive to the survival time distribution.
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