Supporting information may be found in the online version of this article.
Bayesian approach to predicting cancer incidence for an area without cancer registration by using cancer incidence data from nearby areas†
Article first published online: 11 JAN 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 31, Issue 10, pages 978–987, 10 May 2012
How to Cite
Clèries, R., Ribes, J., Buxo, M., Ameijide, A., Marcos-Gragera, R., Galceran, J., Martínez, J. M. and Yasui, Y. (2012), Bayesian approach to predicting cancer incidence for an area without cancer registration by using cancer incidence data from nearby areas. Statist. Med., 31: 978–987. doi: 10.1002/sim.4463
- Issue published online: 11 APR 2012
- Article first published online: 11 JAN 2012
- Manuscript Accepted: 17 OCT 2011
- Manuscript Revised: 10 OCT 2011
- Manuscript Received: 17 AUG 2010
- cancer incidence;
- cancer mortality;
- age-period model;
- age-drift model
This paper compares three different methods for performing cancer incidence prediction in an area without a cancer registry under a Bayesian framework, using linear and log-linear age-period models with either age-specific slopes or a common slope across age groups. The three methods assume that a nearby area with a cancer registration has similar incidence and mortality patterns as the area of interest without a cancer registry where the cancer incidence prediction is carried out. The three methods differ in modeling strategies: (i) modeling the incidence rate directly; (ii) modeling the ratio of the number of incident cases to that of mortality cases; and (iii) modeling the difference between the incidence rate and the mortality rate. Strategy (iii) is a new approach in this type of projection. Empirical assessment is made using real data from the cancer registry of Tarragona, Spain, to predict cancer incidence in Girona, Spain, and vice versa. Predictions of short-term (3–4 years) incidence were made for 2001 in Tarragona using observed cancer incidence and mortality data for 1994–1998 from Girona. Short-term predictions were made for 2002 in Girona using Tarragona's 1994–1998 data. Additionally, long-term (10 years) incidence rate predictions were made for 2002 in Girona using data from Tarragona for the period 1985–1992. Our results suggest that extrapolating time-trends of incidence rates minus mortality rates may have the best predictive performance overall. These methods of population-level disease vincidence prediction are highly relevant to health care planning and policy decisions. Copyright © 2012 John Wiley & Sons, Ltd.