@misc{10481/68077,
year = {2021},
url = {http://hdl.handle.net/10481/68077},
abstract = {Background: Population-based cancer registries are required to calculate cancer incidence in a geographical area,
and several methods have been developed to obtain estimations of cancer incidence in areas not covered by a
cancer registry. However, an extended analysis of those methods in order to confirm their validity is still needed.
Methods: We assessed the validity of one of the most frequently used methods to estimate cancer incidence, on
the basis of cancer mortality data and the incidence-to-mortality ratio (IMR), the IMR method. Using the previous
15-year cancer mortality time series, we derived the expected yearly number of cancer cases in the period 2004–
2013 for six cancer sites for each sex. Generalized linear mixed models, including a polynomial function for the year
of death and smoothing splines for age, were adjusted. Models were fitted under a Bayesian framework based on
Markov chain Monte Carlo methods. The IMR method was applied to five scenarios reflecting different assumptions
regarding the behavior of the IMR. We compared incident cases estimated with the IMR method to observed cases
diagnosed in 2004–2013 in Granada. A goodness-of-fit (GOF) indicator was formulated to determine the best
estimation scenario.
Results: A total of 39,848 cancer incidence cases and 43,884 deaths due to cancer were included. The relative
differences between the observed and predicted numbers of cancer cases were less than 10% for most cancer sites.
The constant assumption for the IMR trend provided the best GOF for colon, rectal, lung, bladder, and stomach
cancers in men and colon, rectum, breast, and corpus uteri in women. The linear assumption was better for lung
and ovarian cancers in women and prostate cancer in men. In the best scenario, the mean absolute percentage
error was 6% in men and 4% in women for overall cancer. Female breast cancer and prostate cancer obtained the
worst GOF results in all scenarios.
Conclusion: A comparison with a historical time series of real data in a population-based cancer registry indicated
that the IMR method is a valid tool for the estimation of cancer incidence. The goodness-of-fit indicator proposed
can help select the best assumption for the IMR based on a statistical argument.},
organization = {Subprogram "Cancer surveillance" of the CIBER of Epidemiology and Public Health (CIBERESP)},
organization = {MINECO/FEDER 

PGC2018-098860-B-I00},
organization = {Andalusian Department of Health Research, Development and Innovation 

PI-0152/2017},
publisher = {BMC},
keywords = {Cancer incidence},
keywords = {Estimation},
keywords = {Goodness-of-fit test},
keywords = {Mortality-to-incidence ratio},
keywords = {Validation},
title = {Cancer incidence estimation from mortality data: a validation study within a population-based cancer registry},
doi = {10.1186/s12963-021-00248-1},
author = {Redondo Sánchez, Daniel and Rodríguez Barranco, Miguel and Ameijide, Alberto and Alonso, Francisco Javier and Fernández-Navarro, Pablo and Jiménez Moleón, José Juan and Sánchez, María José},
}