Bayesian age-period-cohort projection of cancers in Iran: a modeling study.

ABSTRACT:

Introduction

Cancer is a significant public health issue in Iran, and its incidence has been on the rise in recent years. The objective of this study is to predict the incidence of total cancer in Iran using a Bayesian age-period-cohort (APC) model.

Methods

Utilizing age-period-cohort modeling, this study assessed the multifaceted effects of age, period, and cohort on cancer incidence during the period spanning 2005 to 2017. Key metrics, including the net drift (representing the overall annual percentage change), local drift (indicating annual percentage changes within specific age groups), and longitudinal age curves (depicting expected age-specific rates over time), were computed. Moreover, the evaluation encompassed an analysis of period and cohort relative risks. To proj

SUBMITTER: Barati H 

PROVIDER: S-EPMC11657364 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature