Publications by authors named "Z Uhry"
Background: In descriptive epidemiology, there are strong similarities between incidence and survival analyses. Because of the success of multidimensional penalized splines (MPSs) in incidence analysis, we propose in this pedagogical paper to show that MPSs are also very suitable for survival or net survival studies.
Methods: The use of MPSs is illustrated in cancer epidemiology in the context of survival trends studies that require specific statistical modelling.
Article Synopsis
- This study compares two methods for estimating death probabilities in multiple sclerosis (MS) patients: the Cause-Specific Framework (CSF) which requires known causes of death, and the Excess Mortality Framework (EMF) which does not.
- Using data from a large MS registry and a subset with detailed death records, the researchers found that EMF generally estimated higher death probabilities than CSF across different age groups.
- Overall, the analysis revealed varying mortality probabilities for MS patients based on the initial disease type, sex, and age; with significant differences particularly noted between relapsing-onset MS and primary progressive patients over a 30-year follow-up.
Objective: To analyze trends in cancer incidence and mortality (France, 1990-2018), with a focus on men-women disparities.
Methods: Incidence data stemmed from cancer registries (FRANCIM) and mortality data from national statistics (CépiDc). Incidence and mortality rates were modelled using bidimensional penalized splines of age and year (at diagnosis and at death, respectively).
Objective: To determine the effects of current age and disease duration on excess mortality in multiple sclerosis (MS), we describe the dynamics of excess death rates over these 2 time scales and study the effect of age at MS clinical onset on these dynamics, separately in each initial phenotype.
Methods: We used data from 18 French MS expert centers participating in the Observatoire Français de la Sclérose en Plaques. Patients with MS living in metropolitan France and having a clinical onset between 1960 and 2014 were included.
Background: In many countries, epidemiological surveillance of chronic diseases is monitored by local registries (LR) which do not necessarily cover the whole national territory. This gap has fostered interest in using non-registry databases (e.g.
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