PubMed HealthSearch

PubMed · 7644854

Statistical issues in assessing comorbidity.

Abstract

I define three separate and distinct types of non-random comorbidity: epidemiologic, clinical and familial. These might exist singly or in any combination for a pair of disorders. The focus is on their definition and the measurement and interpretation of the types of comorbidity of most common concern: epidemiologic comorbidity. I discuss certain sources of epidemiologic comorbidity such as shared risk factors, or diagnostic 'fuzziness', and I indicate the directions of research design and analyses to disclose such sources.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

H C Kraemer. 1995-04-30. Statistical issues in assessing comorbidity.. https://doi.org/10.1002/sim.4780140803

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N = 87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR = 1.13, 95% CI = 1.09-1.17), also when accounting for comorbidity status (HR = 1.08, 95% CI = 1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta = 0.36 ± 0.03 when considering a linear relationship to beta = 3.21 ± 0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity