|Title||Association networks in a matched case-control design - Co-occurrence patterns of preexisting chronic medical conditions in patients with major depression versus their matched controls.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Kim M-H, Banerjee S, Zhao Y, Wang F, Zhang Y, Zhu Y, DeFerio J, Evans L, Park SMin, Pathak J|
|Journal||J Biomed Inform|
|Date Published||2018 Nov|
OBJECTIVE: We present a method for comparing association networks in a matched case-control design, which provides a high-level comparison of co-occurrence patterns of features after adjusting for confounding factors. We demonstrate this approach by examining the differential distribution of chronic medical conditions in patients with major depressive disorder (MDD) compared to the distribution of these conditions in their matched controls.
MATERIALS AND METHODS: Newly diagnosed MDD patients were matched to controls based on their demographic characteristics, socioeconomic status, place of residence, and healthcare service utilization in the Korean National Health Insurance Service's National Sample Cohort. Differences in the networks of chronic medical conditions in newly diagnosed MDD cases treated with antidepressants, and their matched controls, were prioritized with a permutation test accounting for the false discovery rate. Sensitivity analyses for the associations between prioritized pairs of chronic medical conditions and new MDD diagnosis were performed with regression modeling.
RESULTS: By comparing the association networks of chronic medical conditions in newly diagnosed depression patients and their matched controls, five pairs of such conditions were prioritized among 105 possible pairs after controlling the false discovery rate at 5%. In sensitivity analyses using regression modeling, four out of the five prioritized pairs were statistically significant for the interaction terms.
CONCLUSION: Association networks in a matched case-control design can provide a high-level comparison of comorbid features after adjusting for confounding factors, thereby supplementing traditional clinical study approaches. We demonstrate the differential co-occurrence pattern of chronic medical conditions in patients with MDD and prioritize the chronic conditions that have statistically significant interactions in regression models for depression.
|Alternate Journal||J Biomed Inform|
|PubMed Central ID||PMC6262847|
|Grant List||P50 MH113838 / MH / NIMH NIH HHS / United States |
R01 MH105384 / MH / NIMH NIH HHS / United States
UL1 TR002384 / TR / NCATS NIH HHS / United States
R01 GM105688 / GM / NIGMS NIH HHS / United States
T32 MH019132 / MH / NIMH NIH HHS / United States
UL1 TR000457 / TR / NCATS NIH HHS / United States