Application of multiple testing procedures for identifying relevant comorbidities, from a large set, in traumatic brain injury for research applications utilizing big health-administrative data

Jana, Sayantee and Sutton, Mitchell and Mollayeva, Tatyana and et al, . (2022) Application of multiple testing procedures for identifying relevant comorbidities, from a large set, in traumatic brain injury for research applications utilizing big health-administrative data. Frontiers in Big Data, 5. pp. 1-9. ISSN 2624-909X

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Abstract

Background: Multiple testing procedures (MTP) are gaining increasing popularity in various fields of biostatistics, especially in statistical genetics. However, in injury surveillance research utilizing the growing amount and complexity of health-administrative data encoded in the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10), few studies involve MTP and discuss their applications and challenges. Objective: We aimed to apply MTP in the population-wide context of comorbidity preceding traumatic brain injury (TBI), one of the most disabling injuries, to find a subset of comorbidity that can be targeted in primary injury prevention. Methods: In total, 2,600 ICD-10 codes were used to assess the associations between TBI and comorbidity, with 235,003 TBI patients, on a matched data set of patients without TBI. McNemar tests were conducted on each 2,600 ICD-10 code, and appropriate multiple testing adjustments were applied using the Benjamini-Yekutieli procedure. To study the magnitude and direction of associations, odds ratios with 95% confidence intervals were constructed. Results: Benjamini-Yekutieli procedure captured 684 ICD-10 codes, out of 2,600, as codes positively associated with a TBI event, reducing the effective number of codes for subsequent analysis and comprehension. Conclusion: Our results illustrate the utility of MTP for data mining and dimension reduction in TBI research utilizing big health-administrative data to support injury surveillance research and generate ideas for injury prevention. Copyright © 2022 Jana, Sutton, Mollayeva, Chan, Colantonio and Escobar.

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IITH Creators:

IITH Creators	ORCiD
Jana, Sayantee	UNSPECIFIED

Item Type:

Article

Additional Information:

This study was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health (NIH) [Award No. R21HD089106] and the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Number R01NS117921. AC was funded by the Canadian Institutes of Health Research (CIHR) Chair in Gender, Work and Health [Grant No. CGW-126580], and TM was supported by Canada Research Chair in Neurological Disorders and Brain Health and the Alzheimer's Association Grant [AARF-16-442937]. Please note that the content of the article is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work was funded in part by the Canada Research Chairs Programme. The funders had no role in the study design, data collection, decision to publish or preparation of the manuscript.

Uncontrolled Keywords:

Benjamini-Hochberg; Benjamini-Yekutieli; health-administrative data; ICD-10 codes; McNemar test

Subjects:

Mathematics

Divisions:

Department of Mathematics

Depositing User:

. LibTrainee 2021

Date Deposited:

12 Nov 2022 09:22

Last Modified:

12 Nov 2022 09:22