A Computable Phenotype Model for Classification of Men Who Have Sex With Men Within a Large Linked Database of Laboratory, Surveillance, and Administrative Healthcare Records.

Travis Salway,Ashleigh J Rich,Maria Alvarez,Robert Balshaw,Mel Krajden,Mark Gilbert,Zahid A Butt,Amanda Yu,Aidan Ablona,Carmine Rossi,Jason Wong,Naveed Z Janjua,Younathan Abdia,Stanley Wong,Troy Grennan

doi:10.3389/fdgth.2020.547324

Abstract

Background: Most public health datasets do not include sexual orientation measures, thereby limiting the availability of data to monitor health disparities, and evaluate tailored interventions. We therefore developed, validated, and applied a novel computable phenotype model to classify men who have sex with men (MSM) using multiple health datasets from British Columbia, Canada, 1990–2015.Methods: Three case surveillance databases, a public health laboratory database, and five administrative health databases were linked and deidentified (BC Hepatitis Testers Cohort), resulting in a retrospective cohort of 727,091 adult men. Known MSM status from the three disease case surveillance databases was used to develop a multivariable model for classifying MSM in the full cohort. Models were selected using “elastic-net” (GLMNet package) in R, and a final model optimized area under the receiver operating characteristics curve. We compared characteristics of known MSM, classified MSM, and classified heterosexual men.Findings: History of gonorrhea and syphilis diagnoses, HIV tests in the past year, history of visit to an identified gay and bisexual men's clinic, and residence in MSM-dense neighborhoods were all positively associated with being MSM. The selected model had sensitivity of 72%, specificity of 94%. Excluding those with known MSM status, a total of 85,521 men (12% of cohort) were classified as MSM.Interpretation: Computable phenotyping is a promising approach for classification of sexual minorities and investigation of health outcomes in the absence of routinely available self-report data.

Highlights

Men who have sex with men (MSM) are disproportionately represented in multiple epidemics of public health interest, including HIV, hepatitis C (HCV), hepatitis B (HBV), syphilis, and gonorrhea [1,2,3,4]
In within-sample comparisons of our model, we found that MSM and heterosexual men were similar between the known-MSMstatus datasets and the larger BC-HTC, with a few exceptions
This may be partially attributable to the fact that most known MSM came from HIV, gonorrhea, or syphilis case reports—sexually transmitted infection (STI) diagnoses that tend to occur at older ages—while most known heterosexual men came from chlamydia case reports, which tend to occur at younger ages [20]

Summary

Introduction

Men who have sex with men (MSM) are disproportionately represented in multiple epidemics of public health interest, including HIV, hepatitis C (HCV), hepatitis B (HBV), syphilis, and gonorrhea [1,2,3,4]. MSM experience numerous mental health and substance use-related inequities, including fourfold greater rates of suicide attempts and twofold greater rates of depression, anxiety, and substance use disorders, as compared with heterosexual men [5,6,7] These inequities are at least partially attributable to a social stigma attached to minority sexualities, which induces a minority stress response and adaptive behaviors including substance use and sexual risk-taking, in some MSM [8]. Databases that include MSM or sexual minority self-report status tend to result in small sample sizes which limit the ability to conduct within-group analyses of MSM [9] For these reasons, sexual and gender minority health researchers recommend the use of multiple and novel sampling and measurement strategies for research with MSM and other sexual and gender minorities [9]. We developed, validated, and applied a novel computable phenotype model to classify men who have sex with men (MSM) using multiple health datasets from British Columbia, Canada, 1990–2015

Methods

Results

Discussion

Conclusion