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Study Summary Effect Of Comorbid Mdd On Hiv Disease Profression

Study Summary: Effect of Comorbid MDD on HIV Disease Profression

Owora AH. Major depression disorder trajectories and HIV disease progression: results from a 6-year outpatient clinic cohort. Medicine (Baltimore). 2018;97(12):e0252. doi: 10.1097/MD.0000000000010252.
Background

Up to one-third of patients with HIV in the United States receive a diagnosis of major depressive disorder (MDD) each year. Comorbid MDD may negatively impact the progression of HIV. For example, untreated depression among patients with HIV has been linked to nonadherence to antiretroviral therapy, a greater risk of HIV transmission, virologic failure, progression of HIV infection to AIDS, and decreased retention in HIV care.1

However, detailed information about the association between MDD and HIV progression is lacking. To address this gap, Arthur H. Owora, DrPH, investigated the relationship between MDD and HIV disease progression among patients with HIV.1

Study Design

This was a 6-year retrospective cohort study designed to examine patterns of MDD illness and how they relate to progression of HIV disease. A unique feature of the study was its open dynamic, meaning patients could enter or exit the study over time.1

The study took place at a single outpatient HIV clinic in the United States and included patients with HIV who had not previously received any HIV-related treatment. Patients who had previously visited the study clinic before the start of the study period (2009-2014) were excluded. Medical information was collected from the clinic’s electronic medical record (EMR) system, including information about HIV and MDD diagnoses, treatments, and monitoring. Sociodemographic data were also collected, including information about age, gender, race/ethnicity, and marital status.1

Patients with HIV and MDD were identified using diagnosis codes from the International Classification of Diseases, 9th Revision and 10th Revision (ICD-9/-10). To determine the validity of the medical record data retrieval processes using ICD-9/-10 diagnosis codes, 10% of clinic patients were selected, both with and without an original diagnosis of MDD, and patient medical charts were reviewed; the results of the chart review showed that data abstraction was 100% percent accurate. Patients’ CD4 counts were used as a tool to monitor HIV progression. For the purposes of the study, counts <200 cells/mL were classified as low.1

Statistical tests were performed using the data collected to analyze the relationships among MDD diagnoses, CD4 counts, and various sociodemographic characteristics. Latent class growth analysis (LCGA) was used to analyze the trajectory of MDD over time.1

Results

Data from 2260 patients were retrieved. Most patients were male (79%), single (79%), Caucasian (55%), and 21 to 50 years of age (70%). A relatively small percentage of patients (17%) had low baseline CD4 counts.1

A total of 1494 patients with HIV with a minimum of 1 follow-up evaluation of their MDD and CD4 count every year for at least 4 years were included in the LCGA analyses. Four different trajectories of MDD were identified based on a patient’s probability of MDD diagnosis from baseline through follow-up: low-chronic (74%), moderate-ascending (3%), high-episodic (6%), and high-chronic (17%).1

Patients with a low-chronic trajectory for MDD had a negligible chance (3%) of an MDD diagnosis from baseline through year 6 of the study period. Those with a moderate-ascending trajectory had a steadily increasing chance of receiving a diagnosis of MDD from baseline (50%) through year 6 of the study period (88%). Patients with a high-episodic trajectory had a 28% chance of an MDD diagnosis at baseline, which rose to 80% by year 3 but became negligible by year 6. Patients with a high-chronic trajectory also had a 28% chance of a diagnosis of MDD at baseline, but this probability rose sharply to 90% by year 2 and stabilized around 100% through year 6 of the study period.1

Four patient factors that significantly predicted the trajectory of a patient’s MDD diagnosis were identified: male gender (P = .04), minority race (P <.01), age >30 years (P <.01), and low baseline CD4 count (P = .04). Also, researchers reported that the course of patients’ MDD was correlated with their CD4 counts. As illustrated in the Table, patients in the high-chronic trajectory group were less likely to have a low CD4 count compared with those in the low-chronic trajectory group. On the other hand, patients with a moderate-ascending MDD diagnosis trajectory had increased probability of a low CD4 count.1

Other factors that correlated with decreased probability of a low CD4-cell count were male gender, minority race, and being divorced or separated (Table). In general, the odds of having low CD4 counts dropped during the study period across the MDD trajectory groups (P <.01).1

Conclusions

The findings in this study suggested that the course of MDD among patients with HIV can be categorized into 4 different trajectory groups, and that these groups were associated with different patterns of HIV disease progression. Owora noted that compared with a low-chronic trajectory of MDD, a moderate-ascending trajectory is associated with a higher risk of low CD4 counts, which may be predictive of worsening HIV disease. This finding is consistent with previously published data from studies of MDD among patients with HIV. Patients with HIV in the high-chronic MDD trajectory group had a lower risk of having a low CD4 count throughout the study period compared with patients in the low-chronic MDD trajectory group. Owora suggested that a patient’s pattern of MDD illness over time, rather than status at a single point in time, is correlated with HIV progression. The study was limited by the use of secondary data from EMRs, which increased the probability of missing data and the potential for misclassification bias.1

Reference

1. Owora AH. Major depression disorder trajectories and HIV disease progression: results from a 6-year outpatient clinic cohort. Medicine (Baltimore). 2018;97(12):e0252. doi: 10.1097/MD.0000000000010252.

 
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