Social vulnerability in persons with chronic hepatitis C virus infection is associated with a higher risk of prescription opioid use

Prescription opioid use (POU) is often a precursor to opioid use disorder (OUD) and subsequent consequences. Persons with chronic hepatitis C virus infection (CHC) may be at a higher risk of POU due to a higher comorbidity burden and social vulnerability factors. We sought to determine the burden of POU and associated risk factors among persons with CHC in the context of social vulnerability. We identified CHC persons and propensity-score matched HCV− controls in the electronically retrieved Cohort of HCV-Infected Veterans and determined the frequency of acute, episodic long-term and chronic long-term POU and the prevalence of social vulnerability factors among persons with POU. We used logistic regression analysis to determine factors associated with POU. Among 160,856 CHC and 160,856 propensity-score matched HCV-controls, acute POU was recorded in 38.4% and 38.0% (P = 0.01) respectively. Episodic long-term POU was recorded in 3.9% in each group (P = 0.5), while chronic long-term POU was recorded in 28.4% and 19.2% (P < 0.0001). CHC was associated with a higher risk of chronic long-term POU (OR 1.66, 95%CI 1.63, 1.69), but not with acute or episodic long-term POU. Black race, female sex and homelessness were associated with a higher risk of chronic long-term POU. Presence of ≥ 1 factor was associated with a higher risk of all POU patterns. Persons with CHC have more social vulnerability factors and a higher risk of chronic long-term POU. Presence of ≥ 1 social vulnerability factor is associated with a higher risk of POU. Downstream consequences of POU need further study.

www.nature.com/scientificreports/ factors among Veterans with CHC infection and matched controls. We did not study the temporal associations of the risk variables in the current study.

Data sources and cohort construction. We used the Electronically Retrieved Cohort of HCV Infected
Veterans (ERCHIVES) as the data source for this analysis. ERCHIVES is well defined in numerous previous publications [24][25][26][27][28][29] . Briefly, all persons with HCV infection in the Department of Veterans Affairs healthcare system (VA) diagnosed after October 1, 2001 are identified based on a positive HCV antibody test. Age (5-year blocks), sex and race matched persons with a negative HCV antibody test in the same year are identified as controls. Demographic, clinical, laboratory, pharmacy, anthropometric, vital signs and survival date are retrieved from the Corporate Data Warehouse (CDW) using well established algorithms and definitions. The cohort is updated annually to identify newly diagnosed cases with HCV infection and corresponding controls.
For the current study, we included all persons in ERCHIVES identified between 2001 and 2019. For persons with HCV, we retained those with at least one detectable HCV RNA, thus fulfilling the criteria for CHC infection. For both groups (those with and without CHC), we excluded those with human immunodeficiency virus coinfection and those with missing data to calculate FIB-4 score within 12 months prior to cohort entry date. A propensity score was calculated for each study participant using a logistic regression model including age, race, sex, body mass index, FIB-4, diabetes, hypertension, coronary artery disease, smoking status and alcohol use disorder. Using the propensity score, we conducted propensity score matching to create 1:1 matched sets of persons with CHC and uninfected controls using a propensity score distance. The tails of the propensity scores were not trimmed. We used the greedy matching (CHC selected at random first, then HCV− whose propensity score is closest to the randomly selected CHC is chosen for matching), matching without replacement (once an HCV− has been selected to be matched, that HCV− is no longer available for selecting), and without restriction for the maximum difference between the propensity scores of matched CHC and HCV−.

Primary outcome measures.
Our primary outcome measures were acute and long-term prescription opioid use (POU). All opioids approved by the US Food and Drug Administration were included when determining POU (list available as Appendix 1 in accompanying supplementary materials). Acute POU was defined as an episode whereby an opioid was prescribed with less than 90 days of drug supply. Long-term POU was defined as at least one episode with ≥ 90 days of drug supply including refills. Long-term POU was further subdivided into episodic and chronic use. Episodic long-term use included the subset of persons receiving ≥ 90 days of POU supply with < 50% episode intensity, where episode intensity was calculated as percentage of episode days covered by the prescription. Chronic long-term use included the subset of persons receiving ≥ 90 days of POU supply with > 50% episode intensity.
Clinical covariates. Diabetes was defined using a combination of blood glucose measurements, prescription of insulin or oral hypoglycemic and ICD-9/10 codes 27,30 . We used FIB-4 to estimate the severity of liver disease and presence of cirrhosis. FIB-4 score was calculated based on clinical and an average of two lab values recorded within 12 months preceding entry into the cohort 31 . Psychiatric illness (major depression, schizophrenia, bipolar disorder, post-traumatic stress disorder), alcohol use disorder, hypertension, cancer diagnosis and cardiovascular disease were defined by presence of at least one inpatient or two outpatient International Classification of Diseases, 9th edition, Clinical Modification (ICD-9CM, prior to October 1, 2015) or ICD-10 (from October 1, 2015 onwards) codes 32 . Smoking history was retrieved from the Health Factors Dataset and classified as never, former and current smokers 33 . Since opioid analgesics are often prescribed for short term pain relief after dental procedures and fractures, we identified persons who underwent removal or restoration of teeth and those who sustained major joint dislocation or bone fracture using ICD-9CM and ICD-10 codes.

Social vulnerability factors.
For our current study, we identified the following factors to denote social vulnerability: (1) non-White race; (2) female sex; (3) homelessness; (4) poverty, defined as annual income less than $45,200 thus placing them in the low income or below Federal poverty level; (5) rural or highly rural residence; (6) alcohol use disorder; and (7) diagnosis of psychiatric illness. These variables were retrieved from the CDW datasets where they are recorded based on VA's established algorithms. These factors were chosen to represent persons with social vulnerability since persons with these characteristics have been shown to suffer significant disparities in linkage to treatment and clinical outcomes for various conditions 17-23 . Statistical analyses. Baseline characteristics of persons with CHC and uninfected controls, and persons with and without POU were compared using chi-squared test for dichotomous variables and t-test for continuous variables. We determined the proportion of persons with acute, episodic long-term and chronic long-term POU by number of social vulnerability factors. We also determined the number of social vulnerability factors present among those with CHC only, CHC with POU and POU without CHC. We used logistic regression to generate odds ratios and 95% confidence intervals for factors associated with acute or long-term POU. Covariates of interest were demographic and clinical characteristics at baseline. All statistical analyses were completed using SAS Version 9.4 (SAS Institute Inc., Cary NC).
Missing data. There were 1707 (0.5%) participants with missing income data and 446 (0.1%) with missing data on their residence. These persons were not excluded form the main analysis since they comprised a very small proportion of the study population. We compared the baseline characteristics of persons with and without www.nature.com/scientificreports/ CHC, and with and without POU to ensure that the overall characteristics were not different in the analysis cohort.

Ethical approval. The study was approved by the Institutional Review Board at VA Pittsburgh Healthcare
System and all methods were carried out in accordance with relevant guidelines and regulations. A waiver of informed consent requirement was granted to studies related to ERCHIVES by the same Board.

Results
Baseline characteristics: CHC vs HCV−. Our final dataset included 160,856 persons with CHC and 160,856 propensity score matched controls without CHC infection (Fig. 1). Baseline characteristics of persons with CHC and uninfected controls are shown in Table 1 We compared the baseline characteristics of persons with and without CHC after excluding those with missing data to ensure that the overall characteristics were not different in the analysis cohort. The results were nearly identical to the main analysis results (Supplementary Table 1).  We compared the baseline characteristics of persons with and without POU after excluding those with missing data to ensure that the overall characteristics were not different in the analysis cohort. The results were nearly identical to the main analysis results (Supplementary Table 2).

POU by social vulnerability factors. Proportion of persons with POU increased with increasing number
of social vulnerability factors (Table 3). Among persons with acute POU, 29.46% had no social vulnerability factors, while among those with long-term episodic POU, 2.32% had no social vulnerability factor, and among those with long-term chronic POU, 11.99% had no social vulnerability factor. These proportions were higher for persons with any social vulnerability factor. However, there was no discernible relationship with increasing number of social vulnerability factors and higher rates of POU (Table 3). www.nature.com/scientificreports/ Factors associated with POU. We determined the factors associated with acute, episodic long-term and chronic long-term POU. Increasing age was associated with lower risk of all types of POU. Black and Hispanic races were associated with a higher risk of acute and episodic long-term POU but with a lower risk of chronic long-term use (Table 4). Medical comorbidities (diabetes, cardiovascular disease, cancer) were associated with a higher risk of all types of POU. Rural and highly rural residence were associated with a lower risk of acute POU,  www.nature.com/scientificreports/ but a higher risk of chronic long-term POU. Higher income strata were associated with a lower risk of all types of POU. CHC infection was not associated with episodic long-term POU (OR 0.99, 95% CI 0.95, 1.03), but was significantly associated with chronic long-term POU (OR 1.66, 95% CI 1.63, 1.69) ( Table 4). Presence of any social vulnerability factor was associated with a higher risk of acute, episodic long-term and chronic long-term POU, with increasing number of factors associated with a generally higher risk, though the relationship was not clearly linear (Supplementary Table 3).

Discussion
We provide the first comprehensive picture of POU in persons with CHC and appropriately matched controls in the context of social vulnerability. We found that CHC and multiple social vulnerability factors are associated with a higher risk of chronic long-term POU, but not necessarily acute POU. We found that CHC was associated with a significantly higher risk of chronic long-term POU but not with a higher risk of acute or episodic long-term POU. In fact, CHC was among the strongest risk factor for POU with the odds ratio similar to cancer diagnosis. CHC is associated with a higher burden of medical and psychiatric comorbidities and several extrahepatic manifestations 34,35 . Chronic pain is often associated with CHC infection itself, or with one of several rheumatologic or immunologic manifestations of CHC infection, with up to two-thirds of the patients with CHC experiencing chronic pain 35,36 . In the interferon-era, treatment itself was associated with chronic fatigue and pain. However, since only a small fraction of persons were ever treated with interferon-based regimens, other factors certainly contributed to chronic pain 37 . Newer all-oral direct acting antiviral agents are more tolerable, more efficacious and have fewer side effects. Whether treatment with these newer agents is associated with a lower incidence of pain or resolution of chronic pain requires further study. Such positive association may in turn reduce the need for opioid prescriptions and its downstream consequences. On the other hand, the association between CHC and POU could be due to POU leading to injection drug use, which increases the risk of acquiring CHC. Future studies should also determine the direction of association between CHC and POU.
Persons with POU were more likely to have medical comorbidities. While most comorbidities studied do not necessarily require opioids, they may be a surrogate for other associated conditions. We also found POU to be more common among persons with several individual social vulnerability factors. These included Black race, homelessness, lower income strata and psychiatric illness. Rural or highly rural residence was not associated with a higher rate of POU. However, in logistic regression model, male sex was associated with a lower risk of www.nature.com/scientificreports/ acute or episodic long-term POU but a higher risk of chronic long-term POU. Whether females have actually lesser need for chronic long-term opioids, or whether this is due to lesser access to resources or perception of providers is unknown and warrants further study. Risk of POU was significantly lower in persons with higher income strata independent of other factors studied confirming that persons in lower economic strata are most hardly hit by POU, and by extension possibly opioid use disorder. This highlights co-occurrence of syndemics of socioeconomic marginalization and other vulnerability factors with POU use, which could be related to eventual opioid use disorders. These findings, taken together, indicate a strong association between POU and socially vulnerable CHC infected persons. Since opioid analgesics are frequently prescribed for appropriate medical conditions, an important next step is to determine the proportion of persons using opioid analgesics strictly as prescribed, and to determine the magnitude and factors associated with inappropriate use. Subsequent studies should also determine the proportion of persons with POU progressing to OUD and injection drug use, and risk factors associated with such progression.
Strengths of our study include a large national population and appropriately matched controls. Veterans have a high burden of medical, psychiatric and substance use comorbidities. While this is not truly representative of the overall population, it is critical to understand the magnitude and impact of this epidemic in this particularly high-risk population. A main limitation of the current study is that we only studied POU and not the downstream consequences, namely OUD and illicit injection drug use. However, our specific aim for this study was limited to understanding the first step in this cascade and future studies will look into these downstream effects and clinical consequences. Another limitation of our study is the absence of a quantitative measure of pain which may require opioid prescription. To mitigate this at least partially, we excluded persons with common conditions associated with short-term POU, including acute fractures and dental work, as well as chronic painful conditions like cancer. Our study does not address the question of temporal relationships between POU, injection drug use and CHC infection, since this was not the aim of our study.
In conclusion, persons with CHC have high prevalence of social vulnerability factors, and a higher risk of chronic long-term POU. Consequences of high rate and risk of POU among this population need further study. www.nature.com/scientificreports/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.