Prescription opioid use, opioid overdose, and links to syphilis diagnoses in North Carolina

The United States is facing both a devastating opioid epidemic and increasing syphilis incidence. Duration of opioid therapy influences risk of nonmedical opioid use and overdose, and drug use is associated with behaviors that facilitate infectious disease transmission. Therefore, the opioid epidemic may have a role in recent increases in syphilis diagnoses. This dissertation investigates how initial indication and duration of prescription opioid therapy is associated with risk of opioid overdose and uses spatial regression methods to examine spatiotemporal links between opioid overdoses and rising syphilis rates. We analyzed claims data of 492,983 patients initiating opioid therapy for pain management in North Carolina (NC) from 2006 through 2018. We identified patients exposed to long-term opioid therapy (LTOT) using a conservative definition requiring consistent exposure prescription opioids. In this cohort of opioid-naïve patients initiating opioid therapy, 1.7% of patients went on to have LTOT and 381 opioid overdoses were observed. The three-year risk of opioid overdose was 0.7 percentage points (RDw= 0.007, 95% CI: 0.001, 0.013) higher in the LTOT group compared to patients with shorter durations of use. Sensitivity analyses revealed a dose-response relationship between duration of opioid therapy and risk of opioid overdose. We did not find meaningful modification by clinical indication for opioid therapy. Next, we used surveillance data of diagnosed syphilis cases and emergency department visits for probable opioid overdose in NC from 2008 through 2017. Using spatial regression methods of aggregate zip code-level rate data, we found that recent increases in early syphilis cases in North Carolina may be spatiotemporally associated with the opioid epidemic. This relationship held in an ancillary pseudo-causal analysis that adjusted for relevant population-level confounders. Future work using rigorous causal inference techniques to further disentangle the key points in clinical decision-making around duration of opioid therapy could provide additional insights on how to mitigate risks of opioid use disorders and opioid overdose in pain patients. Further, future analyses of individual-level data to investigate possible causal mechanisms linking opioid use and syphilis incidence are warranted.Doctor of Philosoph

The Relationship Between Stigma, Sexual Risk Behavior and HIV Testing Among Men Who Have Sex with Men (MSM) in Kolkata, India

<p>Men who have sex with men (MSM) are at high risk for HIV, because of engaging in risky sexual practices. In many countries, MSM remain a highly stigmatized and marginalized population, making them harder to reach for HIV prevention intervention. Until recently before the start of this study, homosexual practices in India were criminalized, which may be influential in establishing and upholding stigma towards the MSM community. The prevalence of HIV in MSM populations in India is higher than the Indian national prevalence rate. This study sought to examine the relationship between stigma and use of HIV preventive practices, HIV sexual risk practices, and HIV testing behaviors among MSM. Surveys were conducted with two samples of men in Kolkata, India. One sample was 43 MSM, drawn from an NGO in Kolkata. The other sample was 57 men who do not have sex with men, drawn from men in varying neighborhoods in Kolkata. Correlations, Fisher's exact tests, Wilcoxon rank sum tests, logistic regressions, and ordinary least squares regressions were used to compare the two samples and the relationships between the variables of interest among MSM. It was found that stigma surrounding homosexuality is present in Kolkata and that it is associated with increased sexual risk behavior among MSM. In addition, MSM reported accessing HIV testing more frequently than non-MSM, and greater stigma was in fact associated with increased testing behavior. MSM were also more knowledgeable about HIV and more sexually risky than non-MSM. These results suggest that there is a relationship between stigma, sexual risk behavior, and HIV testing that warrants further study.</p>Thesi

Characterizing Patients using Abuse-deterrent Formulations of Extended-release Opioid Analgesics

Background: Abuse-deterrent formulations (ADFs) of extended-release (ER) opioids are manufactured to address opioid abuse. However, little is known about characteristics of patients who initiate ADF opioids, which is important to identify appropriate comparators to address confounding by indication. Objectives: To describe demographics and medical characteristics of patients prescribed ADF and non-ADF ER opioids in two sources of commercial claims. Methods: Using IBM Marketscan commercial claims (Data A) and a large private insurance provider in North Carolina [USA] (Data B) (both 2009-2018), we conducted a retrospective cohort study to examine patterns of ADF opioid use compared to non-ADF ER opioid use. Patients who initiated ADF and non-ADF ER opioids (18-64 years-old) were selected using both a traditional new user design (no opioid claims during the washout period, defined as six-months prior to ER opioid initiation) and a prevalent new user design (allowed non-ER opioid claims during the washout period and excluded the patients with no six-months eligibility prior to the first immediate-release (IR) opioid claim). Patient characteristics including demographics, medications (gabapentin, benzodiazepine, antidepressants, IR opioids), pain-related symptoms, and cancer were measured during the washout period for patients with ADF and non-ADF ER opioids. Results: Among eligible ER opioid initiators in Data A (N=330,728) and B (N=20,992), 31% and 34% initiated with ADF opioids, respectively. Among these patients, demographics were as follows (Data A and B): age [mean (SD)] = 49.4 (11.8) and 48.4 (11.8); male sex = 51.2% and 55.4%. Among patients with non-ADF ER opioids, demographics were as follows (Data A and Data B): age [mean (SD)] = 49.2 (11.4) and 47.8 (11.3); male sex = 45.8% and 50.4%. About 50% and 62% of patients with ADF opioids initiated with IR opioids, whereas 29%and 34% of patients with non-ADF ER opioids initiated with IR opioids in Data A and B, respectively. In both data sources, the prevalence of several types of pain was higher among patients with ADF opioids than in non-ADF ER group, including acute pain (Data A: 54.5% vs. 40.3%; Data B: 56.7% vs. 41.5%), arthritis pain (35.7% vs. 20.1%; 36.4% vs. 22.7%), and chronic pain (84.8% vs. 76.3%; 89.5% vs. 85.3%). The prevalence of use of medications and cancer was higher in patients with non-ADF ER opioids than in patients with ADF opioids in both data sources. Conclusions: Both data sources revealed differences in characteristics between patients with ADF and non-ADF ER opioids. The implications for research design include identifying appropriate comparator groups when examining ADF opioid use related outcomes

Matching Study Design to Prescribing Intention: The Prevalent New User Design in Opioid Research

Background: In drug studies, research designs requiring no prior exposure to certain drug classes may restrict research on important populations. For example, currently marketed abuse-deterrent formulation (ADF) opioids are routinely used in patients with prior prescription opioid exposure. The traditional new user design excludes patients with prior exposure to prescription opioids, hence incident ADF users are not representative of the overall ADF user population. A prevalent new user design, wherein patients are prescribed similar treatments (or potential comparators) before starting the new treatment, likely better represents the intended ADF patient population. Objectives: To evaluate the appropriateness of new user versus prevalent new user design for estimating post-market effectiveness of ADFs and examine patterns of ADF initiation. Methods: We used pharmaceutical claims data from a large private insurer in North Carolina [USA] from 2009-2018. Included patients were new ADF users age 18-64 with 6 months of continuous enrollment prior to their first ADF claim. Incident users were identified as those with no prescription opioid claims in a 6-month washout period prior to ADF initiation. Prevalent new users were identified as those with non-ADF opioid claims during the 6 months before ADF initiation, so long as they also had a 6-month washout period of no opioid claims prior to first non-ADF opioid claim. We compared sample sizes by study design and described ADF utilization patterns. Results: We identified 8,841 eligible patients who initiated an ADF. Of these, 2,332 (26%) were classified as incident users, whereas 6,509 (74%) were prevalent new users and would be excluded in a traditional new user design. Most incident ADF users started with both an ADF and an immediate-release (IR) opioid concurrently (85%). Among prevalent new users, common ADF initiation patterns were: adding an ADF to an IR opioid regimen (43%), an immediate switch from IR opioids to an ADF (15%), and a delayed switch from IR opioids to an ADF (14%). Conclusions: Three-quarters of patients initiating ADFs had prior prescription opioid use and would be excluded in a traditional new user study design. A prevalent new user design would increase sample size and better capture clinically meaningful patients. These findings may apply to studies of other medications where prior exposure is a labeled prerequisite, such as higher dose ER opioids and second-line therapies. Future work will explore prevalent new user designs and consider nuances in ADF initiation such as immediate versus delayed switching by incorporating time-matching to address opioid tolerance

Antiretroviral Adherence Following Prison Release in a Randomized Trial of the imPACT Intervention to Maintain Suppression of HIV Viremia

Many people living with HIV (PLWH) pass through correctional facilities each year, a large proportion of whom do not maintain viral suppression following release. We examined the effects of imPACT, an intervention designed to promote post-release viral suppression, on antiretroviral therapy (ART) adherence. PLWH awaiting release from prisons in two southern states were randomized to imPACT (consisting of motivational interviewing, care linkage coordination, and text message medication reminders) versus standard care (SC). ART adherence, measured by unannounced monthly telephone pill counts, was compared between study arms over 6 months post-release. Of 381 participants eligible for post-release follow-up, 302 (79%) completed ≥ 1 of 6 possible pill counts (median: 4; IQR 1–6). Average adherence over follow-up was 80.3% (95% CI 77.5, 83.1) and 81.0% (78.3, 83.6) of expected doses taken in the imPACT and SC arms, respectively. There was no difference between arms when accounting for missing data using multiple imputation (mean difference = − 0.2 percentage points [− 3.7, 3.3]), controlling for study site and week of follow-up. Of the 936 (40.9%) pill counts that were missed, 212 (22.7%) were due to re-incarceration. Those who missed pill counts for any reason were more likely to be unsuppressed, suggesting that they had lower adherence. However, missingness was balanced between arms. Among PLWH released from prison, ART adherence averaged > 80% in both study arms over 6 months—a level higher than seen with most other chronic diseases. However, missing data may have led to an overestimate of adherence. Factors independent of the intervention influence ART adherence in this population and should be identified to inform future targeted interventions

Patterns of Buprenorphine Initiation Treatment for Opioid Use Disorder and Association with Opioid-related Overdose Deaths

Oral presentation at the 38th International Society for Pharmacoepidemiolog

Association of Opioid Dose Reduction With Opioid Overdose and Opioid Use Disorder Among Patients Receiving High-Dose, Long-term Opioid Therapy in North Carolina

Importance: Rapid reduction or discontinuation of long-term opioid therapy may increase risk of opioid overdose or opioid use disorder (OUD). Current guidelines for chronic pain management caution against rapid dose reduction but are based on limited evidence. Objective: To characterize the association between rapid reduction or abrupt discontinuation of opioid therapy (vs maintained or gradual reduction) and incidence of opioid overdose and OUD among patients prescribed high-dose, long-term opioid therapy (HDLTOT). Design, setting, and participants: This retrospective cohort study was conducted among patients aged 18 to 64 years who were prescribed HDLTOT (≥90 daily morphine milligram equivalents for ≥90% of 90 days) from January 2006 to September 2018, with follow-up up to 4 years after cohort entry. Claims data were drawn from a large private health insurer in North Carolina and analyzed from March 1, 2006, to September 30, 2018. Exposures: Time-varying exposure of rapid dose reduction or discontinuation (>10% dose reduction/week) vs maintenance, increase, or gradual reduction or discontinuation. Main outcomes and measures: The main outcome was incident opioid overdose (fatal or nonfatal) or diagnosed OUD. Inverse probability-weighted cumulative incidence of outcomes were estimated using the cumulative incidence function and hazard ratios (HRs) using marginal structural Fine-Gray models as a function of rapid dose tapering or discontinuation (vs gradual reduction or discontinuation or maintained or increased), accounting for competing risks. Results: A total of 19 443 patients (median [IQR] age, 49 [41-55] years; 10 073 [51.8%] men) who received HDLTOT were identified. Rapid reduction or discontinuation was associated with higher risk of fatal and nonfatal overdoses compared with gradual reduction after the first year (year 1: HR, 1.43; 95% CI, 0.94-2.18; years 2-4: HR, 1.95; 95% CI, 1.31-2.90). There was no association between rapid reduction or discontinuation and diagnosed OUD through 2 years of follow-up; however, the hazard of incident OUD among patients exposed to rapid tapering or discontinuation was greater 25 to 48 months after the start of follow-up (HR, 1.28; 95% CI, 1.01-1.63). Conclusions and relevance: In this cohort study, rapid dose reduction or discontinuation was associated with increased risk of opioid overdose and OUD during long-term follow-up. These findings reinforce prior concerns about safety of rapid dose reductions for patients receiving HDLTOT and highlight the need for caution when reducing opioid doses

Association Between Statewide Opioid Prescribing Interventions and Opioid Prescribing Patterns in North Carolina, 2006-2018

Objective: To examine the impact of three sequential statewide policy and legislative interventions on opioid prescribing practices among privately insured individuals in North Carolina. Methods: An interrupted time series approach was used to examine level and trajectory changes of new and prevalent opioid prescription rates, days' supply, and daily morphine milligram equivalents before and after implementation of a 1) prescription drug monitoring program, 2) state medical board initiative, and 3) legislative action. Analyses were conducted using individual-level claims data from a large private health insurance provider serving North Carolina residents, ages 18-64 years, from January 2006 to August 2018. Results: Rates of new and prevalent prescription opioid patients were relatively unaffected by the prescription monitoring program but sharply declined in the months immediately following both medical board (-3.7 new and -19.3 prevalent patients per 10,000 person months) and legislative (-14.1 new and -26.7 prevalent patients) actions. Among all opioid prescriptions, days' supply steadily increased on average over the study period but declined after legislative action (-1.5 days' supply per year). Conclusions: The voluntary prescription drug monitoring program launched in 2010 only marginally affected opioid prescribing patterns on its own, but its redeployment as an investigative and clinical tool in multifaceted public policy approaches by the state medical board and legislature later in the decade plausibly contributed to notable declines in prescription rates and days' supply. This study lends new emphasis to the importance of enforcement mechanisms for state and national policies seeking to reverse this critical public health crisis

External validation of a machine learning algorithm to distinguish death from disenrollment in claims data

Poster presentation from the 38th International Conference on Pharmacoepidemiology & Therapeutic Risk Managemen

Distinguishing Death from Disenrollment: Applying a Predictive Algorithm to Reduce Bias in Estimating the Risk of Rehospitalization

Background: The inability to identify dates of death in several insurance claims data sources can result in biased estimates when death is a competing event. To address this issue, an algorithm to predict when plan disenrollment is due to death was developed and validated using the MarketScan insurance claims data. Objectives: We illustrate the bias introduced when estimating the risk of rehospitalization within 90-days of acute myocardial infarction (AMI) if death is not accounted for as a competing event. We demonstrate how this validated algorithm can be used to reduce this bias. Methods: We use a 20% sample of Medicare claims (2007–2017) to identify patients with an incident admission for AMI. Patients were required to be 66+ years of age with employer-sponsored supplemental insurance. We compare 3 methods of estimating the risk of 90-day rehospitalization. The first method uses the true death data available in the Medicare enrollment data. We used cumulative incidence functions to estimate the risk of rehospitalization, accounting for death as a competing risk. The second method mimics scenarios where death data are unavailable, and patients are disenrolled from insurance coverage shortly after death. We used Kaplan Meier curves to estimate the risk of rehospitalization, treating death as non-informative censoring at the time of disenrollment. The third method applies the validated predictive algorithm to the Medicare claims where death date has been obscured. We used a predicted probability threshold of 0.99 to distinguish between plan disenrollment and death (sensitivity = 0.92, specificity = 0.90). We estimated the risk of rehospitalization accounting for predicted death as a competing risk. Results: We identified 12 753 patients with an index hospitalization for AMI (mean age = 77.8 years). When accounting for death as a competing risk using validated death dates, the estimated 90-day risk of rehospitalization was 21.6% (20.8%, 22.3%). When mimicking a scenario where death is treated as non-informative censoring at the time of disenrollment, the estimated 90-day risk was 24.8% (23.9%, 25.6%). When using the algorithm to distinguish between death and disenrollment and accounting for predicted death as a competing risk, the estimated 90-day risk was 21.7% (21.0%, 22.4%). Conclusions: When estimating the risk of rehospitalization following AMI in a cohort of Medicare patients, applying a claims-based algorithm to predict death resulted in estimates that closely mirrored the estimates using validated death data. Alternatively, failure to account for death as a competing risk resulted in an estimate that was biased upwards