Comparative Risk of Injury with Concurrent Use of Opioids and Skeletal Muscle Relaxants.

Concurrent use of skeletal muscle relaxants (SMRs) and opioids has been linked to an increased risk of injury. However, it remains unclear whether the injury risks differ by specific SMR when combined with opioids. We conducted nine retrospective cohort studies within a US Medicaid population. Each cohort consisted exclusively of person-time exposed to both an SMR and one of the three most dispensed opioids-hydrocodone, oxycodone, and tramadol. Opioid users were further divided into three cohorts based on the initiation order of SMRs and opioids-synchronically triggered, opioid-triggered, and SMR-triggered. Within each cohort, we used Cox proportional hazard models to compare the injury rates for different SMRs compared to methocarbamol, adjusting for covariates. We identified 349,543, 139,458, and 218,967 concurrent users of SMRs with hydrocodone, oxycodone, and tramadol, respectively. In the oxycodone-SMR-triggered cohort, the adjusted hazard ratios (HRs) were 1.86 (95% CI, 1.23-2.82) for carisoprodol and 1.73 (1.09-2.73) for tizanidine. In the tramadol-synchronically triggered cohort, the adjusted HRs were 0.69 (0.49-0.97) for metaxalone and 0.62 (0.42-0.90) for tizanidine. In the tramadol-SMR-triggered cohort, the adjusted HRs were 1.51 (1.01-2.26) for baclofen and 1.48 (1.03-2.11) for cyclobenzaprine. All other HRs were statistically nonsignificant. In conclusion, the relative injury rate associated with different SMRs used concurrently with the three most dispensed opioids appears to vary depending on the specific opioid and the order of combination initiation. If confirmed by future studies, clinicians should consider the varying injury rates when prescribing SMRs to individuals using hydrocodone, oxycodone, and tramadol.

Comparing Patient-Reported Outcomes Among Anti-TNF Experienced Patients With Ulcerative Colitis Initiating Vedolizumab Versus Tofacitinib.

Background: Primary and secondary nonresponse to anti-tumor necrosis factor (TNF) therapy is common in patients with ulcerative colitis (UC), yet limited research has compared the effectiveness of subsequent biological therapy. Objective: We sought to compare the effectiveness of vedolizumab and tofacitinib in anti-TNF experienced patients with UC, focusing on patient-prioritized patient-reported outcomes (PROs). Methods: We conducted a prospective cohort study nested within the Crohn's & Colitis Foundation's IBD Partners and SPARC IBD initiatives. We identified anti-TNF experienced patients with UC initiating vedolizumab or tofacitinib and analyzed PROs reported approximately 6 months later (minimum 4 months, maximum 10 months). Co-primary outcomes were Patient Reported Outcome Measurement Information System (PROMIS) domains of Fatigue and Pain Interference. Secondary outcomes included PRO2, treatment persistence, and need for colectomy. Results: We compared 72 vedolizumab initiators and 33 tofacitinib initiators. At follow-up, Pain Interference (P = .04), but not Fatigue (P = .53) was lower among tofacitinib initiators. A trend toward higher Social Role Satisfaction was not significant. The remainder of secondary outcomes (PRO2, treatment persistence, colectomy) did not differ between treatment groups. Conclusions: Among anti-TNF experienced patients with UC, Pain Interference 4-10 months after treatment initiation was lower among tofacitinib users as compared with vedolizumab users. Many, but not all, secondary endpoints and subanalyses also favored tofacitinib. Future studies with larger sample sizes are needed to further evaluate these findings.

Antidepressant drug-drug-drug interactions associated with unintentional traumatic injury: Screening for signals in real-world data.

Antidepressants are associated with traumatic injury and are widely used with other medications. It remains unknown how drug-drug-drug interactions (3DIs) between antidepressants and two other drugs may impact potential injury risks associated with antidepressants. We aimed to generate hypotheses regarding antidepressant 3DI signals associated with elevated injury rates. Using 2000-2020 Optum's de-identified Clinformatics Data Mart, we performed a self-controlled case series study for each drug triad consisting of an antidepressant + codispensed drug (base-pair) with a candidate interacting medication (precipitant). We included persons aged greater than or equal to 16 years who (1) experienced an injury and (2) used a candidate precipitant, during base-pair therapy. We compared injury rates during observation time exposed to the drug triad versus the base-pair only, adjusting for time-varying covariates. We calculated adjusted rate ratios (RRs) using conditional Poisson regression and accounted for multiple comparisons via semi-Bayes shrinkage. Among 147,747 eligible antidepressant users with an injury, we studied 120,714 antidepressant triads, of which 334 (0.3%) were positively associated with elevated injury rates and thus considered potential 3DI signals. Adjusted RRs for signals ranged from 1.31 (1.04-1.65) for sertraline + levothyroxine with tramadol (vs. without tramadol) to 6.60 (3.23-13.46) for escitalopram + simvastatin with aripiprazole (vs. without aripiprazole). Nearly half of the signals (137, 41.0%) had adjusted RRs greater than or equal to 2, suggesting strong associations with injury. The identified signals may represent antidepressant 3DIs of potential clinical concern and warrant future etiologic studies to test these hypotheses.

Thromboembolic Events in Users of Warfarin Treated with Different Skeletal Muscle Relaxants.

Background and Objectives: Warfarin and a skeletal muscle relaxant are co-treatments in nearly a quarter-million annual United States (US) office visits. Despite international calls to minimize patient harm arising from anticoagulant drug interactions, scant data exist on clinical outcomes in real-world populations. We examined effects of concomitant use of warfarin and individual muscle relaxants on rates of hospitalization for thromboembolism among economically disadvantaged persons. Materials and Methods: Using 1999−2012 administrative data of four US state Medicaid programs, we conducted 16 retrospective self-controlled case series studies: half included concomitant users of warfarin + one of eight muscle relaxants; half included concomitant users of an inhaled corticosteroid (ICS) + one of eight muscle relaxants. The ICS analyses served as negative control comparisons. In each study, we calculated incidence rate ratios (IRRs) comparing thromboembolism rates in the co-exposed versus warfarin/ICS-only exposed person-time, adjusting for time-varying confounders. Results: Among ~70 million persons, we identified 8693 warfarin-treated subjects who concomitantly used a muscle relaxant, were hospitalized for thromboembolism, and met all other inclusion criteria. Time-varying confounder-adjusted IRRs ranged from 0.31 (95% confidence interval: 0.13−0.77) for metaxalone to 3.44 (95% confidence interval: 1.53−7.78) for tizanidine. The tizanidine finding was robust after quantitatively adjusting for negative control ICS findings, and in numerous prespecified secondary analyses. Conclusions: We identified a potential >3-fold increase in the rate of hospitalized thromboembolism in concomitant users of warfarin + tizanidine vs. warfarin alone. Alternative explanations for this finding include confounding by indication, a native effect of tizanidine, or chance.

Population-based screening to detect benzodiazepine drug-drug-drug interaction signals associated with unintentional traumatic injury.

Drug interactions involving benzodiazepines and related drugs (BZDs) are increasingly recognized as a contributor to increased risk of unintentional traumatic injury. Yet, it remains unknown to what extent drug interaction triads (3DIs) may amplify BZDs' inherent injury risk. We identified BZD 3DI signals associated with increased injury rates by conducting high-throughput pharmacoepidemiologic screening of 2000-2019 Optum's health insurance data. Using self-controlled case series design, we included patients aged ≥ 16 years with an injury while using a BZD + co-dispensed medication (i.e., base pair). During base pair-exposed observation time, we identified other co-dispensed medications as candidate interacting precipitants. Within each patient, we compared injury rates during time exposed to the drug triad versus to the base pair only using conditional Poisson regression, adjusting for time-varying covariates. We calculated rate ratios (RRs) with 95% confidence intervals (CIs) and accounted for multiple estimation via semi-Bayes shrinkage. Among the 65,123 BZD triads examined, 79 (0.1%) were associated with increased injury rates and considered 3DI signals. Adjusted RRs for signals ranged from 3.01 (95% CI = 1.53-5.94) for clonazepam + atorvastatin with cefuroxime to 1.42 (95% CI = 1.00-2.02, p = 0.049) for alprazolam + hydrocodone with tizanidine. These signals may help researchers prioritize future etiologic studies to investigate higher-order BZD interactions.

Evaluation of Spending Differences Between Beneficiaries in Medicare Advantage and the Medicare Shared Savings Program.

Importance: The 2 primary efforts of Medicare to advance value-based care are Medicare Advantage (MA) and the fee-for-service-based Medicare Shared Savings Program (MSSP). It is unknown how spending differs between the 2 programs after accounting for differences in patient clinical risk. Objective: To examine how spending and utilization differ between MA and MSSP beneficiaries after accounting for differences in clinical risk using data from administrative claims and electronic health records. Design, Setting, and Participants: This retrospective economic evaluation used data from 15 763 propensity score-matched beneficiaries who were continuously enrolled in MA or MSSP from January 1, 2014, to December 31, 2018, with diabetes, congestive heart failure (CHF), chronic kidney disease (CKD), or hypertension. Participants received care at a large nonprofit academic health system in the southern United States that bears risk for Medicare beneficiaries through both the MA and MSSP programs. Differences in beneficiary risk were mitigated by propensity score matching using validated clinical criteria based on data from administrative claims and electronic health records. Data were analyzed from January 2019 to May 2022. Exposures: Enrollment in MA or attribution to an accountable care organization in the MSSP program. Main Outcomes and Measures: Per-beneficiary annual total spending and subcomponents, including inpatient hospital, outpatient hospital, skilled nursing facility, emergency department, primary care, and specialist spending. Results: The sample of 15 763 participants included 12 720 (81%) MA and 3043 (19%) MSSP beneficiaries. MA beneficiaries, compared with MSSP beneficiaries, were more likely to be older (median [IQR] age, 75.0 [69.9-81.8] years vs 73.1 [68.3-79.8] years), male (5515 [43%] vs 1119 [37%]), and White (9644 [76%] vs 2046 [69%]) and less likely to live in low-income zip codes (2338 [19%] vs 750 [25%]). The mean unadjusted per-member per-year spending difference between MSSP and MA disease-specific subcohorts was $2159 in diabetes, $4074 in CHF, $2560 in CKD, and $2330 in hypertension. After matching on clinical risk and demographic factors, MSSP spending was higher for patients with diabetes (mean per-member per-year spending difference in 2015: $2454; 95% CI, $1431-$3574), CHF ($3699; 95% CI, $1235-$6523), CKD ($2478; 95% CI, $1172-$3920), and hypertension ($2258; 95% CI, $1616-2,939). Higher MSSP spending among matched beneficiaries was consistent over time. In the matched cohort in 2018, MSSP total spending ranged from 23% (CHF) to 30% (CKD) higher than MA. Adjusting for differential trends in coding intensity did not affect these results. Higher outpatient hospital spending among MSSP beneficiaries contributed most to spending differences between MSSP and MA, representing 49% to 62% of spending differences across disease cohorts. Conclusions and Relevance: In this study, utilization and spending were consistently higher for MSSP than MA beneficiaries within the same health system even after adjusting for granular metrics of clinical risk. Nonclinical factors likely contribute to the large differences in MA vs MSSP spending, which may create challenges for health systems participating in MSSP relative to their participation in MA.

Identifying Clinically Relevant Drug-Drug Interactions With Methadone and Buprenorphine: A Translational Approach to Signal Detection.

Methadone and buprenorphine have pharmacologic properties that are concerning for a high risk of drug-drug interactions (DDIs). We performed high-throughput screening for clinically relevant DDIs with methadone or buprenorphine by combining pharmacoepidemiologic and pharmacokinetic approaches. We conducted pharmacoepidemiologic screening via a series of self-controlled case series studies (SCCS) in Optum claims data from 2000 to 2019. We included persons 18 years or older who experienced an outcome of interest during target drug treatment. Exposures were all overlapping medications (i.e., the candidate precipitants) during target drug treatment. Outcomes were opioid overdose, non-overdose adverse effects, and cardiac arrest. We used conditional Poisson regression to calculate rate ratios, accounting for multiple comparisons with semi-Bayes shrinkage. We explored the impact of key study design choices in analyses that varied the exposure definitions of the target drugs and the candidate precipitant drugs. Pharmacokinetic screening was conducted by incorporating published data on CYP enzyme metabolism into an equation-based static model. In SCCS analysis, 1,432 events were included from 248,069 new users of methadone or buprenorphine. In the primary analysis, statistically significant DDIs included gabapentinoids with either methadone or buprenorphine; baclofen with methadone; and benzodiazepines with methadone. In sensitivity analysis, additional statistically significant DDIs included methocarbamol, quetiapine, or simvastatin with methadone. Pharmacokinetic screening identified two moderate-to-strong potential DDIs (clonidine and fluconazole with buprenorphine). The combination of clonidine and buprenorphine was also associated with a significantly increased risk of opioid overdose in pharmacoepidemiologic screening. These DDI signals may be the most important targets for future confirmation studies.

Skeletal muscle relaxant drug-drug-drug interactions and unintentional traumatic injury: Screening to detect three-way drug interaction signals.

AIM: The aim of this study was to identify skeletal muscle relaxant (SMR) drug-drug-drug interaction (3DI) signals associated with increased rates of unintentional traumatic injury. METHODS: We conducted automated high-throughput pharmacoepidemiologic screening of 2000-2019 healthcare data for members of United States commercial and Medicare Advantage health plans. We performed a self-controlled case series study for each drug triad consisting of an SMR base-pair (i.e., concomitant use of an SMR with another medication), and a co-dispensed medication (i.e., candidate interacting precipitant) taken during ongoing use of the base-pair. We included patients aged ≥16 years with an injury occurring during base-pair-exposed observation time. We used conditional Poisson regression to calculate adjusted rate ratios (RRs) with 95% confidence intervals (CIs) for injury with each SMR base-pair + candidate interacting precipitant (i.e., triad) versus the SMR-containing base-pair alone. RESULTS: Among 58 478 triads, 29 were significantly positively associated with injury; confounder-adjusted RRs ranged from 1.39 (95% CI = 1.01-1.91) for tizanidine + omeprazole with gabapentin to 2.23 (95% CI = 1.02-4.87) for tizanidine + diclofenac with alprazolam. Most identified 3DI signals are new and have not been formally investigated. CONCLUSION: We identified 29 SMR 3DI signals associated with increased rates of injury. Future aetiologic studies should confirm or refute these SMR 3DI signals.

Opioid Drug-Drug-Drug Interactions and Unintentional Traumatic Injury: Screening to Detect Three-Way Drug Interaction Signals.

Growing evidence suggests that drug interactions may be responsible for much of the known association between opioid use and unintentional traumatic injury. While prior research has focused on pairwise drug interactions, the role of higher-order (i.e., drug-drug-drug) interactions (3DIs) has not been examined. We aimed to identify signals of opioid 3DIs with commonly co-dispensed medications leading to unintentional traumatic injury, using semi-automated high-throughput screening of US commercial health insurance data. We conducted bi-directional, self-controlled case series studies using 2000-2015 Optum Data Mart database. Rates of unintentional traumatic injury were examined in individuals dispensed opioid-precipitant base pairs during time exposed vs unexposed to a candidate interacting precipitant. Underlying cohorts consisted of 16-90-year-olds with new use of opioid-precipitant base pairs and ≥1 injury during observation periods. We used conditional Poisson regression to estimate rate ratios adjusted for time-varying confounders, and semi-Bayes shrinkage to address multiple estimation. For hydrocodone, tramadol, and oxycodone (the most commonly used opioids), we examined 16,024, 8185, and 9330 drug triplets, respectively. Among these, 75 (0.5%; hydrocodone), 57 (0.7%; tramadol), and 42 (0.5%; oxycodone) were significantly positively associated with unintentional traumatic injury (50 unique base precipitants, 34 unique candidate precipitants) and therefore deemed potential 3DI signals. The signals found in this study provide valuable foundations for future research into opioid 3DIs, generating hypotheses to motivate crucially needed etiologic investigations. Further, this study applies a novel approach for 3DI signal detection using pharmacoepidemiologic screening of health insurance data, which could have broad applicability across drug classes and databases.

Population-based signals of benzodiazepine drug interactions associated with unintentional traumatic injury.

Benzodiazepine receptor agonists and related medications, such as Z-drugs and dual orexin receptor antagonists (BZDs), have been associated with unintentional traumatic injury due to their central nervous system (CNS)-depressant effects. Drug-drug interactions (DDIs) may contribute to the known relationship between BZD use and unintentional traumatic injury, yet evidence is still lacking. We conducted high-throughput pharmacoepidemiologic screening using the self-controlled case series design in a large US commercial health insurance database to identify potentially clinically relevant DDI signals among new users of BZDs. We used conditional Poisson regression to estimate rate ratios (RRs) between each co-exposure (vs. not) and unintentional traumatic injury (primary outcome), typical hip fracture (secondary outcome), and motor vehicle crash (secondary outcome). We identified 48 potential DDI signals (1.1%, involving 39 unique co-dispensed drugs), i.e., with statistically significant elevated adjusted RRs for injury. Signals were strongest for DDI pairs involving zolpidem, lorazepam, temazepam, alprazolam, eszopiclone, triazolam, and clonazepam. We also identified four potential DDI signals for typical hip fracture, but none for motor vehicle crash. Many signals have biologically plausible explanations through additive or synergistic pharmacodynamic effects of co-dispensed antidepressants, opioids, or muscle relaxants on CNS depression, impaired psychomotor and cognitive function, and/or somnolence. While other signals that lack an obvious mechanism may represent true associations that place patients at risk of injury, it is also prudent to consider the roles of chance, reverse causation, and/or confounding by indication, which merit further exploration. Given the high-throughput nature of our investigation, findings should be interpreted as hypothesis generating.

Intensity of end-of-life care for gynecologic cancer patients by primary oncologist specialty.

OBJECTIVE: The association of primary oncologist specialty, medical oncology versus gynecologic oncology, on intensity of care at the end of life in elderly patients with gynecologic cancer is unclear. METHODS: This retrospective cohort study used Surveillance, Epidemiology and End Results-Medicare (SEER-M) data. Subjects were fee-for-service Medicare enrollees aged 65 years and older who died of a gynecologic cancer between January 2006 and December 2015. The primary outcome was a composite score for high-intensity care received in the last month of life. Secondary outcomes included invasive procedures and Medicare spending in the last month of life. Simple and multivariable linear and logistic regression analyses evaluated differences in outcomes by primary oncologist specialty. Linear regressions were repeated after creating a more similar control group through nearest-neighbor propensity score matching. RESULTS: Of 12 189 patients, 7705 (63%) had a medical primary oncologist in the last year of life. In adjusted analyses, patients with a gynecologic versus medical primary oncologist received lower rates of high-intensity end-of-life care (53.9% vs 56.6%; p=0.018). Results were similar for the propensity score-matched cohorts. However, having a gynecologic versus medical primary oncologist was associated with higher rates of invasive procedures in the last month of life (43% vs 41%; p=0.014) and higher Medicare spending ($83 859 vs $74 849; p=0.004). CONCLUSIONS: Both specialties engage in overall high levels of intense end-of-life care, with differences by specialty in aspects of aggressive care and spending at the end of life. Physician-level training could be a target for educational or quality improvement initiatives to improve end-of-life cancer care delivery.

Signals of Muscle Relaxant Drug Interactions Associated with Unintentional Traumatic Injury: A Population-Based Screening Study.

BACKGROUND: Use of muscle relaxants is rapidly increasing in the USA. Little is understood about the role of drug interactions in the known association between muscle relaxants and unintentional traumatic injury, a clinically important endpoint causing substantial morbidity, disability, and death. OBJECTIVE: We examined potential associations between concomitant drugs (i.e., precipitants) taken with muscle relaxants (affected drugs, i.e., objects) and hospital presentation for unintentional traumatic injury. METHODS: In a series of self-controlled case series studies, we screened to identify drug interaction signals for muscle relaxant + precipitant pairs and unintentional traumatic injury. We used Optum's de-identified Clinformatics® Data Mart Database, 2000-2019. We included new users of a muscle relaxant, aged 16-90 years, who were dispensed at least one precipitant drug and experienced an unintentional traumatic injury during the observation period. We classified each observation day as precipitant exposed or precipitant unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to estimate rate ratios adjusting for time-varying confounders and then accounted for multiple estimation via semi-Bayes shrinkage. RESULTS: We identified 74,657 people who initiated muscle relaxants and experienced an unintentional traumatic injury, in whom we studied concomitant use of 2543 muscle relaxant + precipitant pairs. After adjusting for time-varying confounders, 16 (0.6%) pairs were statistically significantly and positively associated with injury, and therefore deemed signals of a potential drug interaction. Among signals, semi-Bayes shrunk, confounder-adjusted rate ratios ranged from 1.29 (95% confidence interval 1.04-1.62) for baclofen + sertraline to 2.28 (95% confidence interval 1.14-4.55) for methocarbamol + lamotrigine. CONCLUSIONS: Using real-world data, we identified several new signals of potential muscle relaxant drug interactions associated with unintentional traumatic injury. Only one among 16 signals is currently reported in a major drug interaction knowledge base. Future studies should seek to confirm or refute these signals.

Comparative Safety of Dipeptidyl Peptidase-4 Inhibitors and Sudden Cardiac Arrest and Ventricular Arrhythmia: Population-Based Cohort Studies.

In vivo studies suggest that arrhythmia risk may be greater with less selective dipeptidyl peptidase-4 inhibitors, but evidence from population-based studies is missing. We aimed to compare saxagliptin, sitagliptin, and linagliptin with regard to risk of sudden cardiac arrest (SCA)/ventricular arrhythmia (VA). We conducted high-dimensional propensity score (hdPS) matched, new-user cohort studies. We analyzed Medicaid and Optum Clinformatics separately. We identified new users of saxagliptin, sitagliptin (both databases), and linagliptin (Optum only). We defined SCA/VA outcomes using emergency department and inpatient diagnoses. We identified and then controlled for confounders via a data-adaptive, hdPS approach. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression using a robust variance estimator while adjusting for calendar year. We identified the following matched comparisons: saxagliptin vs. sitagliptin (23,895 vs. 96,972) in Medicaid, saxagliptin vs. sitagliptin (48,388 vs. 117,383) in Optum, and linagliptin vs. sitagliptin (36,820 vs. 78,701) in Optum. In Medicaid, use of saxagliptin (vs. sitagliptin) was associated with an increased rate of SCA/VA (adjusted HR (aHR), 2.01, 95% confidence interval (CI) 1.24-3.25). However, in Optum data, this finding was not present (aHR, 0.79, 95% CI 0.41-1.51). Further, we found no association between linagliptin (vs. sitagliptin) and SCA/VA (aHR, 0.65, 95% CI 0.36-1.17). We found discordant results regarding the association between SCA/VA with saxagliptin compared with sitagliptin in two independent datasets. It remains unclear whether these findings are due to heterogeneity of treatment effect in the different populations, chance, or unmeasured confounding.

Angiotensin-Converting Enzyme Inhibitors Used Concomitantly with Insulin Secretagogues and the Risk of Serious Hypoglycemia.

Serious hypoglycemia is a major adverse event associated with insulin secretagogues. Previous studies have suggested a potential relationship between angiotensin-converting enzyme inhibitors (ACEIs) used with sulfonylureas and serious hypoglycemia, and widely used drug compendia warn of this potential drug-drug interaction. We investigated the association between serious hypoglycemia and concomitant use of ACEIs in patients receiving insulin secretagogues, using the self-controlled case series design and Medicaid claims data from 5 US states linked to Medicare claims from 1999-2011. The exposure of interest was active prescription for ACEIs during insulin secretagogue or metformin (negative control object drug) episodes. The outcome was hospital presentation for serious hypoglycemia, identified by discharge diagnosis codes in inpatient and emergency department claims (positive predictive value ~ 78-89%). We calculated confounder-adjusted rate ratios (RRs) and 95% confidence internals (CIs) of outcome occurrence during ACEI-exposed vs. ACEI-unexposed time using conditional Poisson regression. The RRs for ACEIs were not statistically elevated during observation time of glipizide (RR, 1.06; CI, 0.98-1.15), glyburide (RR, 1.05; CI, 0.96-1.15), repaglinide (RR, 1.15; CI, 0.94-1.41), or metformin (RR, 1.02; CI, 0.97-1.06); but was modestly elevated with glimepiride (RR, 1.23; CI, 1.11-1.37) and modestly reduced with nateglinide (RR, 0.73; CI, 0.56-0.96). The overall pattern of results do not suggest that ACEIs used with insulin secretagogues were associated with increased rates of serious hypoglycemia, with the possible exception of glimepiride.

Long-term Outcomes Following Multiply Recurrent Clostridioides difficile Infection and Fecal Microbiota Transplantation.

BACKGROUND AND AIMS: Fecal microbiota transplantation (FMT) is a commonly used therapy for multiply recurrent Clostridioides difficile (mrCDI). By altering the gut microbiota, there is the potential for FMT to impact the risk for cardiometabolic, intestinal or immune-mediated conditions. Likewise, the microbiota disturbance associated with mrCDI could potentially lead to these conditions. We aimed to assess the associations of mrCDI and FMT with cardiometabolic, immune-mediated diseases, and irritable bowel syndrome. METHODS: This retrospective cohort study using a United States commercial claims database included persons diagnosed with CDI or undergoing FMT. We created 2 pairwise comparisons: mrCDI vs non-mrCDI, and non-mrCDI or mrCDI treated with FMT vs mrCDI without FMT. RESULTS: We found no significant association between mrCDI (vs non-mrCDI) and inflammatory bowel disease (adjusted hazard ratio (aHR) = 1.65; 95% confidence interval, 0.67-4.04), rheumatoid arthritis (HR = 0.86; 0.47-1.56), psoriasis (HR = 0.72; 0.23-2.27), diabetes (aHR = 0.97; 0.67-1.40), hypertension (aHR = 1.05; 0.76-1.44), myocardial infarction (aHR = 0.82; 0.63-1.06), stroke (aHR = 0.83; 0.62-1.12), or irritable bowel syndrome (HR = 0.94; 0.61-1.45). Similarly, we found no association of CDI with FMT (vs mrCDI without FMT) and diabetes (aHR = 0.92; 0.27-3.11), hypertension (aHR = 1.41; 0.64-3.15), stroke (aHR = 1.27; 0.69-2.34) or inflammatory bowel syndrome (aHR = 0.80; 0.26-2.46). However, the incidence of myocardial infarction was increased following FMT (aHR = 1.68; 1.01-2.81). CONCLUSION: Relative to those with CDI, persons with mrCDI do not appear to be intrinsically at higher risk of cardiometabolic, immune-mediated diseases, or irritable bowel syndrome. However, those who underwent FMT for CDI had a higher incidence of myocardial infarction. Future studies should assess this association to assess reproducibility.

Association of gynecologic oncology versus medical oncology specialty with survival, utilization, and spending for treatment of gynecologic cancers.

BACKGROUND: We examined the association of gynecologic oncology (GYO) versus medical oncology (MEDONC) based care with survival, health care utilization and spending outcomes in women undergoing chemotherapy for advanced gynecologic cancers. METHODS: Women with newly diagnosed stage III-IV uterine, ovarian, and cervical cancers from 2000 to 2015 were identified in SEER-Medicare. We assessed the association of provider specialty with overall survival, emergency department utilization, admissions, and spending. Outcomes were assessed using unadjusted and Inverse Treatment Probability Weighted propensity-score applied, multi-variable cox modeling, Poisson regression, and generalized models of log-transformed data. RESULTS: We identified 7930 gynecologic cancer patients (4360 ovarian, 2934 uterine, 643 cervix). 37% were treated by GYO and 63% by MEDONC. For ovarian patients, GYO care was associated with improved OS (median OS 3.3 v. 2.9 years; HR 0.85, 95%CI 0.80, 0.91, p < .0001) and similar mean spending per month ($4015 v. $4316, mean ratio 0.97 (95% CI 0.93, 1.02), p = .19), compared to MEDONC in adjusted analyses. For uterine patients, GYO care was associated with similar OS, but decreased spending ($3573 v. $4081, mean ratio 0.87 (95% CI.81, 0.93), p < .0001), and decreased ED utilization (RR 0.76, 95% CI 0.69, 0.85, p < .0001). For cervical patients, GYO care was associated with similar OS, and similar spending. Admissions were more likely in ovarian (RR 1.23, 95%CI 1.11, 1.37, p = .0001) and cervical patients (RR 1.26, 95% CI 1.05, 1.51, p = .015) treated by GYO, in adjusted analyses. CONCLUSIONS: GYO based care was associated with improved OS and equal spending for patients with advanced stage ovarian cancer. Uterine and cervix patients had similar OS, and less or equal spending respectively, when treated by GYO compared to MEDONC.

Evaluation of serious bleeding signals during concomitant use of clopidogrel and hypnotic drugs.

BACKGROUND: In a previous drug-drug interaction (DDI) screening study intended to generate hypotheses, clopidogrel + either eszopiclone or zolpidem (vs. clopidogrel alone) were associated with serious bleeding. OBJECTIVES: To confirm or refute these DDI signals and examine associations with other hypnotics in an independent population of United States Medicaid beneficiaries METHODS: We employed a bi-directional self-controlled case series design in eligible individuals concomitantly exposed to one of 12 hypnotics (precipitants, exposures of interest) plus either clopidogrel (the object drug) or pravastatin (the negative control object drug). The outcome was hospital presentation with serious bleeding. Using conditional Poisson regression, we calculated confounder-adjusted rate ratios (RRs) and 95% confidence intervals for serious bleeding during clopidogrel + precipitant use (vs. clopidogrel alone). To distinguish a DDI from a precipitant's inherent effect on bleeding, we divided effect measures by the adjusted RR for the corresponding pravastatin + precipitant pair to obtain ratios of RR (RRRs). RESULTS: Among 23,194 users of clopidogrel and 3824 of pravastatin who experienced serious bleeding during an active prescription for one of these agents, confounder-adjusted RRRs for serious bleeding were 6.63 (0.39-113.01) and 0.77 (0.53-1.11) with eszopiclone and zolpidem, respectively, whereas confounder-adjusted RRRs for other hypnotics ranged from 0.18 (0.04-0.85) for triazolam to 1.79 (0.16-20.44) for zaleplon. Statistical imprecision therefore precluded us from confirming or refuting these prior signals with eszopiclone and zolpidem. CONCLUSIONS: While we could not confirm or refute previously identified DDI signals, numerically elevated RRRs for serious bleeding with several clopidogrel + hypnotic pairs warrant further examination.

Population-Based Signals of Antidepressant Drug Interactions Associated With Unintentional Traumatic Injury.

Antidepressants are very widely used and associated with traumatic injury, yet little is known about their potential for harmful drug interactions. We aimed to identify potential drug interaction signals by assessing concomitant medications (precipitant drugs) taken with individual antidepressants (object drugs) that were associated with unintentional traumatic injury. We conducted pharmacoepidemiologic screening of 2000-2015 Optum Clinformatics data, identifying drug interaction signals by performing self-controlled case series studies for antidepressant + precipitant pairs and injury. We included persons aged 16-90 years codispensed an antidepressant and ≥ 1 precipitant drug(s), with an injury during antidepressant therapy. We classified antidepressant person-days as either precipitant-exposed or precipitant-unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to calculate confounder adjusted rate ratios (RRs) and accounted for multiple estimation via semi-Bayes shrinkage. We identified 330,884 new users of antidepressants who experienced an injury. Among such persons, we studied concomitant use of 7,953 antidepressant + precipitant pairs. Two hundred fifty-six (3.2%) pairs were positively associated with injury and deemed potential drug interaction signals; 22 of these signals had adjusted RRs > 2.00. Adjusted RRs ranged from 1.06 (95% confidence interval: 1.00-1.12, P = 0.04) for citalopram + gabapentin to 3.06 (1.42-6.60) for nefazodone + levonorgestrel. Sixty-five (25.4%) signals are currently reported in a seminal drug interaction knowledgebase. We identified numerous new population-based signals of antidepressant drug interactions associated with unintentional traumatic injury. Future studies, intended to test hypotheses, should confirm or refute these potential interactions.