Increasing availability of electronic health databases capturing real-world experiences with medical products has garnered much interest in their use for pharmacoepidemiologic and pharmacovigilance studies. The traditional practice of having numerous groups use single databases to accomplish similar tasks and address common questions about medical products can be made more efficient through well-coordinated multi-database studies, greatly facilitated through distributed data network (DDN) architectures. Access to larger amounts of electronic health data within DDNs has created a growing interest in using data-adaptive machine learning (ML) techniques that can automatically model complex associations in high-dimensional data with minimal human guidance. However, the siloed storage and diverse nature of the databases in DDNs create unique challenges for using ML. In this paper, we discuss opportunities, challenges, and considerations for applying ML in DDNs for pharmacoepidemiologic and pharmacovigilance studies. We first discuss major types of activities performed by DDNs and how ML may be used. Next, we discuss practical data-related factors influencing how DDNs work in practice. We then combine these discussions and jointly consider how opportunities for ML are affected by practical data-related factors for DDNs, leading to several challenges. We present different approaches for addressing these challenges and highlight efforts that real-world DDNs have taken or are currently taking to help mitigate them. Despite these challenges, the time is ripe for the emerging interest to use ML in DDNs, and the utility of these data-adaptive modeling techniques in pharmacoepidemiologic and pharmacovigilance studies will likely continue to increase in the coming years.
OBJECTIVE: While infliximab combined to thiopurines is more effective than infliximab monotherapy in patients with Crohn's disease (CD) and UC, the impact of adding thiopurines to vedolizumab remains controversial. We emulated two target trials comparing the effectiveness of combination therapy versus vedolizumab monotherapy in CD and UC.
DESIGN: Based on two US and the French nationwide healthcare databases, patients with CD and UC who initiated vedolizumab were identified. The study methodology, including confounding adjustment and outcome definitions, were previously validated in successful emulations of the SONIC and SUCCESS trials. Risk ratios for treatment failure based on hospitalisation or surgery related to disease activity, treatment switch, or prolonged corticosteroids use, were estimated after 1:1 propensity score (PS) matching.
RESULTS: Among a total of 10 299 vedolizumab users, 804 CD and 1088 UC pairs of combination therapy versus vedolizumab monotherapy users were PS matched. Treatment failure occurred at week 26 in 236 (29.3%) and 376 (34.3%) patients with CD and at week 16 in 236 (21.7%) and 263 (24.2%) patients with UC initiating combination therapy and vedolizumab monotherapy, respectively. The risk of treatment failure was decreased with combination therapy compared with vedolizumab monotherapy in CD (RR 0.85, 95% CI: 0.74 to 0.98) and to a lesser extent in UC (RR 0.90, 95% CI: 0.77 to 1.05). Findings were consistent across databases.
CONCLUSION: Using validated methodologies, combination therapy with vedolizumab and thiopurines was associated with lower treatment failure compared with vedolizumab monotherapy in CD but not UC across the USA and France.
OBJECTIVES: To characterise the incidence rate of skin cancer associated with methotrexate and hydroxychloroquine in older adults with rheumatoid arthritis (RA).
METHODS: RA patients aged ≥65 years who initiated methotrexate or hydroxychloroquine as their first disease modifying antirheumatic drugs (DMARDs). The primary outcome was new occurrence of any skin cancer (i.e. malignant melanoma or non-melanoma skin cancer; NMSC) based on validated algorithms (positive predictive value >83%). Secondary outcomes were malignant melanoma, NMSC, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). We estimated the incidence rates (IRs) and hazard ratios (HRs) for each outcome in the 1:1 propensity score (PS)-matched methotrexate and hydroxychloroquine groups.
RESULTS: We included 24,577 PS-matched pairs of methotrexate and hydroxychloroquine initiators. Compared with hydroxychloroquine (IR 25.20/1,000 person-years), methotrexate initiators (IR 26.21/1,000 person-years) had a similar risk of any skin cancer [HR 1.03 -(95%CI 0.92, 1.14)] over a mean follow-up of 388 days. The HR (95%CI) associated with methotrexate was 1.39 (0.87, 2.21) for malignant melanoma, 1.01(0.90, 1.12) for NMSC, 1.37 (1.13, 1.66) for BCC, and 0.79 (0.63, 0.99) for SCC compared with hydroxychloroquine.
CONCLUSIONS: In this large cohort of older RA patients initiating methotrexate or hydroxychloroquine as their first DMARD, we found no difference in the risk of skin cancer including malignant melanoma and NMSC. However, for specific components of NMSC, methotrexate initiators had higher risk of BCC but lower risk of SCC compared with hydroxychloroquine initiators.
Little is known about the impact of dose, duration, and timing of prenatal prescription opioid exposure on the risk of neonatal opioid withdrawal syndrome (NOWS). Using a cohort of 18,869 prepregnancy chronic opioid users nested within the 2000-2014 Medicaid Analytic eXtract, we assessed average opioid dosage within biweekly gestational age intervals, created group-based trajectory models, and evaluated the association between trajectory groups and NOWS risk. Women were grouped into 6 distinct opioid use trajectories which, based on observed patterns, were categorized as 1) continuous very low-dose use, 2) continuous low-dose use, 3) initial moderate-dose use with a gradual decrease to very low-dose/no use, 4) initial high-dose use with a gradual decrease to very low-dose use, 5) continuous moderate-dose use, and 6) continuous high-dose use. Absolute risk of NOWS per 1,000 infants was 7.7 for group 1 (reference group), 28.8 for group 2 (relative risk (RR) = 3.7, 95% confidence interval (CI): 2.8, 5.0), 16.5 for group 3 (RR = 2.1, 95% CI: 1.5, 3.1), 64.9 for group 4 (RR = 8.4, 95% CI: 5.6, 12.6), 77.3 for group 5 (RR = 10.0, 95% CI: 7.5, 13.5), and 172.4 for group 6 (RR = 22.4, 95% CI: 16.1, 31.2). Trajectory models-which capture information on dose, duration, and timing of exposure-are useful for gaining insight into clinically relevant groupings to evaluate the risk of prenatal opioid exposure.
OBJECTIVES: Recent results from 'ORAL Surveillance' trial have raised concerns regarding the cardiovascular safety of tofacitinib in patients with rheumatoid arthritis (RA). We further examined this safety concern in the real-world setting.
METHODS: We created two cohorts of patients with RA initiating treatment with tofacitinib or tumour necrosis factor inhibitors (TNFI) using deidentified data from Optum Clinformatics (2012-2020), IBM MarketScan (2012-2018) and Medicare (parts A, B and D, 2012-2017) claims databases: (1) A 'real-world evidence (RWE) cohort' consisting of routine care patients and (2) A 'randomised controlled trial (RCT)-duplicate cohort' mimicking inclusion and exclusion criteria of the ORAL surveillance trial to calibrate results against the trial findings. Cox proportional hazards models with propensity score fine stratification weighting were used to estimate HR and 95% CIs for composite outcome of myocardial infarction and stroke and accounting for 76 potential confounders. Database-specific effect estimates were pooled using fixed effects models with inverse-variance weighting.
RESULTS: In the RWE cohort, 102 263 patients were identified of whom 12 852 (12.6%) initiated tofacitinib. The pooled weighted HR (95% CI) comparing tofacitinib with TNFI was 1.01 (0.83 to 1.23) in RWE cohort and 1.24 (0.90 to 1.69) in RCT-duplicate cohort which aligned closely with ORAL-surveillance results (HR: 1.33, 95% CI 0.91 to 1.94).
CONCLUSIONS: We did not find evidence for an increased risk of cardiovascular outcomes with tofacitinib in patients with RA treated in the real-world setting; however, tofacitinib was associated with an increased risk of cardiovascular outcomes, although statistically non-significant, in patients with RA with cardiovascular risk factors.
TRIAL REGISTRATION NUMBER: NCT04772248.
Real-world evidence (RWE) on the effectiveness of treatments in Crohn's disease (CD) derived from clinical practice data will help fill many evidence gaps left by randomized controlled trials (RCTs). Emulating RCTs with healthcare database studies may calibrate RWE studies in CD. We aimed to emulate the SONIC trial on the effectiveness of infliximab in patients with CD using US and French healthcare claims data. SONIC had shown improved remission with combination therapy (i.e., infliximab plus thiopurines) compared with infliximab monotherapy. Using claims data (2004-2019) from commercially insured patients in the United States (IBM MarketScan and Optum) and France (Système National des Données de Santé (National Healthcare Data System) (SNDS)), we conducted a cohort study of patients with CD who initiated combination therapy and compared them with patients who initiated infliximab alone. The primary outcome was a composite end point of treatment failure including hospitalization or surgery related to CD, treatment switch, or continuation of corticosteroids 26 weeks after infliximab initiation. Risk ratios (RRs) with 95% confidence intervals (CIs) were estimated in propensity score (PS)-matched cohorts. We identified 1,437 PS-matched pairs of combination therapy vs. infliximab monotherapy users. As in SONIC, the risk of treatment failure was decreased with combination therapy in the overall cohort (RR, 0.71; 95% CI, 0.62-0.82; RR, 0.78; 95% CI, 0.62-0.97 in SONIC). Findings were consistent across MarketScan, Optum, and SNDS databases: RR (95% CI), 0.83 (0.63-1.10), 0.66 (0.46-0.93), and 0.68 (0.57-0.82), as well as component end points. These robust findings highlight opportunities in RWE analysis for studying treatment effectiveness in patients with CD in clinical practice.
BACKGROUND: New bone-directed therapies, including denosumab, abaloparatide, and romosozumab, emerged during the past decade, and recent trends in use of these therapies are unknown.
OBJECTIVE: To examine temporal trends in bone-directed therapies.
DESIGN: An open cohort study in a US commercial insurance database, January 2009 to March 2020.
PARTICIPANTS/INTERVENTIONS: All-users of bone-directed therapies age >50 years, users with osteoporosis, users with malignancies, and patients with recent (within 180 days) fractures at key osteoporotic sites.
MAIN MEASURES: The percentage of each cohort with prescription dispensing or medication administration claims for each bone-directed therapy during each quarter of the study period.
KEY RESULTS: We analyzed 15.48 million prescription dispensings or medication administration claims from 1.46 million unique individuals (89% women, mean age 69 years). Among all users of bone-directed therapies, alendronate, and zoledronic acid use increased modestly (49 to 63% and 2 to 4%, respectively, during the study period). In contrast, denosumab use increased rapidly after approval in 2010, overtaking use of all other medications except alendronate by 2017 and reaching 16% of users by March 2020. Similar trends were seen in cohorts of osteoporosis, malignancy, and recent fractures. Importantly, use of any bone-directed therapy after fractures was low and declined from 15 to 8%.
CONCLUSIONS: Rates of denosumab use outpaced growth of all other bone-directed therapies over the past decade. Treatment rates after osteoporotic fractures were low and declined over time, highlighting major failings in osteoporosis treatment in the US.
BACKGROUND & AIMS: The risk of serious infections associated with vedolizumab in patients with inflammatory bowel disease (IBD) is uncertain. We assessed the risk of serious infections associated with use of vedolizumab versus anti-TNF in patients with IBD, according to IBD subtype and previous exposure to anti-TNF.
METHODS: Based on two U.S. nationwide commercial insurance databases and the French nationwide health insurance database, anti-TNF naïve and experienced patients diagnosed with Crohn's disease (CD) and ulcerative colitis (UC) aged 18 years or older who initiated vedolizumab or an anti-TNF agent after 2010 were identified. Hazard ratios for serious infections comparing vedolizumab and anti-TNF were estimated in propensity score matched cohorts.
RESULTS: Among 8768 vedolizumab and 26,656 anti-TNF initiators included after 1:4 variable ratio propensity score matching, 893 serious infections occurred during 37,725 person-years of follow-up. The risk of serious infections was not different between vedolizumab and anti-TNF in the overall IBD cohort (HR, 0.95; 95% CI, 0·79-1.13), while the risk was decreased for vedolizumab users in patients with UC (HR, 0.68; 95% CI, 0.50-0.93), but not CD (HR, 1.10; 95% CI, 0.87-1.38). In patients with UC, vedolizumab was consistently associated with lower risk of serious infections after exclusion of gastrointestinal infections (HR, 0.59; 95% CI, 0.39-0.90).
CONCLUSIONS: While the risk of serious infections associated with vedolizumab was not different compared to anti-TNF in the overall group of patients with IBD, the risk varied according to IBD subtype, by decreasing in patients with UC, but not CD. These findings may help to clarify the optimal position of vedolizumab in the therapeutic management of IBD.
INTRODUCTION: The medication burden of patients with end-stage renal disease (ESRD) on hemodialysis, a patient population with a high comorbidity burden and complex care requirements, is among the highest of any of the chronic diseases. The goal of this study was to describe the medication burden and prescribing patterns in a contemporary cohort of patients with ESRD on hemodialysis in the USA.
METHODS: We used the United States Renal Data System database from January 1, 2013, and December 31, 2017, to quantify the medication burden of patients with ESRD on hemodialysis aged ≥18 years. We calculated the average number of prescription medications per patient during each respective year (January-December), number of medications within classes, including potentially harmful medications, and trends in the number of medications and classes over the 5-year study period.
RESULTS: We included a total of 163,228 to 176,133 patients from 2013 to 2017. The overall medication burden decreased slightly, from a mean of 7.4 (SD 3.8) medications in 2013 to 6.8 (SD 3.6) medications in 2017. Prescribing of potentially harmful medications decreased over time (74.0% with at least one harmful medication class in 2013-68.5% in 2017). In particular, the prescribing of non-benzodiazepine hypnotics, benzodiazepines, and opioids decreased from 2013 to 2017 (12.2%-6.3%, 23.4%-19.3%, and 60.0%-53.4%, respectively). This trend was consistent across subgroups of age, sex, race, and low-income subsidy status.
CONCLUSIONS: Patients with ESRD on hemodialysis continued to have a high overall medication burden, with a slight reduction over time accompanied by a decrease in prescribing of several classes of harmful medications. Continued emphasis on assessment of appropriateness of high medication burden in patients with ESRD is needed to avoid exposure to potentially harmful or futile medications in this patient population.
OBJECTIVE: To evaluate the risk of first trimester exposure to prescription opioids for major congenital malformations, previously reported to be associated with such exposure.
DESIGN: Population based cohort study.
SETTING: Nationwide sample of publicly and commercially insured pregnant women linked to their liveborn infants, nested in the Medicaid Analytic eXtract (MAX, 2000-14) and the MarketScan Research Database (MarketScan, 2003-15).
PARTICIPANTS: 1 602 580 publicly insured (MAX) and 1 177 676 commercially insured (MarketScan) pregnant women with eligibility from at least three months before pregnancy to one month after delivery; infants with eligibility for at least three months after birth.
INTERVENTIONS: Use of prescription opioids was ascertained by requiring two or more dispensations of any opioid during the first trimester.
MAIN OUTCOMES MEASURES: Major malformations overall, cardiac malformations overall, ventricular septal defect, secundum atrial septal defect/patent foramen ovale, neural tube defect, clubfoot, and oral cleft, defined based on validated algorithms. Propensity score stratification was used to adjust for potential confounders and/or proxies for confounders. Estimates from each database were combined using meta-analysis.
RESULTS: 70 447 (4.4%) of 1 602 580 publicly insured and 12 454 (1.1%) of 1 177 676 commercially insured pregnant women had two or more dispensations of an opioid during the first trimester. Absolute risk of malformations overall was 41.0 (95% confidence interval 39.5 to 42.5) per 1000 pregnancies exposed to opioids versus 32.0 (31.7 to 32.3) per 1000 unexposed pregnancies in the MAX cohort, and 42.6 (39.0 to 46.1) and 37.3 (37.0 to 37.7) per 1000, respectively, in the MarketScan cohort. Pooled unadjusted relative risk estimates were raised for all outcomes but shifted substantially toward the null after adjustment; for malformations overall (relative risk 1.06, 95% confidence interval 1.02 to 1.10), cardiovascular malformations (1.09, 1.00 to 1.18), ventricular septal defect (1.07, 0.95 to 1.21), atrial septal defect/patent foramen ovale (1.04, 0.88 to 1.24), neural tube defect (0.82, 0.53 to 1.27), and clubfoot (1.06, 0.88 to 1.28). The relative risk for oral clefts remained raised after adjustment (1.21, 0.98 to 1.50), with a higher risk of cleft palate (1.62, 1.23 to 2.14).
CONCLUSIONS: Prescription opioids used in early pregnancy are not associated with a substantial increase in risk for most of the malformation types considered, although a small increase in the risk of oral clefts associated with their use is possible.
PURPOSE: To evaluate chronic opioid utilization patterns during pregnancy using nationwide data from publicly and commercially insured women.
METHODS: Pregnancy cohorts were identified using data from the Medicaid Analytic eXtract 2008-2014 and the IBM Health MarketScan Research Database 2008-2015. Opioid dispensing was evaluated using claims from filled prescriptions. Two different definitions of chronic opioid use were employed: ≥90 days' supply and ≥180 days' supply of prescription opioids during pregnancy. Patient characteristics were assessed and variations in the prevalence of chronic opioid therapy were described by geographic region and over time.
RESULTS: 1.50% of 975 169 Medicaid-insured and 0.32% of 1 037 599 commercially insured beneficiaries filled opioid prescriptions for ≥90 days' supply; 0.78% (Medicaid) and 0.17% (commercially insured) filled prescriptions for ≥180 days' supply. Prevalence approximately doubled in Medicaid beneficiaries during the study period, while it remained relatively stable for commercial insurance beneficiaries. The most commonly prescribed opioid for chronic therapy was hydrocodone, followed by oxycodone and tramadol. Indications commonly associated with chronic use were back/neck pain, abdominal/pelvic pain, musculoskeletal pain and migraine/headache. Substantial regional variation was observed, with several states reporting a frequency of ≥90 days' supply in excess of 3% in Medicaid-insured patients.
CONCLUSIONS: Despite growing awareness of the risks associated with chronic opioid use and emphasis on improving opioid prescription patterns, prevalence of chronic use in pregnancy among publicly insured women nearly doubled from 2008-2014 and was 5-fold more common when compared to commercially insured women. Findings call for the development of guidelines on chronic pain management during pregnancy.
OBJECTIVE: The objective of this study was to compare the incidence rate of nonvertebral osteoporotic fractures (NVFs) in patients with rheumatoid arthritis (RA) initiating one of the nine biologic or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs).
METHODS: We analyzed claims data from Optum (2008 to March 2019), Medicare, and MarketScan (2008-2017) to identify adults with RA who newly initiated b/tsDMARDs. Adalimumab was the most frequently used and was thus selected as a reference. The primary outcome was a composite of incident NVFs, including hip, humerus, pelvis, and wrist fractures, based on validated algorithms. We adjusted for greater than 70 potential confounders in each database through propensity score-based inverse probability treatment weighting. Follow-up time started the day after cohort entry until the first occurrence of one of the following: outcome, treatment discontinuation, switching, nursing home admission, death, disenrollment, or end of study period. For each drug comparison, weighted Cox proportional hazards models estimated the hazard ratios (HRs) and 95% confidence intervals (CIs). Secondary analyses were conducted in patients switching from a tumor necrosis factor inhibitor to a different b/tsDMARD.
RESULTS: A total of 134,693 b/tsDMARD initiators were identified across three databases. The adjusted HRs showed similar risk of composite NVFs in all b/tsDMARD exposures compared with adalimumab: abatacept, HR 1.03 (95% CI 0.82-1.30); certolizumab, HR 1.08 (95% CI 0.79-1.49); etanercept, HR 1.12 (95% CI 0.89-1.40); golimumab, HR 0.91 (95% CI 0.59-1.39); infliximab, HR 1.03 (95% CI 0.84-1.28); rituximab, HR 1.07 (95% CI 0.74-1.55); tocilizumab, HR 1.24 (95% CI 0.71-2.17); and tofacitinib, HR 1.07 (95% CI 0.69-1.64). Secondary analyses showed similar results.
CONCLUSION: This multidatabase cohort study found no differences in the risk of NVFs across individual b/tsDMARDs for RA, which provides reassurance to physicians prescribing b/tsDMARDs, especially to patients at high risk of developing NVFs.
Importance: List prices set by manufacturers for brand-name prescription drugs in the US have been increasing faster than inflation, although confidential manufacturer rebates offset some of these increases. Most commercially insured patients pay at least some out-of-pocket costs for prescription drugs, and higher patient spending is associated with lower adherence and worse health outcomes.
Objective: To examine whether price changes for brand-name drugs are correlated with changes in patient out-of-pocket spending and whether this association varies by insurance benefit design.
Design, Setting, and Participants: A cohort study of 79 brand-name drugs with available pricing data from January 2015 to December 2017 was conducted, with data obtained from a national commercial insurance claims database.
Exposures: Change in the list prices set by manufacturers and estimated net prices after rebates among non-Medicaid payers.
Main Outcomes and Measures: Change in median out-of-pocket spending among all patients and stratified by insurance pharmacy benefit design, including high-deductible insurance plans and plans with any amount of deductibles or coinsurance.
Results: Among 79 drugs, median increases were 16.7% (interquartile range [IQR], 13.6%-21.1%) for list prices, 5.4% (IQR, -3.9% to 11.7%) for net prices, and 3.5% (IQR, 1.4%-9.1%) for out-of-pocket spending from 2015 to 2017. Changes in list prices were correlated with changes in net prices (r = 0.34; P = .002). Overall, changes in out-of-pocket spending were not correlated with changes in list prices (r = 0.14; P = .22) or net prices (r = 0.04; P = .71). Among 53.7% of patients who paid any drug deductible or coinsurance, median out-of-pocket spending increased by 15.0%, and changes were moderately correlated with changes in list prices (r = 0.38; P = .001) but not net prices (r = 0.06; P = .62).
Conclusions and Relevance: Some commercially insured patients who pay only prescription drug copayments appear to be insulated from increases in drug prices. However, more than half of patients pay deductibles or coinsurance and may experience substantial increases in out-of-pocket spending when drug prices increase. Among these patients, there was no evidence that manufacturer rebates to insurers are associated with patients' out-of-pocket spending. Policies to rein in unregulated annual increases in list prices for brand-name drugs may have important consequences for patient out-of-pocket spending.
OBJECTIVE: To develop a claims-based model to predict persistent high-dose opioid use amongst patients undergoing total knee replacement (TKR).
METHODS: Using Medicare claims (2010-2014), we identified patients ≥65 years who underwent TKR with no history of high-dose opioid use (>25 mean morphine equivalents (MME)/day) in the year prior. We used group-based trajectory modeling to identify distinct opioid use patterns. The primary outcome was persistent high-dose opioid use in the year after TKR. We split the data into training (2010-2013) and test (2014) sets and used logistic regression with least absolute shrinkage and selection operator (LASSO) regularization utilizing a total of 83 pre-operative patient characteristics as candidate predictors. A reduced model with ten pre-specified variables which included demographics, opioid use and medication history was also considered.
RESULTS: The final study cohort included 142,089 patients who underwent TKR. The group-based trajectory model identified 4 distinct trajectories of opioid use (Group 1- short-term, low-dose, Group 2- moderate-duration, low-dose, Group 3- moderate-duration, high-dose, and Group 4-persistent high-dose). The model predicting persistent high-dose opioid use achieved high discrimination (area under the receiver operating characteristic curve (AUC) of 0.85; 95% CI, 0.84-0.86)) in the test set. The reduced model with ten predictors performed equally well (AUC=0.84; 95% CI, 0.84-0.85).
CONCLUSIONS: In this cohort of older patients, 10.6% became persistent high dose (mean=22.4 MME/day) opioid users after TKR. Our model with 10 readily available clinical factors may help identify patients at high risk of future adverse outcomes from persistent opioid use after TKR.
OBJECTIVE: To evaluate the effectiveness of angiotensin receptor-neprilysin inhibitor (ARNI) versus renin-angiotensin system (RAS) blockade alone in older adults with heart failure with reduced ejection fraction (HFrEF).
METHODS: We conducted a cohort study using US Medicare fee-for-service claims data (2014-2017). Patients with HFrEF ≥65 years were identified in two cohorts: (1) initiators of ARNI or RAS blockade alone (ACE inhibitor, ACEI; or angiotensin receptor blocker, ARB) and (2) switchers from an ACEI to either ARNI or ARB. HR with 95% CI from Cox proportional hazard regression and 1-year restricted mean survival time (RMST) difference with 95% CI were calculated for a composite outcome of time to first worsening heart failure event or all-cause mortality after adjustment for 71 pre-exposure characteristics through propensity score fine-stratification weighting. All analyses of initiator and switcher cohorts were conducted separately and then combined using fixed effects.
RESULTS: 51 208 patients with a mean age of 76 years were included, with 16 193 in the ARNI group. Adjusted HRs comparing ARNI with RAS blockade alone were 0.92 (95% CI 0.84 to 1.00) among initiators and 0.79 (95% CI 0.74 to 0.85) among switchers, with a combined estimate of 0.84 (95% CI 0.80 to 0.89). Adjusted 1-year RMST difference (95% CI) was 4 days in the initiator cohort (-1 to 9) and 12 days (8 to 17) in the switcher cohort, resulting in a pooled estimate of 9 days (6 to 12) favouring ARNI.
CONCLUSION: ARNI treatment was associated with lower risk of a composite effectiveness endpoint compared with RAS blockade alone in older adults with HFrEF.
BACKGROUND: Ejection fraction (EF) is an important prognostic factor in heart failure (HF), but administrative claims databases lack information on EF. We previously developed a model to predict EF class from Medicare claims. Here, we evaluated the performance of this model in an external validation sample of commercial insurance enrollees.
METHODS: Truven MarketScan claims linked to electronic medical records (EMR) data (IBM Explorys) containing EF measurements were used to identify a cohort of US patients with HF between 01-01-2012 and 10-31-2019. By applying the previously developed model, patients were classified into HF with reduced EF (HFrEF) or preserved EF (HFpEF). EF values recorded in EMR data were used to define gold-standard HFpEF (LVEF ≥45%) and HFrEF (LVEF<45%). Model performance was reported in terms of overall accuracy, positive predicted values (PPV), and sensitivity for HFrEF and HFpEF.
RESULTS: A total of 7,001 HF patients with an average age of 71 years were identified, 1,700 (24.3%) of whom had HFrEF. An overall accuracy of 0.81 (95% CI: 0.80-0.82) was seen in this external validation sample. For HFpEF, the model had sensitivity of 0.96 (95%CI, 0.95-0.97) and PPV of 0.81 (95% CI, 0.81-0.82); while for HFrEF, the sensitivity was 0.32 (95%CI, 0.30-0.34) and PPV was 0.73 (95%CI, 0.69-0.76). These results were consistent with what was previously published in US Medicare claims data.
CONCLUSIONS: The successful validation of the Medicare claims-based model provides evidence that this model may be used to identify patient subgroups with specific EF class in commercial claims databases as well.
OBJECTIVE: To compare the risk of serious infections requiring hospitalization in patients with psoriasis (PsO) or psoriatic arthritis (PsA) initiating ustekinumab versus other biologics or apremilast.
METHODS: In this multi-database cohort study, we identified patients with PsO/PsA who initiated adalimumab, apremilast, certolizumab, etanercept, golimumab, ixekizumab, secukinumab, or ustekinumab between 2009 and 2018. The primary outcome was hospitalized serious infections including bacterial, viral, or opportunistic infections. We estimated hazard ratios (HR) comparing each study drugs with ustekinumab after applying propensity score fine stratification weights for confounding control in each database. Database-specific weighted HRs were combined by meta-analysis.
RESULTS: We identified 123,383 patients with PsO/PsA who initiated one of the study drugs. During a total of 117,744 person-years of follow-up, 1,514 serious infections occurred with a crude incidence of 1.29 per 100 person-years. After propensity score fine stratification and weighting, the incidence rates of serious infection among ustekinumab initiators ranged from 0.59 to 0.95 per 100 person-years. Compared with ustekinumab, the combined weighted HR (95% confidence interval) for serious infections was 1.66 (1.34-2.06) for adalimumab, 1.42 (1.02-1.96) for apremilast, 1.09 (0.68-1.75) for certolizumab, 1.39 (1.01-1.90) for etanercept, 1.74 (1.00-3.03) for golimumab, 2.92 (1.80-4.72) for infliximab, 2.98 (1.20-7.41) for ixekizumab, and 1.84 (1.24-2.72) for secukinumab.
CONCLUSIONS: Other biologics and apremilast were associated with 1.4- to 3-times higher risk of hospitalized serious infections in PsO/PsA patients when compared with ustekinumab; such safety profile should be considered when selecting appropriate treatment regimens in patients with PsO/PsA.
OBJECTIVE: To evaluate the risk of venous thromboembolism (VTE) with tofacitinib compared with TNFis in patients with RA.
METHODS: RA patients initiating tofacitinib or a TNFi without use of any biologic or tofacitinib any time prior were identified from IBM 'MarketScan' (2012-18), Medicare (parts A, B and D, 2012-17) or 'Optum' Clinformatics (2012-19) and followed until treatment discontinuation, treatment switch, insurance disenrollment or administrative censoring. The primary outcome, VTE, was identified using inpatient claims for pulmonary embolism or deep vein thrombosis. A Cox proportional hazards model provided hazard ratio (HR) and 95% CIs after accounting for confounding through propensity score fine-stratification weighting. HRs were pooled across databases with inverse variance meta-analytic method.
RESULTS: A total of 42 201, 25 078 and 20 374 RA patients were identified from MarketScan, Medicare and Optum, respectively, of whom 7.1, 7.1 and 9.7% were tofacitinib initiators. The crude incidence rates per 100 person-years (95% CI) were 0.42 (0.20-0.77) and 0.35 (0.29-0.42) in MarketScan, 1.18 (0.68-1.92) and 0.83 (0.71-0.97) in Medicare, and 0.19 (0.04-0.57) and 0.34 (0.26-0.44) in Optum for tofacitinib and TNFis, respectively. Propensity score-weighted HRs showed no significant differences in the risk of VTE between tofacitinib and TNFis in any database with a pooled HR (95% CI) of 1.13 (0.77-1.65).
CONCLUSION: Overall, VTE occurred infrequently (<1 per 100) in a total of 87 653 RA patients initiating tofacitinib or a TNFi. We observed no evidence for an increased risk of VTE for tofacitinib vs TNFis in RA patients.