The IBM MarketScan Research Databases contain individual-level, de-identified healthcare claims data including clinical utilization, expenditures, insurance enrollment/plan benefit for inpatient, outpatient, prescription drug, and carve-out services for a large population of individuals and their dependents with employer-provided commercial insurance in the United States of America. De-identified records of more than 250 million patients are included in the database.

Software suite of proprietary databases that contain one of longest running and largest collection of privately and publicly insured, de identified patient data in USA. Family of data sets that fully integrate many types of data for healthcare research.

Annual counts of individuals enrolled in MarketScan Research Databases and counts of patients with ≥1 AMI diagnosis according to ICD-CM codes received in any healthcare setting (2014–2017).

Background: Various methodologies have been reported to assess the real-world epidemiology of amyotrophic lateral sclerosis (ALS) in the United States. The aim of this study was to estimate the prevalence, incidence, and geographical distribution of ALS using administrative claims data and to model future trends in ALS epidemiology. Methods: We performed a retrospective analysis of deidentified administrative claims data for >100 million patients, using 2 separate databases (IBM MarketScan Research Databases and Symphony Health Integrated DataVerse [IDV]), to identify patients with ALS. We evaluated disease prevalence, annual incidence, age- and population-controlled geographical distribution, and expected future trends. Results: From 2013 to 2017, we identified 7,316 and 35,208 ALS patients from the MarketScan databases and IDV, respectively. Average annual incidence estimates were 1.48 and 1.37 per 100,000 and point prevalence estimates were 6.85 and 5.16 per 100,000 and in the United States for the MarketScan databases and IDV, respectively. Predictive modeling estimates are reported out to the year 2060 and demonstrate an increasing trend in both incident and prevalent cases. Conclusions: This study provides incidence and prevalence estimates as well as geographical distribution for what the authors believe to be the largest ALS population studied to date. By using 2 separate administrative claims data sets, confidence in our estimates is increased. Future projections based on either database demonstrate an increase in ALS cases, which has also been seen in other large-scale ALS studies. These results can be used to help improve the allocation of healthcare resources in the future.

Androgen deprivation therapy (ADT) is standard for advanced prostate cancer. Relugolix, a gonadotropin-releasing hormone (GnRH) receptor antagonist, is the only oral ADT, with limited real-world data on therapy persistence and adherence. This retrospective study evaluates persistence and adherence of relugolix, degarelix, and GnRH agonists (leuprolide, goserelin, triptorelin, histrelin) using data from the IBM MarketScan Research Database (Jan 2017 - Dec 2022). The IBM MarketScan Research Database (1 January 2017 - 31 December 2022) was used for enrollment history and claims. ADT adherence was measured by the proportion of days covered (PDC) at 3, 6, and 12 months, calculated as days on ADT divided by period duration. Kaplan-Meier analysis assessed treatment persistence by measuring time to treatment discontinuation. Relugolix had higher adherence (PDC ≥ 80%) at 12 months (60.8%) compared to degarelix (13.0%) and GnRH agonists (46.3%). Median time to discontinuation was also longer for relugolix (13.5 months) than degarelix (3.1 months) and GnRH agonists (8.8 months). Persistence and adherence rates were higher in metastatic prostate cancer. Findings support relugolix use as an oral treatment due to its favorable persistence and long-term adherence profiles. Prostate cancer is the second most common cancer among men in the US. Androgen deprivation therapy (ADT), a key treatment for advanced prostate cancer, lowers testosterone levels, a hormone that helps prostate cancer grow. ADT includes injectable gonadotropin-releasing hormone (GnRH) receptor agonists like leuprolide, which initially raise testosterone before lowering it, and antagonists like degarelix, (injectable) and relugolix (oral), which rapidly lower testosterone. A large clinical trial (phase III) showed relugolix rapidly and consistently lowered testosterone, with similar side effects to leuprolide but fewer major cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and death from any cause). There is limited published real-world data, including healthcare information like medical records and insurance claims, on how well patients stay on treatment (persistence) and take their medication as prescribed (adherence) for different forms of ADT, especially oral relugolix. Data from the IBM MarketScan Research Database (January 2017 to December 2022) was used to compare persistence and adherence among patients taking oral relugolix, injectable degarelix, and injectable GnRH receptor agonists. Patients taking relugolix had a higher rate of adherence to their treatment (60.8%) after 12 months versus those receiving injectable degarelix (13.0%) and other injectables, GnRH receptor agonists (46.3%). Patients on relugolix also stayed on their treatment longer (13.5 months) compared to those on injectable degarelix (3.1 months) and GnRH receptor agonists (8.8 months). These results were especially notable in patients with metastatic prostate cancer. This study demonstrates favorable persistence and adherence rates with oral relugolix in patients receiving ADT for advanced prostate cancer.

Polypharmacy in spinal cord injury (SCI) is common and predisposes patients to increased risk of adverse events. Evaluation of long-term health consequences and economic burden of polypharmacy in patients with SCI is explored. Retrospective cohort. The IBM Marketscan Research Databases claims-based dataset was queried to search for adult patients with SCI with a 2-year follow-up. Two matched cohorts were analyzed: those with and without polypharmacy, analyzing index hospitalization, readmissions, payments, and health outcomes. A total of 11 569 individuals with SCI were included, of which 7235 (63%) were in the polypharmacy group who took a median of 11 separate drugs over two years. Opioid analgesics were the most common medication, present in 57% of patients with SCI meeting the criteria of polypharmacy, followed by antidepressant medications (46%) and muscle relaxants (40%). Risk of pneumonia was increased for the polypharmacy group (58%) compared to the non-polypharmacy group (45%), as were urinary tract infection (79% versus 63%), wound infection (30% versus 21%), depression (76% versus 57%), and adverse drug events (24% versus 15%) at 2 years. Combined median healthcare payments were higher in polypharmacy at 2 years ($44 333 vs. $10 937, P 

IntroductionDiabetes is a major cause of disease burden with considerable public health significance. While the pancreas plays a significant role in glucose homeostasis, the association between pancreatitis and new onset diabetes is not well understood. The purpose of this study was to examine that association using large real-world data.Materials and methodsUtilizing the IBM® MarketScan® commercial claims database from 2016 to 2019, pancreatitis and diabetes regardless of diagnostic category, were identified using International Classification of Diseases, Tenth Revision [ICD-10] codes. We then performed descriptive analyses characterizing non-pancreatitis (NP), acute pancreatitis (AP), and chronic pancreatitis (CP) cohort subjects. Stratified Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) of diabetes across the three clinical categories.ResultsIn total, 310,962 individuals were included in the analysis. During 503,274 person‐years of follow‐up, we identified 15,951 incident diabetes cases. While men and women had higher incidence rates of CP and AP-related diabetes, the rates were significantly greater in men and highest among individuals with CP (91.6 per 1000 persons-years (PY)) followed by AP (75.9 per 1000-PY) as compared to those with NP (27.8 per 1000-PY). After adjustment for diabetes risk factors, relative to the NP group, the HR for future diabetes was 2.59 (95% CI: 2.45-2.74) (P

Real-world healthcare data hold the potential to identify therapeutic solutions for progressive diseases by efficiently pinpointing safe and efficacious repurposing drug candidates. This approach circumvents key early clinical development challenges, particularly relevant for neurological diseases, concordant with the vision of the 21st Century Cures Act. However, to-date, these data have been utilized mainly for confirmatory purposes rather than as drug discovery engines. Here, we demonstrate the usefulness of real-world data in identifying drug repurposing candidates for disease-modifying effects, specifically candidate marketed drugs that exhibit beneficial effects on Parkinson’s disease (PD) progression. We performed an observational study in cohorts of ascertained PD patients extracted from two large medical databases, Explorys SuperMart (N = 88,867) and IBM MarketScan Research Databases (N = 106,395); and applied two conceptually different, well-established causal inference methods to estimate the effect of hundreds of drugs on delaying dementia onset as a proxy for slowing PD progression. Using this approach, we identified two drugs that manifested significant beneficial effects on PD progression in both datasets: rasagiline, narrowly indicated for PD motor symptoms; and zolpidem, a psycholeptic. Each confers its effects through distinct mechanisms, which we explored via a comparison of estimated effects within the drug classification ontology. We conclude that analysis of observational healthcare data, emulating otherwise costly, large, and lengthy clinical trials, can highlight promising repurposing candidates, to be validated in prospective registration trials, beneficial against common, late-onset progressive diseases for which disease-modifying therapeutic solutions are scarce.

Recent studies have suggested that dipeptidyl peptidase 4 (DPP4) inhibitors increase the risk of development of bullous pemphigoid (BP), which is the most common autoimmune blistering skin disease; however, the associated mechanisms remain unclear, and thus far, no therapeutic targets responsible for drug-induced BP have been identified. Therefore, we used clinical data mining to identify candidate drugs that can suppress DPP4 inhibitor-associated BP, and we experimentally examined the underlying molecular mechanisms using human peripheral blood mononuclear cells (hPBMCs). A search of the US Food and Drug Administration Adverse Event Reporting System and the IBM® MarketScan® Research databases indicated that DPP4 inhibitors increased the risk of BP, and that the concomitant use of lisinopril, an angiotensin-converting enzyme inhibitor, significantly decreased the incidence of BP in patients receiving DPP4 inhibitors. Additionally, in vitro experiments with hPBMCs showed that DPP4 inhibitors upregulated mRNA expression of MMP9 and ACE2, which are responsible for the pathophysiology of BP in monocytes/macrophages. Furthermore, lisinopril and Mas receptor (MasR) inhibitors suppressed DPP4 inhibitor-induced upregulation of MMP9. These findings suggest that the modulation of the renin-angiotensin system, especially the angiotensin1-7/MasR axis, is a therapeutic target in DPP4 inhibitor-associated BP.