Journal: Orphanet Journal of Rare Diseases

Article Title: Patient journey to Fabry disease diagnosis in the United States: an observational retrospective analysis of two United States claims databases

doi: 10.1186/s13023-025-04041-3

Figure Lengend Snippet: Study design. CDM, Clinformatics ® Data Mart; HCRU, healthcare resource utilization; RD, Research Dataset. The index date (day 0) represents the date of first Fabry disease diagnosis. The inclusion assessment periods and baseline covariate assessment period are shown relative to the index date. Study periods: Optum CDM (March 31, 2012–March 31, 2022) and Komodo RD (January 1, 2018–September 30, 2022)

Article Snippet: Nonetheless, the impact on our finding is likely minimal for several reasons: (1) the databases cover different time periods (Optum CDM: March 2012 to March 2022; Komodo RD: January 2018 to September 2022), (2) there are differences in the patient populations represented in the two databases: Optum CDM captures only individuals who are covered by commercial insurance or Medicare through a single payer, whereas Komodo RD includes patients covered by multiple commercial and Medicare payers as well as Medicaid, (3) we required two years of continuous enrollment prior to the first recorded Fabry diagnosis to increase the likelihood that we captured patients’ incident diagnosis, (4) our analyses were conducted independently for each database, and results are reported separately.

Techniques: Biomarker Discovery

Journal: Orphanet Journal of Rare Diseases

Article Title: Patient journey to Fabry disease diagnosis in the United States: an observational retrospective analysis of two United States claims databases

doi: 10.1186/s13023-025-04041-3

Figure Lengend Snippet: Diagnosing provider specialty for patients with FD in the US. a Optum CDM. CDM, Clinformatics ® Data Mart; FD, Fabry disease. b Komodo RD. HCP, Healthcare practioner; RD, Reseach Dataset

Article Snippet: Nonetheless, the impact on our finding is likely minimal for several reasons: (1) the databases cover different time periods (Optum CDM: March 2012 to March 2022; Komodo RD: January 2018 to September 2022), (2) there are differences in the patient populations represented in the two databases: Optum CDM captures only individuals who are covered by commercial insurance or Medicare through a single payer, whereas Komodo RD includes patients covered by multiple commercial and Medicare payers as well as Medicaid, (3) we required two years of continuous enrollment prior to the first recorded Fabry diagnosis to increase the likelihood that we captured patients’ incident diagnosis, (4) our analyses were conducted independently for each database, and results are reported separately.

Techniques:

Journal: Orphanet Journal of Rare Diseases

Article Title: Patient journey to Fabry disease diagnosis in the United States: an observational retrospective analysis of two United States claims databases

doi: 10.1186/s13023-025-04041-3

Figure Lengend Snippet: Concomitant therapy use among patients with FD in the 2-year baseline period prior to index date. a Optum CDM. CDM, Clinformatics ® Data Mart. b Komodo RD. RD, Research Dataset

Article Snippet: Nonetheless, the impact on our finding is likely minimal for several reasons: (1) the databases cover different time periods (Optum CDM: March 2012 to March 2022; Komodo RD: January 2018 to September 2022), (2) there are differences in the patient populations represented in the two databases: Optum CDM captures only individuals who are covered by commercial insurance or Medicare through a single payer, whereas Komodo RD includes patients covered by multiple commercial and Medicare payers as well as Medicaid, (3) we required two years of continuous enrollment prior to the first recorded Fabry diagnosis to increase the likelihood that we captured patients’ incident diagnosis, (4) our analyses were conducted independently for each database, and results are reported separately.

Techniques:

Journal: PLoS ONE

Article Title: A new model to predict major bleeding in patients with atrial fibrillation using warfarin or direct oral anticoagulants

doi: 10.1371/journal.pone.0203599

Figure Lengend Snippet: Characteristics of patients with atrial fibrillation according to initial prescribed anticoagulant in the derivation (MarketScan, 2007–2014) and validation (Optum Clinformatics, 2009–2015) cohorts.

Article Snippet: The data for these analyses were made available to the authors by third-party licenses from Truven MarketScan and Optum, commercial data providers in the US.

Techniques:

Journal: PLoS ONE

Article Title: A new model to predict major bleeding in patients with atrial fibrillation using warfarin or direct oral anticoagulants

doi: 10.1371/journal.pone.0203599

Figure Lengend Snippet: Observed bleeding rates in patients with non-valvular AF initiating oral anticoagulation per 100 person-years in the derivation (MarketScan, 2007–2014) and validation (Optum Clinformatics, 2009–2015) cohorts.

Article Snippet: The data for these analyses were made available to the authors by third-party licenses from Truven MarketScan and Optum, commercial data providers in the US.

Techniques:

Journal: PLoS ONE

Article Title: A new model to predict major bleeding in patients with atrial fibrillation using warfarin or direct oral anticoagulants

doi: 10.1371/journal.pone.0203599

Figure Lengend Snippet: Calibration curve relating observed and predicted bleeding rates across deciles of risk in A. Derivation Cohort (MarketScan) B. Validation Cohort (Optum Clinformatics). The 45 degree dashed line indicates perfect fit.

Article Snippet: The data for these analyses were made available to the authors by third-party licenses from Truven MarketScan and Optum, commercial data providers in the US.

Techniques:

Journal: PLoS ONE

Article Title: A new model to predict major bleeding in patients with atrial fibrillation using warfarin or direct oral anticoagulants

doi: 10.1371/journal.pone.0203599

Figure Lengend Snippet: Final model coefficients and hazard ratios in the derivation cohort, MarketScan, 2007–2014.

Article Snippet: The data for these analyses were made available to the authors by third-party licenses from Truven MarketScan and Optum, commercial data providers in the US.

Techniques:

Journal: PLoS ONE

Article Title: A new model to predict major bleeding in patients with atrial fibrillation using warfarin or direct oral anticoagulants

doi: 10.1371/journal.pone.0203599

Figure Lengend Snippet: Model discrimination [c-statistic (95% confidence interval)] by derivation and validation cohorts.

Article Snippet: The data for these analyses were made available to the authors by third-party licenses from Truven MarketScan and Optum, commercial data providers in the US.

Techniques:

Journal: BMC Medical Research Methodology

Article Title: The necessity of validity diagnostics when drawing causal inferences from observational data: lessons from a multi-database evaluation of the risk of non-infectious uveitis among patients exposed to Remicade ®

doi: 10.1186/s12874-024-02428-7

Figure Lengend Snippet: Empirical equipoise, covariate balance, empirical calibration validity diagnostics and representativeness for IBD primary analysis Key: Amb EMR = IQVIA Ambulatory Electronic Medical Records; ASMD = absolute standardized mean difference; CCAE = Merative™ MarketScan ® Commercial Database; CI = Confidence Interval; Clinformatics ® = Optum ® De-Identified Clinformatics ® Data Mart Database; EASE = expected absolute systematic error; HR = Hazard ratio; IBD = irritable bowel diseases (Crohn’s disease or ulcerative colitis); IBD comparator = golimumab, certolizumab pegol, ustekinumab, or vedolizumab; Optum ® EHR = Optum ® De-Identified Electronic Health Record; Pharmetrics = IQVIA Adjudicated Health Plan Claims Data; Remicade ® (m) = Remicade ® exposure; Target covariate prevalence = prevalence of baseline covariates in the initial Remicade ® exposure cohort before study design restrictions were applied; Analytic covariate prevalence = prevalence of baseline covariates in Remicade ® exposure cohort after study design restrictions were applied (i.e., PS matching)

Article Snippet: Databases used in this study are available via license are available for purchase from Merative ® (CCAE), Optum ® (Clinformatics ® and Optum ® EHR), and IQVIA (Pharmetrics and Amb EMR).

Techniques:

Journal: BMC Medical Research Methodology

Article Title: The necessity of validity diagnostics when drawing causal inferences from observational data: lessons from a multi-database evaluation of the risk of non-infectious uveitis among patients exposed to Remicade ®

doi: 10.1186/s12874-024-02428-7

Figure Lengend Snippet: Attrition diagrams for inflammatory bowel diseases (IBD); patient attrition counts and proportions after sequential design choices applied Key: Amb EMR = IQVIA Ambulatory Electronic Medical Records; ASMD = absolute standardized mean difference; CCAE = Merative™ MarketScan ® Commercial Database; CI = Confidence Interval; Clinformatics ® = Optum ® De-Identified Clinformatics ® Data Mart Database; EASE = expected absolute systematic error; HR = Hazard ratio; Optum ® EHR = Optum ® De-Identified Electronic Health Record; Pharmetrics = IQVIA Adjudicated Health Plan Claims Data; RA = rheumatoid arthritis; RA comparator = certolizumab pegol or tocilizumab; Remicade ® (m) = Remicade ® exposure with concurrent methotrexate; Target covariate prevalence = prevalence of baseline covariates in the initial Remicade ® exposure cohort before study design restrictions were applied; Analytic covariate prevalence = prevalence of baseline covariates in Remicade ® exposure cohort after study design restrictions were applied (i.e., PS matching)

Article Snippet: Databases used in this study are available via license are available for purchase from Merative ® (CCAE), Optum ® (Clinformatics ® and Optum ® EHR), and IQVIA (Pharmetrics and Amb EMR).

Techniques:

Journal: BMC Medical Research Methodology

Article Title: The necessity of validity diagnostics when drawing causal inferences from observational data: lessons from a multi-database evaluation of the risk of non-infectious uveitis among patients exposed to Remicade ®

doi: 10.1186/s12874-024-02428-7

Figure Lengend Snippet: Empirical equipoise, covariate balance, empirical calibration validity diagnostics and representativeness for RA primary analysis Key – Target: patients with inflammatory bowel diseases newly exposed to Remicade ® , Comparator: patients with inflammatory bowel diseases newly exposed to [golimumab, certolizumab pegol, ustekinumab, or vedolizumab], CCAE: Merative™ MarketScan ® Commercial Database, Optum ® EHR = Optum ® De-Identified Electronic Health Record; Pharmetrics = IQVIA Adjudicated Health Plan Claims Data

Article Snippet: Databases used in this study are available via license are available for purchase from Merative ® (CCAE), Optum ® (Clinformatics ® and Optum ® EHR), and IQVIA (Pharmetrics and Amb EMR).

Techniques:

Journal: BMC Medical Research Methodology

Article Title: The necessity of validity diagnostics when drawing causal inferences from observational data: lessons from a multi-database evaluation of the risk of non-infectious uveitis among patients exposed to Remicade ®

doi: 10.1186/s12874-024-02428-7

Figure Lengend Snippet: Risk of non-infectious uveitis (NIU) among patients with inflammatory bowel diseases (IBD) Key – PS: propensity score, OT: on-treatment, ITT: intention-to-treat, T: Remicade ® new users with IBD, C: golimumab, certolizumab pegol, ustekinumab, or vedolizumab new users with IBD, IR: incidence rate, PYs: person-years, CCAE: Merative™ MarketScan ® Commercial Database, Optum ® EHR: Optum ® De-Identified Electronic Health Record, Pharmetrics: IQVIA Adjudicated Health Plan Claims Data

Article Snippet: Databases used in this study are available via license are available for purchase from Merative ® (CCAE), Optum ® (Clinformatics ® and Optum ® EHR), and IQVIA (Pharmetrics and Amb EMR).

Techniques:

Journal: Journal of Cardiovascular Electrophysiology

Article Title: A Large, Real‐World Cohort Analysis of Arrhythmia Detection and Therapeutic Interventions in Patients With Insertable Cardiac Monitors and Long‐Term Monitoring

doi: 10.1111/jce.70214

Figure Lengend Snippet: (a) Patient selection flowchart for arrhythmia detection analysis using Carelink Data. (b) Patient selection flowchart for therapeutic interventions analysis using Optum CDM Claims Data. CIEDs, cardiovascular implantable electronic devices; CRT, cardiac resynchronization therapy; ICD, implantable cardioverter defibrillator; ICM, insertable cardiac monitor; IPG, implantable pulse generator; Optum CDM, Optum Clinformatics Data Mart claims database.

Article Snippet: This retrospective cohort study utilized data from two large, nationally represented deidentified databases: Medtronic CareLink data warehouse and Optum Clinformatics Data Mart (CDM) claims database (Central Illustration , ).

Techniques: Selection