High-dimensional propensity score adjustment in studies of treatment effects using health care claims data.

Untitled work

(2001) · RePEc: Research Papers in Economics · Cited by 27,577

Revisiting the Behavioral Model and Access to Medical Care: Does it Matter?

Andersen, R. M. (1995) · Journal of Health and Social Behavior · doi:10.2307/2137284 · Cited by 9,831

Variable Selection for Propensity Score Models

Brookhart, M. A., Schneeweiss, S., Rothman, K. J., Glynn, R. J., Avorn, J., & Stürmer, T. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj149 · Cited by 2,336

Evaluating medication effects outside of clinical trials: new-user designs

Ray, W. A. (2003) · American Journal of Epidemiology · doi:10.1093/aje/kwg231 · Cited by 1,646

A review of uses of health care utilization databases for epidemiologic research on therapeutics

Schneeweiß, S., & Avorn, J. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2004.10.012 · Cited by 1,290

Estimation of Causal Effects using Propensity Score Weighting: An Application to Data on Right Heart Catheterization

Hirano, K., & Imbens, G. W. (2001) · Health Services and Outcomes Research Methodology · doi:10.1023/a:1020371312283 · Cited by 1,039

Unified Methods for Censored Longitudinal Data and Causality

van der Laan, M. J., & Robins, J. M. (2003) · Springer series in statistics · doi:10.1007/978-0-387-21700-0 · Cited by 979

Quantifying Biases in Causal Models: Classical Confounding vs Collider-Stratification Bias

Greenland, S. (2003) · Epidemiology · doi:10.1097/01.ede.0000042804.12056.6c · Cited by 810

A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods

Stürmer‎, T., Joshi, M., Glynn, R. J., Avorn, J., Rothman, K. J., & Schneeweiß, S. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2005.07.004 · Cited by 668

Relationship Between Selective Cyclooxygenase-2 Inhibitors and Acute Myocardial Infarction in Older Adults

Solomon, D. H., Schneeweiß, S., Glynn, R. J., Kiyota, Y., Levin, R., Mogun, H., & Avorn, J. (2004) · Circulation · doi:10.1161/01.cir.0000127578.21885.3e · Cited by 506

Propensity score methods in real‐world epidemiology: A practical guide for first‐time users

Loke, Y. K., & Mattishent, K. (2020) · Diabetes Obesity and Metabolism · doi:10.1111/dom.13926 · Cited by 26

Targeting abnormal metabolism in Alzheimer's disease: The Drug Repurposing for Effective Alzheimer's Medicines (DREAM) study

Desai, R. J., Varma, V. R., Gerhard, T., Segal, J. B., Mahesri, M., Chin, K., Nonnenmacher, E., Gabbeta, A., Oommen, A. M., Varma, S., et al. (2020) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12095 · Cited by 26

Risk of Ischemic Cerebrovascular and Coronary Events in Adult Users of Anticonvulsant Medications in Routine Care Settings

Patorno, E., Glynn, R. J., Hernández–Dı́az, S., Avorn, J., Wahl, P. M., Bohn, R. L., Mines, D. I., Liu, J., & Schneeweiß, S. (2013) · Journal of the American Heart Association · doi:10.1161/jaha.113.000208 · Cited by 26

Mortality associated with lithium and valproate treatment of US Veterans Health Administration patients with mental disorders

Smith, E. G., Austin, K., Kim, H. M., Eisen, S. V., Kilbourne, A. M., Miller, D. R., Zivin, K., Hannemann, C. M., Sauer, B. C., & Valenstein, M. M. (2015) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.113.138685 · Cited by 26

Performance of the High‐dimensional Propensity Score in a Nordic Healthcare Model

Hallas, J., & Pottegård, A. (2016) · Basic & Clinical Pharmacology & Toxicology · doi:10.1111/bcpt.12716 · Cited by 26

Epidemiologic Analysis Along the Mevalonate Pathway Reveals Improved Cancer Survival in Patients Who Receive Statins Alone and in Combination With Bisphosphonates

El-Refai, S. M., Brown, J. D., Arnold, S. M., Black, E. P., Leggas, M. L., & Talbert, J. (2017) · JCO Clinical Cancer Informatics · doi:10.1200/cci.17.00010 · Cited by 27

Post-tuberculosis airway disease: A population-based cohort study of people immigrating to British Columbia, Canada, 1985–2015

Basham, C. A., Karim, M. E., Cook, V. J., Patrick, D. M., & Johnston, J. C. (2021) · EClinicalMedicine · doi:10.1016/j.eclinm.2021.100752 · Cited by 27

The use of clinical trials in comparative effectiveness research on mental health

Blanco, C., Rafful, C. M., & Olfson, M. (2013) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2013.02.013 · Cited by 25

Comparative effectiveness of dupilumab and omalizumab on asthma exacerbations and systemic corticosteroid prescriptions: Real-world US ADVANTAGE study

Bleecker, E. R., Blaiss, M. S., Jacob-Nara, J. A., Huynh, L. Y., Duh, M. S., Guo, T., Ye, M., Stanford, R. H., Wang, Z., Soler, X., et al. (2024) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2024.07.029 · Cited by 25

Simultaneously assessing intended and unintended treatment effects of multiple treatment options: a pragmatic “matrix design”

Rassen, J. A., Solomon, D. H., Glynn, R. J., & Schneeweiß, S. (2011) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.2121 · Cited by 25

Comparison of Different Approaches to Confounding Adjustment in a Study on the Association of Antipsychotic Medication With Mortality in Older Nursing Home Patients

Huybrechts, K. F., Brookhart, M. A., Rothman, K. J., Silliman, R. A., Gerhard, T., Crystal, S., & Schneeweiß, S. (2011) · American Journal of Epidemiology · doi:10.1093/aje/kwr213 · Cited by 25

Reuse of data sources to evaluate drug safety signals: When is it appropriate?

Wang, S. V., Kulldorff, M., Glynn, R. J., Gagne, J. J., Pottegård, A., Rothman, K. J., Schneeweiß, S., & Walker, A. M. (2018) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.4442 · Cited by 25

Arteriovenous Access Type and Risk of Mortality, Hospitalization, and Sepsis Among Elderly Hemodialysis Patients: A Target Trial Emulation Approach

Lyu, B., Chan, M. R., Yevzlin, A. S., Gardezi, A. I., & Astor, B. C. (2021) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2021.03.030 · Cited by 25

Transparency of high‐dimensional propensity score analyses: Guidance for diagnostics and reporting

Tazare, J., Wyss, R., Franklin, J. M., Smeeth, L. L., Evans, S. J. W., Wang, S. V., Schneeweiß, S., Douglas, I., Gagne, J. J., & Williamson, E. (2022) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5412 · Cited by 25

Drug interactions in hospital prescriptions in Denmark: Prevalence and associations with adverse outcomes

Rodríguez, C. L., Kaas‐Hansen, B. S., Eriksson, R., Biel, J. H., Belling, K., Andersen, S. E., & Brunak, S. (2022) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5415 · Cited by 28

Applying Machine Learning in Distributed Data Networks for Pharmacoepidemiologic and Pharmacovigilance Studies: Opportunities, Challenges, and Considerations

Wong, J., Prieto‐Alhambra, D., Rijnbeek, P. R., Desai, R. J., Reps, J., & Toh, S. (2022) · Drug Safety · doi:10.1007/s40264-022-01158-3 · Cited by 25

Risk of New-Onset Prostate Cancer for Metformin Versus Sulfonylurea Use in Type 2 Diabetes Mellitus: A Propensity Score–Matched Study

Lee, Y. H. A., Zhou, J., Hui, J. M. H., Liu, X., Lee, T. T. L., Hui, K., Chan, J. S. K., Wai, A. K. C., Wong, W. T., Liu, T., et al. (2022) · Journal of the National Comprehensive Cancer Network · doi:10.6004/jnccn.2022.7010 · Cited by 25

Risk of Ischemic Stroke Associated with the Use of Antipsychotic Drugs in Elderly Patients: A Retrospective Cohort Study in Korea

Shin, J., Choi, N., Lee, J., Seong, J.-M., Park, M.-J., Lee, S. H., & Park, B. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119931 · Cited by 25

Hospitalization for Hemorrhage Among Warfarin Recipients Prescribed Amiodarone

Lam, J., Gomes, T., Juurlink, D. N., Mamdani, M., Pullenayegum, E., Kearon, C., Spencer, F. A., Paterson, M. J., Zheng, H. Y., & Holbrook, A. M. (2013) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2013.03.051 · Cited by 25

The Comparison of Matching Methods Using Different Measures of Balance: Benefits and Risks Exemplified within a Study to Evaluate the Effects of German Disease Management Programs on Long‐Term Outcomes of Patients with Type 2 Diabetes

Fullerton, B., Pöhlmann, B., Krohn, R., Adams, J., Gerlach, F. M., & Erler, A. (2016) · Health Services Research · doi:10.1111/1475-6773.12452 · Cited by 25

Comparative Effectiveness of Intra-Articular Hyaluronic Acid and Corticosteroid Injections on the Time to Surgical Knee Procedures

Shewale, A. R., Barnes, C. L., Fischbach, L. A., Ounpraseuth, S., Painter, J. T., & Martin, B. C. (2017) · The Journal of Arthroplasty · doi:10.1016/j.arth.2017.07.007 · Cited by 25

Degree of serotonin reuptake inhibition of antidepressants and ischemic risk

Douros, A., Dell’Aniello, S., Dehghan, G., Boivin, J., & Renoux, C. (2019) · Neurology · doi:10.1212/wnl.0000000000008060 · Cited by 26

Retail clinic utilization associated with lower total cost of care.

Sussman, A. J., Dunham, L. N., Snower, K., Hu, M., Matlin, O. S., Shrank, W. H., Choudhry, N. K., & Brennan, T. A. (2013) · PubMed · Cited by 25

Risk of Thyroid Cancer Associated with Use of Liraglutide and Other Antidiabetic Drugs in a US Commercially Insured Population

Funch, D., Mortimer, K., Ziyadeh, N. J., Seeger, J. D., Zhou, L., Ng, E., Ross, D., Major-Pedersen, A., Bosch-Traberg, H., Gydesen, H., et al. (2021) · Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy · doi:10.2147/dmso.s305496 · Cited by 24

Artificial intelligence for optimizing benefits and minimizing risks of pharmacological therapies: challenges and opportunities

Crisafulli, S., Ciccimarra, F., Bellitto, C., Carollo, M., Carrara, E., Stagi, L., Triola, R., Capuano, A., Chiamulera, C., Moretti, U., et al. (2024) · Frontiers in Drug Safety and Regulation · doi:10.3389/fdsfr.2024.1356405 · Cited by 29

Comparative Effectiveness and Safety of Apixaban, Rivaroxaban, and Warfarin in Patients With Cirrhosis and Atrial Fibrillation

Simon, T. G., Singer, D. E., Zhang, Y., Mastrorilli, J. M., Cervone, A., DiCesare, E., & Lin, K. J. (2024) · Annals of Internal Medicine · doi:10.7326/m23-3067 · Cited by 24

Pirfenidone and risk of lung cancer development in idiopathic pulmonary fibrosis: a nationwide population-based study

Yoon, H., Kim, H., Bae, Y., & Song, J. W. (2024) · European Respiratory Journal · doi:10.1183/13993003.01484-2024 · Cited by 24

Assessing Covariate Balance With Small Sample Sizes

Hripcsak, G. M., Zhang, L., Chen, Y., Li, K., Suchard, M. A., Ryan, P. B., & Schuemie, M. J. (2025) · Statistics in Medicine · doi:10.1002/sim.70212 · Cited by 24

Comparative Safety of Dipeptidyl Peptidase-4 Inhibitors Versus Sulfonylureas and Other Glucose-lowering Therapies for Three Acute Outcomes

Gamble, J., Donnan, J. R., Chibrikov, E., Twells, L., Midodzi, W. K., & Majumdar, S. R. (2018) · Scientific Reports · doi:10.1038/s41598-018-33483-y · Cited by 24

Effectiveness of angiotensin-neprilysin inhibitor treatment versus renin-angiotensin system blockade in older adults with heart failure in clinical care

Desai, R. J., Patorno, E., Vaduganathan, M., Mahesri, M., Chin, K., Levin, R., Solomon, S. D., & Schneeweiß, S. (2021) · Heart · doi:10.1136/heartjnl-2021-319405 · Cited by 24

Adverse Cardiovascular Complications following prescription of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) inhibitors: a propensity-score matched Cohort Study with competing risk analysis

Zhou, J., Lee, S., Lakhani, I., Yang, L., Liu, T., Zhang, Y., Xia, Y., Wong, W. T., Bao, K. K. H., Wong, I. C. K., et al. (2022) · Cardio-Oncology · doi:10.1186/s40959-021-00128-5 · Cited by 24

Covariate Selection in Propensity Scores Using Outcome Proxies

Kelcey, B. (2011) · Multivariate Behavioral Research · doi:10.1080/00273171.2011.570164 · Cited by 24

Super learning to hedge against incorrect inference from arbitrary parametric assumptions in marginal structural modeling

Neugebauer, R. S., FIREMAN, B. H., Roy, J. A., Raebel, M. A., Nichols, G. A., & O’Connor, P. J. (2013) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2013.01.016 · Cited by 25

Suicide risk in Veterans Health Administration patients with mental health diagnoses initiating lithium or valproate: a historical prospective cohort study

Smith, E. G., Austin, K., Kim, H. M., Miller, D. R., Eisen, S. V., Christiansen, C. L., Kilbourne, A. M., Sauer, B. C., McCarthy, J. F., & Valenstein, M. M. (2014) · BMC Psychiatry · doi:10.1186/s12888-014-0357-x · Cited by 24

Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example

Le, H. V., Poole, C., Brookhart, M. A., Schoenbach, V. J., Beach, K. J., Layton, J. B., & Stürmer‎, T. (2013) · BMC Medical Research Methodology · doi:10.1186/1471-2288-13-142 · Cited by 24

Pregabalin and heart failure: A population‐based study

Ho, J. M.-W., Macdonald, E. M., Luo, J., Gomes, T., Antoniou, T., Mamdani, M., & Juurlink, D. N. (2017) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.4239 · Cited by 24

Recent Methodological Trends in Epidemiology: No Need for Data-Driven Variable Selection?

Staerk, C., Byrd, A., & Mayr, A. J. (2023) · American Journal of Epidemiology · doi:10.1093/aje/kwad193 · Cited by 23

Excess cardiometabolic risk in children and adolescents initiating antipsychotic treatment compared to young adults: results from a nationwide cohort study

Højlund, M., Wesselhoeft, R. T., Heinrichsen, M., Pagsberg, A. K., Correll, C. U., & Steinhausen, H. (2025) · World Psychiatry · doi:10.1002/wps.21279 · Cited by 23

“Weekend effect” on stroke mortality revisited

Hsieh, C., Lin, H., Chen, C., Li, C., Chiu, M.-J., & Sung, S. (2016) · Medicine · doi:10.1097/md.0000000000004046 · Cited by 23

Early Spontaneous Abdominal Bleeding is associated with Poor Outcome in Moderate to Severe Acute Pancreatitis Patients: A Propensity Matched Study

Chen, Y., Zhou, J., Li, G., Tong, Z., Dong, J., Pan, Y., Ke, L., Li, W., & Li, J. (2017) · Scientific Reports · doi:10.1038/srep42607 · Cited by 23

Effectiveness and Safety of Rivaroxaban 15 or 20 mg Versus Vitamin K Antagonists in Nonvalvular Atrial Fibrillation

Blin, P., Fauchier, L., Dureau-Pournin, C., Sacher, F., Dallongeville, J., Bernard, M., Lassalle, R., Droz‐Perroteau, C., & Moore, N. D. (2019) · Stroke · doi:10.1161/strokeaha.119.025824 · Cited by 23

In Utero Antidepressants and Neurodevelopmental Outcomes in Kindergarteners

Singal, D., Chateau, D. G., Struck, S., Lee, J. B., Dahl, M. E., Derksen, S., Katz, L. Y., Ruth, C., Hanlon‐Dearman, A., & Brownell, M. D. (2020) · PEDIATRICS · doi:10.1542/peds.2019-1157 · Cited by 23

Risk of Cardiovascular Events and Mortality Among Elderly Patients With Reduced GFR Receiving Direct Oral Anticoagulants

Ashley, J., McArthur, E., Bota, S. E., Harel, Z., Battistella, M., Molnar, A. O., Jun, M., Badve, S. V., Garg, A. X., Manuel, D. G., et al. (2020) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2020.02.446 · Cited by 23

Proton pump inhibitors and the risk of inflammatory bowel disease: population-based cohort study

Abrahami, D., Pradhan, R., Yin, H., Yanofsky, R. P., McDonald, E. G., Bitton, A., & Azoulay, L. (2023) · Gut · doi:10.1136/gutjnl-2022-328866 · Cited by 23

Metformin Versus Insulin and Risk of Major Congenital Malformations in Pregnancies With Type 2 Diabetes: A Nordic Register-Based Cohort Study

Kjerpeseth, L. J., Cesta, C. E., Furu, K., Engeland, A., Gissler, M., Gulseth, H. L., Karlstad, Ø., Leinonen, M. K., Pazzagli, L., Zoëga, H., et al. (2023) · Diabetes Care · doi:10.2337/dc23-0256 · Cited by 24

Direct-Acting Oral Anticoagulants and Antiseizure Medications for Atrial Fibrillation and Epilepsy and Risk of Thromboembolic Events

Acton, E. K., Hennessy, S., Gelfand, M. A., Leonard, C. E., Bilker, W. B., Shu, D., Willis, A. W., & Kasner, S. E. (2024) · JAMA Neurology · doi:10.1001/jamaneurol.2024.2057 · Cited by 23

Medical management, costs, and consequences of Alzheimer’s disease in Germany: an analysis of health claims data

Brüggenjürgen, B., Andersohn, F., Ezzat, N., Lacey, L. A., & Willich, S. N. (2015) · Journal of Medical Economics · doi:10.3111/13696998.2015.1014090 · Cited by 23

Use of Leukotriene Receptor Antagonists Are Associated with a Similar Risk of Asthma Exacerbations as Inhaled Corticosteroids

Wu, A. C., Li, L., Fung, V., Kharbanda, E. O., Larkin, E. K., Vollmer, W. M., Butler, M. G., Miroshnik, I. L., Rusinak, D., Davis, R. L., et al. (2014) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2014.05.009 · Cited by 23

Real-World Data Analytics Fit for Regulatory Decision-Making

Schneeweiß, S., & Glynn, R. J. (2018) · American Journal of Law & Medicine · doi:10.1177/0098858818789429 · Cited by 23

Relationship between early prescription dispensing patterns and work disability in a cohort of low back pain workers’ compensation claimants: a historical cohort study

Carnide, N., Hogg‐Johnson, S., Koehoorn, M. W., Furlan, A. D., & Côté, P. (2019) · Occupational and Environmental Medicine · doi:10.1136/oemed-2018-105626 · Cited by 23

E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance

Pretis, F. D., Landes, J., & Osimani, B. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.01317 · Cited by 24

Analytic and Data Sharing Options in Real‐World Multidatabase Studies of Comparative Effectiveness and Safety of Medical Products

Toh, S. (2019) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1754 · Cited by 23

Association between myelofibrosis and thromboembolism: A population‐based retrospective cohort study

Saliba, W., Mishchenko, E., Cohen, S., Rennert, G., & Preis, M. (2020) · Journal of Thrombosis and Haemostasis · doi:10.1111/jth.14754 · Cited by 23

Comparison of Calipers for Matching on the Disease Risk Score

Connolly, J. G., & Gagne, J. J. (2016) · American Journal of Epidemiology · doi:10.1093/aje/kwv302 · Cited by 22

Comparison of Mortality and Major Cardiovascular Events Among Adults With Type 2 Diabetes Using Human vs Analogue Insulins

Neugebauer, R. S., Schroeder, E. B., Reynolds, K., Schmittdiel, J. A., Loes, L., Dyer, W., DESAI, J. R., Vazquez‐Benitez, G., Ho, P. M., Anderson, J. P., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.18554 · Cited by 22

Prescribed opioid analgesics in early pregnancy and the risk of congenital anomalies: a population-based cohort study

Bowie, A. C., Werler, M. M., Vélez, M. P., Li, W., Camden, A., Guttmann, A., & Brogly, S. B. (2022) · Canadian Medical Association Journal · doi:10.1503/cmaj.211215 · Cited by 22

Identifying Protective Drugs for Parkinson's Disease in Health‐Care Databases Using Machine Learning

Courtois, É., Nguyen, T. T. H., Fournier, A., Carcaillon‐Bentata, L., Moutengou, E., Escolano, S., Tubert‐Bitter, P., Elbaz, A., Thiébaut, A. C. M., & Ahmed, I. (2022) · Movement Disorders · doi:10.1002/mds.29205 · Cited by 22

Restricted Mean Survival Time Analysis to Estimate SGLT2i–Associated Heterogeneous Treatment Effects on Primary and Secondary Prevention of Cardiorenal Outcomes in Patients With Type 2 Diabetes in Taiwan

Peng, Z., Yang, C., Kuo, S., Wu, C., Lin, W., & Ou, H. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.46928 · Cited by 23

Effectiveness and safety of empagliflozin: final results from the EMPRISE study

Htoo, P. T., Tesfaye, H., Schneeweiß, S., Wexler, D. J., Everett, B. M., Glynn, R. J., Schmedt, N., Koeneman, L., Déruaz‐Luyet, A., Paik, J. M., et al. (2024) · Diabetologia · doi:10.1007/s00125-024-06126-3 · Cited by 22

Propensity Score Methods and Unobserved Covariate Imbalance: Comments on “Squeezing the Balloon”

Ali, M. S., Groenwold, R. H. H., & Klungel, O. H. (2014) · Health Services Research · doi:10.1111/1475-6773.12152 · Cited by 22

Predicting 1-Year Statin Adherence Among Prevalent Users: A Retrospective Cohort Study

Krumme, A. A., Franklin, J. M., Isaman, D. L., Matlin, O. S., Tong, A. Y., Spettell, C. M., Brennan, T. A., Shrank, W. H., & Choudhry, N. K. (2017) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2017.23.4.494 · Cited by 22

Association between perioperative oral care and postoperative pneumonia after cancer resection: conventional versus high-dimensional propensity score matching analysis

Ishimaru, M., Ono, S., Matsui, H., & Yasunaga, H. (2019) · Clinical Oral Investigations · doi:10.1007/s00784-018-2783-5 · Cited by 22

Big data and real-world data-based medicine in the management of hypertension

Okada, M. (2020) · Hypertension Research · doi:10.1038/s41440-020-00580-3 · Cited by 24

Pharmacoepidemiology

Garbe, E., & Suissa, S. (2013) · Springer eBooks · doi:10.1007/978-0-387-09834-0_31 · Cited by 22

Observational Studies of Drug Safety in Multi-Database Studies: Methodological Challenges and Opportunities

Platt, R. W., Dormuth, C. R., Chateau, D. G., & Filion, K. B. (2016) · eGEMs (Generating Evidence & Methods to improve patient outcomes) · doi:10.13063/2327-9214.1221 · Cited by 21

Development and Application of Two Semi-Automated Tools for Targeted Medical Product Surveillance in a Distributed Data Network

Connolly, J. G., Wang, S. V., Fuller, C. C., Toh, S., Panozzo, C. A., Cocoros, N. M., Zhou, M., Gagne, J. J., & Maro, J. C. (2017) · Current Epidemiology Reports · doi:10.1007/s40471-017-0121-0 · Cited by 21

Effectiveness of spironolactone dispensation in reducing weekly alcohol use: a retrospective high-dimensional propensity score-matched cohort study

Palzes, V. A., Farokhnia, M., Kline‐Simon, A. H., Elson, J., Sterling, S., Leggio, L., Weisner, C. M., & Chi, F. W. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01117-z · Cited by 21

Research and scholarly methods: Propensity scores

Medaglio, D., Stephens‐Shields, A. J., & Leonard, C. E. (2022) · JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY · doi:10.1002/jac5.1591 · Cited by 22

Effectiveness of Prophylactic Use of Hepatoprotectants for Tuberculosis Drug-Induced Liver Injury: A Population-Based Cohort Analysis Involving 6,743 Chinese Patients

Chen, Q., Hu, A., Ma, A., Jiang, F., Xiao, Y., Chen, Y., Huang, R., Yang, T., & Zhou, J. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.813682 · Cited by 21

Machine learning for improving high‐dimensional proxy confounder adjustment in healthcare database studies: An overview of the current literature

Wyss, R., Yanover, C., El‐Hay, T., Bennett, D., Platt, R. W., Zullo, A. R., Sari, G., Wen, X., Ye, Y., Yuan, H., et al. (2022) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5500 · Cited by 22

Tell me what you want, what you really really want: Estimands in observational pharmacoepidemiologic comparative effectiveness and safety studies

Luijken, K., van EEKELEN, R., Gardarsdóttir, H., Groenwold, R. H. H., & van Geloven, N. (2023) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5620 · Cited by 21

Chronic kidney outcomes associated with GLP-1 receptor agonists versus long-acting insulins among type 2 diabetes patients requiring intensive glycemic control: a nationwide cohort study

Peng, Z., Yang, C.-T., Lin, W., Yao, W., Ou, H., & Kuo, S. (2023) · Cardiovascular Diabetology · doi:10.1186/s12933-023-01991-5 · Cited by 21

Analyzing patterns of drug use in clinical notes for patient safety.

LePendu, P., Liu, Y., Iyer, S. V., Udell, M. R., & Shah, N. H. (2012) · Europe PMC (PubMed Central) · Cited by 21

Near-Real-Time Monitoring of New Drugs: An Application Comparing Prasugrel Versus Clopidogrel

Gagne, J. J., Rassen, J. A., Choudhry, N. K., Bohn, R. L., Patrick, A. R., Sridhar, G., Daniel, G. W., Liu, J., & Schneeweiß, S. (2014) · Drug Safety · doi:10.1007/s40264-014-0136-0 · Cited by 21

Effect Estimation in Point-Exposure Studies with Binary Outcomes and High-Dimensional Covariate Data – A Comparison of Targeted Maximum Likelihood Estimation and Inverse Probability of Treatment Weighting

Pang, M., Schuster, T., Filion, K. B., Schnitzer, M. E., Eberg, M., & Platt, R. W. (2016) · The International Journal of Biostatistics · doi:10.1515/ijb-2015-0034 · Cited by 21

A General Propensity Score for Signal Identification Using Tree-Based Scan Statistics

Wang, S. V., Maro, J. C., Gagne, J. J., Patorno, E., Sreedhara, S. K., Stojanović, D., Eworuke, E., Baro, E., Ouellet‐Hellstrom, R., Nguyen, M., et al. (2021) · American Journal of Epidemiology · doi:10.1093/aje/kwab034 · Cited by 20

Association of Low-Dose Quetiapine and Diabetes

Højlund, M., Lund, L. C., Andersen, K., Correll, C. U., & Hallas, J. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.3209 · Cited by 20

The Relationship Between Valproate and Lamotrigine/Levetiracetam Use and Prognosis in Patients With Epilepsy and Heart Failure: A Danish Register-Based Study

Liang, D., Gardella, E., Kragholm, K. H., Polcwiartek, C., & Sessa, M. (2021) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2021.07.020 · Cited by 20

Spotlight influenza: Estimation of influenza vaccine effectiveness in elderly people with assessment of residual confounding by negative control outcomes, Finland, 2012/13 to 2019/20

Baum, U., Kulathinal, S., & Auranen, K. J. (2021) · Eurosurveillance · doi:10.2807/1560-7917.es.2021.26.36.2100054 · Cited by 20

A comparison of confounder selection and adjustment methods for estimating causal effects using large healthcare databases

Benasseur, I., Talbot, D. C., Durand, M., Holbrook, A. M., Matteau, A., Potter, B. J., Renoux, C., Schnitzer, M. E., Tarride, J., & Guertin, J. R. (2021) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5403 · Cited by 20

The incidence of cancer deaths among hypertensive patients in a large Chinese population: A cohort study

Wong, M. C. S., Tam, W., Lao, X. Q., Wang, H., Kwan, M. W. M., Cheung, C. S. K., Tong, E. L. H., Cheung, N. T., Griffiths, S. M., & Coats, A. J. S. (2014) · International Journal of Cardiology · doi:10.1016/j.ijcard.2014.10.028 · Cited by 20

Comparative cardiovascular safety of insulin secretagogues following hospitalization for ischemic heart disease among type 2 diabetes patients: a cohort study

Huang, Y., Abdelmoneim, A. S., Light, P. E., Qiu, W., & Simpson, S. H. (2014) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2014.11.012 · Cited by 21

Comparative effectiveness research: what is it and why do we need it in nephrology?

Chang, T. I., & Winkelmayer­, W. C. (2012) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfs154 · Cited by 20

Incentive-Based Primary Care: Cost and Utilization Analysis

Hollander, M. J., & Kadlec, H. (2015) · The Permanente Journal · doi:10.7812/tpp/15-045 · Cited by 20

Dose‐response relationship between sulfonylureas and major adverse cardiovascular events in elderly patients with type 2 diabetes

Abdelmoneim, A. S., Eurich, D. T., Senthilselvan, A., Qiu, W., & Simpson, S. H. (2016) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.4014 · Cited by 20

Tofacitinib Persistence in Patients with Rheumatoid Arthritis: A Retrospective Cohort Study

Fisher, A., Hudson, M., Platt, R. W., & Dormuth, C. R. (2020) · The Journal of Rheumatology · doi:10.3899/jrheum.191252 · Cited by 20

Risk for Post-Colonoscopy Irritable Bowel Syndrome in Patients With and Without Antibiotic Exposure: A Retrospective Cohort Study

Vajravelu, R. K., Shapiro, J. M., Ni, J., Thanawala, S. U., Lewis, J. D., & El‐Serag, H. B. (2021) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2021.08.049 · Cited by 20

Evaluating A Nonemergency Medical Transportation Benefit For Accountable Care Organization Members

Berkowitz, S. A., Ricks, K. A. B., Wang, J., Parker, M., Rimal, R., & DeWalt, D. A. (2022) · Health Affairs · doi:10.1377/hlthaff.2021.00449 · Cited by 20

On the role of marginal confounder prevalence – implications for the high‐dimensional propensity score algorithm

Schuster, T., Pang, M., & Platt, R. W. (2015) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.3773 · Cited by 20

FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal InferencePreprint

Wang, T., Morucci, M., Awan, M. U., Liu, Y., Roy, S., Rudin, C. D., & Volfovsky, A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.06315 · Cited by 22

Comparative Safety of In Utero Exposure to Buprenorphine Combined With Naloxone vs Buprenorphine Alone

Straub, L., Bateman, B. T., Hernández–Dı́az, S., Zhu, Y., Suarez, E. A., Vine, S. M., Jones, H. E., Connery, H. S., Davis, J. M., Gray, K. J., et al. (2024) · JAMA · doi:10.1001/jama.2024.11501 · Cited by 19

The risk of sudden cardiac arrest and ventricular arrhythmia with rosiglitazone versus pioglitazone: real-world evidence on thiazolidinedione safety

Leonard, C. E., Brensinger, C. M., Dawwas, G. K., Deo, R., Bilker, W. B., Soprano, S. E., Dhopeshwarkar, N., Flory, J., Bloomgarden, Z. T., Gagne, J. J., et al. (2020) · Cardiovascular Diabetology · doi:10.1186/s12933-020-00999-5 · Cited by 20

Better adherence with out-of-hospital healthcare improved long-term prognosis of acute coronary syndromes: Evidence from an Italian real-world investigation

Rea, F., Ronco, R., Pedretti, R. F. E., Merlino, L. G., & Corrao, G. (2020) · International Journal of Cardiology · doi:10.1016/j.ijcard.2020.06.017 · Cited by 19

Real-world effect of a potential drug-drug interaction between topiramate and oral contraceptives on unintended pregnancy outcomes

Sarayani, A., Winterstein, A., Cristofoletti, R., Vozmediano, V., Schmidt, S., & Brown, J. D. (2023) · Contraception · doi:10.1016/j.contraception.2023.109953 · Cited by 19

Novel methods for pregnancy drug safety surveillance in the FDA Sentinel System

Suarez, E. A., Nguyen, M., Zhang, D., Zhao, Y., Stojanović, D., Muñoz, M. A., Liedtka, J., Anderson, A., Liu, W., Dashevsky, I., et al. (2022) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5512 · Cited by 19

CT With CTA Versus MRI in Patients Presenting to the Emergency Department With Dizziness: Analysis Using Propensity Score Matching

Tu, L., Navaratnam, D. S., Melnick, E. R., Forman, H. P., Venkatesh, A. K., Malhotra, A., Yaesoubi, R., Sureshanand, S., Sheth, K. N., & Mahajan, A. K. (2023) · American Journal of Roentgenology · doi:10.2214/ajr.23.29617 · Cited by 19

Beneficiaries With Cardiovascular Disease and the Part D Coverage Gap

Polinski, J. M., Shrank, W. H., Glynn, R. J., Huskamp, H. A., Roebuck, M. C., & Schneeweiß, S. (2012) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.111.964866 · Cited by 19

Phenobarbital compared to benzodiazepines in alcohol withdrawal treatment: A register-based cohort study of subsequent benzodiazepine use, alcohol recidivism and mortality

Askgaard, G., Hallas, J., Fink‐Jensen, A., Molander, A., Madsen, K. G., & Pottegård, A. (2016) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2016.02.016 · Cited by 19

Increased risk of ischemic stroke in patients with burn injury: a nationwide cohort study in Taiwan

Hung, T., Lee, Y., Huang, M.-Y., Hsu, C.-Y., & Su, Y. (2016) · Scandinavian Journal of Trauma Resuscitation and Emergency Medicine · doi:10.1186/s13049-016-0236-1 · Cited by 19

A Review of Disease Risk Scores and Their Application in Pharmacoepidemiology

Wyss, R., Glynn, R. J., & Gagne, J. J. (2016) · Current Epidemiology Reports · doi:10.1007/s40471-016-0088-2 · Cited by 19

Evaluation of the Performance of the High-Dimensional Propensity Score Algorithm to Adjust for Confounding of Treatment Effects Estimated in Healthcare Claims Data

Le, H. V. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/9srw-nw85

Confounding adjustment via a semi‐automated high‐dimensional propensity score algorithm: an application to electronic medical records

Toh, S., Rodríguez, L. A. G., & Hernán, M. Á. (2011) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.2152 · Cited by 85

High dimensional versus conventional propensity score matching investigating gastrointestinal complications in coxib users vs. nonselective NSAIDS users

Garbe, E., Kloss, S., Schill, W., Suling, M., & Schneeweiss, S. (2011) · German Medical Science (German Research Foundation) · doi:10.3205/11gmds243

Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example

Le, H. V., Poole, C., Brookhart, M. A., Schoenbach, V. J., Beach, K. J., Layton, J. B., & Stürmer‎, T. (2013) · BMC Medical Research Methodology · doi:10.1186/1471-2288-13-142 · Cited by 24

High-dimensional versus conventional propensity scores in a comparative effectiveness study of coxibs and reduced upper gastrointestinal complications

Garbe, E., Kloss, S., Suling, M., Pigeot, I., & Schneeweiß, S. (2012) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-012-1334-2 · Cited by 60