Scientific Publications



Selected Publications by the Aetion Team

Members of the Aetion team publish frequently on methods for the evaluation of the effectiveness, safety and value of medical products in major peer-reviewed journals.  Below you will find a selection of recent and high-impact publications, all of which are available for download from their publishers. 

Publications on Research with Real-World Data

Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005;58:323-37.

Schneeweiss S. A basic study design for expedited safety signal evaluation based on electronic healthcare data. Pharmaceopidemiol Drug Safety 2010;19:858-68.

Rassen JA, Solomon DH, Glynn RJ, Schneeweiss S. Simultaneously assessing intended and unintended treatment effects of multiple treatment options: a pragmatic “matrix design”. Pharmacoepidemiol Drug Safety 2011;20:675-83.

Schneeweiss S. Learning from big healthcare data. N Engl J Med 2014;370:2161-3.

Schneeweiss S, Gagne JJ, Glynn RJ, Ruhl M, Rassen JA. Assessing the comparative effectiveness of newly marketed medications. Clin Pharm Ther 2011;90:777-90.

Goodman SN, Schneeweiss S, Baiocchi M. Big Data and “Real World Evidence”: Time to differentiate the useful from the known bad. JAMA 2017 in press.

Najafzadeh M, Schneeweiss S. From trials to target populations: calibrating risk-factor information. N Engl J Med 2017 in press.  

Publications Demonstrating Key Analytic Methods

Scientific Reporting

Schneeweiss S, Suissa S. Advanced approaches to controlling confounding in pharmacoepidemiologic studies, pp. 868-891. In: Strom BL, Kimmel SE, Hennessey S: Pharmacoepidemiology, 5th edition, John Wiley&Sons, Chichester, 2012.

Comparative Effectiveness

Gagne JJ, Bykov K, Willke RJ, Kahler KH, Subedi P, Schneeweiss S. Treatment dynamics of newly marketed drugs: implications for comparative effectiveness research. Value Health 2013;16:1054-62.

Eichler HG, Baird LG, Barker R, Bloechl-Daum B, Børlum-Kristensen F, et al. From adaptive licensing to adaptive pathways: delivering a flexible life-span approach to bring new drugs to patients. Clin Pharmacol Ther. 2015;97:234-46.

Franklin JM, Eddings W, Schneeweiss S Rassen JA. Incorporating linked healthcare claims to improve confounding control in a study of in-hospital medication use. Drug Safety 2015;38:589-600.

Program Evaluation

Schneeweiss S, Maclure M, Dormuth C, Glynn RJ, Canning C, Avorn J. A therapeutic substitution policy for proton pump inhibitors: clinical and economic consequences. Clin Pharm Ther 2006;79:379-88.

Schneeweiss S, Patrick AR, Maclure M, Dormuth C, Glynn RJ. Adherence to statin therapy under drug cost-sharing in patients with and without acute MI: A population-based natural experiment. Circulation 2007;115:2128-35.

Drug Use

Polinski J, Glynn RJ, Brookhart MA, Schneeweiss S. Medicare Part D’s impact on antipsychotic drug use and cost among elderly patients without prior drug insurance. J Clin Psychopharm 2012;32:3-10.

Population Description

Rassen JA, Schneeweiss S. Newly marketed medications present unique challenges for non-randomized comparative effectiveness analyses. J Comp Effect Res 2012;1:109-11.

Patient Privacy

Sarpatwari A, Kesselheim AS, Malin BA, Gagne JJ, Schneeweiss S. Utility and Liability Trade-Offs in Sharing Data for Post-Approval Drug and Device Research. N Engl J Med 2014;371:1644-9.

Publications On Development of Analytic Methods

Propensity Score Methods

Schneeweiss S, Rassen JR, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 2009;20:512-22. 

Rassen JA, Schneeweiss S. Using high-dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system. Pharmacoepidemiol Drug Safety 2012;21 S1:41-9.

Brookhart MA, Schneeweiss S, Rothman K, Glynn RJ, Avorn J, Sturmer T. Variable selection in propensity score models. Am J Epidemiol 2006;163:1149-56. 

Rassen JA, Shelat AA, Myers J, Glynn RJ, Rothman KJ, Schneeweiss S. One-to-many propensity score matching in cohort studies. Pharmacoepidemiol Drug Saf 2012;21(S2):69-80.

Rassen JA, Shelat AA, Myers J, Glynn RJ, Schneeweiss S. Matching by propensity score in cohort studies with three treatment groups. Epidemiology 2013;24:401-9.

Franklin JM, Rassen JA, Ackermann D, Bartels DB, Schneeweiss S. Metrics for covariate balance in cohort studies of causal effects: Varying associations with bias. Stat Med 2014;33:1685-99. 

Franklin JM, Schneeweiss S, Polinski JM, Rassen JA. Plasmode simulation for the evaluation of pharmaco­epidemiologic methods in complex healthcare databases. Comp Stat Data Analysis 2014;72:219-26 

Neugebauer R, Schmittdiel JA, Zhu Z, Rassen JA, Seeger JD, Schneeweiss S. High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions. Stat Med 2014;34:753-81.

Glynn RJ, Gagne JJ, Schneeweiss S. Role of disease risk scores for comparative effectiveness with emerging therapies. Pharmacoepidemiol Drug Saf 2012; 21(S2): 138-47.

Franklin JM, Eddings W, Austin PC, Stuart EA, Schneeweiss S.  Comparing the performance of propensity score methods in healthcare database studies with rare outcomes. Statistics in Medicine 2017 Feb 17. [Epub ahead of print]

Schneeweiss S, Eddings W, Glynn RJ, Patorno E, Rassen JA, Franklin JM. Variable selection for confounding adjustment in high-dimensional covariate spaces when analyzing healthcare databases. Epidemiology 2017;28:237-48.

Net Benefit Analyses

Najafzadeh M, Gagne JJ, Choudhry NK, Polinski J, Avorn J, Schneeweiss S. Patients’ preferences for risk and benefits of anticoagulant therapy: A discrete choice experiment. Circulation: Cardio Qual Outcomes 2014;7:912-9.

Najafzadeh M, Schneeweiss S, Choudhry NK, Bykov K, Martin D, Kahler K, Gagne JJ. A unified framework for classification of methods for benefit-risk assessment. Value Health 2015;18:250-9

Instrumental Variable Analyses

Rassen JA, Brookhart MA, Glynn RJ, Mittleman M, Schneeweiss S. Instrumental variables I: Instrumental variables exploit natural variation in non-experimental data to estimate causal relationships. J Clin Epidemiol 2009;62:1226-32.

Rassen J, Schneeweiss S, Glynn RJ, Mittleman M, Brookhart MA. Two-stage instrumental variable modeling approaches for estimation of treatment effects with dichotomous outcomes. Am J Epidemiol 2009;169:273-84.

Myers J, Rassen J, Gagne JJ, Huybrechts K, Schneeweiss S, Rothman KJ, Joffe MM, Glynn RJ. Effects of adjusting for instrumental variables on bias and precision of effect estimates. Am J Epidemiol 2011;174:1213-22.