Prevalent new-user cohort designs for comparative drug effect studies by time-conditional propensity scores.
OBJECTIVE
Studies of the real-world comparative effectiveness of drugs conducted using computerized healthcare databases typically involve an incident new-user cohort design for head-to-head comparisons between two medications, using exclusively treatment-naïve patients. However, the desired contrast often involves one new drug compared with an older drug, of which many users of the new drug may have switched from, seriously restricting the scope of incident new-user studies.


METHODS
We introduce prevalent new-user cohort designs for head-to-head comparative drug effect studies, where incident new users are scarce. We define time-based and prescription-based exposure sets to compute time-conditional propensity scores of initiating the newer drug and to identify matched subjects receiving the comparator drug. We illustrate this approach using data from the UK's Clinical Practice Research Datalink to evaluate whether the newer glucagon-like peptide-1 receptor agonists (GLP-1 analogs) used to treat type 2 diabetes increase the risk of heart failure, in comparison with the older similarly indicated sulfonylureas.


RESULTS
Of the 170 031 users of antidiabetic agents from 2000 onwards, 79 682 used sulfonylureas (first use 2000), while 6196 used GLP-1 analogs (first use 2007), 75% of which had previously used a sulfonylurea. After matching each GLP-1 analog user to a sulfonylurea user on the time-conditional propensity scores from prescription-based exposure sets, the hazard ratio of heart failure with GLP-1 use was 0.73 (95%CI: 0.57-0.93).


CONCLUSIONS
The proposed prevalent new-user cohort design for comparative drug effects studies allows the use of all or most patients exposed to the newer drug, thus permitting a more comprehensive assessment of a new drug's safety. Copyright © 2016 John Wiley & Sons, Ltd.
Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada.|McGill Pharmacoepidemiology Research Unit, McGill University, Montreal, Quebec, Canada.|Centre for Clinical Epidemiology, Jewish General Hospital, Montreal, Quebec, Canada.
Samy
S
Suissa
Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada.
Erica E M
EE
Moodie
McGill Pharmacoepidemiology Research Unit, McGill University, Montreal, Quebec, Canada.|Centre for Clinical Epidemiology, Jewish General Hospital, Montreal, Quebec, Canada.
Sophie
S
Dell'Aniello
D000368:Aged; D015331:Cohort Studies; D057186:Comparative Effectiveness Research / Q000379:methods; D016208:Databases, Factual / Q000706:statistics & numerical data*; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy; D005260:Female; D006333:Heart Failure / Q000139:chemically induced / Q000453:epidemiology; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage / Q000009:adverse effects*; D008297:Male; D008875:Middle Aged; D017891:Pharmacoepidemiology / Q000379:methods*; D057216:Propensity Score; D016016:Proportional Hazards Models; D012107:Research Design; D013453:Sulfonylurea Compounds / Q000008:administration & dosage / Q000009:adverse effects; D013997:Time Factors; D006113:United Kingdom; D000097789:Glucagon-Like Peptide-1 Receptor Agonists
D007004:Hypoglycemic Agents; D013453:Sulfonylurea Compounds; D000097789:Glucagon-Like Peptide-1 Receptor Agonists
cohort studies; comparative effectiveness; database research; drug safety; epidemiologic design; pharmacoepidemiology