Individualized NSAID prescribing based on gastrointestinal and cardiovascular risks
A decision model in the SOS project
Masclee, GMC., Valkhoff, VE., Straatman, H., Herings, R., Garbe, E., Schink, T., Kollhorst, B., Arfe, A., Lucchi, S., Villa, M., Castellsague, J., Perez-Gutthann, S., Varas-Lorenzo, C., Schade, R., Schuemie, MJ., Vergouwe, Y., Steyerberg, E., Sturkenboom, M., & Romio, SA. (2015). Individualized NSAID prescribing based on gastrointestinal and cardiovascular risks: A decision model in the SOS project. Pharmacoepidemiology and Drug Safety, 24(S1), 36-37. https://doi.org/10.1002/pds.3838
Background: Use of non-steroidal anti-inﬂammatory drugs (NSAIDs) can increase the risk of upper gastro-intestinal complications (UGIC) and cardiovascular(CV) events. However, the risk may differ between individual NSAIDs and subjects. Decision models for selecting the safest NSAID to treat individual patients are not available. Objectives: The aim of this study was to provide a decision analytic model to guide physicians in the choice of NSAID treatment that would yield the lowest GI and CV risk for individual patients. Methods: Design: We produced a decision model integrating information from (i) a case–control studyon individual NSAIDs and UGIC and CV events; (ii)a risk function for patient characteristics associated with UGIC and CV events; and (iii) disutility weights at 4 weeks: 0.54 for UGIC, 0.65 for ischemic stroke (iCVA), 0.63 for acute myocardial infarction(AMI), and 0.29 for heart failure (HF). Setting: Weused six European healthcare data sources: (IPCI,PHARMO (NL); SISR, OSSIFF (Italy); GePaRD(Germany) and THIN (UK). The data source speciﬁc study period was 1999–2011. Exposure: Thirteen NSAIDs were used. Outcome: Outcomes were UGIC, iCVA, AMI and HF hospitalizations. Statistical analysis: We calculated adjusted odds ratios (ORs) for UGIC and CV events during individual NSAID exposure. A Poisson regression model was used forrisk function. A decision tree was used for the decision model. Results: In the case–control study, 23411 UGIC,35691 iCVA, 68 757 AMI, and 79876 HF cases were identiﬁed among 8.9 million new NSAID users. The lowest risks were seen for use of celecoxib for UGIC(OR= 1.1) and for HF (OR =1.0), for iCVA for ketoprofen (OR =0.9) and for AMI for tenoxicamand aceclofenac (OR = 1.0). For all outcomes, ketorolac yielded the highest risks. In the risk function, for each outcome, age was the most important predictor, followed by a prior history of the event and sex. In the ﬁnal decision model, over different scenarios, most preferable NSAIDs we reaceclofenac and celecoxib; thereafter, nimesulide and ibuprofen. Piroxicam and ketorolac were the least preferable NSAIDs. Conclusions: The SOS study provided an integratedGI and CV safety decision model for new NSAID users, which may guide physicians in clinical decision making.