%0 Journal Article %1 Franklin2015 %A Franklin, Jessica M. %A Krumme, Alexis A. %A Tong, Angela Y. %A Shrank, William H. %A Matlin, Olga S. %A Brennan, Troyen A. %A Choudhry, Niteesh K. %D 2015 %J Pharmacoepidemiology and Drug Safety %K adherence comparativeeffectiveness epidemiologicmethods prediction trajectories %N 10 %P 1105-1113 %R 10.1002/pds.3787 %T Association between trajectories of statin adherence and subsequent cardiovascular events %U http://www.ncbi.nlm.nih.gov/pubmed/25903307 http://doi.wiley.com/10.1002/pds.3787 %V 24 %X PURPOSE Trajectory models have been shown to (1) identify groups of patients with similar patterns of medication filling behavior and (2) summarize the trajectory, the average adherence in each group over time. However, the association between adherence trajectories and clinical outcomes remains unclear. This study investigated the association between 12-month statin trajectories and subsequent cardiovascular events. METHODS We identified patients with insurance coverage from a large national insurer who initiated a statin during January 1, 2007 to December 31, 2010. We assessed medication adherence during the 360 days following initiation and grouped patients based on the proportion of days covered (PDC) and trajectory models. We then measured cardiovascular events during the year after adherence assessment. Cox proportional hazards models were used to evaluate the association between adherence measures and cardiovascular outcomes; strength of association was quantified by the hazard ratio, the increase in model C-statistic, and the net reclassification index (NRI). RESULTS Among 519 842 statin initiators, 8777 (1.7%) had a cardiovascular event during follow-up. More consistent medication use was associated with a lower likelihood of clinical events, whether adherence was measured through trajectory groups or PDC. When evaluating the prediction of future cardiovascular events by including a measure of adherence in the model, the best model reclassification was observed when adherence was measured using three or four trajectory groups (NRI = 0.189; 95% confidence interval: 0.171, 0.210). CONCLUSIONS Statin adherence trajectory predicted future cardiovascular events better than measures categorizing PDC. Thus, adherence trajectories may be useful for targeting adherence interventions.

@article{Franklin2015, abstract = {PURPOSE Trajectory models have been shown to (1) identify groups of patients with similar patterns of medication filling behavior and (2) summarize the trajectory, the average adherence in each group over time. However, the association between adherence trajectories and clinical outcomes remains unclear. This study investigated the association between 12-month statin trajectories and subsequent cardiovascular events. METHODS We identified patients with insurance coverage from a large national insurer who initiated a statin during January 1, 2007 to December 31, 2010. We assessed medication adherence during the 360 days following initiation and grouped patients based on the proportion of days covered (PDC) and trajectory models. We then measured cardiovascular events during the year after adherence assessment. Cox proportional hazards models were used to evaluate the association between adherence measures and cardiovascular outcomes; strength of association was quantified by the hazard ratio, the increase in model C-statistic, and the net reclassification index (NRI). RESULTS Among 519 842 statin initiators, 8777 (1.7%) had a cardiovascular event during follow-up. More consistent medication use was associated with a lower likelihood of clinical events, whether adherence was measured through trajectory groups or PDC. When evaluating the prediction of future cardiovascular events by including a measure of adherence in the model, the best model reclassification was observed when adherence was measured using three or four trajectory groups (NRI = 0.189; 95% confidence interval: [0.171, 0.210]). CONCLUSIONS Statin adherence trajectory predicted future cardiovascular events better than measures categorizing PDC. Thus, adherence trajectories may be useful for targeting adherence interventions.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Franklin, Jessica M. and Krumme, Alexis A. and Tong, Angela Y. and Shrank, William H. and Matlin, Olga S. and Brennan, Troyen A. and Choudhry, Niteesh K.}, biburl = {https://www.bibsonomy.org/bibtex/2162584b4fef2d732b900f9290b6dd371/jepcastel}, doi = {10.1002/pds.3787}, interhash = {cdc7ade562d4e8c467851fe4088e5d7f}, intrahash = {162584b4fef2d732b900f9290b6dd371}, issn = {10538569}, journal = {Pharmacoepidemiology and Drug Safety}, keywords = {adherence comparativeeffectiveness epidemiologicmethods prediction trajectories}, month = {10}, note = {Adherence; Group-based trajectory models}, number = 10, pages = {1105-1113}, pmid = {25903307}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Association between trajectories of statin adherence and subsequent cardiovascular events}, url = {http://www.ncbi.nlm.nih.gov/pubmed/25903307 http://doi.wiley.com/10.1002/pds.3787}, volume = 24, year = 2015 }