| アブストラクト | INTRODUCTION: A patient is eligible for statins in England if they have a 10-year risk of cardiovascular disease >10%. We hypothesize that if statin discontinuation rates are high it may be better to delay statin initiation until patients are at a higher risk, to maximize the benefit of the drug. METHODS: A four-state health state transition model was used to assess the optimal time to initiate statins after a risk assessment, in order to prevent the highest number of cardiovascular events, for a given risk profile (age, gender, risk) and adherence rate. A Clinical Practice Research Datalink dataset linked to Hospital Episodes Statistics and Office for National Statistics was used to inform the transition probabilities in this model, taking into account observed statin discontinuation and re-continuation patterns. RESULTS: Our results suggest, if statins are initiated in a cohort of 50-year old men with a 10% 10-year risk, we prevent 4.78 events per 100 individuals. If we wait 10 years to prescribe, at which point 10-year risk scores are at 20%, we prevent 5.45 events per 100 individuals. If the observed discontinuation rate was reduced by a sixth, third or half in the same cohort, we would prevent 7.29, 9.01 or 10.22 events per 100 individuals. CONCLUSIONS: In certain scenarios, extra cardiovascular disease events could be prevented by delaying statin initiation beyond a risk of 10% until reaching a age (59 for men, 63 for women), based on statin discontinuation rates in England. The optimal time to initiate statins was driven by age, not by cardiovascular risk. |
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| ジャーナル名 | Pharmacoepidemiology and drug safety |
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| 投稿日 | 2020/5/13 |
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| 投稿者 | Pate, Alexander; Elliott, Rachel A; Gkountouras, Georgios; Thompson, Alexander; Emsley, Richard; van Staa, Tjeerd |
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| 組織名 | Centre for Health Informatics, School of Health Sciences, Faculty of Biology,;Medicine and Health, The University of Manchester, Manchester, UK.;Manchester Centre for Health Economics, School of Health Sciences, Faculty of;Biology, Medicine and Health, The University of Manchester, Manchester, UK.;Department of Biostatistics and Health Informatics, Institute of Psychiatry,;Psychology and Neuroscience, King's College London, London, UK. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/32394495/ |
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