Optimal threshold of adherence to lipid lowering drugs in predicting acute coronary syndrome, stroke, or mortality: A cohort study
Autoři:
Arsène Zongo aff001; Scot Simpson aff004; Jeffrey A. Johnson aff001; Dean T. Eurich aff001
Působiště autorů:
School of Public Health, University of Alberta, Edmonton, Alberta, Canada
aff001; Faculty of Pharmacy, Université Laval, Quebec City, Quebec, Canada
aff002; Population Health and Optimal Health Practices Research Unit, CHU de Québec—Université Laval Research Centre, Quebec City, Quebec, Canada
aff003; Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
aff004
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223062
Souhrn
Objective
Thresholds defining medication adherence are rarely evidence-based. A threshold of 0.8 is typically presumed to achieve improved outcomes. We aimed to assess the optimal threshold of adherence to lipid-lowering drugs (LLD) in predicting cardiovascular-related (CV) outcomes in patients with hypertension.
Design
Cohort study of new users of LLDs.
Setting
Comprehensive healthcare administrative databases of the province of Alberta (Canada) from 2008 to 2016.
Participants
Patients with hypertension, who were new users of LLDs. Patients who had the outcomes prior to the initiation of LLD were excluded.
Main outcomes measures
Hospitalization for acute coronary syndrome (ACS)/stroke, CV-related mortality and all-cause mortality.
Statistical analysis
Adherence to LLDs was assessed as the proportion of days covered (PDC) by any LLD, from drug initiation to censoring, outcome, or study end. Three methods were used to assess the threshold: Contal and O'Quigley method, minimum distance method, and Youden's J index. Cox regressions were used to assess the risk associated with each method-specific threshold and Akaike information criteria were used to retain the optimal threshold after adjustment.
Results
52229 patients were included; 4.0% were hospitalized for ACS/stroke, 3.4% died, and 1.3% died from CV-related cause. In predicting ACS/stroke, CV-related and all-cause mortality, the optimal adherence threshold was 0.52 (range: 0.51–0.54), 0.79 (0.45–0.87), and 0.84 (0.79–0.89), respectively. These results were consistent among patients aged ≥ 65 years (n = 19804). However, the results varied among those aged < 65 years, where the incidence rates of outcomes were low.
Conclusion
In new-users of LLDs with hypertension, approximately 50% days covered by LLDs may be enough to prevent long-term occurrence of ACS, or stroke. However, a threshold near 0.80 may be needed to prevent or reduce the risk of all-cause or CV-related mortality.
Klíčová slova:
Coronary heart disease – Drug adherence – Heart failure – Hypertension – Lipids – Mental health and psychiatry – Alberta
Zdroje
1. Poulter NR, Prabhakaran D, Caulfield M. Hypertension. Lancet. 2015;386(9995):801–12. Epub 2015/04/03. doi: 10.1016/S0140-6736(14)61468-9 25832858.
2. Mahmood SS, Levy D, Vasan RS, Wang TJ. The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective. Lancet. 2014;383(9921):999–1008. Epub 2013/10/03. doi: 10.1016/S0140-6736(13)61752-3 24084292; PubMed Central PMCID: PMC4159698.
3. O'Donnell CJ, Elosua R. Cardiovascular risk factors. Insights from Framingham Heart Study. Rev Esp Cardiol. 2008;61(3):299–310. Epub 2008/03/26. 18361904.
4. Naci H, Brugts JJ, Fleurence R, Tsoi B, Toor H, Ades AE. Comparative benefits of statins in the primary and secondary prevention of major coronary events and all-cause mortality: a network meta-analysis of placebo-controlled and active-comparator trials. Eur J Prev Cardiol. 2013;20(4):641–57. doi: 10.1177/2047487313480435 23447425.
5. Stewart J, Manmathan G, Wilkinson P. Primary prevention of cardiovascular disease: A review of contemporary guidance and literature. JRSM Cardiovasc Dis. 2017;6:2048004016687211. Epub 2017/03/14. doi: 10.1177/2048004016687211 28286646; PubMed Central PMCID: PMC5331469.
6. Thavendiranathan P, Bagai A, Brookhart MA, Choudhry NK. Primary prevention of cardiovascular diseases with statin therapy: a meta-analysis of randomized controlled trials. Arch Intern Med. 2006;166(21):2307–13. Epub 2006/11/30. doi: 10.1001/archinte.166.21.2307 17130382.
7. Banach M, Stulc T, Dent R, Toth PP. Statin non-adherence and residual cardiovascular risk: There is need for substantial improvement. Int J Cardiol. 2016;225:184–96. Epub 2016/10/12. doi: 10.1016/j.ijcard.2016.09.075 27728862.
8. Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ. 2006;332(7549):1080. doi: 10.1136/bmj.332.7549.1080 16675816; PubMed Central PMCID: PMC1458573.
9. Sackett DL, Haynes RB, Gibson ES, Hackett BC, Taylor DW, Roberts RS, et al. Randomised clinical trial of strategies for improving medication compliance in primary hypertension. Lancet. 1975;1(7918):1205–7. Epub 1975/05/31. doi: 10.1016/s0140-6736(75)92192-3 48832.
10. Karve S, Cleves MA, Helm M, Hudson TJ, West DS, Martin BC. Good and poor adherence: optimal cut-point for adherence measures using administrative claims data. Curr Med Res Opin. 2009;25(9):2303–10. Epub 2009/07/29. doi: 10.1185/03007990903126833 19635045.
11. Lo-Ciganic WH, Donohue JM, Thorpe JM, Perera S, Thorpe CT, Marcum ZA, et al. Using machine learning to examine medication adherence thresholds and risk of hospitalization. Med Care. 2015;53(8):720–8. Epub 2015/07/07. doi: 10.1097/MLR.0000000000000394 26147866; PubMed Central PMCID: PMC4503478.
12. McCormick N, Bhole V, Lacaille D, Avina-Zubieta JA. Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review. PLoS One. 2015;10(8):e0135834. Epub 2015/08/21. doi: 10.1371/journal.pone.0135834 26292280; PubMed Central PMCID: PMC4546158.
13. McCormick N, Lacaille D, Bhole V, Avina-Zubieta JA. Validity of myocardial infarction diagnoses in administrative databases: a systematic review. PLoS One. 2014;9(3):e92286. Epub 2014/04/01. doi: 10.1371/journal.pone.0092286 24682186; PubMed Central PMCID: PMC3969323.
14. Toms JD M-A V. Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives. Avian Conservation and Ecology. 2015;10(1):2. http://dx.doi.org/10.5751/ACE-00715-100102.
15. Contal C, O'Quigley J. An application of changepoint methods in studying the effect of age on survival in breast cancer. Computational Statistics & Data Analysis. 1999;30(3):253–70. https://doi.org/10.1016/S0167-9473(98)00096-6.
16. Mandrekar JN MS, Cha SS. Cutpoint determination methods in survival analysis using SAS®. (Paper 261–28). Proceedings of the 28th SAS Users Group International Conference (SUGI 28). 2003.
17. Meyers J. P. MJN, Mayo Clinic, Rochester, MN. Cutpoint Determination Methods in Survival Analysis using SAS®: Updated %FINDCUT macro (Paper 3249) http://www.sascommunity.org/mwiki/images/0/01/Findcut_Final_Paper.pdf. 2015.
18. Indrayan A. Medical Biostatistics. Chapman & Hall/CRC Press. 2012;Third Edition:1008.
19. Hajian-Tilaki K. Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation. Caspian J Intern Med. 2013;4(2):627–35. Epub 2013/09/07. 24009950; PubMed Central PMCID: PMC3755824.
20. Burnham KP, Anderson DR. Multimodel Inference:Understanding AIC and BIC in Model Selection. Sociological Methods & Research. 2004;33(2):261–304. doi: 10.1177/0049124104268644
21. Corella D, Ordovas JM. Aging and cardiovascular diseases: the role of gene-diet interactions. Ageing Res Rev. 2014;18:53–73. doi: 10.1016/j.arr.2014.08.002 25159268.
22. North BJ, Sinclair DA. The intersection between aging and cardiovascular disease. Circ Res. 2012;110(8):1097–108. doi: 10.1161/CIRCRESAHA.111.246876 22499900; PubMed Central PMCID: PMC3366686.
Článek vyšel v časopise
PLOS One
2019 Číslo 9
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Je libo čepici místo mozkového implantátu?
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
- AI může chirurgům poskytnout cenná data i zpětnou vazbu v reálném čase
- Nová metoda odlišení nádorové tkáně může zpřesnit resekci glioblastomů
Nejčtenější v tomto čísle
- Graviola (Annona muricata) attenuates behavioural alterations and testicular oxidative stress induced by streptozotocin in diabetic rats
- CH(II), a cerebroprotein hydrolysate, exhibits potential neuro-protective effect on Alzheimer’s disease
- Comparison between Aptima Assays (Hologic) and the Allplex STI Essential Assay (Seegene) for the diagnosis of Sexually transmitted infections
- Assessment of glucose-6-phosphate dehydrogenase activity using CareStart G6PD rapid diagnostic test and associated genetic variants in Plasmodium vivax malaria endemic setting in Mauritania
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy