{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T19:30:56Z","timestamp":1767900656541,"version":"3.49.0"},"reference-count":43,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"21","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circulation"],"published-print":{"date-parts":[[2013,11,19]]},"abstract":"<jats:sec>\n            <jats:title>Background\u2014<\/jats:title>\n            <jats:p>Current guidelines for prescribing antihypertensive medications focus on reaching specific blood pressure targets. We sought to determine whether antihypertensive medications could be used more effectively by a treatment strategy based on tailored estimates of cardiovascular disease events prevented.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods and Results\u2014<\/jats:title>\n            <jats:p>We developed a nationally representative sample of American adults aged 30 to 85 years with no history of myocardial infarction, stroke, or severe congestive heart failure using the National Health and Nutrition Examination Survey III. We then created a simulation model to estimate the effects of 5 years of treatment with treat-to-target (treatment to specific blood pressure goals) and benefit-based tailored treatment (treatment based on estimated cardiovascular disease event reduction) approaches to antihypertensive medication management. All effect size estimates were derived directly from meta-analyses of randomized trials. We found that 55% of the overall population of 176 million Americans would be treated identically under the 2 treatment approaches. Benefit-based tailored treatment would prevent 900\u2009000 more cardiovascular disease events and save 2.8 million more quality-adjusted life-years, despite using 6% fewer medications over 5 years. In the 45% of the population treated differently by the strategies, benefit-based tailored treatment would save 159 quality-adjusted life-years per 1000 treated versus 74 quality-adjusted life-years per 1000 treated by the treat-to-target approach. The findings were robust to sensitivity analyses.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions\u2014<\/jats:title>\n            <jats:p>We found that benefit-based tailored treatment was both more effective and required less antihypertensive medication than current guidelines based on treating to specific blood pressure goals.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/circulationaha.113.002290","type":"journal-article","created":{"date-parts":[[2013,11,5]],"date-time":"2013-11-05T04:14:10Z","timestamp":1383624850000},"page":"2309-2317","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":76,"title":["Using Benefit-Based Tailored Treatment to Improve the Use of Antihypertensive Medications"],"prefix":"10.1161","volume":"128","author":[{"given":"Jeremy","family":"Sussman","sequence":"first","affiliation":[{"name":"From the Division of General Internal Medicine, University of Michigan (J.S., S.V., R.H.), and the Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI (J.S., S.V., R.H.)."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandeep","family":"Vijan","sequence":"additional","affiliation":[{"name":"From the Division of General Internal Medicine, University of Michigan (J.S., S.V., R.H.), and the Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI (J.S., S.V., R.H.)."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rod","family":"Hayward","sequence":"additional","affiliation":[{"name":"From the Division of General Internal Medicine, University of Michigan (J.S., S.V., R.H.), and the Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI (J.S., S.V., R.H.)."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"276","reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-6-18"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1161\/circoutcomes.111.964676"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1161\/circoutcomes.110.959239"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0002-9343(02)01160-9"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(98)11415-0"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-152-2-201001190-00004"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(09)60503-1"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1001\/archinternmed.2010.150"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1475-6773.2009.01075.x"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.289.19.2560"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1136\/hrt.2005.079988"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/0002-8703(91)90861-B"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.b1665"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1001\/archinternmed.2010.150"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1475-6773.2009.01075.x"},{"key":"e_1_3_4_17_2","unstructured":"National Center for Health Statistics. 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