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Evidence-Based Medicine, Heterogeneity of Treatment Effects, and the Trouble with Averages
Evidence-based medicine is the application of scientific evidence to clinical practice. This article discusses the difficulties of applying global evidence ("average effects" measured as population means) to local problems (individual patients or groups who might depart from the population...
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Published in: | The Milbank quarterly 2004-01, Vol.82 (4), p.661-687 |
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description | Evidence-based medicine is the application of scientific evidence to clinical practice. This article discusses the difficulties of applying global evidence ("average effects" measured as population means) to local problems (individual patients or groups who might depart from the population average). It argues that the benefit or harm of most treatments in clinical trials can be misleading and fail to reveal the potentially complex mixture of substantial benefits for some, little benefit for many, and harm for a few. Heterogeneity of treatment effects reflects patient diversity in risk of disease, responsiveness to treatment, vulnerability to adverse effects, and utility for different outcomes. Recognizing these factors, researchers can design studies that better characterize who will benefit from medical treatments, and clinicians and policymakers can make better use of the results. |
doi_str_mv | 10.1111/j.0887-378X.2004.00327.x |
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This article discusses the difficulties of applying global evidence ("average effects" measured as population means) to local problems (individual patients or groups who might depart from the population average). It argues that the benefit or harm of most treatments in clinical trials can be misleading and fail to reveal the potentially complex mixture of substantial benefits for some, little benefit for many, and harm for a few. Heterogeneity of treatment effects reflects patient diversity in risk of disease, responsiveness to treatment, vulnerability to adverse effects, and utility for different outcomes. Recognizing these factors, researchers can design studies that better characterize who will benefit from medical treatments, and clinicians and policymakers can make better use of the results.</description><subject>Adverse effects</subject><subject>Clinical trials</subject><subject>Drug Approval - legislation & jurisprudence</subject><subject>Evidence based medicine</subject><subject>Experimentation</subject><subject>genomics</subject><subject>Health care</subject><subject>Health outcomes</subject><subject>Heterogeneity</subject><subject>Humans</subject><subject>Medical practice</subject><subject>Medical research</subject><subject>Original</subject><subject>Policy Making</subject><subject>Population characteristics</subject><subject>Practice Patterns, Physicians</subject><subject>Randomized controlled trials</subject><subject>Randomized Controlled Trials as Topic</subject><subject>Research design</subject><subject>Research methodology</subject><subject>Sample size</subject><subject>Side effects</subject><subject>Sociology</subject><subject>Sociology of health and medicine</subject><subject>Statistics</subject><subject>Strokes</subject><subject>Treatment Outcome</subject><subject>United States</subject><subject>United States Food and Drug Administration</subject><subject>USA</subject><issn>0887-378X</issn><issn>1468-0009</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><sourceid>7TQ</sourceid><sourceid>8BJ</sourceid><recordid>eNqNkV1v0zAUhiMEYt3gHyAUIbGrpdiOv3IB0laVbVI3xDQE4saynZPWXZoMO-3af49Dqw64Ad_4433eo-PzJkmK0RDH9W4-RFKKLBfy25AgRIcI5UQM10-SAaZcZgih4mky2EMHyWEI8_iK8lw-Tw4wYwUrKB8k38crV0JjITvTAcr0CkpnXQMn6QV04NspNOC6TdpW6a0H3S2g6dJxVYHtwkmqmzLtZhCldmlqSB9cN0tPV-D1FMKL5Fml6wAvd_tR8uXj-HZ0kU0-nV-OTieZ5YKKTDNKiDAFpZgZjYgpLGem4BY0VCx-zlhGcmNKSQwFbHS8lSWRotRlqQHnR8mHbd37pVlAaWOHXtfq3ruF9hvVaqf-VBo3U9N2pQgvEJYyFjjeFfDtjyWETi1csFDXuoF2GRQXmHPM-D9BJjAWkuURfPMXOG-XvolTUIRIjvMC99XkFrK-DcFDtW8ZI9XHrOaqT1D1Cao-ZvUrZrWO1te_f_nRuMs1Am93gA5W15XXjXXhkRNx5ELQyL3fcg-uhs1_N6CuLief4yn6X23989C1fu-nmBZI9nK2lV3oYL2Xtb-LQ80FU1-vz9XNzRm5ZiOuZP4TTQnc4w</recordid><startdate>20040101</startdate><enddate>20040101</enddate><creator>KRAVITZ, RICHARD L.</creator><creator>DUAN, NAIHUA</creator><creator>BRASLOW, JOEL</creator><general>Blackwell Publishing, Inc</general><general>Blackwell Publishers</general><general>Blackwell</general><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>7TQ</scope><scope>8BJ</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20040101</creationdate><title>Evidence-Based Medicine, Heterogeneity of Treatment Effects, and the Trouble with Averages</title><author>KRAVITZ, RICHARD L. ; 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subjects | Adverse effects Clinical trials Drug Approval - legislation & jurisprudence Evidence based medicine Experimentation genomics Health care Health outcomes Heterogeneity Humans Medical practice Medical research Original Policy Making Population characteristics Practice Patterns, Physicians Randomized controlled trials Randomized Controlled Trials as Topic Research design Research methodology Sample size Side effects Sociology Sociology of health and medicine Statistics Strokes Treatment Outcome United States United States Food and Drug Administration USA |
title | Evidence-Based Medicine, Heterogeneity of Treatment Effects, and the Trouble with Averages |
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