Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations

Background There are no shared decision‐making frameworks for selecting blood pressure (BP) targets for individuals with hypertension. This study addressed whether results from the SPRINT (Systolic Blood Pressure Intervention Trial) could be tailored to individuals using predicted risks and simulate...

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Main Authors: Simon B. Ascher, Richard L. Kravitz, Rebecca Scherzer, Jarett D. Berry, James A. de Lemos, Michelle M. Estrella, Daniel J. Tancredi, Anthony A. Killeen, Joachim H. Ix, Michael G. Shlipak
Format: Article
Language:English
Published: Wiley 2024-08-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
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Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.124.033995
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author Simon B. Ascher
Richard L. Kravitz
Rebecca Scherzer
Jarett D. Berry
James A. de Lemos
Michelle M. Estrella
Daniel J. Tancredi
Anthony A. Killeen
Joachim H. Ix
Michael G. Shlipak
author_facet Simon B. Ascher
Richard L. Kravitz
Rebecca Scherzer
Jarett D. Berry
James A. de Lemos
Michelle M. Estrella
Daniel J. Tancredi
Anthony A. Killeen
Joachim H. Ix
Michael G. Shlipak
author_sort Simon B. Ascher
collection DOAJ
description Background There are no shared decision‐making frameworks for selecting blood pressure (BP) targets for individuals with hypertension. This study addressed whether results from the SPRINT (Systolic Blood Pressure Intervention Trial) could be tailored to individuals using predicted risks and simulated preferences. Methods and Results Among 8202 SPRINT participants, Cox models were developed and internally validated to predict each individual's absolute difference in risk from intensive versus standard BP lowering for cardiovascular events, cognitive impairment, death, and serious adverse events (AEs). Individual treatment effects were combined using simulated preference weights into a net benefit, which represents a weighted sum of risk differences across outcomes. Net benefits were compared among those above versus below the median AE risk. In simulations for which cardiovascular, cognitive, and death events had much greater weight than the AEs of BP lowering, the median net benefit was 3.3 percentage points (interquartile range [IQR], 2.0–5.7), and 100% of participants had a net benefit favoring intensive BP lowering. When simulating benefits and harms to have similar weights, the median net benefit was 0.8 percentage points (IQR, 0.2–2.2), and 87% had a positive net benefit. Compared with participants at lower risk of AEs from BP lowering, those at higher risk had a greater net benefit from intensive BP lowering despite experiencing more AEs (P<0.001 in both simulations). Conclusions Most SPRINT participants had a predicted net benefit that favored intensive BP lowering, but the degree of net benefit varied considerably. Tailoring BP targets using each patient's risks and preferences may provide more refined BP target recommendations.
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spelling doaj-art-be1b5e76a58f45fab32b44480a670c3b2024-11-28T09:27:28ZengWileyJournal of the American Heart Association: Cardiovascular and Cerebrovascular Disease2047-99802024-08-01131610.1161/JAHA.124.033995Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target RecommendationsSimon B. Ascher0Richard L. Kravitz1Rebecca Scherzer2Jarett D. Berry3James A. de Lemos4Michelle M. Estrella5Daniel J. Tancredi6Anthony A. Killeen7Joachim H. Ix8Michael G. Shlipak9Department of Internal Medicine, Kidney Health Research Collaborative San Francisco Veterans Affairs Health Care System and University of California San Francisco San Francisco CADepartment of Internal Medicine University of California Davis Sacramento CADepartment of Internal Medicine, Kidney Health Research Collaborative San Francisco Veterans Affairs Health Care System and University of California San Francisco San Francisco CADepartment of Internal Medicine University of Texas at Tyler Health Science Center Tyler TXDivision of Cardiology, Department of Internal Medicine University of Texas Southwestern Medical Center Dallas TXDepartment of Internal Medicine, Kidney Health Research Collaborative San Francisco Veterans Affairs Health Care System and University of California San Francisco San Francisco CADepartment of Pediatrics University of California Davis Sacramento CADepartment of Laboratory Medicine and Pathology University of Minnesota Minneapolis MNDivision of Nephrology‐Hypertension University of California San Diego La Jolla CADepartment of Internal Medicine, Kidney Health Research Collaborative San Francisco Veterans Affairs Health Care System and University of California San Francisco San Francisco CABackground There are no shared decision‐making frameworks for selecting blood pressure (BP) targets for individuals with hypertension. This study addressed whether results from the SPRINT (Systolic Blood Pressure Intervention Trial) could be tailored to individuals using predicted risks and simulated preferences. Methods and Results Among 8202 SPRINT participants, Cox models were developed and internally validated to predict each individual's absolute difference in risk from intensive versus standard BP lowering for cardiovascular events, cognitive impairment, death, and serious adverse events (AEs). Individual treatment effects were combined using simulated preference weights into a net benefit, which represents a weighted sum of risk differences across outcomes. Net benefits were compared among those above versus below the median AE risk. In simulations for which cardiovascular, cognitive, and death events had much greater weight than the AEs of BP lowering, the median net benefit was 3.3 percentage points (interquartile range [IQR], 2.0–5.7), and 100% of participants had a net benefit favoring intensive BP lowering. When simulating benefits and harms to have similar weights, the median net benefit was 0.8 percentage points (IQR, 0.2–2.2), and 87% had a positive net benefit. Compared with participants at lower risk of AEs from BP lowering, those at higher risk had a greater net benefit from intensive BP lowering despite experiencing more AEs (P<0.001 in both simulations). Conclusions Most SPRINT participants had a predicted net benefit that favored intensive BP lowering, but the degree of net benefit varied considerably. Tailoring BP targets using each patient's risks and preferences may provide more refined BP target recommendations.https://www.ahajournals.org/doi/10.1161/JAHA.124.033995hypertensionpatient preferencesprecision medicinepredictionshared decision‐making
spellingShingle Simon B. Ascher
Richard L. Kravitz
Rebecca Scherzer
Jarett D. Berry
James A. de Lemos
Michelle M. Estrella
Daniel J. Tancredi
Anthony A. Killeen
Joachim H. Ix
Michael G. Shlipak
Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
hypertension
patient preferences
precision medicine
prediction
shared decision‐making
title Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations
title_full Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations
title_fullStr Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations
title_full_unstemmed Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations
title_short Incorporating Individual‐Level Treatment Effects and Outcome Preferences Into Personalized Blood Pressure Target Recommendations
title_sort incorporating individual level treatment effects and outcome preferences into personalized blood pressure target recommendations
topic hypertension
patient preferences
precision medicine
prediction
shared decision‐making
url https://www.ahajournals.org/doi/10.1161/JAHA.124.033995
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