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Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control

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Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control. / Zanisi, Lorenzo; Floyd, Christopher N; Barrett, James E; Bunce, Catey; Frohmaier, Chris; Shankar, Francesco; Chowienczyk, Phil J.

In: Journal of Hypertension, 29.06.2020.

Research output: Contribution to journalArticle

Harvard

Zanisi, L, Floyd, CN, Barrett, JE, Bunce, C, Frohmaier, C, Shankar, F & Chowienczyk, PJ 2020, 'Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control', Journal of Hypertension. https://doi.org/10.1097/HJH.0000000000002546

APA

Zanisi, L., Floyd, C. N., Barrett, J. E., Bunce, C., Frohmaier, C., Shankar, F., & Chowienczyk, P. J. (2020). Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control. Journal of Hypertension. https://doi.org/10.1097/HJH.0000000000002546

Vancouver

Zanisi L, Floyd CN, Barrett JE, Bunce C, Frohmaier C, Shankar F et al. Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control. Journal of Hypertension. 2020 Jun 29. https://doi.org/10.1097/HJH.0000000000002546

Author

Zanisi, Lorenzo ; Floyd, Christopher N ; Barrett, James E ; Bunce, Catey ; Frohmaier, Chris ; Shankar, Francesco ; Chowienczyk, Phil J. / Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control. In: Journal of Hypertension. 2020.

Bibtex Download

@article{b2ced26385df4b07a2d7131792668ab8,
title = "Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control",
abstract = "OBJECTIVES: To assess the impact of variable drug response and measurement error on SBP control.METHODS: We simulated a treat-to-target strategy for populations with different pretreatment SBP, whereby medications were added sequentially until measured SBP (mSBP) less than 140 mmHg. Monte Carlo simulations determined variability of both drug response (drugeff ± σdrug; 10 ± 5 mmHg base case) and measurement error (σmeas; 10 mmHg base case) of true SBP (tSBP). The primary outcome measure was the proportion of individuals who achieved target less than 140 mmHg.RESULTS: Decision-making based on mSBP resulted in 35.0{\%} of individuals with initial tSBP 150 mmHg being either inappropriately given, or inappropriately denied a second drug. When the simulation was run for multiple drug titrations, measurement error limited tSBP control for all populations tested. A strategy of drug titration based on a second measurement for individuals at risk of incorrect decisions (mSBP 120-150 mmHg; σmeas 15 mmHg) reduced the proportion above target from 40.1 to 30.0{\%} when initial tSBP 160 mmHg. When the measurement variability for the second reading was reduced below that usually seen in clinical practice (σmeas 5 mmHg), the proportion above target decreased further to 17.4{\%}.CONCLUSION: In this simulation, measurement error had the greatest impact on the proportion of individuals achieving their SBP target. Efforts to reduce this error through repeated measures, alternative measurement techniques or changing thresholds, are promising strategies to reduce cardiovascular morbidity and mortality and should be investigated in clinical trials. Here we have shown that Monte Carlo simulations are a useful technique to investigate the influence of uncertainty for different hypertension management strategies.",
author = "Lorenzo Zanisi and Floyd, {Christopher N} and Barrett, {James E} and Catey Bunce and Chris Frohmaier and Francesco Shankar and Chowienczyk, {Phil J}",
year = "2020",
month = "6",
day = "29",
doi = "10.1097/HJH.0000000000002546",
language = "English",
journal = "Journal of Hypertension",
issn = "0263-6352",
publisher = "Lippincott Williams and Wilkins",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Monte Carlo simulation of uncertainty to identify barriers to optimizing blood pressure control

AU - Zanisi, Lorenzo

AU - Floyd, Christopher N

AU - Barrett, James E

AU - Bunce, Catey

AU - Frohmaier, Chris

AU - Shankar, Francesco

AU - Chowienczyk, Phil J

PY - 2020/6/29

Y1 - 2020/6/29

N2 - OBJECTIVES: To assess the impact of variable drug response and measurement error on SBP control.METHODS: We simulated a treat-to-target strategy for populations with different pretreatment SBP, whereby medications were added sequentially until measured SBP (mSBP) less than 140 mmHg. Monte Carlo simulations determined variability of both drug response (drugeff ± σdrug; 10 ± 5 mmHg base case) and measurement error (σmeas; 10 mmHg base case) of true SBP (tSBP). The primary outcome measure was the proportion of individuals who achieved target less than 140 mmHg.RESULTS: Decision-making based on mSBP resulted in 35.0% of individuals with initial tSBP 150 mmHg being either inappropriately given, or inappropriately denied a second drug. When the simulation was run for multiple drug titrations, measurement error limited tSBP control for all populations tested. A strategy of drug titration based on a second measurement for individuals at risk of incorrect decisions (mSBP 120-150 mmHg; σmeas 15 mmHg) reduced the proportion above target from 40.1 to 30.0% when initial tSBP 160 mmHg. When the measurement variability for the second reading was reduced below that usually seen in clinical practice (σmeas 5 mmHg), the proportion above target decreased further to 17.4%.CONCLUSION: In this simulation, measurement error had the greatest impact on the proportion of individuals achieving their SBP target. Efforts to reduce this error through repeated measures, alternative measurement techniques or changing thresholds, are promising strategies to reduce cardiovascular morbidity and mortality and should be investigated in clinical trials. Here we have shown that Monte Carlo simulations are a useful technique to investigate the influence of uncertainty for different hypertension management strategies.

AB - OBJECTIVES: To assess the impact of variable drug response and measurement error on SBP control.METHODS: We simulated a treat-to-target strategy for populations with different pretreatment SBP, whereby medications were added sequentially until measured SBP (mSBP) less than 140 mmHg. Monte Carlo simulations determined variability of both drug response (drugeff ± σdrug; 10 ± 5 mmHg base case) and measurement error (σmeas; 10 mmHg base case) of true SBP (tSBP). The primary outcome measure was the proportion of individuals who achieved target less than 140 mmHg.RESULTS: Decision-making based on mSBP resulted in 35.0% of individuals with initial tSBP 150 mmHg being either inappropriately given, or inappropriately denied a second drug. When the simulation was run for multiple drug titrations, measurement error limited tSBP control for all populations tested. A strategy of drug titration based on a second measurement for individuals at risk of incorrect decisions (mSBP 120-150 mmHg; σmeas 15 mmHg) reduced the proportion above target from 40.1 to 30.0% when initial tSBP 160 mmHg. When the measurement variability for the second reading was reduced below that usually seen in clinical practice (σmeas 5 mmHg), the proportion above target decreased further to 17.4%.CONCLUSION: In this simulation, measurement error had the greatest impact on the proportion of individuals achieving their SBP target. Efforts to reduce this error through repeated measures, alternative measurement techniques or changing thresholds, are promising strategies to reduce cardiovascular morbidity and mortality and should be investigated in clinical trials. Here we have shown that Monte Carlo simulations are a useful technique to investigate the influence of uncertainty for different hypertension management strategies.

U2 - 10.1097/HJH.0000000000002546

DO - 10.1097/HJH.0000000000002546

M3 - Article

C2 - 32618898

JO - Journal of Hypertension

JF - Journal of Hypertension

SN - 0263-6352

ER -

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