Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations.

Liang, J; Jackson, RT; Pylypchuk, R; Choi, Y; Chung, C; Crengle, S; Gao, P; Grey, C; Harwood, M; Holt, A; Kerr, A; Mehta, S; Wells, S; Poppe, K

Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations.

Liang, J Jackson, RT Pylypchuk, R

Choi, Y Chung, C Crengle, S Gao, P Grey, C Harwood, M Holt, A Kerr, A Mehta, S Wells, S Poppe, K

Permalink

Publisher:: BMJ
Publication Type:: Journal Article
Citation:: Heart, 2024, 110, (17), pp. 1083-1089
Issue Date:: 2024-08-14

Closed Access

	Filename	Description	Size
	1083.full.pdf	Published version	1.5 MB		View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Liang, J
dc.contributor.author	Jackson, RT
dc.contributor.author	Pylypchuk, R https://orcid.org/0000-0002-8507-0467
dc.contributor.author	Choi, Y
dc.contributor.author	Chung, C
dc.contributor.author	Crengle, S
dc.contributor.author	Gao, P
dc.contributor.author	Grey, C
dc.contributor.author	Harwood, M
dc.contributor.author	Holt, A
dc.contributor.author	Kerr, A
dc.contributor.author	Mehta, S
dc.contributor.author	Wells, S
dc.contributor.author	Poppe, K
dc.date.accessioned	2024-10-18T03:16:08Z
dc.date.available	2024-06-11
dc.date.available	2024-10-18T03:16:08Z
dc.date.issued	2024-08-14
dc.identifier.citation	Heart, 2024, 110, (17), pp. 1083-1089
dc.identifier.issn	1355-6037
dc.identifier.issn	1468-201X
dc.identifier.uri	http://hdl.handle.net/10453/181454
dc.description.abstract	BACKGROUND: No routinely recommended cardiovascular disease (CVD) risk prediction equations have adjusted for CVD preventive medications initiated during follow-up (treatment drop-in) in their derivation cohorts. This will lead to underestimation of risk when equations are applied in clinical practice if treatment drop-in is common. We aimed to quantify the treatment drop-in in a large contemporary national cohort to determine whether equations are likely to require adjustment. METHODS: Eight de-identified individual-level national health administrative datasets in Aotearoa New Zealand were linked to establish a cohort of almost all New Zealanders without CVD and aged 30-74 years in 2006. Individuals dispensing blood-pressure-lowering and/or lipid-lowering medications between 1 July 2006 and 31 December 2006 (baseline dispensing), and in each 6-month period during 12 years' follow-up to 31 December 2018 (follow-up dispensing), were identified. Person-years of treatment drop-in were determined. RESULTS: A total of 1 399 348 (80%) out of the 1 746 695 individuals in the cohort were not dispensed CVD medications at baseline. Blood-pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time in the group untreated at baseline and increased significantly with increasing predicted baseline 5-year CVD risk (12%, 31%, 34% and 37% in <5%, 5-9%, 10-14% and ≥15% risk groups, respectively) and with increasing age (8% in 30-44 year-olds to 30% in 60-74 year-olds). CONCLUSIONS: CVD preventive treatment drop-in accounted for approximately one-third of follow-up time among participants typically eligible for preventive treatment (≥5% 5-year predicted risk). Equations derived from cohorts with long-term follow-up that do not adjust for treatment drop-in effect will underestimate CVD risk in higher risk individuals and lead to undertreatment. Future CVD risk prediction studies need to address this potential flaw.
dc.format	Electronic
dc.language	eng
dc.publisher	BMJ
dc.relation.ispartof	Heart
dc.relation.isbasedon	10.1136/heartjnl-2024-324179
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	1102 Cardiorespiratory Medicine and Haematology, 1103 Clinical Sciences
dc.subject.classification	Cardiovascular System & Hematology
dc.subject.classification	3201 Cardiovascular medicine and haematology
dc.subject.classification	3202 Clinical sciences
dc.subject.mesh	Humans
dc.subject.mesh	Middle Aged
dc.subject.mesh	Male
dc.subject.mesh	Female
dc.subject.mesh	Cardiovascular Diseases
dc.subject.mesh	Aged
dc.subject.mesh	Risk Assessment
dc.subject.mesh	Adult
dc.subject.mesh	New Zealand
dc.subject.mesh	Heart Disease Risk Factors
dc.subject.mesh	Hypolipidemic Agents
dc.subject.mesh	Antihypertensive Agents
dc.subject.mesh	Humans
dc.subject.mesh	Cardiovascular Diseases
dc.subject.mesh	Antihypertensive Agents
dc.subject.mesh	Risk Assessment
dc.subject.mesh	Adult
dc.subject.mesh	Aged
dc.subject.mesh	Middle Aged
dc.subject.mesh	New Zealand
dc.subject.mesh	Female
dc.subject.mesh	Male
dc.subject.mesh	Hypolipidemic Agents
dc.subject.mesh	Heart Disease Risk Factors
dc.title	Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations.
dc.type	Journal Article
utslib.citation.volume	110
utslib.location.activity	England
utslib.for	1102 Cardiorespiratory Medicine and Haematology
utslib.for	1103 Clinical Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Health
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Women & Children’s Health Research Collaborative (WCHC)
pubs.organisational-group	University of Technology Sydney/UTS Groups/INSIGHT: Institute for Innovative Solutions for Well-being and Health
utslib.copyright.status	closed_access	*
dc.date.updated	2024-10-18T03:16:01Z
pubs.issue	17
pubs.publication-status	Published online
pubs.volume	110
utslib.citation.issue	17

Abstract:

BACKGROUND: No routinely recommended cardiovascular disease (CVD) risk prediction equations have adjusted for CVD preventive medications initiated during follow-up (treatment drop-in) in their derivation cohorts. This will lead to underestimation of risk when equations are applied in clinical practice if treatment drop-in is common. We aimed to quantify the treatment drop-in in a large contemporary national cohort to determine whether equations are likely to require adjustment. METHODS: Eight de-identified individual-level national health administrative datasets in Aotearoa New Zealand were linked to establish a cohort of almost all New Zealanders without CVD and aged 30-74 years in 2006. Individuals dispensing blood-pressure-lowering and/or lipid-lowering medications between 1 July 2006 and 31 December 2006 (baseline dispensing), and in each 6-month period during 12 years' follow-up to 31 December 2018 (follow-up dispensing), were identified. Person-years of treatment drop-in were determined. RESULTS: A total of 1 399 348 (80%) out of the 1 746 695 individuals in the cohort were not dispensed CVD medications at baseline. Blood-pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time in the group untreated at baseline and increased significantly with increasing predicted baseline 5-year CVD risk (12%, 31%, 34% and 37% in <5%, 5-9%, 10-14% and ≥15% risk groups, respectively) and with increasing age (8% in 30-44 year-olds to 30% in 60-74 year-olds). CONCLUSIONS: CVD preventive treatment drop-in accounted for approximately one-third of follow-up time among participants typically eligible for preventive treatment (≥5% 5-year predicted risk). Equations derived from cohorts with long-term follow-up that do not adjust for treatment drop-in effect will underestimate CVD risk in higher risk individuals and lead to undertreatment. Future CVD risk prediction studies need to address this potential flaw.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/181454