Evidence map›Paper›PMID 29391835›Full record

ArticleClinical epidemiology2018

Cardiovascular medication changes over 5 years in a national data linkage study: implications for risk prediction models.

Suneela Mehta, Rod Jackson, Sue Wells, Jeff Harrison, Daniel J Exeter, Andrew J Kerr

Open access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Data Resource: Vascular Risk in Adult New Zealanders (VARIANZ) datasets.International journal of population data science · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Suneela MehtaSection of Epidemiology and Biostatistics.
Rod JacksonSection of Epidemiology and Biostatistics.
Sue WellsSection of Epidemiology and Biostatistics.
Jeff HarrisonSchool of Pharmacy, University of Auckland.
Daniel J ExeterSection of Epidemiology and Biostatistics.
Andrew J KerrSection of Epidemiology and Biostatistics.
Cancer Research And Biostatistics · USMiddlemore Hospital · NZUniversity of Auckland · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite widespread use of cardiovascular disease (CVD) preventive medications in cohorts used to develop CVD risk prediction models, only some incorporate baseline CVD pharmacotherapy and none account for treatment changes during study follow-up. Therefore, current risk prediction scores may underestimate the true CVD event risk. We examined changes in CVD pharmacotherapy over 5 years in preparation for developing new 5-year risk prediction models.

methodsAnonymized individual-level linkage of eight national administrative health datasets enabled identification of all New Zealanders aged 30-74 years, without prior hospitalization for CVD or heart failure, who utilized publicly funded health services during 2006. We determined proportions of participants dispensed blood pressure lowering, lipid lowering, and antiplatelet/anticoagulant pharmacotherapy at baseline in 2006, and the proportion of person years of follow-up (2007-2011) where dispensing occurred.

resultsThe study population comprised of 1,766,584 individuals, representinĝ85% of all New Zealanders aged 30-74 years without prior CVD or heart failure in 2006, with mean follow-up of 4.9 years (standard deviation 0.6 years; 8,589,931 total person years). CVD medications were dispensed to 21% of people at baseline, with most single or combination pharmacotherapies continuing for ≥80% of follow-up. Complete discontinuation of baseline treatment accounted for 2% of follow-up time while CVD pharmacotherapy that commenced after baseline accounted for 7% of total follow-up time.

conclusionIn a national primary prevention cohort of 30-74 year olds, one in five received baseline CVD primary preventive pharmacotherapy and medication changes over the subsequent 5 years were modest. Baseline medication use is an important consideration when estimating CVD risk from modern cohorts. It is currently unclear how to incorporate available methods to account for treatment changes during follow-up into risk prediction scores, but this study demonstrates that baseline therapy captures most of the effect of treatment in 5-year risk models. However, the impact of treatment changes on the more common 10-year risk models requires further investigation.

Indexed as

cardiovascular diseasesdrug therapyprimary preventionrecord linkageroutine data

Identifiers

PMID29391835
PMCPMC5774482
OpenAlexW2782868532

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.