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Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: best marker for monitoring and cost-effectiveness of different monitoring frequencies

Overview of attention for article published in Health technology assessment : HTA / NHS R & D HTA Programme., December 2015
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  • Good Attention Score compared to outputs of the same age (71st percentile)

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1 policy source
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2 X users

Citations

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29 Dimensions

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154 Mendeley
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Title
Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: best marker for monitoring and cost-effectiveness of different monitoring frequencies
Published in
Health technology assessment : HTA / NHS R & D HTA Programme., December 2015
DOI 10.3310/hta191000
Pubmed ID
Authors

Rafael Perera, Emily McFadden, Julie McLellan, Tom Lung, Philip Clarke, Teresa Pérez, Thomas Fanshawe, Andrew Dalton, Andrew Farmer, Paul Glasziou, Osamu Takahashi, John Stevens, Les Irwig, Jennifer Hirst, Sarah Stevens, Asuka Leslie, Sachiko Ohde, Gautam Deshpande, Kevin Urayama, Brian Shine, Richard Stevens

Abstract

Various lipid measurements in monitoring/screening programmes can be used, alone or in cardiovascular risk scores, to guide treatment for prevention of cardiovascular disease (CVD). Because some changes in lipids are due to variability rather than true change, the value of lipid-monitoring strategies needs evaluation. To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. We searched databases and clinical trials registers from 2007 (including the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, the Clinical Trials Register, the Current Controlled Trials register, and the Cumulative Index to Nursing and Allied Health Literature) to update and extend previous systematic reviews. Patient-level data from the Clinical Practice Research Datalink and St Luke's Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. In two meta-analyses, we used prospective studies to examine associations of lipids with CVD and mortality, and randomised controlled trials to estimate lipid-lowering effects of atorvastatin doses. Patient-level data were used to estimate progression and variability of lipid measurements over time, and hence to model lipid-monitoring strategies. Results are expressed as rates of true-/false-positive and true-/false-negative tests for high lipid or high CVD risk. We estimated incremental costs per quality-adjusted life-year. A total of 115 publications reported strength of association between different lipid measures and CVD events in 138 data sets. The summary adjusted hazard ratio per standard deviation of total cholesterol (TC) to high-density lipoprotein (HDL) cholesterol ratio was 1.25 (95% confidence interval 1.15 to 1.35) for CVD in a primary prevention population but heterogeneity was high (I (2) = 98%); similar results were observed for non-HDL cholesterol, apolipoprotein B and other ratio measures. Associations were smaller for other single lipid measures. Across 10 trials, low-dose atorvastatin (10 and 20 mg) effects ranged from a TC reduction of 0.92 mmol/l to 2.07 mmol/l, and low-density lipoprotein reduction of between 0.88 mmol/l and 1.86 mmol/l. Effects of 40 mg and 80 mg were reported by one trial each. For primary prevention, over a 3-year period, we estimate annual monitoring would unnecessarily treat 9 per 1000 more men (28 vs. 19 per 1000) and 5 per 1000 more women (17 vs. 12 per 1000) than monitoring every 3 years. However, annual monitoring would also undertreat 9 per 1000 fewer men (7 vs. 16 per 1000) and 4 per 1000 fewer women (7 vs. 11 per 1000) than monitoring at 3-year intervals. For secondary prevention, over a 3-year period, annual monitoring would increase unnecessary treatment changes by 66 per 1000 men and 31 per 1000 women, and decrease undertreatment by 29 per 1000 men and 28 per 1000 men, compared with monitoring every 3 years. In cost-effectiveness, strategies with increased screening/monitoring dominate. Exploratory analyses found that any unknown harms of statins would need utility decrements as large as 0.08 (men) to 0.11 (women) per statin user to reverse this finding in primary prevention. Heterogeneity in meta-analyses. While acknowledging known and potential unknown harms of statins, we find that more frequent monitoring strategies are cost-effective compared with others. Regular lipid monitoring in those with and without CVD is likely to be beneficial to patients and to the health service. Future research should include trials of the benefits and harms of atorvastatin 40 and 80 mg, large-scale surveillance of statin safety, and investigation of the effect of monitoring on medication adherence. This study is registered as PROSPERO CRD42013003727. The National Institute for Health Research Health Technology Assessment programme.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 1%
Netherlands 1 <1%
United States 1 <1%
Unknown 150 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 18%
Student > Master 20 13%
Other 14 9%
Student > Bachelor 13 8%
Student > Ph. D. Student 9 6%
Other 28 18%
Unknown 42 27%
Readers by discipline Count As %
Medicine and Dentistry 43 28%
Pharmacology, Toxicology and Pharmaceutical Science 11 7%
Nursing and Health Professions 11 7%
Economics, Econometrics and Finance 9 6%
Biochemistry, Genetics and Molecular Biology 5 3%
Other 25 16%
Unknown 50 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 January 2018.
All research outputs
#7,779,140
of 25,377,790 outputs
Outputs from Health technology assessment : HTA / NHS R & D HTA Programme.
#803
of 1,235 outputs
Outputs of similar age
#111,274
of 395,426 outputs
Outputs of similar age from Health technology assessment : HTA / NHS R & D HTA Programme.
#17
of 20 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,235 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 395,426 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.