Evidence map›Paper›PMID 27927162›Full record

ArticleBMC cardiovascular disorders2016

Use of low density lipoprotein particle number levels as an aid in statin treatment decisions for intermediate risk patients: a cost-effectiveness analysis.

Dov Shiffman, Andre R Arellano, Michael P Caulfield, Judy Z Louie, Lance A Bare, James J Devlin, Olle Melander

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 31% 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, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Using Published Health Utilities in Cost-Utility Analyses: Discrepancies and Issues in Cardiovascular Disease.Medical decision making : an international journal of the Society for Medical Decision Making · 2021
    Article
  3. 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

7 authors at 2 institutions in 2 countries.

Dov ShiffmanQuest Diagnostics, Nichols Institute, 33608 Ortega Highway, 92675, San Juan Capistrano, CA, USA. dov.shiffman@questdiagnostics.com.
Andre R ArellanoQuest Diagnostics, Nichols Institute, 33608 Ortega Highway, 92675, San Juan Capistrano, CA, USA.
Michael P CaulfieldQuest Diagnostics, Nichols Institute, 33608 Ortega Highway, 92675, San Juan Capistrano, CA, USA.
Judy Z LouieQuest Diagnostics, Nichols Institute, 33608 Ortega Highway, 92675, San Juan Capistrano, CA, USA.
Lance A BareQuest Diagnostics, Nichols Institute, 33608 Ortega Highway, 92675, San Juan Capistrano, CA, USA.
James J DevlinQuest Diagnostics, Nichols Institute, 33608 Ortega Highway, 92675, San Juan Capistrano, CA, USA.
Olle MelanderDepartment of Clinical Sciences, Lund University, Malmö, Sweden.
Quest Diagnostics (United States) · USLund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 2013 ACC/AHA guideline recommended either no statin therapy or moderate-intensity statin therapy (MST) for intermediate risk patients-those with 5-7.5% 10-year risk and without cardiovascular disease (CVD), hypercholesterolemia or diabetes. The guideline further suggested that the therapy choice be based on patient-clinician discussions of risks and benefits. Since low-density lipoprotein particle (LDL-P) levels were reported to be associated with CVD independently of traditional risk factors in intermediate and low risk patients, we investigated the cost-effectiveness of using LDL-P levels to identify intermediate risk patients likely to benefit from initiating or intensifying statin therapy.

methodsWe evaluated 5 care strategies for intermediate risk patients. These included the strategies suggested by the guideline: no-statin therapy and MST. We compared each of these strategies to a related strategy that incorporated LDL-P testing. No-statin therapy was compared with the strategy of MST for those with high LDL-P levels and no statin therapy for all other patients (test-and-MST). MST was compared with the strategy of high-intensity statin therapy (HST) for those with high LDL-P levels and MST for all other patients (test-and-HST). We also evaluated the strategy of HST for all. Costs (payer perspective) and utilities were assessed over a 5-year time horizon in a Markov model of 100,000 hypothetical intermediate risk patients.

resultsHST dominated all other strategies, costing less and-despite causing 739 more cases of diabetes than did MST-resulting in more quality adjusted life-years (QALYs). For patient-clinician discussions that would otherwise lead to the MST strategy, we found the test-and-HST strategy reduced costs by $4.67 MM and resulted in 134 fewer CVD events and 115 additional QALYs. For patient-clinician discussions that would otherwise lead to no statin therapy, we found that the test-and-MST strategy reduced costs by $3.25 MM, resulted in 97 fewer CVD events and 44 additional QALYs.

conclusionsThe HST strategy was cost saving and improved outcomes in intermediate risk patients. For patient and clinicians concerned about the adverse events associated with HST, using LDL-P levels to target intensified statin therapy could improve outcomes and reduce costs.

Indexed as

Decision MakingForecastingAdultAgedCholesterol, LDLCost-Benefit AnalysisFemaleHumansHydroxymethylglutaryl-CoA Reductase InhibitorsHypercholesterolemiaMaleMiddle AgedQuality-Adjusted Life YearsRisk FactorsCholesterol, LDLHydroxymethylglutaryl-CoA Reductase InhibitorsCost-effectiveness analysisLDL-P testPrimary prevention

Identifiers

PMID27927162
PMCPMC5142314
OpenAlexW2560709547

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.