ArticleBMJ open2017
Effectiveness and cost-effectiveness of a cardiovascular risk prediction algorithm for people with severe mental illness (PRIMROSE).
Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Clinical Practice Guideline on the Pharmacological Management of Antipsychotic-Related Dyslipidemia.Schizophrenia bulletin · 2026Guideline
- A five-year risk prediction model of cardiovascular disease in individuals with bipolar disorder: a nationwide register study from Sweden.Molecular psychiatry · 2026Article
- Treating hearts and minds: adverse cardiovascular effects of psychiatric medications.Therapeutic advances in drug safety · 2026Review
- Comparative effectiveness and prescribing trends of modified release versus immediate release indapamide in patients with hypertension: cohort study.BMJ medicine · 2025Article
- An integrated primary care service to reduce cardiovascular disease risk in people with severe mental illness: Primrose-A - thematic analysis of its acceptability, feasibility, and implementation.BMC health services research · 2024Article
- Assessing Effects of Diet Alteration on Carbohydrate-Lipid Metabolism of Antipsychotic-Treated Schizophrenia Patients in Interventional Study.Nutrients · 2023Article
- Establishing a Care Continuum for Cardiometabolic Conditions for Patients with Serious Mental Illness.Current cardiology reports · 2023Review
- Cardiovascular disease in patients with severe mental illness.Nature reviews. Cardiology · 2021Review
- Schizophrenia Treatment with Second-Generation Antipsychotics: A Multi-Country Comparison of the Costs of Cardiovascular and Metabolic Adverse Events and Weight Gain.Neuropsychiatric disease and treatment · 2021Article
- Article
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 5 countries.
Funding
Abstract
objectivesTo determine the cost-effectiveness of two bespoke severe mental illness (SMI)-specific risk algorithms compared with standard risk algorithms for primary cardiovascular disease (CVD) prevention in those with SMI.
settingPrimary care setting in the UK. The analysis was from the National Health Service perspective.
participants1000 individuals with SMI from The Health Improvement Network Database, aged 30-74 years and without existing CVD, populated the model.
interventionsFour cardiovascular risk algorithms were assessed: (1) general population lipid, (2) general population body mass index (BMI), (3) SMI-specific lipid and (4) SMI-specific BMI, compared against no algorithm. At baseline, each cardiovascular risk algorithm was applied and those considered high risk ( PRIMARY AND SECONDARY OUTCOME MEASURES: Quality-adjusted life years (QALYs) and costs were accrued for each algorithm including no algorithm, and cost-effectiveness was calculated using the net monetary benefit (NMB) approach. Deterministic and probabilistic sensitivity analyses were performed to test assumptions made and uncertainty around parameter estimates.
resultsThe SMI-specific BMI algorithm had the highest NMB resulting in 15 additional QALYs and a cost saving of approximately £53 000 per 1000 patients with SMI over 10 years, followed by the general population lipid algorithm (13 additional QALYs and a cost saving of £46 000).
conclusionsThe general population lipid and SMI-specific BMI algorithms performed equally well. The ease and acceptability of use of an SMI-specific BMI algorithm (blood tests not required) makes it an attractive algorithm to implement in clinical settings.
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Registered trials
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