Henriksson, M;
Palmer, S;
Chen, R;
Damant, J;
Fitzpatrick, NK;
Abrams, K;
Hingorani, AD;
Stenestrand, U;
Janzon, M;
Feder, G;
et al.
Henriksson, M; Palmer, S; Chen, R; Damant, J; Fitzpatrick, NK; Abrams, K; Hingorani, AD; Stenestrand, U; Janzon, M; Feder, G; Keogh, B; Shipley, MJ; Kaski, JC; Timmis, A; Sculpher, M; Hemingway, H
(2010)
Assessing the cost effectiveness of using prognostic biomarkers with decision models: case study in prioritising patients waiting for coronary artery surgery.
BRITISH MEDICAL JOURNAL, 340.
pp. 1-9.
ISSN 0959-535X
https://doi.org/10.1136/bmj.b5606
SGUL Authors: Kaski, Juan Carlos
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Abstract
Abstract:
Objective To determine the effectiveness and cost effectiveness of using information from circulating biomarkers to inform the prioritisation process of patients with stable angina awaiting coronary artery bypass graft surgery.
Design: Decision analytical model comparing four prioritisation strategies without biomarkers (no formal prioritisation, two urgency scores, and a risk score) and three strategies based on a risk score using biomarkers: a routinely assessed biomarker (estimated glomerular filtration rate), a novel biomarker (C reactive protein), or both. The order in which to perform coronary artery bypass grafting in a cohort of patients was determined by each prioritisation strategy, and mean lifetime costs and quality adjusted life years (QALYs) were compared.
Data sources: Swedish Coronary Angiography and Angioplasty Registry (9935 patients with stable angina awaiting coronary artery bypass grafting and then followed up for cardiovascular events after the procedure for 3.8 years), and meta-analyses of prognostic effects (relative risks) of biomarkers.
Results: The observed risk of cardiovascular events while on the waiting list for coronary artery bypass grafting was 3 per 10 000 patients per day within the first 90 days (184 events in 9935 patients). Using a cost effectiveness threshold of £20 000-£30 000 (€22 000-€33 000; $32 000-$48 000) per additional QALY, a prioritisation strategy using a risk score with estimated glomerular filtration rate was the most cost effective strategy (cost per additional QALY was <£410 compared with the Ontario urgency score). The impact on population health of implementing this strategy was 800 QALYs per 100 000 patients at an additional cost of £245 000 to the National Health Service. The prioritisation strategy using a risk score with C reactive protein was associated with lower QALYs and higher costs compared with a risk score using estimated glomerular filtration rate.
Conclusion: Evaluating the cost effectiveness of prognostic biomarkers is important even when effects at an individual level are small. Formal prioritisation of patients awaiting coronary artery bypass grafting using a routinely assessed biomarker (estimated glomerular filtration rate) along with simple, routinely collected clinical information was cost effective. Prioritisation strategies based on the prognostic information conferred by C reactive protein, which is not currently measured in this context, or a combination of C reactive protein and estimated glomerular filtration rate, is unlikely to be cost effective. The widespread practice of using only implicit or informal means of clinically ordering the waiting list may be harmful and should be replaced with formal prioritisation approaches.
Item Type: |
Article
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Additional Information: |
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode. |
Keywords: |
Aged, Angina Pectoris, Biological Markers, C-Reactive Protein, Coronary Artery Bypass, Cost-Benefit Analysis, Decision Support Techniques, Glomerular Filtration Rate, Humans, Myocardial Infarction, Postoperative Complications, Prognosis, Quality-Adjusted Life Years, Risk Assessment, Stroke, Triage, Waiting Lists, Science & Technology, Life Sciences & Biomedicine, Medicine, General & Internal, General & Internal Medicine, BYPASS GRAFT-SURGERY, STABLE ANGINA-PECTORIS, CARDIOVASCULAR-DISEASE, CARDIAC-SURGERY, DEATH, RISK, REVASCULARIZATION, PREVENTION, MANAGEMENT, OUTCOMES |
SGUL Research Institute / Research Centre: |
Academic Structure > Molecular and Clinical Sciences Research Institute (MCS) |
Journal or Publication Title: |
BRITISH MEDICAL JOURNAL |
ISSN: |
0959-535X |
Related URLs: |
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Dates: |
Date | Event |
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19 January 2010 | Published |
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Web of Science ID: |
WOS:000273951200002 |
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URI: |
https://openaccess.sgul.ac.uk/id/eprint/1045 |
Publisher's version: |
https://doi.org/10.1136/bmj.b5606 |
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