Conversion of the Seattle Angina Questionnaire into EQ-5D utilities for ischemic heart disease: a systematic review and catalog of the literature

Introduction

Economic evaluations with cost-effectiveness analyses are important in the decision-making process for health resource allocation. Cost-effectiveness analysis involves estimation of the incremental cost of a new intervention as well as its incremental net health benefit, in comparison with a reference. To facilitate the comparison of different interventions, it is important that the health effects be reported in standardized units. Current guidelines recommend that the metric of choice for reporting health benefits in cost-effectiveness analysis is the quality-adjusted life-year.^1–5

A variety of techniques have been developed to assess patient quality of life. Available instruments can be generally classified into two major categories, ie, descriptive measurement instruments or preference-based methods. Descriptive measurement instruments are designed to measure quality of life across important aspects of a patient’s health state, such as physical, psychosocial, or functional well-being.⁶ Such instruments provide a score for each health domain and a quantitative measure that represents a patient’s current health state. In contrast, preference-based or utility instruments, such as the European Quality of Life-5 Dimensions (EQ-5D), add a valuation component to a patient’s reported health state.⁷ These instruments are designed to reflect both a quantitative description of a patient’s health state and society’s preference for that particular health state. This preference component is the primary distinction between a utility instrument and a descriptive measurement instrument. Preference-based instruments allow for the calculation of quality-adjusted life-years.

In ischemic heart disease (IHD) research, there is an abundance of published literature on the Seattle Angina Questionnaire (SAQ), a descriptive quality of life instrument. The SAQ is a validated descriptive instrument that evaluates quality of life in patients with IHD across five domains, specifically physical limitation, treatment satisfaction, angina frequency, angina stability, and disease perception.⁸ In contrast, there is a paucity of studies that report utility weights for patients with IHD.³ The absence of available and up-to-date utility weights is a substantial limitation when performing economic analyses in IHD. To address this lack of utility information, we have previously published a mapping algorithm to convert SAQ descriptive scores to utility weights, based on the EQ-5D preference-based utility instrument.^9,10

In this study, we extended our previous work by performing a systematic review of the literature to identify all previous studies that used the SAQ to measure health state, and then applied our validated mapping algorithm to create a comprehensive catalog of utility weights across the spectrum of IHD, with the intention that our catalog be used for future economic evaluations in IHD.

Materials and methods

Search strategy

First, we conducted a systematic review of the published literature, conforming to the standards recommended by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.¹¹ We used the search terms “Seattle Angina Questionnaire”, “SAQ”, or slight modifications of these terms (see Supplementary material for full search strategy) to identify potentially relevant citations from inception to November 7, 2012 using the following medical literature databases: MEDLINE (Ovid), EMBASE (Ovid), Cochrane Library (Wiley), HealthStar (Ovid), and PubMed. We subsequently performed a citation search in Google Scholar (Google), Web of Science (Thomson Reuters), and Scopus (Elsevier) to identify articles citing the original paper by Spertus et al⁸ that first examined the validity and reliability of the SAQ. Finally, we searched major clinical trial registries (clinicaltrials.gov and clinicaltrialsregister.eu) from inception to November 7, 2012 for studies that used the SAQ as an outcome measure, using the search terms “Seattle Angina Questionnaire” or “SAQ”.

Upon removal of duplications, two independent reviewers (SF and HCW) screened each reference. We utilized a hierarchal approach, screening citations by title, then abstract, and finally by full text to determine relevance. Reviewers assessed the eligibility of these selected articles according to two prespecified inclusion criteria, ie, that publication was in English and that mean scores and standard errors (or the ability to calculate standard errors from the available data) were reported for all five domains of the SAQ. Although the SAQ has been translated into multiple languages, the original SAQ validation studies were based on the English version; as such, we restricted our algorithm to English articles. All five domains were needed to utilize our mapping algorithm. Exclusion criteria were articles that reported on experimental interventions (eg, transmyocardial laser revascularization, herbal medicine) that are not part of standard therapy. The following information was extracted from eligible studies: baseline characteristics of study participants (age, gender); inclusion and exclusion criteria for each study, interventions (eg, myocardial infarction, revascularization) and follow-up duration; and reported SAQ scores and standard errors.

Data synthesis

We have previously created and published a prediction algorithm using multivariable linear regression modeling, with the utility weight from the EQ-5D being our response variable of interest. Details of the derivation and validation of the mapping algorithm are available elsewhere.⁹ In brief, all model fitting was done using Bayesian methods. The posterior probability distribution for each of the model parameters was estimated using Markov Chain Monte Carlo simulation methods, with noninformative prior distributions for all model parameters. The data for model development were from 1,992 consecutive patients who underwent coronary angiography in 2004 as part of the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease database. The final mapping algorithm was a linear regression model, with the dependent variable being the EQ-5D, and a conditional distribution of Y_i~N(μ_i,σ_i). The specification of the mean was given by:

with the following parameter estimates:

intercept 0.4388 (0.4015–0.4763), β AF 0.0010 (0.0007–0.0013), β AS −0.0002 (−0.0005 to 0.0000), β DP 0.0023 (0.0020–0.0027), β PL 0.0019 (0.0017–0.0022), β TS 0.0004 (−0.0001 to 0.0008).

Using the posterior distribution for the coefficients of the final linear regression mapping algorithm, we calculated the EQ-5D based on the scores for the five SAQ domains for each included study. To fully incorporate uncertainty in the estimated EQ-5D utilities, we assumed that the inputted SAQ values from each paper had a normal distribution, based on the mean and standard error. We sampled from this distribution to calculate the mean and 95% credible interval of the estimated EQ-5D.

The mapping algorithm and EQ-5D estimates were calculated using WinBUGS version 1.4 (Medical Research Council, London, UK).

Results

Study selection

We identified 2,776 citations from various sources using our search criteria. After removing duplications, 1,092 articles were screened to identify articles in English that were potentially relevant and that reported scores and standard errors (or standard deviation and sample size, or confidence intervals, in order to calculate the standard error) for all five domains of the SAQ. Full review was done on 60 articles. We excluded 24 of these articles because they provided SAQ scores following experimental interventions, ie, neurostimulation (six articles), autologous bone marrow transplant (three articles), transmyocardial laser revascularization (six articles), herbal medicine (two articles), fibroblast growth factor (one article), granulocyte colony-stimulating factor (one article), cognitive behavioral therapy (one article), and other (four articles). A total of 36 articles met our eligibility criteria and were included in the final analysis. Figure 1 presents the flow diagram of our review process.

Figure 1 Process of study selection.

Study characteristics

The 36 studies in our systematic review represent a wide spectrum of patients with IHD. Eight of these studies focused exclusively on patients with stable angina,^12–19 and four included patients with a previous myocardial infarction.^12,20–22 Four studies specifically assessed SAQ in patients with advanced IHD unsuitable for revascularization.^18,23–25 These studies reported SAQ scores in patients with general angina, or specifically with severe or refractory angina. Five studies were restricted to an elderly population,^23,26–29 one study was restricted to women with IHD,³⁰ and one study reported SAQ data in diabetic patients with IHD.¹⁷ SAQ data were compared among South Asians versus Europeans with IHD in one study,³¹ while another study reported the SAQs of Caucasians and African Americans with IHD.²⁰ The studies ranged from cross-sectional evaluations with no follow-up to longitudinal studies with follow-up ranging from 7 days to a mean of 6 years and 11 months.

Given our intent to form a catalog such that estimated utility scores can be easily referenced, we categorized the 36 included articles in three groups, as shown in Tables 1–3. Thirteen studies focused on general IHD patients (Table 1), four focused on patients with recent acute coronary syndrome (Table 2), and 19 assessed revascularized patients (Table 3), of which eight included only patients who underwent coronary artery bypass grafting (CABG)^{23,28,29,32–36} and six included only patients who had percutaneous coronary intervention.^{19,21,27,37–39}

Table 1 General ischemic heart disease Note: SAQ values include standard error; EQ-5D values include 95% confidence intervals. Abbreviations: I, inclusion criteria; E, exclusion criteria; EF, ejection fraction; IHD, ischemic heart disease; LVEF, left ventricular ejection fraction; LDL, low-density lipoprotein; MI, myocardial infarction; NYHA class, New York Heart Association classification; CHF, congestive heart failure; Mets, metabolic equivalents; HF, heart failure; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft; CCS, Canadian Cardiovascular Society; NA, not available; SAQ, Seattle Angina Questionnaire; PL, physical limitation; TS, treatment satisfaction; AF, angina frequency; AS, angina stability; DP, disease perception; EQ-5D, European Quality of Life-5 Dimensions; QTc, corrected QT.

Table 2 Acute coronary syndrome, MI, and acute chest pain Notes: SAQ values include standard error; EQ-5D values include 95% confidence intervals. Abbreviations: I, inclusion criteria; E, exclusion criteria; TIMI, Thrombolysis in Myocardial Infarction; ECG, electrocardiogram; SAQ, Seattle Angina Questionnaire; PL, physical limitation; TS, treatment satisfaction; AF, angina frequency; AS, angina stability; DP, disease perception; EQ-5D, European Quality of Life-5 Dimensions.

Table 3 Revascularization Notes: SAQ values include standard error, EQ-5D values include 95% confidence intervals. * Valve surgery is aortic or mitral valve replacement/repair. ** Dor or Maze is for treatment of atrial fibrillation. Abbreviations: I, inclusion criteria; E, exclusion criteria; IHD, ischemic heart disease; LVEF, left ventricular ejection fraction; MI, myocardial infarction; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft; CCS, Canadian Cardiovascular Society; PTCA, percutaneous transluminal coronary angioplasty; TIMI, Thrombolysis in Myocardial Infarction; OMT, optimal medical therapy; SAQ, Seattle Angina Questionnaire; PL, physical limitation; TS, treatment satisfaction; AF, angina frequency; AS, angina stability; DP, disease perception; EQ-5D, European Quality of Life-5 Dimensions.

Predicted EQ-5D

The SAQ scores from the original publications and the calculated EQ-5D scores are shown in Tables 1–3. The estimated baseline EQ-5D scores for the general IHD patients were in the range of 0.605–0.843, increasing to 0.649–0.877 post follow-up (Table 1). The baseline range was 0.706–0.796 for the studies focused on patients with a recent acute coronary syndrome, increasing to 0.795–0.942 post follow-up (Table 2). The revascularization studies had EQ-5D scores in the range of 0.616–0.790 at baseline, increasing to 0.653–0.928 after treatment (Table 3). Studies that included only CABG as the revascularization modality had an EQ-5D score range that increased from 0.643–0.788 at baseline to 0.653–0.928 after CABG; the studies that focused only on percutaneous coronary intervention had scores that increased from 0.616–0.790 at baseline to 0.668–0.897 after treatment.

Discussion

In this report, we have provided a comprehensive catalog of predicted EQ-5D utility scores for patients with IHD. We first performed a systematic review of the literature to identify studies that reported SAQ scores and then applied our previously validated mapping algorithm to convert SAQ scores to EQ-5D scores. The studies included in our systematic review represent a broad spectrum of IHD patients and assessed quality of life at baseline and/or following a broad range of nonpharmacologic, medical, or surgical interventions.

Patient-reported health status has gained an increasingly important role in the decision-making process for health resource allocation.⁴⁰ Patient health status independently predicts mortality, cardiovascular events, hospitalizations, and costs of care in cardiovascular illnesses.^41–43 Current methodologic guidelines emphasize the importance of preference-based measures in comparative effectiveness studies of health technologies. For example, the National Institute for Health and Clinical Excellence suggests that EQ-5D is the preferred method in quantifying the health outcome of various interventions.⁴⁴ However, in many circumstances, preference-based instruments have not been included in cardiovascular studies. In the absence of such information, mapping techniques such as that applied in the current study can be used to estimate utility weights from available descriptive quality of life data.⁴⁵

Dyer et al recently published a summary of available EQ-5D scores from the entire spectrum of cardiovascular diseases,⁴⁶ and were able to identify 18 studies in IHD. They observed significant heterogeneity in the reported EQ-5D scores across these studies, in the range of 0.45–0.88. We believe our study is an important addition to this early work, by providing utility scores on additional studies in IHD, covering a wide spectrum of revascularization modalities and patient populations. Similar to the previous work by Dyer et al, we found heterogeneity between studies. This heterogeneity in utility weights between studies underscores the importance of a catalog such as ours. When researchers are developing economic models, it is essential that the utility weights inputted are reflective of the population being studied. Our catalog provides detailed information on the population being evaluated, as well as interventions, which will provide researchers with the information needed such that they can utilize the most appropriate utility weights when developing economic models.

Our mapping algorithm was designed to estimate EQ-5D scores using the scores and standard errors in all five domains of the SAQ.⁹ An important limitation is that we had to exclude studies that did not publish scores on all five domains of the SAQ. However, our final catalog included estimated EQ-5D scores across a wide range of baseline patient demographics, disease severity, and various treatment interventions. A weakness of our systematic review is that we failed to capture studies that did not use the name of the SAQ scale in the text of the paper and failed to cite the source of the questionnaire.

In conclusion, in the current era of budgetary constraints, cost-effectiveness analysis has become increasingly important in decision-making for health resource allocation. In the absence of directly measured individual patient preference-based data, our catalog of estimated EQ-5D scores can be useful in IHD-related economic evaluations.

Acknowledgment

HCW is supported by a Distinguished Clinical Scientist Award from the Heart and Stroke Foundation of Canada.

Author contributions

HCW was involved in the conception, design, acquisition, analysis and interpretation of the data, and critically revised the manuscript. SFZ was involved in the conception and design, acquisition of data, and interpretation of the data, and drafted the manuscript. WW was involved in conception of the study, performed the systematic search, and revised the manuscript critically. MCB was involved in the acquisition of data, analysis and interpretation of data, and revised the manuscript critically. All authors approved the final manuscript for publication and agree to be accountable for all aspects of the work.

Disclosure

The authors report no competing interests in this work.

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Supplementary materials

The following method describes the search strategy used to collect the references analyzed in this study. This strategy had three primary facets, outlined below.

• Identification of materials in the primary databases of medical literature that referenced the Seattle Angina Questionnaire. These databases were MEDLINE (Ovid), EMBASE (Elsevier), OVID HealthStar, MEDLINE (PubMed), and the Cochrane Library (Wiley).
• Use of the citation mapping tools Google Scholar (Google), Scopus (Elsevier), and Web of Science (Thomson Reuters), to find all available references to the paper in which Seattle Angina Questionnaire was first described by John Spertus et al in the Journal of the American College of Cardiology in 1995. The search strategy was to locate the original article by Spertus et al and export the references that the tool identified as having cited that article.
• Use of the major clinical trial registries to determine the studies that used the SAQ as an outcome measure. These registries have simple search functions, and so our search terms were “Seattle Angina Questionnaire” or “SAQ”. The strategy then underwent peer review by a librarian experienced in the creation and review of systematic search strategies.

Search strategy

The following search strategy was applied to MEDLINE (Ovid), HealthStar (Ovid), and EMBASE (Ovid). It was adapted for use in PubMed by updating the syntax to match that offered in the PubMed search tool. When searching the Cochrane Library, only the words “Seattle Angina Questionnaire” were used. Databases were searched from inception until 2013.

1. (Development and evaluation of the Seattle Angina Questionnaire: a new functional status measure for coronary artery disease).m_titl.
2. seattle angina questionnaire.mp.
3. seattle angina questionnaire.tw.
4. (seattle adj3 angina).af.
5. (angina adj3 questionnaire).af.
6. saq.mp.
7. or/1–6.
8. spertus ja.au.
9. 7 and 8.