a systematic literature review of cardiovascular event utilities

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Acute and chronic impact of cardiovascular events on health state utilities

Louis s matza, katie d stewart, shravanthi r gandra, philip r delio, brett e fenster, evan w davies, jessica b jordan, mickael lothgren, david h feeny.

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Corresponding author.

Received 2014 Jun 27; Accepted 2015 Feb 27; Collection date 2015.

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Cost-utility models are frequently used to compare treatments intended to prevent or delay the onset of cardiovascular events. Most published utilities represent post-event health states without incorporating the disutility of the event or reporting the time between the event and utility assessment. Therefore, this study estimated health state utilities representing cardiovascular conditions while distinguishing between acute impact including the cardiovascular event and the chronic post-event impact.

Health states were drafted and refined based on literature review, clinician interviews, and a pilot study. Three cardiovascular conditions were described: stroke, acute coronary syndrome (ACS), and heart failure. One-year acute health states represented the event and its immediate impact, and post-event health states represented chronic impact. UK general population respondents valued the health states in time trade-off tasks with time horizons of one year for acute states and ten years for chronic states.

A total of 200 participants completed interviews (55% female; mean age = 46.6 y). Among acute health states, stroke had the lowest utility (0.33), followed by heart failure (0.60) and ACS (0.67). Utility scores for chronic health states followed the same pattern: stroke (0.52), heart failure (0.57), and ACS (0.82). For stroke and ACS, acute utilities were significantly lower than chronic post-event utilities (difference = 0.20 and 0.15, respectively; both p < 0.0001).

Conclusions

Results add to previously published utilities for cardiovascular events by distinguishing between chronic post-event health states and acute health states that include the event and its immediate impact. Findings suggest that acute versus chronic impact should be considered when selecting scores for use in cost-utility models. Thus, the current utilities provide a unique option that may be used to represent the acute and chronic impact of cardiovascular conditions in economic models comparing treatments that may delay or prevent the onset of cardiovascular events.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-015-0772-9) contains supplementary material, which is available to authorized users.

Keywords: Utility, Cardiovascular disease, Acute coronary syndrome, Heart failure, Stroke, Cost-utility, Time trade-off

Cardiovascular disease is a worldwide health concern and the primary cause of non-communicable disease-related death in the United States and Europe [ 1 - 4 ]. Cardiovascular conditions such as heart disease and stroke are associated with serious acute symptoms [ 5 - 8 ], long-term disability [ 9 - 11 ], and substantial costs for patients and healthcare systems [ 1 , 12 , 13 ]. Treatments such as statins have been shown to reduce the risk of cardiovascular events [ 14 - 16 ], and new treatments are in development [ 17 - 19 ].

As new treatments are introduced, cost-effectiveness analyses are needed to examine and compare their value relative to existing treatments. Cost-utility analyses (CUA) are a type of cost-effectiveness analysis commonly conducted to examine treatments for cardiovascular disease and risk factors such as hyperlipidemia [ 20 - 23 ]. A CUA requires health state utility values, which represent the strength of preferences for various health states and are used to calculate quality-adjusted life years (QALYs) [ 24 - 26 ]. A recent systematic review found that a wide range of published utility values are available to represent health states with cardiovascular conditions such as stroke, acute coronary syndrome (ACS), and heart failure [ 27 ].

An important limitation of available cardiovascular utilities is that the time between the cardiovascular event and the utility assessment is not usually reported. For example, commonly cited studies have derived utilities from large surveys in which individuals provided assessments of their own health using a generic preference-based measure [ 28 , 29 ]. These studies reported utilities for subgroups of patients who had experienced cardiovascular events, such as stroke or myocardial infarction, at an unspecified time in their medical history. Therefore, the resulting utility values represent a post-event health state rather than the event itself, and the utility assessment may have occurred many years after the cardiovascular event when patients may have substantially recovered. Because time between the cardiovascular event and utility assessment is not known, the utilities do not necessarily capture the impact of the event or the substantial quality-of-life impact that occurs during the first months or even years following the event. Due to this limitation, utilities from studies that do not report duration of time between the cardiovascular event and utility assessment are difficult to interpret and may underestimate the disutility of cardiovascular events.

Some studies address this problem by documenting and reporting the time between the cardiovascular event and utility assessment. For example, studies conducted in Thailand, the Netherlands, Sweden, and the UK have reported EQ-5D values for stroke patients at specific time points after the event including two months [ 30 ], three months [ 31 ], six months [ 30 - 32 ], nine months [ 31 ], and/or 12 months [ 31 ] post-stroke. Other studies have evaluated utilities at specific time points in relation to hospital discharge [ 32 - 36 ]. Studies in the UK, Australia, and multiple European countries have identified EQ-5D values for myocardial infarction or angina patients before hospital discharge [ 37 ], at discharge [ 38 ], six weeks [ 37 , 39 ], three months [ 37 ], and/or one year [ 38 ] after the event. However, all of these studies may also be underestimating the impact of cardiovascular events because they do not capture the disutility of the event itself.

Therefore, the purpose of this study was to estimate utilities of health states representing cardiovascular conditions while distinguishing between chronic post-event impact and acute impact including the cardiovascular event. Researchers have commented that it would be difficult or perhaps impossible to have patients complete a generic preference-based measure (e.g., EQ-5D) or another type of utility rating in the acute phases immediately following a major cardiovascular event, such as a stroke [ 30 , 40 - 42 ]. As an alternative method, the current study used a health state description (often called a vignette-based) utility assessment approach, which allowed for assessment of chronic post-event health states as well as acute health states including the event itself. Acute health states described a year beginning with the cardiovascular event, followed by description of a typical course of recovery for the remainder of the one-year duration. Chronic health states described patients experiencing ongoing effects of cardiovascular events that occurred in the past. All health states were valued by general population respondents in time trade-off (TTO) tasks, with a one-year time horizon for acute health states and a 10-year time horizon for chronic health states.

Overview of study design

Health state descriptions were drafted based on literature review and input from clinicians who treat cardiovascular disease. Then, the health states were refined based on additional clinician interviews and a pilot study with general population respondents in Edinburgh, UK. Finally, health states were rated in a TTO valuation study with general population participants in Edinburgh and London, UK.

Three cardiovascular conditions were represented in the health states (stroke, ACS, heart failure). For each of these three conditions, a one-year health state was drafted to represent the acute impact, and a post-event health state was drafted to represent ongoing chronic impact. Every participant rated all six health states, and to control for order effects, participants were randomized to begin with either the chronic or the acute health states.

Health state development

Throughout the health state development process, telephone interviews were conducted with a total of nine clinicians (all with MD and/or MBChB degrees) including six cardiologists, two neurologists (who primarily described patients’ experiences of stroke), and one chemical pathologist specializing in diseases related to hyperlipidemia. Five of the clinicians were from the US, while the other four were based in the UK. In the initial phase, telephone interviews were conducted with six clinicians to inform health state development with questions focusing on patients’ typical experiences with stroke, ACS, and heart failure including symptoms; treatment procedures and regimens; and acute and chronic impact. To characterize the acute health states, clinicians were asked to describe the typical patient experience of the event itself; experiences during and after hospitalization; typical course of recovery; duration of treatment and hospitalization; and impact on functioning during the first year after the event. For chronic health states, clinicians were asked to describe typical ongoing symptoms, treatment, and impact in years following an event. Although there is substantial variation in patients’ experiences of cardiovascular events, clinicians were asked to try to focus on the “most typical patient experience” when providing descriptions.

Draft health states were then sent to two of the original six clinicians and three new clinicians who provided comments regarding the clarity and accuracy of the descriptions. This process of refining the health states was iterative, and several of the clinicians were interviewed multiple times as health states were revised during this second phase of interviews. Clinicians’ descriptions of the health states were generally consistent with each other. For some relatively minor points pertaining to treatment (e.g., frequency of clinic visits, typical duration of hospital stay), there were occasional discrepancies between US and UK clinicians. When these discrepancies arose, health states were drafted to be consistent with treatment patterns reported by UK clinicians because these descriptions were intended to be valued in the UK.

Literature review was conducted throughout the health state development process to inform the clinician interview questions and ensure that the health state descriptions were consistent with published research. Literature searches focused on the symptoms, impact, and treatment of stroke [ 8 , 9 , 14 ], ACS [ 5 , 7 , 43 ], and heart failure [ 15 , 44 , 45 ]. The stroke literature revealed the greatest degree of heterogeneity in patient experience, ranging from mild stroke with complete recovery to severe stroke with long-term impairment in speech, cognition, and mobility [ 8 - 10 ]. During the clinician interviews, the clinicians were asked to provide descriptions of a stroke of moderate severity. Initially, literature searches were conducted to identify distinct characteristics of myocardial infarction and unstable angina. However, clinicians reported that patients’ experiences of these two cardiovascular events and their treatment were quite similar, and published literature often groups these events into the single category of ACS [ 5 - 7 , 46 ]. Therefore, acute and chronic health states representing ACS were drafted, instead of separate health states representing myocardial infarction and unstable angina.

Pilot study and selection of utility elicitation methods

After conducting the second round of clinician interviews and making the corresponding health state revisions, the health states were tested in a pilot study with 20 general population participants in Edinburgh, Scotland (13 female; mean age = 41.5 years; age range = 21 to 74) recruited via newspaper and online advertisements. In order to identify the most appropriate utility valuation method for these health states, each participant valued the states using multiple methods including TTO and standard gamble (SG) with several time horizons [ 24 - 26 ]. In utility elicitation procedures, particularly TTO, the duration of time in the health state being rated (i.e., the time horizon) is an important component of the task. This time horizon varies across TTO studies [ 47 ]. The most commonly used TTO time horizon appears to be 10 years, which provides for comparability with previously published TTO utility studies including the influential Measurement and Valuation of Health (MVH) study that elicited utilities for EQ-5D health states [ 48 , 49 ]. However, other time horizons are also frequently used, including shorter durations intended to match the typical clinical course of the health state [ 50 - 52 ] or longer time horizons corresponding to each respondent’s additional life expectancy [ 52 - 57 ]. In the pilot study, 1-year and 6-month time horizons were attempted for the acute health states. For the chronic health states, two time horizons were also attempted: a 10-year time horizon and a time horizon based on each respondent’s self-reported life expectancy. The order of the methods (TTO vs. SG) and time horizons was varied.

In this pilot study, participants consistently reported that the health states were clear and easy to understand. Some participants suggested minor revisions in formatting and word choice, and the health states were edited accordingly. All TTO and SG methods yielded utility scores in a reasonable range with logical discrimination among health states. The TTO method was selected for use in the subsequent main study because it was relatively easy for participants to understand and complete, and because it is consistent with the methods used in many recent utility valuation studies, including the MVH study [ 48 , 49 ].

Based on pilot study results, the 1-year time horizon was selected for the acute health states because some participants seemed resistant to trading time in the 6-month TTO, which resulted in a ceiling effect. For chronic health states, the 10-year time horizon was selected to maintain consistency with the MVH study. Furthermore, although the additional life expectancy time horizon yielded logical results, it resulted in implausible clinical situations in some cases. For example, younger respondents with longer additional life expectancies could be presented with an option of living with chronic heart failure for 40 years, which may be unrealistically long for this cardiovascular condition.

Final health states administered in the time trade-off interviews

Six health states describing cardiovascular events were rated in TTO interviews (see Additional file 1 for full health state text). To avoid the potential bias that could be introduced by health state labels, none of the descriptions provided the name of the cardiovascular condition (i.e., health states did not mention the terms stroke, myocardial infarction, heart attack, ACS, unstable angina, or heart failure) [ 58 ]. Instead, the health states described the relevant events, along with symptoms, treatment, and impact of the events.

Three acute health states described a single year in which a cardiovascular event occurred. The acute stroke (health state A) and ACS (B) descriptions consisted of bullet points grouped into four chronologically ordered sections: the event, the hospital experience, the first 6 months after the event, and 7 to 12 months after the event. The acute heart failure health state (C) described a year in which heart failure occurred for a patient who was at risk of this event due to previous ACS. This health state description included: a brief explanation of the event that occurred before the current year (i.e., ACS), current health subsequent to the earlier event, and the event during the current year (i.e., heart failure). This health state structure was designed to reflect clinicians’ descriptions of the most typical patient who experiences acute heart failure.

The three chronic health states described ongoing health of individuals with cardiovascular disease. These health states can be characterized as post-event health states that describe the ongoing impact of a previous event on subsequent years, rather than the acute impact of the event itself. All three descriptions briefly mentioned the prior event, while focusing primarily on current ongoing health, treatment, and impact. Health states D and E represented long-term effects of stroke and ACS, respectively. Health state F described a patient with chronic heart failure, following ACS that had occurred in a prior year.

Participants

Participants were required to be at least 18 years old; able to understand the assessment procedures; able and willing to give written informed consent; and residing in the UK. Inclusion criteria did not specify particular clinical characteristics because interviews were intended to yield utilities that may be used in cost-utility analyses for submission to health technology assessment agencies, most of whom prefer that utilities represent general population values [ 59 - 62 ]. Participants were recruited via advertisements in three newspapers in Edinburgh, two newspapers in London, and the website Gumtree.com. Potentially interested individuals left voicemail messages with their contact information.

Utility interview procedures and scoring

Utilities were derived by eliciting values for the health state descriptions in a TTO utility interview with a one-year time horizon for acute health states and a 10-year time horizon for chronic health states. All participants evaluated two groups of health states: acute (A, B, C) and chronic (D, E, F). To control for order effects, participants were randomly assigned to rate either the acute or chronic group first, followed by the other group. Prior to beginning TTO procedures, participants completed an introductory ranking task intended to familiarize them with the health state content. During the ranking task, the three health state descriptions (i.e., either acute or chronic) were presented to participants on individual cards. Participants were asked to read the cards carefully and place them in order from most preferable to least preferable. All participants completed the ranking task and the TTO for the first group of three health states before proceeding to the second group of health states.

For TTO ratings of the acute health states (A, B, C), participants were offered a choice between spending one year in the health state being rated or shorter amounts of time in full health (with choices varying in 1-month increments). For TTO ratings of the chronic health states (D, E, F), participants were offered a choice between spending 10 years in the health state being rated or a shorter duration in full health (with choices varying in 1-year increments). Each health state considered better than dead received a utility value on a scale with the anchors of dead (0) and full health (1). The assigned value was calculated based on the choice in which the respondent is indifferent between y months/years in the health state being evaluated and x months/years in full health (followed by dead). The resulting utility estimate (u) is calculated as u = x / y.

If participants indicated that a health state was worse than dead, the interviewer altered the task so that respondents were offered a choice between immediate death (alternative 1) and a 1-year/10-year life span (alternative 2) beginning with varying amounts of time in the health state being rated, followed by full health for the remainder of the time horizon (one example of alternative 2 with a 10-year TTO task would be three years in health state D, followed by 7 years in full health). For these health states, the current study used a bounded scoring approach, which is commonly used for negative utilities [ 24 ]. This scoring approach limits the utility range of health states worse than dead to values between 0 and −1. To compute these bounded negative utility values, the Dolan method was used [ 49 ], as described by Rowen & Brazier [ 63 ]. This method uses the formula u = −x / t, where x is the duration of time in full health and t is the total life span of alternative 2 in the TTO choice. In the current study, t was one year for acute states and 10 years for chronic states, which were the periods of time in the health states being rated plus subsequent months/years in full health.

Data collection and statistical analysis procedures

Interviews were conducted in private conference rooms in London and Edinburgh in November 2013. All procedures and materials were approved by an independent Institutional Review Board (Ethical & Independent Review Services; Study Number 13105–01), and every participant provided written informed consent before completing any study procedures. Participants completed a brief demographic and clinical form, followed by the TTO utility interview described above. Statistical analyses were completed using SAS version 9.2 (SAS Institute, Cary, NC).

Continuous variables, including utilities and pairwise differences between health state utilities, are summarized in terms of means and standard deviations, and categorical variables such as gender and racial/ethnic background are summarized as frequencies and percentages. Demographic characteristics of the London and Edinburgh subgroups were compared with chi-square analyses (for categorical variables) and t-tests (for continuous variables). Descriptive statistics were also used to summarize willingness to trade time and rates of positive and negative utilities for each health state. In addition, pairwise comparisons were performed using t -tests to compare health states within each time horizon (e.g., acute stroke vs. acute ACS) and to compare analogous cardiovascular events across the time horizons (e.g., acute stroke vs. chronic stroke).

Sample description

A total of 268 potential participants were reached for screening. Of these, 262 were eligible, 219 were scheduled for interviews, and 206 attended the interviews. Six of the 206 participants were unable to complete the TTO interview procedures to provide valid TTO data. Thus, a total of 200 valid utility interviews were completed.

The sample was 55% female (n = 110), with a mean age of 46.6 years (Table  1 ). The majority of participants reported ethnicity as white (78.0%), and more participants reported being single (49.0%) than married/living with a partner (36.5%). Most participants reported being employed (28.0% full-time and 33.5% part-time). Less than half of the sample had completed a university degree (n = 89; 44.5%). When asked to report health conditions, the most common responses were depression (n = 29; 14.5%), arthritis (n = 28; 14.0%), diabetes (n = 12; 6.0%), hypertension (n = 19; 9.5%), asthma (n = 9; 4.5%), cancer (n = 9; 4.5%), and thyroid conditions (n = 9; 4.5%). Only four participants reported cardiovascular conditions, two with stable angina (1.0%) and two who had experienced a myocardial infarction (1.0%).

Demographic characteristics

1 P-values are based on t-tests for continuous variables and chi-square analyses for categorical variables.

2 Other self-reported background includes Arab (n = 3) and Latino (n = 2).

3 Includes married (n = 64) and living with partner (n = 9).

4 Includes divorced (n = 20), separated (n = 6), and widowed (n = 3).

5 Includes retired (n = 29), student (n = 15), homemaker (n = 6), disabled (n = 6), “career break” (n = 1), caregiver for elderly parent (n = 1), “live on investments” (n = 1), volunteer (n = 1), and unspecified (n = 1).

There were no significant differences between the London (n = 93) and Edinburgh (n = 107) samples in age, gender, marital status, or employment status (Table  1 ). The Edinburgh sample had a significantly higher percentage of white participants than the London sample (93.5% vs. 60.2%; p < 0.0001).

Health state rankings and utilities

In the introductory ranking task, the acute health states were ranked separately from the chronic health states, and rankings ranged from 1 (most preferable health state) to 3 (least preferable health state). For both acute and chronic health states, stroke was consistently ranked as least preferable. Mean rankings for the acute health states were 1.22 (health state B; ACS), 1.96 (C; acute heart failure), and 2.83 (A; stroke). Mean chronic health state rankings were 1.03 (E; ACS) 2.42 (F; chronic heart failure), and 2.56 (D; stroke).

Mean health state utility scores followed the same order as the health state rankings (Figure  1 ). For the acute health states, the cardiovascular event with the lowest utility was stroke (health state A; utility = 0.33), followed by heart failure (C; 0.60) and ACS (B; 0.67). Utility scores for chronic health states followed the same pattern with the lowest utility for stroke (D; 0.52) and higher scores for heart failure (F; 0.57) and ACS (E; 0.82).

Mean TTO 1 utility scores (N = 200). 1 TTO utility scores are on a scale anchored with 0 representing dead and 1 representing full health. TTO = Time trade-off; ACS = Acute coronary syndrome.

Health state comparisons

Each of the acute health states was significantly different from the other two (Table  2 ). For example, acute stroke (A) had a significantly lower utility than both acute ACS (B) and heart failure (C) with substantial differences between health states (difference scores = 0.34 and 0.28, respectively; both p < 0.0001). The difference between utilities for ACS and heart failure was also statistically significant (p < 0.0001) but of a smaller magnitude (difference = 0.07).

T-tests comparing select pairs of health state utilities (N = 200)

1 TTO utility scores are on a scale anchored with 0 representing dead and 1 representing full health.

Among health states representing long-term effects of cardiovascular conditions, stroke (D) and chronic heart failure (F) had substantially lower utilities than ACS (E) (difference scores = 0.30 and 0.25, respectively; p < 0.0001). Although the difference between stroke (D) and chronic heart failure (F) was still statistically significant (p = 0.04), the difference between these two health states was of a smaller magnitude (0.05).

Each of the acute health states was also compared directly to its parallel chronic health state. For stroke (A vs. D) and ACS (B vs. E), acute utilities were substantially lower than their parallel chronic utilities (difference = 0.20 and 0.15, respectively; both p < 0.0001). The difference between utilities for acute and chronic heart failure was not significant (0.03; p = 0.16).

Rates of positive/negative utilities and willingness to trade time

Additional descriptive analyses were conducted to characterize patterns of responses. The majority of participants rated each of the six health states as better than dead (i.e., utility score > 0): A (84.0%); B (96.0%); C (94.5%); D (94.0%); E (100.0%); F (97.0%). Three of the health states (A, D, and F) were rated as equal to dead (i.e., utility = 0) by one participant. The health state receiving the most negative utility ratings was health state A (acute stroke), which was considered worse than dead by 31 (15.5%) participants. Health state E (chronic ACS) did not receive any negative utility scores. The other four health states (B, C, D, F) were rated as negative by 5.5% or less of the sample.

As expected for relatively severe medical conditions, most participants were willing to trade time to avoid living in the acute health states. A total of 97.0% (n = 194) were willing to trade time to avoid stroke (health state A), 84.5% (n = 169) traded time when presented with heart failure (C), and 74.5% (n = 149) traded to avoid ACS (B). Although there was less willingness to trade when presented with the chronic health states, most participants were still willing to trade time to avoid any of the chronic conditions: 87.0% for stroke, 83.0% for chronic heart failure, and 51.0% for ACS.

These results add to previously published utilities for cardiovascular events by differentiating between acute and chronic effects. Estimates of clinically important differences in utilities obtained via direct elicitation methods (e.g., TTO methods) have suggested that differences of 0.05 to 0.10 can be considered important [ 25 , 64 ]. The differences between chronic and acute phases of stroke and ACS identified in the current study clearly exceed these criteria. These findings suggest that it may be important to consider whether utilities represent the acute or chronic impact when selecting scores for use in cardiovascular cost-utility models. In addition, these results raise questions about previously published utilities that have been assessed without knowledge of the duration of time between the cardiovascular event and the utility assessment. Given that the disutility associated with cardiovascular events is likely to vary depending on the duration of time since the event, it is difficult to interpret utility values without this information.

Of the cardiovascular conditions rated in the current study, acute stroke was the least preferred health state with the lowest mean utility and the greatest proportion of negative utility scores (15.5%). Almost all respondents (97.0%) were willing to trade time to avoid living in this health state. Although chronic stroke had a higher utility than acute stroke, the chronic stroke health state was also considered quite aversive by most participants (utility = 0.52). When completing the TTO task, respondents often said the stroke health states were particularly undesirable because of the functional impact likely to be associated with the impairments in cognition and mobility. The acute health state representing a year in which ACS occurs also had a relatively low utility (0.67), while the chronic ACS health state had a notably higher utility, which is consistent with clinicians’ descriptions of the strong recovery often observed in patients experiencing an ACS.

The two heart failure health states also had relatively low utilities, with little difference between acute and chronic heart failure. Unlike stroke and ACS, the chronic heart failure health state was not drafted to represent the long-term impact of acute heart failure. Instead, the acute and chronic health states were qualitatively different from each other, as described by clinicians interviewed for the current study. The acute health state was drafted to describe a patient experiencing an episode of acute heart failure following a previous ACS event (which occurred prior to the year described in the health state), while the chronic episode was drafted to describe chronic heart failure in a patient who had previously experienced an ACS event.

It is challenging to place the utilities for the three acute health states (A, B, C) in the context of previously published utilities for these cardiovascular conditions. Whereas previous results are primarily based on assessments of patient health at either an unknown or known time following a cardiovascular event, the current acute health states represent a year that includes the event. Utilities of the current chronic health states (D, E, F) are more comparable with previously published values, although variation in respondent samples, geographical region, severity of the health state, and utility elicitation methods also limit comparability with previous research. Still, it does appear that utilities in this study are in an expected range based on previously published cardiovascular utilities. For example, a utility of 0.52 representing chronic effects of a moderate stroke (health state D) is roughly in the middle of the range of utilities (0.12 to 0.81) for moderate stroke reported in a review of previous TTO and SG studies [ 65 ]. The lower utility score of 0.33 for the year including a stroke (health state A) is similar to relatively low values reported by two previous studies assessing utility with the EQ-5D at time points during the first year after a stroke, ranging from 0.21 to 0.41 [ 30 , 32 ]. In addition, the lower utility for acute stroke than for chronic stroke (difference = 0.20) is consistent with the findings of a recent review, which noted that EQ-5D scores tend to improve over time following a stroke [ 27 ]. However, some contrasting results have also been reported, including those from two studies with relatively high utility values during the first year after a stroke [ 31 , 34 ].

When using the current utility scores in a model, researchers would need to be aware of the difference between the acute and chronic health states to ensure that values are being applied appropriately. The three chronic health states (D, E, F) described stable health with a duration of 10 years occurring after an acute event that happened in a previous time period. In contrast, the acute health states (A, B, C) describe an acute event, plus subsequent treatment and recovery in the first year after the acute event. The three acute health states may be conceptualized as path states lasting for a total time period of one year. Path states are health states that describe the experience of a hypothetical patient who proceeds through a sequence of different health states [ 66 , 67 ]. Conceptually, the path-state approach is appealing because the states can be designed to represent the typical course of a patient with a particular medical condition. It allows respondents to consider the duration of each state within the sequence when valuing the overall path. However, the limitation of this approach is that the resulting utilities represent the path, rather than the individual events or health state components within the path. If participants are rating the path as a whole, it is not possible to determine the impact of each health-related event within the path. Therefore, when using the utility scores for health states A, B, and C in a cost-utility model, these values would be most appropriately used to represent a one-year cycle in which the cardiovascular event occurs.

Utility assessment based on hypothetical health states is associated with limitations that should be considered when interpreting data. Previous researchers have commented that it would be difficult or impossible to capture the disutility of these events with the EQ-5D or another method of assessing patients’ current health [ 30 , 40 - 42 ]. Essentially, it is not considered feasible to ask patients to rate their own health during the immediate days or even weeks after a serious cardiovascular event, particularly a stroke, which may cause temporary or permanent cognitive impairment. Therefore, the health state description-based approach was used in the current study because it was feasible to draft and value health state descriptions that included the acute events. Although this method is well-suited for identifying the utility impact of specific medical events, results should be interpreted with appropriate caution. The resulting utility scores represent the specific health states, which are based on clinicians’ descriptions of a typical patient rather than the broad range of symptom severity and outcomes that would be observed in an actual patient sample. Therefore, the extent to which these utilities might differ from values reported by actual patients living in the health states is not known. Still, the utility valuation methodology was selected to maximize comparability to published health state utilities. For example, health states were valued by UK general population participants in a TTO task, which is similar to methods used to value the EQ-5D health states in the MVH study [ 48 , 49 ].

Another possible limitation of the current study is that the acute health states, particularly the description of acute stroke, were longer and more detailed than those used in many similar studies (see health state text in Additional file 1 ). Based on clinicians’ input during health state development, these details were considered necessary to accurately represent key aspects of a typical year beginning with an event and continuing with a gradual partial recovery. However, due to the length, it is possible that some participants may not have been able to consider all parts of the health states when completing evaluations. Some respondents appeared to attend primarily to aspects of impaired functioning that were particularly salient to them, while possibly overlooking other aspects of the health states. If participants fail to notice and consider aspects of the health states, this would lead to some degree of error and inconsistency in the ratings. Although it is possible that this occurred in some cases, steps were taken to minimize this risk. For example, participants were only asked to rate three acute health states, rather than the larger number of health states often included in other studies, and the three chronic health states were presented separately to avoid providing too much information at once. In addition, the acute health states were formatted in a series of sections with headers indicating the chronological structure, which was intended to ensure that the content and sequence of information would be clear. Finally, interviewers were carefully trained to ask questions to ensure that respondents understood and attended to all aspects of the health states, while avoiding leading questions that could bias valuations.

The sample recruitment strategy should also be acknowledged as a limitation of the current data. Utilities were based on evaluations of a general population sample because most health technology assessment agencies prefer that utilities represent the general public or societal view [ 59 - 62 ]. However, the sample was recruited in only two UK locations, and it should not be considered nationally representative. The extent to which the current utility scores would differ from values derived in a nationally representative sample is not known.

Despite limitations, this study and its methodology have several strengths. The health state-based method allows for an addition to published post-event utilities because the acute values are based on health states that include cardiovascular events. Thus, the current utilities provide a unique option that may be used to represent the impact of cardiovascular conditions in models, possibly supplementing utilities derived from actual patients with standardized preference-based measures. With the current utilities, cost-utility models comparing treatments that may delay or prevent the onset of cardiovascular events can distinguish between acute and chronic impact of these cardiovascular events.

Acknowledgments

The authors would like to thank Christine Thompson for statistical programming; Loni Ajagbe, Chantelle Browne, Julia Chen, David Hengerer, Jacqui Kostelec, Amanda Landrian, Sue Thompson, Amara Tiebout, and Nana Young for assistance with data collection; and Amara Tiebout for production assistance.

Abbreviations

Acute coronary syndrome

Cost-utility analyses

Measurement and Valuation of Health study

Quality-adjusted life years

Standard gamble

Time trade-off

United Kingdom

United States

Additional file

Cardiovascular Health States.

Competing interests

Funding for this study was provided by Amgen, Inc., Thousand Oaks, CA, USA. Two of the authors (SG, ML) are employees of Amgen, but their input into the conceptualization and interpretation of this study represented their own opinions, rather than those of the company. LM, KS, ED, and JJ are employees of Evidera, a company that received funding from Amgen for this research. PD, BF, and DF received funding from Amgen for time spent contributing to this research.

Authors’ contributions

LM was the primary writer of this manuscript, and he directed the study including the study design, health state development, data collection, data analysis, and data interpretation. All other authors (KS, SG, PD, BF, ED, JJ, ML, DF) made substantial contributions to the study design, health state development, and/or data interpretation. In addition, KS and JJ co-wrote the manuscript. All authors provided input on multiple drafts of the manuscript and approval of the final draft.

Contributor Information

Louis S Matza, Email: [email protected].

Katie D Stewart, Email: [email protected].

Shravanthi R Gandra, Email: [email protected].

Philip R Delio, Email: [email protected].

Brett E Fenster, Email: [email protected].

Evan W Davies, Email: [email protected].

Jessica B Jordan, Email: [email protected].

Mickael Lothgren, Email: [email protected].

David H Feeny, Email: [email protected].

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• Published: 27 July 2020

Utility value estimates in cardiovascular disease and the effect of changing elicitation methods: a systematic literature review

• Marissa Blieden Betts   ORCID: orcid.org/0000-0002-0557-3946 1 ,
• Pratik Rane 2 ,
• Evelien Bergrath 1 ,
• Madhura Chitnis 1 ,
• Mohit Kumar Bhutani 3 ,
• Claudia Gulea 4 ,
• Yi Qian 5 &
• Guillermo Villa 6  

Health and Quality of Life Outcomes volume  18 , Article number:  251 ( 2020 ) Cite this article

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Identify the most recent utility value estimates for cardiovascular disease (CVD) via systematic literature review (SLR) and explore trends in utility elicitation methods in the last 6 years.

This SLR was updated on January 25, 2018, and identified studies reporting utilities for myocardial infarction (MI), stroke, angina, peripheral artery disease (PAD), and any-cause revascularization by searching Embase, PubMed, Health Technology Assessment Database, and grey literature.

A total of 375 studies reported CVD utilities (pre-2013 vs post-2013: MI, 38 vs 32; stroke, 86 vs 113; stable angina, 8 vs 9; undefined/unstable angina, 23 vs 8; PAD, 29 vs 13; revascularization, 54 vs 40). Median average utilities for MI, stroke, and revascularization increased over time (pre-2013 vs post-2013: MI, 0.71 vs 0.79; stroke, 0.63 vs 0.64; revascularization, 0.76 vs 0.81); angina and PAD showed a decrease in median values over time (stable angina, 0.83 vs 0.72; undefined/unstable angina, 0.70 vs 0.69; PAD, 0.76 vs 0.71). The proportion of utility estimates from trials increased across health states (pre-2013 vs post-2013: 22.5% vs 37.2%), as did the proportion of trials using the EuroQol Five Dimensions Questionnaire (EQ-5D; pre-2013 vs post-2013: 73.8% vs 91.4%). Use of methods such as the standard gamble, time trade-off, and Health Utilities Index has declined.

Conclusions

Health state utilities for cardiovascular health states have changed in the last 6 years, likely due to changes in the types of studies conducted, the patient populations evaluated, and possibly changing utility elicitation methods. The EQ-5D has been used more frequently.

Introduction

Cardiovascular disease (CVD) is the leading cause of mortality worldwide and imposes a significant clinical and economic burden on society. In 2016, CVD accounted for approximately 17.9 million deaths worldwide, representing 31% of all global cases [ 1 ]. In 2010, the estimated global cost of CVD was $863 billion, and it is estimated to rise to $1044 billion by 2030 [ 2 , 3 ]. CVD causes long-term disability, affecting the health-related quality of life (HRQoL) of patients [ 4 ].

Although conventional treatments reduce the risk of CVD, exploring new drugs that provide clinical and economic value—given the current clinical and economic burden—is an ongoing need. Economic evaluations, such as cost-effectiveness analyses (CEAs), are important for comparing new and existing treatments; they are used to determine a treatment’s economic value and to demonstrate that value to patients, physicians, and third-party payers [ 5 , 6 ]. These analyses often inform healthcare reimbursement decisions [ 7 ]. The preferred outcome measure of one type of CEA—cost-utility analyses—is quality-adjusted life-years (QALYs) gained, where the quality of life adjustment is based on utility values [ 8 ]. In order to generate QALYs, health utilities are constructed with values that are usually anchored at 0 and 1, which represent the strength of preferences for health states (ie, 1 represents full health and 0 represents dead). Some methods allow for health states to be regarded as worse than death and have negative valuations [ 9 , 10 ].

Health state utilities are generated using direct methods, indirect methods, or a combination of the two. The main difference between these methods is that direct methods are used to elicit patients’ preferences to health states, whereas indirect methods evaluate patients’ current quality of life and apply population preferences to weight these scores to obtain a utility estimate [ 4 , 11 ].

Smith et al. 2013 previously conducted a systematic literature review (SLR) in 2012 (including studies published between September 1992 and September 2012) that found utility values were lower in patients who experienced cardiovascular (CV) events than in patients who did not [ 12 ]. Furthermore, the authors suggested that the utility estimates for each individual CV event varied greatly, likely due to differences in assessment methodologies and patient populations. The goal of this current systematic review was to update and expand upon the review by Smith et al., which evaluated utilities for myocardial infarction (MI), angina, and stroke to identify the most recent utility values for these health states, as well as revascularization and peripheral artery disease (PAD) and to gain insight into changing trends in utility elicitation methods and values, which can be used to inform/calculate QALYs. In addition, this review identified the methods used to elicit utilities and examine variability among utility values for a given CV health state, and how those values may be impacted by factors such as type of respondent, study design, and geographic location.

Search strategy

The methodology of this SLR update was consistent with the original SLR presented in Smith et al. [ 12 ]. The SLR was designed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. The original search identified studies published between September 1992 and September 2012. For the update, an electronic database search was conducted in Embase, MEDLINE, and Health Technology Assessment Database (HTAD), and it used search algorithms that were aimed at identifying relevant studies published between September 2012 and January 2018 presenting utilities for MI, stroke, and angina, as well as studies published between September 1992 and January 2018 presenting utilities for new CV health states, PAD, and revascularization (any-cause, including both peripheral and coronary). The search identified publications using keywords related to the CV health states (MI, stroke, angina, PAD, and revascularization) and utilities (eg, utility, time trade-off [TTO], standard gamble [SG], Health Utilities Index [HUI], Short-Form Six Dimensions [SF-6D], and EuroQol Five Dimensions Questionnaire [EQ-5D]). These most commonly used direct and indirect methods across the CV events of interest are described in Table  1 . The complete list of keywords is provided in Supplementary Tables  1 , 2 , and 3 . Only papers published in English, pertaining to humans, and indexed during the search period (September 1992 to January 2018) were eligible for inclusion. To supplement the database searches, grey literature (reports and conference abstracts) presented by relevant scientific organizations or health technology assessment (HTA) body websites within the last 6 years (2012–2018) were also searched using the same main keywords. Supplementary Table  4 provides an overview of the scientific conferences and HTA websites that were examined for this review.

To understand the changing trends in utility value estimates (median and interquartile ranges [IQRs]) and methods used for utility elicitation, studies from the previous review and updated SLR were compared. This was done by assessing trends in the last 6 years by stratifying the period as pre-2013 (1992–2012) vs post-2013 (2013–2018).

Study review and selection

All abstracts were manually reviewed by a single reviewer, who used prespecified inclusion and exclusion criteria (Supplementary Table  5 ; participants, interventions, comparators, outcomes, and study design [PICOS] criteria) to select primary studies and systematic reviews that reported utilities for CV health states. All papers accepted during abstract screening were reviewed in full text by 2 independent reviewers, who also used the same prespecified inclusion and exclusion criteria. Any discrepancies in the decisions were reviewed and resolved by a third, senior reviewer.

This review was not limited by the type of utility measure; however, simple visual analogue scale (VAS) methods, which represent a direct approach, were not considered as valid utility elicitation methods [ 15 ] and were excluded.

Data extraction

The following data and characteristics were captured from all articles included in the systematic review: publication year, study design, interventions (if applicable), country, CV health state, utility methods, utility values, population of respondents, and sample size. The studies on angina that did not specify whether the patients had stable or unstable angina, or reported on a mixed angina population, were grouped with the unstable angina studies. This was because the utility values for unspecified and unstable angina were similar to each other (average of 0.71 for both), whereas those for stable angina appeared to be slightly higher (average of 0.77).

Qualitative synthesis

Studies that were published before 2013 (1992–2012) were compared with studies published after 2013 (2013–2018) in terms of utility value estimates and utility elicitation methods in order to explore trends over time by means of a qualitative synthesis. As only a qualitative synthesis was prospectively planned, no statistical inference was performed. Additionally, due to the wide range and skewed utility value distributions in the identified studies, median and IQRs were generated from average utility values reported (as either mean or median) in the literature for both time periods.

Definition of minimally important differences

Although HRQoL is currently recognized as an important endpoint in clinical trials, the meaningfulness of HRQoL scores may not be apparent to patients, clinicians, or researchers [ 16 ]. Minimally important differences (MIDs) for health state utilities vary by measure and are not well established. It has been suggested that differences among health state utilities of at least 0.05 can be considered clinically important [ 17 ].

A total of 11,035 citations were identified across the databases. After removing duplicates, 8768 unique citations were eligible for abstract screening. Of these, 1905 were included for full-text screening, during which 1549 articles further were excluded, as described in the PRISMA diagram (Fig.  1 ). In total, 375 publications reported qualitative and quantitative utility values in MI, stroke, angina, revascularization, and/or PAD and were included in the SLR.

PRISMA diagram. Abbreviations: CV cardiovascular, HTAD Health Technology Assessment Database

Among the included papers, 70 publications reported utilities associated with MI, of which 38 were published before 2013 and 32 after 2013. For stroke, a total of 199 publications reporting utilities were identified, of which 86 were published before 2013 and 113 after 2013. Additionally, 17 publications reported stable angina utilities (8 pre-2013 and 9 post-2013), 31 publications reported utilities for undefined/unstable angina (23 pre-2013 and 8 post-2013), 42 publications for PAD (29 pre-2013 and 13 post-2013), and 94 publications for revascularization (54 pre-2013 and 40 post-2013). The process and results of the searching and screening are presented in Fig. 1 .

Trends in utility values over time by type of CV event

Table  2 presents the estimated median (IQR) utility values by method of elicitation, type of disease, and publication year. When looking across CV events, regardless of the utility measure used, the median utility values were lowest for stroke compared with the other CV events of interest. When comparing median (IQR) utility values between the 2 time periods (pre-2013 vs post-2013), several trends were observed: median (IQR) utility values for MI and revascularization showed an increase over time (pre-2013 vs post-2013, respectively: MI, 0.71 [0.64–0.76] vs 0.79 [0.73–0.86]; revascularization, 0.76 [0.67–0.82] vs 0.81 [0.74–0.85]), and values for stroke showed a slight increase over time (0.63 [0.45–0.72] vs 0.64 [0.44–0.78]). However, values for stable angina (0.83 [0.68–0.94] vs 0.72 [0.66–0.78]), unstable/unspecified angina (0.70 [0.62–0.82] vs 0.69 [0.62–0.85]), and PAD (0.76 [0.69–0.85] vs 0.71 [0.63–0.78]) decreased over time. It should be noted that only 4 studies reported utilities for unstable angina, whereas the majority of studies in this group did not specify the type of angina. Figure  2 presents the distribution of utility values for MI and stroke. Most studies reported utilities between > 0.7 and 0.8 for MI in both time periods and values from > 0.6 to 0.7 for stroke.

Distribution of utility values by event type (MI, stroke) . Abbreviation: MI myocardial infarction

These findings varied by method of utility elicitation (Fig.  3 ). Across CV health states, utilities measured by the EQ-5D and the HUI typically improved over time when comparing studies published before 2013 to those published after 2013, whereas utilities measured by the direct methods (SG and TTO) consistently worsened over time. However, the HUI, SG, and TTO were only used by a limited number of studies within the last 6 years.

Proportion a of utility values by method of elicitation . a Percentages may add to > 100%, as some studies reported utility values using more than 1 method of elicitation. b Other methods include Quality of Well-Being, Utility Based Quality of life-Heart questionnaire, Assessment of Quality of Life, and Preference-based Stroke Index. Abbreviations: CVD cardiovascular disease, EQ-5D EuroQol Five Dimensions Questionnaire, HUI Health Utilities Index, MI myocardial infarction, PAD peripheral artery disease, SF-6D Short-Form Six Dimensions, SG standard gamble, TTO time trade-off

Trends in utility values over time by method of utility elicitation

When comparing direct elicitation methods with indirect elicitation methods across CV health states, direct methods yielded, on average, the highest utilities within studies published prior to 2013; in contrast, direct methods yielded the lowest utility value estimates among studies published after 2013. This was largely driven by a reduction in the average utilities generated from direct methods over time (pre-2013 vs post-2013, respectively: 0.85 vs 0.50), as the change in utilities generated via indirect methods was less extreme (0.69 vs 0.73).

Trends in utility over time by methodologies used by CV health state

Table  3 displays the characteristics of the included studies. The usage of the SG and TTO methods decreased substantially in the last 6 years across all CV health states (pre-2013 vs post-2013, respectively: SG, 12.8% vs 2.1%; TTO, 14.4% vs 2.1%). The EQ-5D was the most common utility elicitation method in both time periods, followed by the SF-6D. There was a notable increase in the use of the EQ-5D for all CV health states (pre-2013 vs post-2013, respectively: 66.3% vs 88.3%) in studies that were published in the last 6 years compared with studies published prior to 2013. Use of the HUI decreased substantially in the last 6 years across the CV health states (pre-2013 vs post-2013, respectively: HUI, 10.2% vs 1.1%) when compared to studies published before 2013. Of note, the HUI was not used among studies reporting utilities for angina in either time period. Use of the SF-6D showed a slight increase over the last 6 years (pre-2013 vs post-2013, respectively: 7.5% vs 8.0%), which was driven primarily by its increased incorporation for estimating utilities for MI, stable angina, PAD, and revascularization, as its use has actually decreased for stroke and unstable/unspecified angina.

The increase in use of the EQ-5D coincides with an increase in trials generating utility data (Supplementary Fig.  1 ). The proportion of utility estimates coming from trials increased from 22.5% (pre-2013) to 37.2% (post-2013) across all CV health states. Prior to 2013, prospective cohort studies were the most commonly used study design to derive utilities from CV health states (35.8%), whereas over the last 6 years this decreased to 31.4%. Trials were more likely to measure utilities via the EQ-5D, with 31 of 42 (73.8%) trials and 93 of 145 (64.1%) other study designs publishing CV utility values prior to 2013 using the EQ-5D. The increase in use of the EQ-5D can be attributed not only to the increase in the proportion of trials publishing utilities, but also that trials currently use the EQ-5D more often, with 64 of 70 (91.4%) trials publishing CV utility values in the last 6 years using the EQ-5D. An increase in the use of the EQ-5D among surveys and prospective cohorts was also observed in the last 6 years, with 25 of 39 (64.1%) surveys and 54 of 59 (91.5%) prospective cohorts publishing CV utility values.

The use of direct methods declined specifically for studies eliciting utilities from patients, but otherwise remained steady (Supplementary Fig.  2 ). The proportion of studies using indirect methods that evaluated respondents other than patients (general population, caregivers, or mixed) increased slightly from 1.5% among studies published before 2013 to 2.8% among more recent studies. However, it should be noted that only a few studies elicited values from respondents other than patients. Across CV health states, most studies that reported utilities derived them from patients in both time periods (pre-2013 vs post-2013, respectively: 183 of 187 [97.9%] vs 181 of 188 [96.3%]). The proportion of utility values derived from general-population studies remained stable over this period (pre-2013 vs post-2013, respectively: 5 of 187 [2.7%] vs 6 of 188 [3.2%]). Since the proportion of studies using direct methods has decreased, and the proportion of studies eliciting utilities from general-population respondents has slightly increased, it follows that the proportion of direct measures evaluating general-population respondents increased from pre-2013 (5 of 42 [11.9%]) to post-2013 (4 of 8 [50.0%]) among all CV health states. Only a few studies featured utility values derived from caregivers or mixed respondents, all of which estimated utilities for stroke as the health state.

Trends in utility over time by geographical region

Across CV health states and in both time periods, most studies were conducted in Europe, followed by the United States (US) and Canada (Supplementary Fig.  3 ). There was a decrease in studies conducted in the US and Canada in the last 6 years (pre-2013 vs post-2013, respectively: 28.3% vs 14.4%). In contrast, more utility studies emerged from Asia. Among the studies conducted in Asia, the vast majority of data reported were for stroke, and there were a limited number of studies reporting utility values for the other CV health states.

The goal of this SLR was to update and expand upon the review conducted by Smith et al. [ 12 ] to identify the most recent utility values for stroke, MI, angina, PAD, and revascularization and to gain insight into changing trends in utility values over time and corresponding elicitation methods. The results of the SLR are summarized qualitatively, to depict the variation in utility values observed across studies in this broad SLR. The decision not to conduct a meta-analysis was further confirmed by a 2015 review of utility value meta-analyses, which found substantial differences when direct vs indirect methods were compared, and noted that meta-techniques may not be appropriate given substantial heterogeneity among utility methods [ 18 ]. In another systematic review on the EQ-5D utility values in CVD, the authors attempted to conduct a meta-analysis but deemed it was inappropriate to further estimate pooled utility scores via meta-analytic techniques due to the substantial observed heterogeneity with respect to both study design and patient characteristics. Given this observed heterogeneity, effect sizes obtained via meta-analytic techniques are not generalizable to other methods or health states [ 19 ].

This SLR reports utility values consistent with values used in several large-scale economic evaluations in CVD [ 20 , 21 ], in particular for MI and stroke. For example, in the study conducted by Ara et al. [ 20 ], the authors used the Health Surveys for England (HSEs) conducted in 2003 and 2006 to elicit EQ-5D scores for stroke, heart attack, and angina; the mean EQ-5D score for patients with heart attack was 0.74, which was in line with the median (IQR) utility value pre-2013 for MI in the current SLR (0.72 [0.68–0.76]). The mean EQ-5D utility value for individuals with stroke was 0.66, which aligns with the median (IQR) utility value post-2013 for stroke observed in the current SLR (0.65 [0.44–0.78]). In our study, widely varying utility values were observed for stroke. The observed heterogeneity suggests that it may be difficult to assess utilities for stroke.

The mean utility value for angina (0.692) in the Ara et al. [ 20 ] paper was slightly lower compared with the pre-2013 median (IQR) utility values for angina (stable angina, 0.83 [0.68–0.94]; unstable/undefined angina, 0.70 [0.62–0.82]), but similar to post-2013 values (stable angina, 0.72 [0.66–0.78]; unstable/undefined angina, 0.69 [0.62–0.85]) in the current review. The study conducted by Ara et al. did not report utility values on PAD or revascularization.

In comparing the 187 CV utility studies published during or before 2012 with the 188 published during or after 2013, we observed changes in recent years with respect to the actual values being published in CV utility studies; average utility values for MI, stroke, PAD, and revascularization increased over this period, whereas utilities for angina declined. This likely represents changes in the types of populations and health states being measured. Improvements in healthcare over time may have also contributed to the observed changes. Disease characteristics, disease severity, and duration of disease all contribute to substantial variation in utility scores [ 12 , 22 ]. As we did not control for sample characteristics, the higher utility estimates observed for several instruments could have been influenced by the population under evaluation rather than the specific utility method. These changes in recent years underscore the necessity of selecting utility values that precisely represent the health state of interest for a cost-utility analysis.

However, the observed changes in CV values, particularly the increases observed for MI and stroke, may be confounded by changes in the methods used. This review found that the EQ-5D is the most common measure across types of CV health states, its use is increasing, and it yielded higher utilities than direct methods in the last 6 years. In the last 6 years, the average values for indirect measures have risen, whereas the average values for direct methods have declined. This increase in the use of the EQ-5D appears to be related to the general increase in trials estimating utility values; however, even among trials, the EQ-5D was utilized more frequently in the last 6 years. The National Institute for Health and Care Excellence (NICE) and other payers, such as the Scottish Medicines Consortium (SMC), recommended the EQ-5D as the preferred utility in the reference case for cost-utility analyses in 2004 (to encourage comparability across studies) [ 23 ] and clarified recommendations in 2013 [ 24 ], and it is possible that these trends reflect increasing uptake of those recommendations in the last 6 years. It is also likely that trials are measuring utility values more often, as the need for cost-utility assessment, and consequently utility values representing the precise patient population in question, has grown in the current health reimbursement market. Our review also observed a substantial increase in the number of CV utility studies conducted in Asia. This likely reflects the growing HTA trend in this part of the world [ 25 , 26 ].

Furthermore, our review observed that the implementation of direct utility elicitation methods has declined substantially in CVDs in recent years. This could be due to the ease of implementation and lower cost of a standardized questionnaire, such as the EQ-5D, compared with direct methods, which often require bespoke design. In addition, it is likely that investigators are also relying more frequently on the EQ-5D as they have become increasingly comfortable with the validity of the measure. However, given that indirect methods represent an estimation of utility values and do not measure the patient preference, direct methods should still be considered a valuable tool. We did not include VAS utility measures in our SLR because of their potentially limited use for measuring preferences for health states [ 15 ]. Moreover, others have raised concerns regarding the validity of VAS for this purpose [ 27 , 28 , 29 ].

The differences in utility values across methods observed in our review is well documented in the literature [ 30 , 31 , 32 , 33 , 34 , 35 ]. However, the relationship between direct and indirect utility measures has not been as thoroughly documented. There is a widely held impression among health economists that direct methods tend to yield higher utilities (reflecting better reported health) for given health states compared with indirect methods, regardless of the type of direct or indirect method used (eg, TTO vs SF-6D or EQ-5D vs SF-6D) [ 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Different methods of utility elicitation can result in varying scores, even for the same patient population assessed. For example, Hallan et al. [ 43 ] used both SG and TTO methods and found significantly higher scores for both minor and major stroke health states using SG compared with TTO assessments. Utility scales also vary in sensitivity, which may further hinder comparisons of utility values across measures. For example, the EQ-5D index score has been shown to have a ceiling effect, and the SF-6D has been observed to have a floor effect [ 31 , 44 , 45 ]. However, the EQ-5D scale has been reported to be more sensitive than the SF-6D in monitoring values for HRQoL, particularly at the lower end of the scale for patients with chronic obstructive airways disease, osteoarthritis, irritable bowel syndrome, lower back pain, or leg ulcers, and for postmenopausal women and healthy elderly individuals (aged 75+ years) [ 31 ]; this trend was also observed in the current SLR, although this is not usually the case for CVD. In addition, the HUI focuses on physical and emotional health and does not include questions on social functioning or satisfaction [ 46 ].

This review found that health utility values for MI, stroke, angina, PAD, and revascularization have changed substantially when comparing different time periods (pre-2013 vs post-2013), likely due to changes in the types of studies being conducted (increase in trials eliciting utilities) and the patient populations being evaluated (in particular, changes in disease severity and duration of disease). Changing utility methods may also partially explain the observed changes in utility values. The EQ-5D has been used more frequently, with an increasing number of trials using this measure. Additionally, an increasing number of studies in Asia estimating CV utilities has been observed. With varying values observed across utility methods used and populations, care should be taken when choosing utility values to use in economic evaluations of new technologies. Future analyses that assess changes in utilities by duration of disease and/or treatment could be useful to identify any trends for patients with early vs late stage disease and help inform the choice of utility values for use in economic evaluations of new cardiovascular technologies.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

Cost-effectiveness analysis

Cardiovascular

• Cardiovascular disease

EuroQol Five Dimensions Questionnaire

Health-related quality of life

Health Surveys for England

Health technology assessment

Health Technology Assessment Database

Health utilities index

Interquartile range

Myocardial infarction

Minimally important difference

National Institute for Health and Care Excellence

Peripheral artery disease

Participants, interventions, comparators, outcomes, and study design

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Quality-adjusted life-year

Short-Form Six Dimensions

Standard gamble

Systematic literature review

Scottish Medicines Consortium

Time trade-off

United States

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Betts, M.B., Rane, P., Bergrath, E. et al. Utility value estimates in cardiovascular disease and the effect of changing elicitation methods: a systematic literature review. Health Qual Life Outcomes 18 , 251 (2020). https://doi.org/10.1186/s12955-020-01407-y

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Utility value estimates in cardiovascular disease and the effect of changing elicitation methods: a systematic literature review

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• 1 Evidence Synthesis, Modeling & Communication Evidera Inc, Waltham, MA, USA. [email protected].
• 2 Amgen Inc, Global Health Economics, Thousand Oaks, CA, USA.
• 3 Evidence Synthesis, Modeling & Communication Evidera Inc, Waltham, MA, USA.
• 4 BresMed Health Solutions Ltd., Gurugram, Haryana, India.
• 5 Evidence Synthesis, Modeling & Communication, Evidera, London, UK.
• 6 Amgen Inc, Intercontinental HQ-Value, Access & Policy, Thousand Oaks, CA, USA.
• 7 Amgen (Europe) GmbH, Global Health Economics, Zug, Switzerland.
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• DOI: 10.1186/s12955-020-01407-y

Objective: Identify the most recent utility value estimates for cardiovascular disease (CVD) via systematic literature review (SLR) and explore trends in utility elicitation methods in the last 6 years.

Methods: This SLR was updated on January 25, 2018, and identified studies reporting utilities for myocardial infarction (MI), stroke, angina, peripheral artery disease (PAD), and any-cause revascularization by searching Embase, PubMed, Health Technology Assessment Database, and grey literature.

Results: A total of 375 studies reported CVD utilities (pre-2013 vs post-2013: MI, 38 vs 32; stroke, 86 vs 113; stable angina, 8 vs 9; undefined/unstable angina, 23 vs 8; PAD, 29 vs 13; revascularization, 54 vs 40). Median average utilities for MI, stroke, and revascularization increased over time (pre-2013 vs post-2013: MI, 0.71 vs 0.79; stroke, 0.63 vs 0.64; revascularization, 0.76 vs 0.81); angina and PAD showed a decrease in median values over time (stable angina, 0.83 vs 0.72; undefined/unstable angina, 0.70 vs 0.69; PAD, 0.76 vs 0.71). The proportion of utility estimates from trials increased across health states (pre-2013 vs post-2013: 22.5% vs 37.2%), as did the proportion of trials using the EuroQol Five Dimensions Questionnaire (EQ-5D; pre-2013 vs post-2013: 73.8% vs 91.4%). Use of methods such as the standard gamble, time trade-off, and Health Utilities Index has declined.

Conclusions: Health state utilities for cardiovascular health states have changed in the last 6 years, likely due to changes in the types of studies conducted, the patient populations evaluated, and possibly changing utility elicitation methods. The EQ-5D has been used more frequently.

Keywords: Cardiovascular disease; EQ-5D; Health state utilities; Trends.

Publication types

• Systematic Review
• Cardiovascular Diseases / economics*
• Cardiovascular Diseases / psychology
• Cost-Benefit Analysis
• Health Status Indicators*
• Middle Aged
• Quality of Life*
• Quality-Adjusted Life Years
• Surveys and Questionnaires / standards

Grants and funding

• Not Applicable/Amgen