Expert Review of Pharmacoeconomics & Outcomes Research

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Challenges to time trade-off utility assessment methods: when should you consider alternative approaches? Kristina S Boye, Louis S Matza, David H Feeny, Joseph A Johnston, Lee Bowman & Jessica B Jordan To cite this article: Kristina S Boye, Louis S Matza, David H Feeny, Joseph A Johnston, Lee Bowman & Jessica B Jordan (2014) Challenges to time trade-off utility assessment methods: when should you consider alternative approaches?, Expert Review of Pharmacoeconomics & Outcomes Research, 14:3, 437-450 To link to this article: http://dx.doi.org/10.1586/14737167.2014.912562

Published online: 15 May 2014.

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Challenges to time trade-off utility assessment methods: when should you consider alternative approaches? Expert Rev. Pharmacoecon. Outcomes Res. 14(3), 437–450 (2014)

Kristina S Boye*1, Louis S Matza2, David H Feeny3,4, Joseph A Johnston1, Lee Bowman1 and Jessica B Jordan2 1 Global Health Outcomes, Eli Lilly and Company, Lilly Corporate Center, DC 2142, Indianapolis, IN, USA 2 Outcomes Research, Evidera, 7101 Wisconsin Avenue, Suite 600, Bethesda, MD, USA 3 Department of Economics, University of Alberta, Edmonton, AB, Canada 4 Health Utilities Incorporated, Dundas, ON, Canada *Author for correspondence: Tel.: +1 317 651 4039 Fax: +1 317 277 1697 [email protected]

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In recent years, the time trade-off (TTO) method, most commonly with a 10-year time horizon, has been the most frequently used approach for direct health state utility assessment, likely due to National Institute for Health and Care Excellence (NICE) preference for comparability with the EQ-5D, which has a utility scoring algorithm derived via this method. Although comparability to previous utility studies is important, there are situations when the TTO method may not be appropriate. The purpose of the current review is to highlight challenges to the TTO method. Five challenges to the TTO method are discussed: mild health states, small differences among health states, temporary health states, pediatric health states, and assessment of samples with particular characteristics. Some of these challenges are associated with the 10-year time horizon, while other situations may raise issues for TTO methods regardless of the time horizon. Alternative approaches for valuing health states are suggested. KEYWORDS: patient preference • QALY • standard gamble • time horizon • time trade-off • TTO • utility

The time trade-off (TTO) method is a commonly used approach for determining the desirability of a health state and estimating health state utilities, which are scores that can be used to calculate quality-adjusted life years (QALYs) in cost–utility models of healthcare interventions [1]. TTO was originally developed as a potentially less complex alternative to standard gamble (SG) methods for obtaining health state utilities. The term health state may refer to patients’ own current health, but more frequently refers to health state descriptions that are often called vignettes or hypothetical health states. TTO and SG methods may be used to value respondents’ own current health, hypothetical health states, or health state profiles derived from condition-specific or generic classification systems such as the EuroQol EQ-5D. Although both TTO and SG are choicebased direct utility assessment methods, TTO differs from SG in that it does not require the respondent to consider probabilities [1–3]. In the SG approach, respondents indicate their

10.1586/14737167.2014.912562

value for health states by choosing between two options: either certainty of living in the health state being rated or a gamble between full health and death. The probability of the gamble is varied until respondents are indifferent between the two alternatives. TTO health state valuations involve a choice between living in a health state for a given period of time or living in full health for a shorter period of time. The amount of time in full health is varied until the respondent is indifferent between the two alternatives. In both SG and TTO valuations, the health state is assigned a utility score anchored to values of zero representing dead and one representing full health. Although SG methods were developed first, TTO appears to be the most frequently used approach for direct utility assessment of health states, as indicated by several literature reviews [4–6]. For example, one review examined the selection and use of utility values for economic models in NICE technology appraisals from 2004 to 2008 [7]. Findings revealed that utilities came from a broad range of

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sources including previously published literature, the EQ-5D, mapping to a generic preference-based health-related quality of life measure, and direct utility assessment of health states. TTO was the most common method for direct health state valuation, appearing in 54% of submissions. The dominance of the TTO method reflects recommendations stated in the influential NICE Guide to the Methods of Technology Appraisal. The current and previous NICE guides state a preference for utility values based on the EQ-5D in order to maximize ‘consistency across appraisals’ [8–10]. The guides also allow for alternative utility assessment approaches when the EQ-5D is not ‘available’ or ‘appropriate.’ Other reimbursement authorities, such as those in Canada, Scotland and Australia, provide similar or possibly greater flexibility [11–14]. For situations where the EQ-5D is not available or appropriate, the NICE guides have provided brief recommendations. For example, the 2008 guide specified that alternative approaches should be ‘comparable to those used for the EQ-5D,’ specifying that valuation methods ‘should use the TTO method in a representative sample of the UK population…to retain methodological consistency with the methods used to value the EQ-5D.’ Utilities for the EQ-5D health states were originally derived in the Measurement and Valuation of Health (MVH) study, which used TTO methods with a 10-year time horizon [15,16]. The 2013 guide no longer explicitly recommends TTO methods for situations when the EQ-5D is unavailable or inappropriate, but given the continuing stated preference for the EQ-5D and consistency across appraisals, it seems likely that the 10-year TTO will continue to be a favored direct elicitation method when deriving utilities for use in NICE submissions. In response to the NICE guides, researchers frequently design and implement utility valuation studies with TTO methods consistent with those used in the MVH study. Published utility studies frequently cite the NICE guides when explaining why TTO methods were selected [17–19]. Furthermore, some articles have specified that details of TTO methodology, such as the 10-year time horizon, were selected in order to maintain consistency with MVH study methods or ‘standard’ methods [20,21]. Although the MVH methodology has been a useful approach for identifying utilities of a wide range of health states, some researchers have questioned the validity of TTO methods and the comparability of TTO utilities derived from different studies [22–24]. Because the TTO method is so commonly used, it is important to carefully consider its strengths, limitations and appropriate use. The purpose of the current review is to highlight situations that present challenges to the TTO method and suggest alternative approaches for health state valuation (challenges are summarized in TABLE 1, and alternative approaches are listed in TABLE 2). Some of these challenges are associated with the 10-year time horizon, while other situations may raise issues for TTO methods regardless of the time horizon. 438

Mild health states

TTO methods may not be effective for valuing and differentiating among health states in the upper/healthy range of the utility scale. When respondents perceive medical conditions to be relatively mild, they may be unlikely to accept any reduction in lifespan in order to avoid these health states. If a respondent is not willing to trade time, the TTO task suffers from a ceiling effect. If a study has multiple mild health states suffering from this ceiling effect, the TTO task would be unable to distinguish among health states even when respondents genuinely prefer one health state over another. Therefore, the resulting utilities would not accurately represent differences in treatment outcomes in cost–utility models. Several published studies have reported a ceiling effect with TTO methods used to rate both hypothetical health states and patients’ own current health. In one study, women were given hypothetical health state descriptions of menopausal symptoms, and some respondents were unwilling to trade any time to avoid the health state representing mild menopausal symptoms [25]. Women who had personal experience with more severe symptoms were less likely to trade time than women with milder symptoms (e.g., 8 of 21 ‘severe sufferers’ did not trade time). The TTO ceiling effect was also noted in a study reporting utility values associated with visual function in patients with glaucoma [26]. The median utility was at the ceiling for patients in the top three quartiles of visual function, and the authors described this result as a ‘high documented percentage of zero-traders.’ In this study, patients’ health state utilities were also assessed with two generic preference-based measures, the EQ-5D and SF-6D, and neither of these two measures suffered from a similar ceiling effect. One explanation for unwillingness to trade has been provided by a study involving qualitative interviews with respondents from the MVH study. This study was conducted to examine three key issues emerging from the MVH study, including why some respondents are unwilling to trade any time in TTO in order to avoid a health state that they rated below full health on a visual analogue scale [27]. The respondents were asked to explain their choices at various points in the TTO exercise. Of 43 respondents, 15 (34.8%) refused to trade even a few days to avoid a health state that they rated below full health on the visual analogue scale. The predominant explanation was that it was not worth sacrificing any time from their life if they believed they could cope with the health state in question. The authors describe this as a ‘threshold of tolerability’ effect, which means that a health state must be below some tolerance level in order for participants to trade even a small amount of time. These findings suggest that the TTO method in the MVH study may not be the ideal approach for assessing utilities of mild conditions or medical events, particularly when a study aims to distinguish among health states at the upper end of the utility scale. Therefore, when it is necessary to represent mild events or conditions in cost–utility modeling, it may be beneficial to consider deriving utilities via alternative approaches. Expert Rev. Pharmacoecon. Outcomes Res. 14(3), (2014)

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• Use a condition-specific multiattribute measure [30,31]. • Use a generic preference-based measure (e.g., EQ-5D or HUI), preferably one that includes relevant dimensions [2,67]. • Use a chaining approach [3,32,34–36,38–41]. • Change the time horizon of the TTO task. For example, a time horizon based on the respondent’s own additional life expectancy or the clinical condition described in hypothetical health states may be more sensitive in the upper range of the utility scale [29]. • Use a condition-specific measure with a utility scoring algorithm developed via mapping to a generic preference-based measure [108] or via item response theory and Rasch analysis [30,31,109]. • Use a generic preference-based measure that includes a relevant domain (e.g., EQ-5D or HUI). • Personalize the TTO time horizon based on each respondent’s self-reported additional life expectancy, which may increase sensitivity to health state differences [29]. • Conduct an observational study in which patients rate their own current health at the time they are experiencing a temporary event. • Shorten the TTO time horizon to provide a realistic representation of the duration of the temporary health state [60]. • Rate temporary health states as if they were chronic [32,61–63]. • Use a path state method [32,64,65]. • Use a chaining approach [3,32,34–36,38–41]. • Use a two-step rating process that involves adding temporary events to a chronic health state and estimating the disutility associated with the temporary events [60]. • Use a post-event health state approach. • Use a parent proxy direct utility approach [39,69,75]. • Use a generic preference-based measure that has been used to estimate utility values for children [43,77–85]. • Use a child-specific multiattribute measure such as the CHU9D [86,87]. • Use a collective utility value based on a combination of child and family perspectives [43]. • Extend the time horizon to be consistent with children’s longer life expectancy, if the health state can reasonably apply across an entire lifespan [69,73].

• Set recruitment targets to ensure a reasonably diverse sample. • Collect data on relevant demographic characteristics to ensure that the sample is reasonably balanced with regard to variables that have been shown to affect TTO responses (e.g., age, religion, education level and caregiver status). • If the respondent sample will include a substantial proportion of younger respondents, then SG, generic preference-based measures or a TTO with a longer time horizon may be more appropriate than a 10-year TTO.

1. Mild health states: • With health states describing mild symptoms, participants may be unwilling to trade even a small amount of time. If participants are unwilling to trade, the TTO task suffers from a ceiling effect. If a study has multiple health states suffering from a ceiling effect, the TTO task would be unable to distinguish among health states and respondents’ preferences for one health state over another would not be detected.

2. Small differences among health states: • The TTO method may not be optimal for studies involving valuation of multiple health states with minor variations that may be important to some respondents.

3. Temporary health states: • The TTO with relatively long time horizons (e.g., the commonly used 10-year time horizon) is not useful for valuing some temporary health states because respondents would be faced with unrealistic or illogical choices.

4. Pediatric health states: • Many children are unlikely to have a sufficient understanding of the abstract concepts of extended time horizons and mortality. Without this comprehension, children are unable to provide valid TTO responses. • Some researchers have questioned whether it is ethical to ask children to think about decisions involving their own death. • The time horizon may be challenging. With longer time horizons, it may not be plausible to present a childhood health state as lasting for one’s entire life. However, shorter time horizons may be too short to be consistent with children’s longer life expectancy.

5. Sample characteristics: • Several demographic variables have been found to have an influence on TTO results, possibly resulting in biased responses (e.g., age, religious beliefs, educational level, marital status). • Over-representation of any particular group in a study sample could limit generalizability to the broader population.

CHU9D: Child Health Utility 9D; HUI: Health Utilities Index; SG: Standard gamble methods; TTO: Time trade-off.

Examples of alternative methods that may be considered

Five challenges to the TTO method

Table 1. Five challenges to the time trade-off method.

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Table 2. Summary grid of other methods to consider in situations when there are challenges to time trade-off methods†.

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Alternative methods that may be considered

Challenges to the TTO method Mild health states

Small differences among health states

Temporary health states

Pediatric health states

Sample characteristics

X

X

X

Vary the TTO task (e.g., alter the time horizon)

X

X

Use a generic preference-based measure (e.g., EQ-5D or HUI), preferably one that includes a domain relevant to the specific population

X

X

Use a chaining approach

X

Use a condition-specific preference-based measure

X

X

X X

Rate temporary health states as if they were chronic

X

Use a path state method

X

Use a two-step rating process that involves adding temporary events to a chronic health state

X

Use a post-event health state approach

X

Conduct an observational study in which patients rate their own current health at the time they are experiencing a temporary event

X

Use a proxy direct utility approach

X

Use a child-specific multiattribute measure (e.g., the CHU9D)

X

Use a collective utility value based on a combination of child and family perspectives

X X

Minimize potential demographic biases in study sample (e.g., set recruitment targets to ensure reasonably diverse sample) An ‘X’ in each cell indicates methods that are likely to be useful for the specified situation. CHU9D: Child Health Utility 9D; HUI: Health Utilities Index; TTO: Time trade-off.



TTO methods may be varied in ways [28] that could reduce resistance to trading and the resulting ceiling effects. For example, one option is to change the 10-year time horizon of the TTO task. If longer time horizons result in more trading as reported in one study [29], there may be less ceiling effect with a time horizon based on the respondent’s own additional life expectancy than with a shorter fixed time horizon. Other alternatives would be to use either a condition-specific measure with a scoring algorithm that yields a utility value on the conventional dead (0.00) to full health (1.00) scale [30,31] or a generic preference-based measure with items relevant to the particular health states. If these instruments are sensitive to specific mild symptoms, they may not suffer from ceiling effects. An additional option for assessment of mild health states is a ‘chaining’ approach with either TTO or SG methods [2,3,32–39]. In a standard TTO or SG task, participants rate chronic health states on a scale ranging from dead (0) to full health (1). With chaining, however, health states can be rated relative to a 440

different lower anchor, often called a ‘worst health state,’ rather than using dead as the lower anchor. As a final step, the ‘worst’ health state is rated as a chronic health state relative to the lower anchor of dead. Then, the raw utility values obtained with the alternative lower anchor can be transformed onto the standard utility scale (i.e., with dead corresponding to 0) [3,34,38,40]. Chaining is often considered useful for discriminating among health states in the upper/healthy range of the utility scale [32,40]. When health states do not seem very adverse, participants may be reluctant to gamble with death or trade time from their lives to avoid a health state, which limits the accuracy and range of utility scores from SG or TTO assessments. In these situations, the direct utility elicitation tasks may yield more useful data if a less threatening temporary health state is used as a lower anchor. However, some researchers have criticized chaining. More time is required for the two-step administration [41]. In addition, because each utility valuation is associated with error, chained utility values are Expert Rev. Pharmacoecon. Outcomes Res. 14(3), (2014)

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associated with increased error because they are based on a series of two choices [41–43]. Chaining also tends to result in higher utility values than direct elicitation as chained scores tend to be adjusted upward with the linear transformation [2,40]. Therefore, while chaining often yields logical, reasonable utility scores, the alternative lower anchor must be drafted carefully and results should be interpreted with appropriate caution. A recent valuation of osteoarthritis health states demonstrated that the ceiling effect for mild health states can be reduced with minor alterations to the TTO task [29]. In this study, several health states representing osteoarthritis were rated in a series of utility tasks by members of the UK general population. In a TTO with a 10-year time horizon (i.e., the MVH approach), there was a ceiling effect for 62.5% of the sample when rating mild osteoarthritis and 46.3% of the sample when rating moderate osteoarthritis. The rate of responses at the ceiling decreased substantially (to 48.6% for mild and 22.9% for moderate) when the time horizon was instead based on each respondent’s self-reported additional life expectancy. Perhaps, many participants were less willing to trade time with the shorter time horizon because 10 years already seemed like a reduced life expectancy, and they were hesitant to sacrifice more time. The ceiling effect was also reduced with a chaining approach (to 43.9 and 17.1%, respectively), using a severe osteoarthritis health state as a lower anchor instead of the lower anchor of dead. Small differences among health states

A common goal of utility valuation studies is to identify differences among multiple health states. These differences among health state utilities may be large, such as the difference between health states with and without serious chronic medical conditions. In other studies, differences between health states may be relatively small. For example, health states have been developed to differentiate among treatments that vary in dose frequency [44–46]; route of administration including oral, injectable, intravenous infusion and inhaled [21,47–50]; and daily aspirin versus no treatment [51]. Small differences between utilities have also been reported for health states representing treatment-related adverse events or side effects such as nausea, vomiting, injection site reactions, 2% differences in body weight, hyperprolactinemia and orthostatic hypotension [40,44,46,52,53]. In addition, it is common for studies to estimate the utility of multiple severity levels of a single medical condition, and utility differences between mild and moderate disease may not be large in all cases. Even when differences between health states are small, these differences may still be important when characterizing patient groups in cost–utility models. Small differences in utility can have a substantial impact on the outcomes of a cost–utility analysis, particularly when modeling large numbers of patients over extended periods of time. Therefore, when conducting a study involving valuation of multiple health states with small variations, it is important to use utility assessment methods that are sensitive enough to detect small but important differences in preference. informahealthcare.com

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Utility assessment methods are likely to differ in their sensitivity to differences among health states. In situations when TTO valuation may not be sensitive enough to distinguish between health states or patient groups, researchers should consider alternative utility assessment methods. A study of patients with primary open-angle glaucoma provides a thoughtprovoking example [26]. In this study, patients were categorized into quartiles based on integrated visual field scores. TTO, EQ-5D and SF-6D utility values were only able to distinguish between the first (i.e., minimal visual impairment) and fourth (i.e., severe visual impairment) quartiles. None of these utility measures were sensitive enough to distinguish between the first, second and third quartiles, even though these three groups of patients had meaningful differences in visual function that would likely affect health-related quality of life. This finding is consistent with a previous study indicating that TTO scores were not sensitive enough to detect a difference between patients with mild and moderate visual loss [54]. In contrast, the condition-specific National Eye Institute Visual Function Questionnaire (VFQ-25) demonstrated greater ability to distinguish between patient quartiles [26]. Recently, scoring algorithms have been derived to estimate utilities from the VFQ-25, both via mapping to a generic preference-based measure [55] and via Rasch analysis [56,57]. Because the VFQ-25 appears to be sensitive in patients with visual loss, these VFQ-25 utility scoring algorithms may be preferable to TTO or generic measures for obtaining utilities. Alternatively, a generic preference-based measure that includes visual function may be sensitive to differences in this population. For instance, the Health Utilities Index Mark 3 (HUI3) has been shown to register gains in quality of life associated with cataract surgery [58]. A study involving valuation of osteoarthritis health states illustrates how sensitivity to differences among health states may vary with alterations to the TTO task [29]. In this study, a sample of general population respondents in the UK rated a set of health states in two TTO tasks with two different time horizons. In a TTO task with a 10-year time horizon, only 32.5% of the sample differentiated between mild and moderate osteoarthritis health states. However, when the time horizon was personalized based on each respondent’s self-reported additional life expectancy, 54.3% of respondents differentiated between these two health states. This finding suggests that alterations of utility assessment procedures could result in improved sensitivity to differences among health states. Temporary health states

TTO methods have frequently been used to identify utilities of chronic health states. The choices presented in a TTO task require the respondent to choose between two health states that remain constant over an extended period of time. Even when altering the time horizon to a shorter or longer duration, the choice between two options is straightforward as long as the health states remain constant over time. However, TTO may not be an appropriate utility assessment approach for obtaining 441

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utilities representing temporary health states. Temporary health states have been defined as health states lasting less than 1 year or health states that lead to other health states which are not necessarily death [35,41]. The commonly used direct utility elicitation methods, including the TTO, are often not useful for valuing many temporary health states because respondents would often be faced with unrealistic or illogical choices [59]. For example, a bone fracture is a painful health-related event that is likely to be associated with a significant disutility (i.e., utility decrease). However, it is not possible to capture this disutility with the typical TTO approach because respondents know that a fracture is a brief event that will not persist unchanged for an extended period of time. Perhaps, the simplest strategy for estimating temporary health state utilities is to conduct an observational study in which patients rate their own current health at the time they are experiencing a temporary event. Patients can provide these utilities via TTO, SG, generic preference-based measures or condition-specific preference-based measures. However, it may not be feasible to collect utility data from a sample of patients at the precise time they experience the event for which utility values are needed. Therefore, it is often necessary to obtain temporary health state utilities with studies in which respondents (who may be either patients or general population participants) rate hypothetical health state descriptions. When designing a study to value temporary health states, researchers will have to identify a utility assessment method that is appropriate for the health states and the structure of the model in which the utilities will be used. One approach is to shorten the time horizon of a direct utility assessment so that the task provides a realistic representation of the duration of the relevant temporary health states. This can be a useful adaptation of both TTO and SG methods, but this approach may not be effective if the event is too brief. For example, a fracture that is likely to heal in less than 3 months would require a TTO task with a 3-month time horizon. When participants are presented with choices involving very short additional life expectancy, the time horizon may seem more important than the health states themselves. Some respondents will be thinking about living long enough to experience a specific event (e.g., a child’s graduation), which would prevent them from responding in a way that accurately represents preferences among the health states. A time horizon as brief as 2 years has been found to yield useful logical responses [60]. Shorter time horizons could be problematic, and therefore, it is recommended that such methods be tested in a pilot study prior to proceeding with the full data collection. Another option is to rate temporary health states as if they were chronic. Some health states that are actually temporary can be presented as chronic and rated with TTO, SG or generic preference-based questionnaires. For example, irritable bowel syndrome is a condition characterized by symptom fluctuations over time rather than chronic unchanging health states. In a study that assessed temporary irritable bowel syndrome 442

health states as if they were chronic, respondents completed an SG procedure to rate the health states that were described as lasting for the rest of their life [32]. A chronic approach has also been used to assess other temporary health states including pain associated with herpes zoster [61], treatment for ovarian cancer [62] and chemotherapy for metastatic breast cancer [63]. Because QALYs in a cost–utility model are based on the assumption of constant proportional trade-off (i.e., the utility of the health state remains the same regardless of the health state duration), the resulting utility value from this chronic utility assessment task can then be used to represent a temporary period of time in a cost–utility model. It should be noted that this approach would only be appropriate for temporary events that can be presented as chronic. For example, while some temporary symptoms can be plausibly described as chronic, a surgical procedure or a bone fracture event could not logically be presented as a chronic health state. Another limitation is that some issues, such as medication-related adverse events, may not have a substantial effect on patient preference if they do not last long. However, if temporary issues are presented as chronic in a utility task, the resulting utility values could overestimate the importance and utility impact of these temporary events. A more sophisticated approach that may be considered is the path state method. Path states are health states that change over time, usually involving a sequence of different health states that each occur for a specified period of time [32,64,65]. Then, the path can be rated as a single health state in a TTO or other utility valuation task. Conceptually, the path state approach is appealing. Paths can be drafted to capture a series of temporary health states likely to be experienced by patients. This approach also allows respondents to consider the typical duration of events within each path as well as the order of events, whereas the QALY model assumes that the sequence does not matter. However, results may have limited use because the resulting utilities represent the path rather than the individual events or health states 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 on the path. Therefore, the resulting utilities may only be used in models designed specifically to match the path as presented to respondents, and it may be impossible to combine path-based utilities with other utilities in a single model. Another limitation is that path state descriptions tend to be longer and more complicated than ‘traditional’ health state descriptions, often imposing an additional cognitive burden on respondents. Furthermore, if there are a number of possible clinical courses, the number of unique paths can accumulate, and capturing all important paths may not be feasible. In sum, the path approach may be appropriate if a cost– utility model can be designed specifically to match the utility assessment, but because of several limitations, the path approach is not frequently used. A commonly used direct utility assessment approach for temporary health states is chaining (which was described in detail in the prior section on mild health states) [3,32–39]. When chaining is used to assess temporary health states, the temporary Expert Rev. Pharmacoecon. Outcomes Res. 14(3), (2014)

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states are said to last for a temporary duration and rated relative to a lower anchor health state. After rating the temporary health states relative to this temporary lower anchor, the temporary lower anchor is then rated as a chronic health state relative to the lower anchor of dead. Based on the value of the temporary lower anchor on the standard utility scale anchored to dead (0) and full health (1), the raw utility values for the temporary health states can be converted to the standard utility scale through a linear transformation [3,40]. A recent study introduced a new approach using a different two-step rating process to estimate the disutility associated with temporary events [60]. The purpose of this study was to quantify the disutility of skeletal-related events associated with bone metastases. The method involved adding temporary events to a chronic health state. In the first step, respondents completed a TTO rating of a chronic health state describing a patient with bone metastases (i.e., health state A). Then, participants rated an otherwise identical chronic health state with the addition of a temporary skeletal-related event (i.e., health state B), such as a bone fracture or bone surgery, occurring in the middle of the health state’s time period. The disutility of the temporary event was computed as the difference between the utility of the two health states. The primary limitation of this approach is that disutilities are intrinsically tied to the timeframe of the task. The disutility of the temporary event would likely differ depending on the time horizon of the TTO task. For example, a temporary event lasting 3 months may have a substantial impact on preference for a 1-year time horizon but less impact on a 10-year time period. Therefore, when using results from this approach in a cost–utility model, researchers would need to ensure that the utility values are being used in a way that is consistent with the time horizon of the utility assessment procedure. It is also possible to transform disutilities from this approach into QALY decrements that can be applied to specific cycles of the model [60]. Another option for quantifying the impact of a temporary event is to assess the utility of a hypothetical chronic health state that follows the event without including the event itself in the health state. This post-event health state approach may be appropriate for conditions such as stroke that begin with a brief acute event followed by chronic sequelae of the event. The post-event health state can be valued with any of the common approaches including TTO, SG or generic preference-based measures. The health states would describe symptoms and impact associated with the chronic state occurring after the event without describing the event itself. These symptoms would be present and unchanged for the full duration of the health state. The primary limitation of this approach is that it does not capture the impact of the acute event. Therefore, post-event health states may not be adequate for quantifying temporary health-related events that have an important acute impact. In sum, temporary health states present a methodological challenge for utility assessment. When designing a study to assess the utility impact of temporary health-related events, informahealthcare.com

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researchers should consider a wide range of options and select the approach that best represents the health states and provides utilities that are a good fit for subsequent modeling. Guidelines issued by reimbursement authorities, such as NICE, do not address the challenges of temporary health state assessment. Because no standardized recommendations are available, researchers will need to determine an appropriate approach for each individual study while providing explanation of their approach and justification for the methods. Pediatric health states

It is often necessary to conduct cost–utility models to examine and compare the value of treatments for childhood conditions. A recent review found over 300 pediatric cost–utility analyses published from 1997 to 2009, and the authors reported that the number of studies published per year and the quality of these studies increased during these years [66]. Pediatric utilities are usually derived using the same methods used for adult utilities, including indirect methods such as the EQ-5D or HUI [67], as well as direct methods including SG and TTO [68]. These methods have been used to estimate utility values representing the health of actual pediatric patients as well as hypothetical health state descriptions. Although TTO interviews have been conducted with children as young as 8 years old [69], it has been suggested that direct utility assessment methods including TTO have serious limitations for pediatric respondents. The ability to provide valid TTO responses requires that the respondent comprehends extended time horizons and mortality. Most children are unlikely to have a sufficient understanding of these abstract concepts [43,70]. The TTO task also requires the respondent to determine the point of indifference between the two alternatives, and children may not have the cognitive ability to consider fully the options and provide a valid response [71]. Some researchers have also questioned whether it is ethical to ask children to think about decisions involving their own death [72]. Furthermore, the commonly used 10-year TTO would not be appropriate for pediatric samples or health states. Some researchers have noted that the 10-year time horizon is too short to provide realistic choices for child respondents, and consequently, some studies have been conducted with a longer time horizon to be consistent with children’s longer life expectancy [69,73]. Wittenberg [74] suggested that the key challenge in valuing children’s health states is that the individual experiencing the state may not be able to explain their experience or have the cognitive ability to express value or preference in the same way that adults understand these terms. It may also be difficult for children to imagine hypothetical health states that are outside of their direct experience. Furthermore, younger children would not be expected to understand the TTO task. Consequently, studies have often had parents complete direct utility assessment tasks to rate child health states. There are several variations of this proxy approach. For example, parents have been asked to rate their own child’s health [69] as well as hypothetical 443

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health state descriptions [39]. Parents have also been asked to respond as if they were the child, as in research conducted for development of the HUI2 scoring function [75]. One study used a novel TTO design in which parents trade time from their own life in exchange for their child’s health [76]. Although these proxy approaches have often yielded useful utility values, they have limitations that could interfere with accurate health state valuation. For example, parents are often not willing to trade much time from their children’s lives, and this resistance can lead to elevated utility values [69]. Furthermore, proxy TTO responses could be influenced by priorities and beliefs other than the health states themselves such as other family members’ needs, parental guilt in reaction to trading time from their child’s life, perceptions of what a ‘good’ parent would say, and perceived impact on the parent’s own life [77]. In addition, parents have been shown to provide lower TTO utility values than their children [73], which raises questions about whether parents can accurately value their child’s health state. Therefore, while parent proxy utility assessment is a practical approach that has yielded useful utility scores, results should be interpreted with caution. In light of the challenges of implementing direct utility assessment strategies with children or parent proxies, many researchers have used indirect preference-based measures. With these instruments, such as the EQ-5D or HUI, respondents can provide information on their own health, someone else’s health or hypothetical health states by completing a brief questionnaire. Based on the responses (which comprise a health state), the utility value is computed using weights or tariffs derived from direct utility assessment with general population respondents [2]. The original adult version of the EQ-5D, as well as the HUI2 and HU3, has been used frequently to estimate utility values for children [44,77–82]. HUI2 was developed for pediatric application, namely cancer in childhood [83]. HUI2 and HUI3 have been validated for use in pediatric samples for children as young as 5 years of age. Although the content of HUI2 was designed to assess health in both children and adults, the scoring function for HUI2 is based on preference scores obtained from parents judging the quality of life for health states that a child would experience from the age of 10 to 70. The HUI3 scoring function is based on preference scores obtained from a representative sample of the general population aged 16 years or older. It is possible that children would value HUI2 and HUI3 health states differently. As stated in the NICE guide [10], the EQ-5D was not originally designed for use in children. However, it has recently been adapted for children. The updated version, called the EQ-5D-Y, has modified child-friendly wording, but it covers the same content as the adult EQ-5D, and no child-specific tariffs or scoring algorithm are available [84,85]. As an alternative to direct utility assessment, these generic preference-based measures have strengths including ease of administration and comparability to values reported for many health conditions, but their limitations must be considered when they are applied to pediatric samples. 444

One interesting new measure is the Child Health Utility 9D, a 9-item multiattribute measure of health-related quality of life for children aged 7–11 years old [86,87]. The nine items included in this descriptive system were derived from qualitative interviews with children about the important dimensions of health status from the point of view of children. The items include homework/schoolwork, being worried, being sad, being tired, being annoyed, sleep, pain, daily routine and the ability to join in activities. Weights for deriving utilities from the pattern of responses have been obtained from SG interviews with general population adults in the UK [72], as well as best–worst scaling discrete choice experiment methods with adolescents via a Web survey [88]. As evidence on the construct validity, reliability, responsiveness and interpretability of this measure becomes available, it could prove to be a useful and relatively simple approach for deriving pediatric utilities. Other pediatric multiattribute utility measures that may be considered include the 16D [89] designed for early adolescents aged 12–15 years and the 17D [90] designed for children aged 8–11 years. In sum, there seems to be a consensus that direct assessment methods commonly used with adults may not be effective for pediatric health states. Several alternative methods are available, including proxy direct utility assessment, generic multiattribute measures and child-specific multiattribute measures. Future research in this area may also look beyond utility values derived from a single individual’s preferences or ratings. Given that children are inevitably embedded within a family system, some researchers have suggested considering a family perspective in which the child’s utility may be a collective value based on a combination of child and family perspectives [43]. The evaluation of pediatric health states is a challenging and growing area of research, and more work is needed to examine utility assessment methods for this population. Sample characteristics

Demographic characteristics of respondents may also present challenges for implementation of TTO methods and interpretation of TTO utility scores. Reports of differences in utility scores associated with demographic characteristics vary across studies, making it difficult to draw general conclusions from the literature. Despite these inconsistent findings, published studies have identified several demographic variables that could have an influence on TTO results and produce a response bias. The age of respondents is often suggested as a characteristic that may influence TTO valuations. For example, one study reported that respondents for whom subjective life expectancy exceeded the 10-year time horizon of the MVH TTO task were less willing to trade time [91]. This leads to higher utility values for younger respondents. The EQ-5D TTO valuation study also reported age differences in utility values, with values increasing from ages 18 to 45 and then decreasing after the age of 45 years [92]. Further analysis of the EQ-5D valuations found that participants over 60 years old provided lower TTO utility scores for more severely ill health states, suggesting a possible interaction between respondents’ age and the content Expert Rev. Pharmacoecon. Outcomes Res. 14(3), (2014)

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of the health states [27]. Still, other studies have reported no significant differences in age for utilities derived from standard TTO methodology [93–95]. Overall, it is difficult to draw specific conclusions regarding the influence of the respondent’s age and TTO valuations, but some findings suggest that age could be an influential factor. The respondent’s religious beliefs may also have an impact on TTO utility scores as well as the feasibility of the TTO task. Several studies have reported that a small number of participants cited religious beliefs as the reason why they would not trade time or complete the TTO task [26,96,97]. Studies examining predictors of TTO utility scores have found that higher scores on measures of spirituality and spiritual being are associated with higher TTO scores, indicating less willingness to trade [98,99]. Similarly, another study reported that respondents who believe in life after death provided higher TTO values [100]. TTO utilities have occasionally been found to differ by sample characteristics including education level [101], quantitative skills [102], gender [92], marital status [92] and being a parent or caregiver of others [103,104]. TTO values may also vary by country or culture. For example, EQ-5D valuations in the UK have been shown to differ from those in the USA [105] and Japan [106]. However, the associations between demographic factors and TTO scores have not been entirely consistent or replicated across multiple samples. For example, some studies have reported no TTO differences associated with gender, marital status, education level or number of children [93,95]. Overall, there does not appear to be evidence suggesting that TTO methods are not feasible in any particular demographic group. However, results suggest that characteristics of the respondent have the potential to influence TTO utility values. Because TTO utility scores could vary by demographic subgroup, it may be beneficial to consider these variables when designing a study, collecting data or interpreting utility scores. For example, an overrepresentation of any particular group (e. g., parents or elderly, highly religious or highly educated respondents) could lead to results that may not generalize to the broader population. Although it is not usually possible to collect data from a sample that is truly representative of a large population, there are strategies for minimizing potential demographic biases. First, when collecting data, recruitment targets can be set to ensure that a sample is reasonably diverse with regard to demographic variables such as age. Second, relevant demographic characteristics can be collected from participants to ensure that the sample is reasonably balanced with regard to variables that have been shown to be associated with TTO responses. Third, if over-representation of some demographic groups cannot be avoided, alternative methodology may be considered. For example, the 10-year TTO may yield biased responses in young adults. Therefore, if it is known in advance that the sample will include a substantial proportion of younger respondents, then SG, generic preference-based measures or TTO with a longer time horizon may be more appropriate approaches. informahealthcare.com

Review

Finally, when using TTO utility scores in a cost–utility model, researchers should review the demographics of the sample from which the utilities were derived to ensure that the values are appropriate for their intended use. Expert commentary

Although it is important to consider comparability to previous studies and published utility scores, researchers should select a utility assessment method that fits the clinical condition and population under investigation [107]. For situations when the most common TTO methods may not be appropriate, many alternative approaches are available including variations of the TTO [28], other direct utility assessment methods (e.g., SG with or without chaining), measures developed specifically for children, mapping condition-specific health-related quality of life questionnaires to generic preference-based measures [108], and condition-specific preference-based measures derived from condition-specific questionnaires using item response theory and Rasch analysis [30,31,109]. Condition-specific measures may, however, introduce focusing effects which could lead to overestimating the impact of condition-specific attributes on utility [110]. While some clinical situations present problems for all TTO methods regardless of the time horizon, other limitations may be specifically linked to the commonly used 10-year time horizon. Previous researchers have noted that this time horizon presents most respondents with unrealistic or implausible choices [107,111]. For respondents in their 60s or 70s, the 10-year time horizon may seem reasonable. However, it may seem unrealistically short to younger respondents and unexpectedly long to respondents in their 80s or 90s. This potential problem with a 10-year TTO was highlighted in a study examining the link between subjective life expectancy and willingness to trade [91]. Greater subjective life expectancy (i.e., greater difference between subjective life expectancy and the 10-year time horizon) was associated with reduced willingness to trade, which in turn leads to higher utility scores. In sum, the 10-year TTO presents many respondents with an unrealistic choice, and feasibility and validity of the task may be compromised based on the extent to which the respondent’s subjective additional life expectancy differs from 10 years. This problem can be avoided by adjusting the time horizon of the TTO task based on each individual’s additional life expectancy. This alternative approach has been used effectively across a wide range of studies and health states [18,112–118]. The strengths of the 10-year TTO should also be considered. It has been used in many studies to value a wide range of health states, and it has been shown to be effective for identifying utilities of chronic health states representing medical conditions of at least moderate severity in adult populations. Because the 10-year TTO is the most common direct utility assessment method, it has the advantage of maximizing comparability across studies. Utility scores derived from two studies using the same method can be used in a single cost–utility model without introducing variability associated with methodological 445

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differences [28]. Therefore, if the 10-year TTO is a good fit for a specific clinical condition, it would be prudent to use this approach in order to gather utility values that are as comparable as possible to the greatest number of previously published values including utilities based on the EQ-5D. Before beginning a utility valuation study, it may not be possible to accurately predict the sensitivity of any specific utility assessment method. One useful strategy is to conduct a pilot study in which the methods are tested in a small sample. If the intended methodology reveals differences between health state preferences in the pilot study, then researchers can proceed to the larger study knowing that the methods are likely to be sufficiently sensitive. If the pilot study finds no difference between health states, there are two possible explanations. It is possible that the two health states are equally preferable, and therefore the two health states will not differ in utility value, regardless of the utility assessment method that is used. However, it is also possible that there are true differences in preferences, but the utility assessment methods are not sensitive enough to detect these differences. In these situations, researchers can pilot alternative methods to examine whether another approach can detect small differences between health states. One limitation of the current review is that it is not possible to recommend a specific utility assessment strategy for each situation when commonly used TTO methods are not a good fit. The goal of this review was to identify situations in which alternative utility valuation methods should be considered. The selection of a method for each situation will depend on the specific health states, target population and the specifications of the cost–utility model in which utility scores will be used. For each situation, alternative approaches are suggested, and it is hoped that researchers may use these suggestions as a starting point when considering alternatives to TTO utility valuation. In sum, although it is important to consider comparability with previous studies and published utility values, the selection of a utility assessment method should also be based on the relevance and validity of the methodology for particular clinical contexts and health states. There are a wide range of situations in which commonly used TTO methods, including TTO with a 10-year time horizon, may not yield valid utility scores, detect small but important differences among health states, or accurately represent the clinical condition being studied. Therefore, researchers should remain open to alternative methods that can provide a valid utility assessment. Five-year view

Researchers have likely used the 10-year TTO approach more than other approaches in response to the NICE Guide to the Methods of Technology Appraisal [9,10]. While the 2008 guide specifically recommended TTO as a direct elicitation alternative to the EQ-5D, the recently updated 2013 guide omitted the statement explicitly recommending TTO methods and consistency with the EQ-5D. It is possible that this change indicates increasing flexibility with regard to direct utility assessment

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methods in situations when the EQ-5D may not be appropriate. As cost–utility models continue to be submitted in support of health technology assessment evaluations in the UK and elsewhere, researchers will gain additional experience with the extent to which health technology assessment authorities may be flexible with regard to utility assessment methodology. Clearly, the updated 2013 NICE guide allows for alternative utility assessment approaches when the EQ-5D is not a good fit. Conclusions

In recent years, the TTO method with a 10-year time horizon has been the most frequently used approach for direct health state utility assessment. It is likely that researchers have favored this method because the NICE Guide to the Methods of Technology Appraisal states a preference for consistency with the EQ-5D, which has a utility scoring algorithm derived via 10-year TTO valuations. Although comparability to previous utility studies is important, there are situations when TTO methods, particularly with the 10-year time horizon, may not be appropriate. Because the TTO method is so commonly used, it is important to carefully consider its strengths, limitations and appropriate use. The purpose of the current review is to highlight situations that present challenges to the TTO method and suggest alternative approaches. Challenges to the TTO method include mild health states, small differences among health states, temporary health states and pediatric health states. Some of these challenges are associated with the 10-year time horizon, while other situations may raise issues for TTO methods regardless of the time horizon. Alternative approaches for health state valuation are suggested. Although it is important to consider comparability with previous studies and published utility values, the selection of a utility assessment method should also be based on the relevance and validity of the methodology for the health states being valued, the target population and the specifications of the cost–utility model in which utility scores will be used. Acknowledgements

The authors would like to thank Mary K Devine for proofreading and literature review as well as Amara Tiebout for production assistance. Financial & competing interests disclosure

Funding for this study was provided by Eli Lilly and Co. K Boye, J Johnston and L Bowman are employees of Lilly, but their input into the conceptualization and interpretation of this study represented their own opinions, rather than those of the company. L Matza and J Jordan are employees of Evidera, a company that received funding from Lilly for this research. D Feeny received funding from Lilly for time spent contributing to this research. Further, it should be noted that D Feeny has a pecuniary interest in Health Utilities Incorporated, which distributes copyrighted Health Utilities Index materials. No writing assistance was utilized in the production of this manuscript.

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Review

Key issues • In recent years, the time trade-off (TTO) method with a 10-year time horizon has been the most frequently used approach for direct health state utility assessment. • It is likely that researchers have favored the 10-year TTO because the UK NICE Guide to the Methods of Technology Appraisal has stated a preference for comparability with the EQ-5D, which has a utility scoring algorithm derived via 10-year TTO valuations. • Although comparability to previous utility elicitation studies is important, there are situations when TTO methods, particularly with the 10-year time horizon, may not be appropriate. • Because the TTO method is so commonly used, it is important to carefully consider its strengths, limitations and appropriate use. • The purpose of the current review is to highlight five challenges to the TTO method: mild health states, small differences among health states, temporary health states, pediatric health states and assessment of samples with particular characteristics. • Some of these challenges are associated with the 10-year time horizon, while other situations may raise issues for TTO methods

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regardless of the time horizon. • Alternative approaches for valuing health states are suggested, including variations of the TTO (e.g., varying the time horizon), other direct utility assessment methods (e.g., standard gamble methods with or without chaining), measures developed specifically for children, mapping condition-specific health-related quality of life questionnaires to generic preference-based measures, and condition-specific preference-based measures derived from condition-specific questionnaires using item response theory and Rasch analysis. • Pilot studies are often helpful in identifying an appropriate utility assessment approach. • Although it is important to consider comparability with previous studies and published utility values, the selection of a utility assessment method should also be based on the relevance and validity of the methodology for the health states being valued, the target population and the specifications of the cost–utility model in which utility scores will be used.

Clinical Excellence (NICE) Technology Appraisals. Value Health 2011;14(1):102-9

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Expert Rev. Pharmacoecon. Outcomes Res. 14(3), (2014)

Challenges to time trade-off utility assessment methods: when should you consider alternative approaches?

In recent years, the time trade-off (TTO) method, most commonly with a 10-year time horizon, has been the most frequently used approach for direct hea...
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