The Impact of Chronic Hepatitis B on Quality of Life: A Multinational Study of Utilities from Infected and Uninfected Persons

The Impact of Chronic Hepatitis B on Quality of Life: A Multinational Study of Utilities from Infected and Uninfected Persons

PDFlib PLOP: PDF Linearization, Optimization, Protection Page inserted by evaluation version www.pdflib.com – [email protected] Volume 11 • Number 3 ...

127KB Sizes 0 Downloads 14 Views

PDFlib PLOP: PDF Linearization, Optimization, Protection Page inserted by evaluation version www.pdflib.com – [email protected]

Volume 11 • Number 3 • 2008 VA L U E I N H E A LT H

The Impact of Chronic Hepatitis B on Quality of Life: A Multinational Study of Utilities from Infected and Uninfected Persons Adrian R. Levy, PhD,1,2 Kris V. Kowdley, MD,3 Uchenna Iloeje, MD, MPH,4 Eskinder Tafesse, PhD,4 Jayanti Mukherjee, PhD,4 Robert Gish, MD,5 Natalie Bzowej, MD,5 Andrew H. Briggs, DPhil1,6 1 Oxford Outcomes Ltd,Vancouver, BC, Canada; 2University of British Columbia,Vancouver, BC, Canada; 3Digestive Disease Institute,Virginia Mason Medical Center, Seattle, WA, USA; 4Bristol-Myers Squibb Company, Wallingford, CT, USA; 5California Pacific Medical Center, San Francisco, CA, USA; 6Glasgow University, Glasgow, UK

A B S T R AC T

Objectives: Chronic hepatitis B (CHB) is a condition that results in substantial morbidity and mortality worldwide because of progressive liver damage. Investigators undertaking economic evaluations of new therapeutic agents require estimates of health-related quality of life (HRQOL). Recently, evidence has begun to accumulate that differences in cultural backgrounds have a quantifiable impact on perceptions of health. The objective was to elicit utilities for six health states that occur after infection with the hepatitis B virus from infected and uninfected respondents living in jurisdictions with low and with high CHB endemicity. Methods: Standard gamble utilities were elicited from hepatitis patients and uninfected respondents using an interviewer-administered survey in the United States, Canada, United Kingdom, Spain, Hong Kong, and mainland China. Generalized linear models were used to the effect on utilities of current health, age and sex, jurisdiction and, for infected respondents, current disease state. Results: The sample included 534 CHB-infected patients and 600 uninfected respondents. CHB and compensated cirrhosis

had a moderate impact on HRQOL with utilities ranging from 0.68 to 0.80. Decompensated cirrhosis and hepatocellular carcinoma had a stronger impact with utilities ranging from 0.35 to 0.41. Significant variation was observed between countries, with both types of respondents in mainland China and Hong Kong reporting systematically lower utilities. Conclusions: Health states related to CHB infection have substantial reductions in HRQOL and the utilities reported in this study provide valuable information for comparing new treatment options. The observed intercountry differences suggest that economic evaluations may benefit from country-specific utility estimates. The extent that systematic intercountry differences in utilities hold true for other infectious and chronic diseases remains an open question and has considerable implications for the proper conduct and interpretation of economic evaluations. Keywords: cost-effectiveness, cost-utility international variation, hepatitis B, quality of life, utilities.

Introduction

ment of quality of life is germane to decision-making because the interpretations of economic evaluations can change according to the utilities that are used [3]. A review of 70 cost-effectiveness articles found that the interpretations changed in approximately one-third of investigator-reported sensitivity analyses [4]. Recently, evidence has begun to accumulate that differences in ethnic and cultural backgrounds have a quantifiable impact on perceptions of health [5]. Nevertheless, the precise nature of that effect on utilities is poorly understood [5]. Chronic hepatitis B (CHB) infection is a condition for which several new treatments have recently become available [6]. The clinical course of CHB infection can be divided into two phases: replicative (active viral replication which may or may not be associated with host immunologic response) and integrative (absence of active viral replication associated with a clinically

Valuations of health states are fundamental to decision models and economic evaluations. During the 60 years that have elapsed since von Neumann and Morgenstern proposed “expected utility theory” as a normative framework for making rational decisions under uncertainty [1], much effort has been devoted to applying this theory to health and developing methods to validly evaluate different health states. Despite these efforts, obtaining valid and reliable health state valuations and understanding the sources of variability continue to pose a formidable challenge for researchers, clinicians, and decision-makers [2]. Valid assessAddress correspondence to: Adrian R. Levy, Oxford Outcomes Ltd, 450–688 West Hastings Street, Vancouver, BC, Canada V6B 1P1. E-mail: [email protected] 10.1111/j.1524-4733.2007.00297.x

© 2007, International Society for Pharmacoeconomics and Outcomes Research (ISPOR)

1098-3015/08/527

527–538

527

Levy et al.

528 quiescent phase) [7]. Many persons infected early in life remain in the replicative stage for several years before stimulating a host immune response that can lead to progressive liver damage and potentially fatal complications including compensated and decompensated cirrhosis (ascites, jaundice, portal hypertension, esophageal and gastric variceal bleeding). Hepatocellular carcinoma is a complication that may develop after a long duration of infection in the replicative and nonreplicative phases [6]. The 5-year cumulative incidence of compensated cirrhosis among hepatitis B virus (HBV) patients ranges from 8% to 20% and may be even higher [8]. The rate of progression is dependent on clinical and serological features, such as age at diagnosis, sex, alcohol intake, coinfection with hepatitis C or D virus or human immunodeficiency virus, HBV genotype, hepatitis B e antigen positivity [8], and the level of circulating virus [9–12]. Compared to uninfected persons, chronically infected patients progressing to compensated and decompensated cirrhosis have an approximately 100-fold increased risk of hepatocellular carcinoma [13,14]. As liver disease from CHB progresses, so do the morbidity and the costs of care [15–23]. Decompensated cirrhosis and hepatocellular cancer are associated with severe morbidity and high mortality if the patient does not undergo liver transplantation. That is a costly procedure with a long recovery time and impaired healthrelated quality of life (HRQOL) in the first year post transplant [24]. Directly elicited valuations of health states commonly reported in the literature are “ratings,” derived from a visual analog scale [25], and “utilities,” derived using elicitation techniques in which respondents are obliged to make a trade-off between the likelihoods of survival, called standard gamble, or duration of survival, called time trade-off [26]. Investigators conducting cost-utility analyses of treatments for hepatitis B have not incorporated utilities elicited specifically for CHB-related health states from either CHB patients or uninfected persons [27–31]. One study [27] incorporated published standard gamble utilities from hepatitis C virus patients [32] and another study used data elicited from a panel of seven physicians familiar with treating hepatitis C patients, with the mean utilities combined from both standard gamble and time tradeoff techniques [28]. The type of respondents and the ad hoc method of combining utilities from both elicitation techniques in the study raise concerns regarding the validity of the quality-of-life adjustments and the resultant cost-utility ratios. The objective of this study was to elicit utilities for six health states that occur after chronic infection with the HBV from infected and uninfected respondents living in regions with low and with high CHB endemicity. As there is no consensus whether lay persons naïve to the disease under study or patients suffering

from the disease provide more appropriate data on utilities [33–36], we collected information from both groups: uninfected persons were included to represent the general population [37] and respondents infected with CHB were included to provide the patients’ perspective. Although differences in ethnic and cultural backgrounds are likely to have an impact on perceptions of health, the nature of these differences on utilities is poorly understood. In the case of infectious hepatitis, risk attitudes and utilities may be influenced by societal awareness about the condition because of: the likelihood of personally knowing someone who is infected, to the public health burden, to the contagious nature of the virus, or to other reasons. Thus, we collected data in jurisdictions with hepatitis B surface antigen seroprevalence ranging from less than 1% in the United States, Canada, and Western European countries to between 10% and 12% in North and Central Asian countries (China, South Korea, and Taiwan) [6] to reflect the potential impact on utilities of low and high prevalences of CHB infection.

Methods

Design and Study Respondents We used trained interviewers to directly elicit utilities for CHB-related health states using the standard gamble technique [38]. Data were collected from respondents enrolled in 11 cities in six jurisdictions: United States, Canada, United Kingdom, Spain, mainland China, and Hong Kong. (Data were collected separately in Hong Kong and mainland China because of differences in their economies and health-care systems.) These countries represented regions with low and high endemicity of HBV infection as well as different ethnic and cultural backgrounds [6]. We aimed to recruit 100 uninfected respondents and 100 HBV-infected patients at each site. These targets were established within the context of inadequate knowledge of standard gamble (SG) utilities characterized by the lack of information on variability, little theoretical guidance on the minimal clinically important difference, and poor understanding of the effect of demographic and cultural factors. The sample size thus represented a compromise between precision, cost, speed of data collection, and the need to maximize the number of respondents. Several useful, but arbitrary, rules of thumb have been suggested for utility measurement that can be used as a rough guide to estimate power: 0.1 is the minimal clinically important difference (i.e., effect size) and standard deviations are greater for the general public (0.3) than for patient groups (0.2) [39]. Using those figures and a projected sample size of 600, the power of detecting a difference among uninfected respondents was 17% for an effect size of 0.05 and 53% for

529

Health State Utilities for Hepatitis B an effect size of 0.10; among infected respondents the power was 28% for an effect size of 0.05 and 78% for an effect size of 0.10. Uninfected respondents were primarily recruited from staff and students at local universities as well as the population at large. Infected respondents were recruited consecutively from 11 liver disease treatment centers and clinics, transplant centers, and hospital hepatology units (one in Hong Kong and two in each other site [see Acknowledgments]). Ethical approval was obtained from institutional review boards in all countries and all respondents provided informed consent. The inclusion criterion for uninfected respondents was age 18 years or older, and the exclusion criteria were: inability to communicate in the official language(s) of the country; known cognitive impairment; or, visible intoxication that, in the interviewer’s opinion, prevented valid responses. The inclusion criteria for infected respondents were: age 18 years or older, hepatitis B e antigen positivity for at least 6 months, and classifiable into one of the six health states. The exclusion criteria for infected respondents were the same as those for uninfected respondents, as well as: less than 3 weeks post transplant or post hepatectomy; end-stage chronic illness unrelated to CHB; or known co-infection with human immunodeficiency virus, hepatitis C, or hepatitis D.

Standardized Descriptions of Health States We developed standardized descriptions [40] that characterize six CHB-related health states: CHB, compensated and decompensated cirrhosis, hepatocellular carcinoma, and liver transplantation within and after the first year. Health states were developed in a tabular format as these have been shown to be the preferred format for presentation [41]. Relevant dimensions of HRQOL were based on the Liver Disease Quality-ofLife Instrument version 1.0 [42]. Based on the interviews with three experienced hepatology experts (from Canada, United States, and Hong Kong), we iteratively developed written descriptions of each health state that portrayed typical symptoms, frequency of tests, hospitalizations, procedures, and dimensions of health such as pain, ability for self-care, activities of daily living, psychological well-being, and future outlook. The final versions of the health state descriptions achieved consensual agreement among the experts (Table 1). Pretesting included forward and backward translation and linguistic validation interviews (Canada: English and French; United Kingdom: English; United States: English; Castilian Spanish; China: Cantonese and Mandarin). The elicitation instruments and health state descriptions were pilot-tested in a sample of 14 uninfected respondents in Canada and the United Kingdom.

Interview Process We standardized the data collection process by conducting a 1-day training session in each site before data collection that involved: live practice sessions; having interviewers employ the same script to explain the study; and instructing interviewers to minimize unscripted dialogue. The interviewers presented the health states to respondents in different orders. Respondents saw only the health state description and remained unaware of the health state name. Infected respondents were aware that these were health states related to hepatitis (but not necessarily to their own health state). To familiarize respondents with the health states, the interview process began by eliciting visual analog scale ratings [43]. Respondents were asked to rate all six health states, their own current health and death using a vertical visual analog scale ranging from 0 (worst imaginable health state) to 100 (perfect health) [25]. Then, a probability wheel was employed as a prop to elicit the standard gamble utilities associated with their current health and each of the six CHB-related health states. Respondents were asked to choose repeatedly between two options: 1) remaining with certainty in the health state without improvement; or 2) a hypothetical treatment that may either result in full health (utility level of 1) or cause immediate death (utility level of 0) [2]. The probabilities for the second option were changed until respondents reached a point of indifference between the alternatives. The process incorporated a “ping-pong” approach with probabilities traded back and forth between higher and lower values that iteratively narrowed to the point of indifference [2]. The utility weight is calculated as 1 minus the probability of death at that point [2].

Analysis Mean standard gamble utilities and the corresponding 95% confidence intervals (CIs) were calculated for each health state including current health. Statistical testing of differences in utilities was conducted using generalized linear models [44]. Two types of models were considered: Gaussian with an identity link (i.e., ordinary least squares) and a gamma family with a log link. The second model was considered because the ordinary least squares model has the disadvantage of potentially predicting values above the upper boundary (i.e., 1.0). Given that utilities may be non-normal and have an upper bound of 1.0, we modeled (1—utility). The goodness of fit was compared using the model deviances. Using the best fitting model (i.e., that with the lowest deviance), the regression modeling was used to determine: the effect of age (in years) and sex among both groups of respondents; whether utilities differed by type of respondent or country; and among infected respondents only, whether respondents categorized in one health state rated that state differently than other

Levy et al.

530 Table 1

Standardized descriptions used to characterize six chronic hepatitis B-related health states

Chronic hepatitis B • Sometimes I feel tired, but otherwise I feel healthy most of the time. • My condition doesn’t really limit my daily life. I still participate in many activities such as sports, household chores, and social events. • Occasionally I go to the doctor’s office or clinic for different tests. • I have heard that my condition can be progressive and sometimes I feel anxious about it. • I occasionally have concerns about my future. Compensated cirrhosis • Sometimes I feel tired, but otherwise I feel healthy most of the time. • Most days I feel rested, but a little of the time I don’t sleep as well. • My condition doesn’t really limit my daily life. I still participate in many activities such as sports, household chores, and social events. • I go to the doctor’s office or clinic periodically for a variety of medical tests. • I feel somewhat worried and anxious about my future. Decompensated cirrhosis • I feel like I have the flu all of the time. Some days I am exhausted because I have difficulty sleeping at night. My feet and legs may be swollen and sometimes I feel bloated. • Sometimes I vomit blood and have to go to the hospital for a blood transfusion and to have a tube placed in my stomach through my nose. • My diet is restricted because of my condition. • Sometimes I am reluctant to leave the house because I’m not feeling well. • My condition takes up too much of my life. I make frequent trips to the hospital for tests and I take several medications. These medications may have unpleasant side effects such as diarrhea, cramps, bloating, and fatigue. • There are times when I am confused and I often have trouble remembering things. • I worry about whether or not a life-saving treatment will be available when I need one. I am very concerned about my future. • I find I am less inclined to spend time with my friends because of my condition. Transplantation (1st year) • I feel tired during the day because I don’t sleep very well at night. • Sometimes I have the energy to go for a walk or do the housekeeping, but I tire easily. • Most of the time I have good appetite and am able to eat and enjoy regular meals. • I make frequent trips to the hospital or clinic for a battery of tests. • I take several medications, some of which may have unpleasant side effects such as fatigue or nausea. • I feel anxious and worried about my life and hope that my health problems will resolve. • I feel that my appearance has changed and sometimes I feel embarrassed about it. Transplantation (>1st year) • I have a healthy appetite which allows me to eat and enjoy regular meals. • Although I tire easily, my level of energy is improving and I find it easier to participate in household tasks and leisure activities. • I take several medications which have some side effects, such as headaches and bloating. • I may experience aches and pain in my bones and joints. • My appearance is improving and I am more comfortable going out in public. • My visits to the hospital and the doctor’s office are becoming less frequent and I spend less time managing my condition. • I am somewhat optimistic about my future and that my health will stay the same. Hepatocellular carcinoma • I find that I have very little energy. I often have sharp pains in my abdomen and I frequently feel nauseous. • I am often uncomfortable because of swelling in my legs, and sometimes in my abdomen. • I am able to eat only small amounts of food because I have no appetite and the food doesn’t seem to taste good anymore. • I spend a lot of time at the hospital and specialized clinic to undergo tests. • If I receive treatment, the side effects can include pain, nausea, hair loss or fever. • I know my condition is serious and I feel that my future is bleak. • I feel depressed and irritable. • My condition severely limits my ability to participate in usual activities such as house chores and seeing friends.

infected respondents. To examine if infected respondents who had progressed to a more severe health state rated the less severe states differently than infected respondents with milder forms of disease, we grouped infected respondents into more (decompensated cirrhosis, hepatocellular carcinoma, and the two transplant states) or less (CHB, compensated cirrhosis) severe. We then compared between more and less severe respondents the ratings for CHB and compensated cirrhosis. Statistical analyses were undertaken using Stata for Windows versions 8.2 (Stata Corporation, College Station, TX). All statistical comparisons were two-tailed and used alpha of 0.05. The standard gamble technique does not allow respondents to record states as worse than death. Although adjustments to the technique have been proposed to quantify such states [45], these procedures were not employed to avoid respondent burden.

Instead, an arbitrary weight of -0.1 was applied to all states where immediate death was preferred. The impact of this assumption was assessed using sensitivity analysis by examining the impact of changing the arbitrary weight of -0.1 to -0.5 for states in which immediate death was preferred.

Results A total of 1134 respondents were enrolled, 600 uninfected and 534 infected with CHB virus (Table 2). For uninfected respondents, the mean age was 41.5 years, 43% were male and 36% were Asian, while for infected respondents, the mean age was 45.5 years, 76% were male and 62% were Asian. Among infected respondents, the preponderance of men and those in the CHB health state reflected epidemiological distributions of the infection.

531

Health State Utilities for Hepatitis B

Table 2 Sociodemographic and disease characteristics of infected and uninfected respondents from whom utilities for hepatitis B-related health states were elicited* Infected respondents

Uninfected respondents

Characteristic

N*

n (%)

N*

n (%)

Male sex Age (year)*† (Range) Country United States Canada United Kingdom Spain Hong Kong China Race White Asian Black Unknown Marital status––married/common-law Employment—full time Education—continued after age 16 years Proportion in each health state Chronic hepatitis B Compensated cirrhosis Decompensated cirrhosis Liver transplant—1st year Liver transplant—>1st year Hepatocellular carcinoma Missing

530 531

402 (75.9) 45.5 (13.1) 18 to 80

599 598

256 (42.7) 41.5 (16.7) 18 to 88

534

600 56 100 93 85 100 100

(10.5) (18.7) (17.4) (15.9) (18.7) (18.7)

155 332 30 16 397 299 368

(29.1) (62.3) (5.6) (3.0) (77.7) (57.5) (70.9)

225 98 49 56 50 39 17

(42.1) (18.4) (9.2) (10.5) (9.4) (7.3) (3.1)

533

100 100 100 100 100 100

(16.7) (16.7) (16.7) (16.7) (16.7) (16.7)

373 216 10 1 332 319 460

(62.2) (36.0) (1.7) (0.0) (57.4) (54.8) (77.2)

600

511 520 519 534

578 582 596

*As some respondents did not answer all questions, the number of valid response for each characteristic differs. †Values represent mean (SD).

The rank ordering of health states using standard gamble utilities was identical among both infected and uninfected respondents (Table 3). The health states with the highest mean utilities were CHB and compensated cirrhosis and the lowest mean utilities were observed for decompensated cirrhosis and hepatocellular carcinoma. The mean utility for the first year of liver transplant was intermediate between the least preferred and most preferred health states and liver transplant after the first year had similar utilities to CHB and compensated cirrhosis. For all comparisons, the Gaussian model with an identity link showed lower deviances, and therefore a better fit for the data, than the gamma family with a log link. All results pertaining to the regressions therefore

refer to the ordinary least squares model. Statistical testing for the entire model indicated significant heterogeneity so that we explored the sources of variation. There were significant differences between uninfected and infected respondents for current health and for CHB, compensated cirrhosis, and the two transplant health states. Nevertheless, no differences between the two groups were observed for utilities assigned to decompensated cirrhosis or hepatocellular carcinoma. We observed that, as expected because they had an identified illness and more than 35% were in the more serious health states (decompensated cirrhosis, hepatocellular carcinoma, or transplant), infected respondents had significantly lower mean utilities for their current health state than uninfected respondents.

Table 3 Distributions of standard gamble utilities for six chronic hepatitis B-related health states and current health according to type of respondent Infected respondents

Uninfected respondents

Health state

Mean

95% CI

Median

IQR

Mean

95% CI

Median

IQR

Chronic hepatitis B Compensated cirrhosis Decompensated cirrhosis Hepatocellular carcinoma Liver transplant (1st year) Liver transplant (>1st year) Current health

0.68 0.69 0.35 0.38 0.57 0.67 0.70

0.66–0.70 0.66–0.71 0.32–0.37 0.36–0.41 0.54–0.60 0.64–0.69 0.67–0.73

0.75 0.75 0.35 0.40 0.65 0.75 0.75

0.40 0.40 0.50 0.50 0.40 0.40 0.40

0.77 0.80 0.35 0.41 0.65 0.76 0.87

0.76–0.79 0.79–0.82 0.33–0.37 0.39–0.43 0.63–0.67 0.75–0.78 0.86–0.89

0.85 0.85 0.35 0.45 0.75 0.85 0.95

0.30 0.20 0.40 0.50 0.38 0.30 0.10

CI, confidence interval; IQR, interquartile range.

Levy et al.

532

Table 4 Mean standard gamble utilities by age group and sex for 534 infected and 600 uninfected persons for current health and six chronic hepatitis B-related health states according to age and sex Number of subjects Infected respondents Age (year) <30 64 30–39 120 40–49 123 50–59 131 ⱖ60 89 Sex Male 397 Female 128 Uninfected respondents Age (year) <30 200 30–39 100 40–49 98 50–59 98 ⱖ60 102 Sex Male 256 Female 343

Current health

Chronic hepatitis B

Compensated cirrhosis

Decompensated cirrhosis

Liver transplant, year 1

Liver transplant, after year 1

Hepatocellular carcinoma

0.64 0.72 0.73 0.71 0.66

0.70 0.68 0.69 0.70 0.63

0.68 0.70 0.68 0.70 0.66

0.30 0.31 0.38 0.35 0.37

0.57 0.54 0.63 0.56 0.55

0.62 0.68 0.69 0.68 0.66

0.32 0.37 0.41 0.39 0.41

0.69 0.74

0.66 0.73

0.68 0.71

0.35 0.33

0.55 0.62

0.67 0.68

0.38 0.40

0.91 0.87 0.85 0.82 0.84

0.80 0.80 0.77 0.71 0.76

0.81 0.84 0.80 0.75 0.80

0.37 0.32 0.36 0.39 0.30

0.67 0.66 0.65 0.61 0.64

0.78 0.79 0.75 0.72 0.76

0.42 0.40 0.41 0.41 0.39

0.85 0.88

0.78 0.77

0.79 0.81

0.33 0.36

0.64 0.66

0.76 0.77

0.40 0.41

Table 4 shows the mean utilities for current health and the six CHB-related health states according to age group and sex separately for infected and uninfected respondents. There were no statistically significant differences between women and men of either respondent group in utilities elicited for any of the health states. Age was significantly associated with the utility for current health among uninfected respondents with values declining with increasing age The effect of age on current health was not significant among infected respondents. Of the six hepatitis-related health states, age was a significant predictor of utilities for CHB only, among both infected and uninfected respondents. There were significant differences between countries in utilities for infected and uninfected respondents. Both groups of respondents in mainland China and Hong Kong reported lower mean utilities than those from respondents in other countries (Fig. 1). The differences between countries in utilities were statistically significant for both respondent groups for all health states except decompensated cirrhosis and hepatocellular carcinoma. None of the regression models indicated that infected subjects currently in one health state rated that particular health state differently than other infected respondents. For CHB, infected respondents in more severe health states assigned a significantly lower utility than those in less severe health states, 0.644 versus 0.719, respectively. Table 5 shows the country-specific utilities for each respondent group after adjusting for age and sex using ordinary least squares regression. To investigate the impact of assigning an arbitrary value of -0.1 to states in which immediate death was preferred, we conducted a sensitivity analysis using a

value of -0.5 for the 3.5% of values where -0.1 was assigned and found that the mean utilities were lowered slightly (decompensated cirrhosis = 0.31 and hepatocellular carcinoma = 0.37) with the relative rankings remained unaffected.

Discussion It is estimated that more than 350 million people worldwide are infected with HBV [46,47]. More severe stages of liver disease due to CHB infection cause reduced HRQOL and are associated with increased treatment costs [15–23]. Despite the availability of effective prophylaxis and treatment options [48], no information has been published on utilities for health states resulting from CHB infection elicited from uninfected lay persons. The current study fills that gap by presenting standard gamble utilities for six relevant health states that were elicited using standardized procedures from respondents in six diverse jurisdictions. To contextualize the study in the light of current understanding about preferences, it is worth noting that each major element in collecting and valuing utilities—choosing between types of respondents and identifying a representative sampling frame, selecting the type of scaling task (e.g., standard gamble vs. time trade-off), identifying and portraying relevant health states, summarizing utilities across subjects, and assessing reliability and validity—is contentious [49]. Nevertheless, this study is among the largest in the literature to present information on health state utilities for any disease, one of the few investigations to include international comparisons within the same study, and included both infected and uninfected respondents.

533

Health State Utilities for Hepatitis B 1.0 Infected Uninfected

0.8

Standard Gamble Utilities

UK SP US CA HK

Infected Uninfected

SP K U US CA CH HK

SP UK H K US CA

Infected Uninfected

Infected Uninfected

SP U K US CA CH HK

Infected Uninfected

K U SP

SP HK US CA UK

0.6 CH

U K CA SP US

CA SP US UK HK CH

SP US H K CA UK

CA US H K CH

HK CH

CH

0.4

Infected Uninfected

CH US CA SP

SP UK CA

U US K

U HK

HK

HK CH

CH

CH

SP CA

CH

US

0.2

0.0

Chronic HBV

Comp Cirrhosis

Decomp Cirrhosis

Transplant (year<1)

Transplant (year>1)

HCC

Health State Figure 1 Mean standard gamble utilities elicited from infected and uninfected respondents for six chronic hepatitis B-related health states, by geographic location. Comp, compensated; Decomp, decompensated; HBV, hoursepatitis B virus; HCC, hoursepatocellular carcinoma. Countries: CA, Canada; CH, China; HK, Hong Kong; SP, Spain; UK, United Kingdom; US, United States.

Some insight into the representativeness of the uninfected sample can be gleaned by comparing the values for current health elicited from those respondents (mean 0.87, 95% CI 0.86–0.89) to population norms reported in other studies. Two studies, reporting data from 17,626 community dwelling Canadians and 3010 community dwelling Australians, reported utilities that were derived from different multiattribute systems based on the time trade-off technique (the Health Utilities Index Mark II and the Assessment of Quality of Life, respectively) [50,51]. The mean value for the 43% of the Canadian sample without any chronic conditions was 0.93, and ranged between 0.58 and 0.92 for different conditions reported in the remainder of the sample [50]. The values reported in the current study were similar to those elicited from younger Australians [51]. Similar to both surveys and other studies [52], we also found that the utilities assigned to current health for uninfected respondents declined with age. Including two categories of respondents, CHBinfected and uninfected persons, was a feature designed to collect utilities from individuals who may fundamentally differ in terms of their utilities for health states [37]. We observed that uninfected respondents had higher mean utilities than infected respon-

dents for most of the health states. Testing indicated that these values were statistically higher for all but the most severe health states (decompensated cirrhosis and hepatocellular carcinoma). This finding suggests that both patients and lay persons tend to have similar risk attitudes to more severe health conditions. There is no consensus whether patients who have direct experience of a disease’s impact or lay persons from the general population yield more representative utilities when a societal perspective is sought. In contrast to our findings, the prevailing interpretation literature is that lay persons tend to provide lower utilities than persons with disease because of the “disability paradox” [53–55] and response shift and adaptation to chronic health states [56]. Although some studies have shown differences between the two groups [33,57–60], the finding has not been universal [40,61,62] such that the interpretation is coming under greater scrutiny. For example, a recent meta-analysis showed no systematic differences between patients and persons without disease [63]. Furthermore, as approximately 42% of infected respondents were asymptomatic, personal anxiety about disease progression before any possible response shift or adaptation may have resulted in lower utilities among infected respondents.

Levy et al. 0.31 0.38 0.46 0.43 0.42 0.48 0.31 0.38 0.47 0.43 0.42 0.48 0.55 0.64 0.64 0.64 0.66 0.70 0.70 0.80 0.80 0.80 0.82 0.85 0.41 0.56 0.58 0.57 0.57 0.61 0.54 0.69 0.71 0.69 0.69 0.74 0.26 0.30 0.44 0.37 0.35 0.44 0.28 0.32 0.45 0.39 0.36 0.45 0.57 0.64 0.65 0.66 0.68 0.71 0.76 0.82 0.83 0.85 0.87 0.89 0.52 0.60 0.66 0.67 0.69 0.67 0.71 0.79 0.85 0.86 0.88 0.86 China Hong Kong Canada United States United Kingdom Spain

Infected Uninfected Infected Uninfected Infected Uninfected Infected Uninfected Infected Uninfected Infected

Liver transplant— after first year Liver transplant— first year Decompensated cirrhosis Compensated cirrhosis Chronic hepatitis B

Uninfected Country

Table 5

Age- and sex-adjusted standard gamble utilities from infected and uninfected persons for six chronic hepatitis B-related health states, according to country

Hepatocellular carcinoma

534

We observed that respondents exhibited disutility even for health states with less severe health effects such as CHB, which showed mean utilities of 0.68 and 0.77 among infected and uninfected respondents, respectively. Given that the health effects were described as relatively minor (see Table 1), it is possible that respondents focused on the likelihood that the disease would progress. The observation that infected respondents in more severe health states assigned a lower score to CHB than those in less severe health states suggests that this anxiety was stronger among persons who were more familiar with disease progression and that the differences between types of respondents may have been larger had a larger proportion of severe patients been included. There is little existing information on the effect of age or sex on utilities. In one study done on more than 3000 members of the UK general population, age influenced utilities derived using the EQ-5D, with lower values reported from persons aged more than 60 years than those aged 18 to 59 years [64]. Nevertheless, those differences were attenuated when adjusted for states worse than death. We found no differences in utilities between sexes, and significant differences by age in utilities only for CHB. Another important finding was the difference in utilities between countries, with lower utilities reported from mainland China and Hong Kong, both jurisdictions with high endemicity of hepatitis B infection. The lower ratings of even the milder health states (CHB and compensated cirrhosis) in mainland China and Hong Kong may reflect a greater fear of the social consequences of infection. For example, discrimination against Chinese carriers of CHB—130 million persons equivalent to 10% of the population—can result in difficulties in finding employment and access to education [65]. Perceptions of health are complex functions of cultural conceptions of health, contact with health services, and sociodemographic variables [66]. Nevertheless, the means by which these issues interact and affect self-perceived HRQOL are poorly understood. One interpretation of the significant intercountry differences is that researchers conducting economic evaluations, and decision-makers allocating funding for health technologies, should consider the geographic source of utilities to assess whether those utilities were elicited from respondents living in a jurisdiction with a similar disease occurrence. In the case of CHB, our study indicates that applying utilities elicited in China or Hong Kong would likely be inappropriate for economic evaluations submitted to the UK National Institute for Health and Clinical Excellence or the Canadian Common Drug Review. We found that the statistical variability was greater among infected than uninfected respondents. This supports findings from studies in which the distributions

535

Tabular 534

114

*Includes first and subsequent years post transplant combined. † Variceal bleeding was a separate state and had a mean utility of 0.40. ‡Standard deviation.

Six plus current health

Six

Narrative

0.68

0.69

0.35

0.48

0.48

0.72 (0.62–0.82)* 0.72 (0.62–0.82) 0.30 ⫾ 0.29‡ 0.60 (0.37–0.83) 0.74† ⫾ 0.20‡ 0.80 (0.70–0.90) 0.88 ⫾ 0.15‡ 0.79 (0.70–0.87) None mentioned Current health only

Standard gamble with visual prop Questionnaire-based time trade-off Standard gamble with visual prop 193

Chong, Toronto, Canada, 2003 Wells, Birmingham, Alabama, 2004 Current study, six jurisdictions

Hepatocellular carcinoma Decompensated cirrhosis Compensated cirrhosis Chronic hepatitis Health state description Number of health states evaluated Elicitation technique Number of infected respondents Author, location, publication year

Mean utilities (95% confidence intervals) for hepatitis-related health states elicited from persons infected with hepatitis reported in the literature Table 6

of utility measurements were wider for the general public than for patients [39]. The difference has been hypothesized to arise because diseased respondents have first-hand experience of the health problems and a greater understanding of the impact on quality of life [67]. Investigators planning future utility studies can use the data published herein to estimate power and sample size. Comparisons between ratings derived from scaling methods such as the visual analog scale and standard gamble or time-trade-off utilities have produced both similar and divergent results [68,69]. Some of this discrepancy may be due to the upper reference point, whether it is the absence of the dysfunction and discomfort being assessed or “perfect health” [70]. Using “full health” as the anchor, among uninfected respondents, we found that visual analog scale ratings were consistently lower than the standard gamble (data not shown). This is consistent with other published findings [25,71]. In contrast, we did not observe consistent differences between the visual analog scale and the standard gamble among infected respondents (data not shown). This finding was unexpected because, for visual analog scale ratings, respondents are not asked to choose between potentially undesirable alternatives [25,49]. Published economic evaluations of CHB treatment options have been based on utility estimates that were likely not representative of either societal or patient perspectives. In one study, utilities were elicited from seven physicians familiar with treating hepatitis C patients and the mean utilities combined from both standard gamble and time trade-off techniques were reported for CHB, compensated cirrhosis, and decompensated cirrhosis. Those values were higher than observed in the current study: 0.94, 0.92, and 0.54, respectively [28]. Two other studies have recently been published that report patient-elicited utilities for hepatitis-related health states (Table 6) [32,72]. For all health states, the utilities measured in our study were generally slightly lower than those estimates. One study presented utilities from 73 patients for liver transplant but did not describe the elicitation methods [73]. Other investigators have published utilities based on clinical judgment for CHB [74], compensated and decompensated cirrhosis [74,75], liver transplant [74], and asymptomatic, mildly symptomatic and severely symptomatic HBV infection [76]. A meta-analysis of the agreement between physicians and patients on HRQOL assessments found that long-term assessments of patients’ well-being by physicians and patients readily diverge [36]. Physician-reported standard gamble utilities have been shown to be significantly higher than those elicited from patients [33], perhaps because physicians systematically overestimate how well patients feel and do not understand the real impact of illness on patients’ lives.

Transplant

Health State Utilities for Hepatitis B

Levy et al.

536 Our study had limitations. First, because recruitment was undertaken at sites located in at most two cities per country, respondents may not be representative of the respective country’s uninfected or infected populations. This could have an effect on the generalizability of the results. Second, the standard gamble employed did not allow respondents to specify negative values when a state was considered worse than death. Rather, we assigned a value of -0.1 to the states when this situation occurred. To investigate the impact, we conducted a sensitivity analysis and found that our assumption had only a minor effect on the mean utility estimates and no effect on the rankings. Third, human factors derived from interviewer-administered measures rather than paper- or computer-based methods may have introduced a bias of unknown direction. For practical reasons, and because computer-based utility elicitation interviews have other limitations including the need for specialized software and respondents’ potential lack of familiarity with using a computer, we chose interviewer-administered methods. We used extensive standardization procedures during the data collection process to mitigate the possibility of interviewer bias. Fourth, for logistic reasons, uninfected respondents were primarily recruited from local universities. Utilities elicited from students may be different than those from other representatives of society [33,34]. In the current study, we conducted a sensitivity analysis by comparing utilities among uninfected persons categorizing those aged less than 25 years and those aged 25 years or older. That analysis indicated no significant difference in utilities between the two age groups. Fifth, the ratings were almost certainly influenced by the specific wording. Did respondents note the difference between “occasionally” (in CHB) and “periodically” (in compensated cirrhosis) with respect to physician visits and between “. . . feel anxious” and “. . . somewhat worried and anxious”? There are two statements about the future in CHB and only one in compensated cirrhosis, which may explain why the former was ranked lower. To our knowledge, only one other study has published health state descriptions for liver disease [72] and that was published after the data collection in the current study was underway. This study represents the first in which health state utilities for CHB-related health states were elicited from both infected patients and uninfected lay persons. The populations that were included reflect the diverse nature of the populations afflicted by CHB. We found that health states related to CHB infection were associated with substantial reductions in HRQOL in all countries. The differences across countries in utilities for the same health state underscore the need for country-specific adaptations of analyses assessing the value and cost-utility of new treatment options in CHB. The health state utilities reported in this study provide valuable information for comparing treatment

options for CHB therapies. Integrating these utilities into cost-utility analyses will improve the quality and applicability of economic evaluations and decisionmaking in CHB. The extent that systematic intercountry differences in utilities holds true for other infectious and chronic diseases remains an open question and has considerable implications for the proper conduct and interpretation of economic evaluations. The authors gratefully acknowledge the contributions of: the country-specific investigators Lise Poissant (Canada), Frank Anderson (Canada), Natalie Rock (Canada), JiQian Fang (mainland China), Cindy Lam (Hong Kong), Stephen J. Coons (United States), and Michael Herdman (Spain); the study personnel: Yves Gagnon, Sarah Hargreaves, Andrew Machuk, Greta Lozano Ortega, Diego Ossa, and Hong Wang; and Karissa Johnston and Natasha LaPierre. All authors contributed to the interpretation of the results and development of the manuscript, and approved the final version of the text. ARL is the study’s guarantor and accepts full responsibility for the conduct of the study, had full access to the data and controlled the decision to publish. Source of financial support: Funding for this study was provided by a grant from the Pharmaceutical Research Institute, Bristol-Myers Squibb Company KVK is supported by DK 02957. Supplementary materials for this article can be found at: http://www.ispor.org/publications/value/ViHsupplementary. asp

References 1 von Neumann J, Morgenstern O. Theory of Games and Economic Behavior. Princeton, NJ: Princeton University Press, 1947. 2 Torrance GW. Measurement of health state utilities for economic appraisal. J Health Econ 1986;5:1–30. 3 Testa MA, Nackley JF. Methods for quality-of-life studies. Annu Rev Public Health 1994;15:535–59. 4 Schackman BR, Gold HT, Stone PW, Neumann PJ. How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions? Pharmacoeconomics 2004;22:293–300. 5 Souchek J, Byrne MM, Kelly PA, et al. Valuation of arthritis health states across ethnic groups and between patients and community members. Med Care 2005;43:921–8. 6 Custer B, Sullivan SD, Hazlet TK, et al. Global epidemiology of hepatitis B virus. J Clin Gastroenterol 2004;38(Suppl.):S158–68. 7 Lee WM. Hepatitis B virus infection. N Engl J Med 1997;337:1733–45. 8 Fattovich G. Natural history of hepatitis B. J Hepatol 2003;39(Suppl. 1):S50–8. 9 Chen CJ, Yang HI, Su J, et al. Elevated serum level of hepatitis B virus DNA is an independent risk factor for hepatocellular carcinoma: a long-term follow-up study in Taiwan. J Hepatol 2005;42(Suppl. 2):S16– 17.

Health State Utilities for Hepatitis B 10 Chen G, Lin WY, Shen FM, et al. Viral load as a predictor of mortality from hepatocellular carcinoma and chronic liver disease in chronic hepatitis B infection. J Hepatol 2005;42(Suppl. 2):S173. 11 Iloeje UH, Yang HI, Su J, et al. Viral load not serum alanine aminotransferase (ALT) is the primary predictor of progression to cirrhosis in persons chronically infected with hepatitis B virus. Gastroenterology 2005;128:A–740. 12 Iloeje UH, Yang HI, Su J, et al. Predicting cirrhosis risk based on the level of circulating hepatitis B viral load. Gastroenterology 2006;130:678–86. 13 Fattovich G, Stroffolini T, Zagni I, Donato F. Hepatocellular carcinoma in cirrhosis: incidence and risk factors. Gastroenterology 2004;127(Suppl.):S35–50. 14 Ganem D, Prince AM. Hepatitis B virus infection–– natural history and clinical consequences. N Engl J Med 2004;350:1118–29. 15 Brown RE, De CE, Colin X, et al. Hepatitis B management costs in France, Italy, Spain, and the United Kingdom. J Clin Gastroenterol 2004;38(Suppl.): S169–74. 16 Butler JR, Pianko S, Korda RJ, et al. The direct cost of managing patients with chronic hepatitis B infection in Australia. J Clin Gastroenterol 2004;38(Suppl.): S187–92. 17 Gagnon YM, Levy AR, Iloeje UH, Briggs AH. Treatment costs in Canada of health conditions resulting from chronic hepatitis B infection. J Clin Gastroenterol 2004;38(Suppl.):S179–86. 18 Hsieh CR, Kuo CW. Cost of chronic hepatitis B virus infection in Taiwan. J Clin Gastroenterol 2004; 38(Suppl.):S148–52. 19 Kowdley KV. The cost of managing chronic hepatitis B infection: a global perspective. J Clin Gastroenterol 2004;38(Suppl.):S132–3. 20 Lee TA, Veenstra DL, Iloeje UH, Sullivan SD. Cost of chronic hepatitis B infection in the United States. J Clin Gastroenterol 2004;38(Suppl.):S144–7. 21 Li SC, Ong SC, Lim SG, et al. A cost comparison of management of chronic hepatitis B and its associated complications in Hong Kong and Singapore. J Clin Gastroenterol 2004;38(Suppl.):S136–43. 22 Yang BM, Kim CH, Kim JY. Cost of chronic hepatitis B infection in South Korea. J Clin Gastroenterol 2004; 38(Suppl.):S153–7. 23 Zhiqiang G, Zhaohui D, Qinhuan W, et al. Cost of chronic hepatitis B infection in China. J Clin Gastroenterol 2004;38(Suppl.):S175–8. 24 Mueller AR, Platz KP, Kremer B. Early postoperative complications following liver transplantation. Best Pract Res Clin Gastroenterol 2004;18:881–900. 25 Brazier J, Green C, McCabe C, Stevens K. Use of visual analog scales in economic evaluation. Expert Rev Pharmacoeconomics Outcomes Res 2003;3:293–302. 26 Torrance GW, Furlong W, Feeny D. Health utility estimation. Exp Rev Pharmacoeconom Res 2002;2: 99–108. 27 Kanwal F, Gralnek IM, Martin P, et al. Treatment alternatives for chronic hepatitis B virus infection: a cost-effectiveness analysis. Ann Intern Med 2005; 142:821–31.

537 28 Wong JB, Koff RS, Tine F, Pauker SG. Costeffectiveness of interferon-alpha 2b treatment for hepatitis B e antigen-positive chronic hepatitis B. Ann Intern Med 1995;122:664–75. 29 Arevalo JA, Washington AE. Cost-effectiveness of prenatal screening and immunization for hepatitis B virus. JAMA 1988;259:365–9. 30 Bloom BS, Hillman AL, Fendrick AM, Schwartz JS. A reappraisal of hepatitis B virus vaccination strategies using cost-effectiveness analysis. Ann Intern Med 1993;118:298–306. 31 Krahn M, Detsky AS. Should Canada and the United States universally vaccinate infants against hepatitis B? A cost-effectiveness analysis. Med Decis Making 1993;13:4–20. 32 Chong CA, Gulamhussein A, Heathcote EJ, et al. Health-state utilities and quality of life in hepatitis C patients. Am J Gastroenterol 2003;98:630–8. 33 Boyd NF, Sutherland HJ, Heasman KZ, et al. Whose utilities for decision analysis? Med Decis Making 1990;10:58–67. 34 De Wit GA, Busschbach JJV, De Charro FT. Sensitivity and perspective in the valuation of health status: whose values count? Health Econ 2000;9:109–26. 35 Dolan P. Whose preferences count? Med Decis Making 1999;19:482–6. 36 Janse AJ, Gemke RJ, Uiterwaal CS, et al. Quality of life: patients and doctors don’t always agree: a metaanalysis. J Clin Epidemiol 2004;57:653–61. 37 Gold MR, Siegel JE, Russel LB, Weinstein MC. CostEffectiveness in Health and Medicine. New York: Oxford University Press, 1996. 38 Bennet KJ, Torrance GW. Measuring health state preferences and utilities: rating scale, time trade-off and standard gamble techniques. In: Spilker B, ed. Quality of Life and Pharmacoeconomics in Clinical Trials. Philadelphia, PA: Lippincott-Raven, 1996. 39 Furlong W, Feeny D, Torrance GW, et al. Guide to Design and Development of Health State Utility Instrumentation. Working Paper 90-9. Hamilton, ON: McMaster University Centre for Health Economics and Policy Analysis, 1990. 40 Llewellyn-Thomas H, Sutherland HJ, Tibshirani R, et al. Describing health states. Methodologic issues in obtaining values for health states. Med Care 1984; 22:543–52. 41 Schunemann HJ, Stahl E, Austin P, et al. A comparison of narrative and table formats for presenting hypothetical health states to patients with gastrointestinal or pulmonary disease. Med Decis Making 2004;24:53–60. 42 Gralnek IM, Hays RD, Kilbourne A, et al. Development and evaluation of the Liver Disease Quality of Life instrument in persons with advanced, chronic liver disease––the LDQOL 1.0. Am J Gastroenterol 2000;95:3552–65. 43 Torrance GW, Feeny D, Furlong W. Visual analog scales: do they have a role in the measurement of preferences for health states? Med Decis Making 2001;21:329–34. 44 Hoffmann JP. Generalized Linear Models: an Applied Approach. Boston, MA: Pearson Education Inc, 2004.

Levy et al.

538 45 Patrick DL, Starks HE, Cain KC, et al. Measuring preferences for health states worse than death. Med Decis Making 1994;14:9–18. 46 Lok AS, McMahon BJ. Chronic hepatitis B. Hepatology 2001;34:1225–41. 47 World Health Organization. Hepatitis B. World Health Organization Fact Sheet 204. 2000. Available form: http://www.who.int/mediacentre/factsheets/fs204/en/ [Accessed July 23, 2007]. 48 Pramoolsinsup C. Management of viral hepatitis B. J Gastroenterol Hepatol 2002;17(Suppl.):S125–45. 49 Mulley AG Jr. Assessing patients’ utilities. Can the ends justify the means? Med Care 1989;27(Suppl.): S269–81. 50 Mittmann N, Trakas K, Risebrough N, Liu BA. Utility scores for chronic conditions in a communitydwelling population. Pharmacoeconomics 1999;15: 369–76. 51 Hawthorne G, Osborne R. Population norms and meaningful differences for the Assessment of Quality of Life (AQoL) measure. Aust N Z J Public Health 2005;29:136–42. 52 Albrecht GL, Devlieger PJ. The disability paradox: high quality of life against all odds. Soc Sci Med 1999;48:977–88. 53 Sherbourne CD, Keeler E, Unutzer J, et al. Relationship between age and patients’ current health state preferences. Gerontologist 1999;39:271–8. 54 Levine S, Feldman JJ, Elinson J. Does medical care do any good? In: Mechanic D, ed. Handbook of Health, Health Care and the Health Professions. New York: The Free Press 1983. 55 Amick BC, Levine S, Tarlov AR, Walsh DC (eds). Society and Health. New York: Oxford University Press, 1994. 56 Schwartz CE, Andresen EM, Nosek MA, Krahn GL. Response shift theory: important implications for measuring quality of life in people with disability. Arch Phys Med Rehabil 2007;88:529–36. 57 Gabriel SE, Kneeland TS, Melton LJ III, et al. Healthrelated quality of life in economic evaluations for osteoporosis: whose values should we use? Med Decis Making 1999;19:141–8. 58 Postulart D, Adang EM. Response shift and adaptation in chronically ill patients. Med Decis Making 2000;20:186–93. 59 Sackett DL, Torrance GW. The utility of different health states as perceived by the general public. J Chronic Dis 1978;31:697–704. 60 Tsevat J, Cook EF, Green ML, et al. Health values of the seriously ill. SUPPORT investigators. Ann Intern Med 1995;122:514–20. 61 Balaban DJ, Sagi PC, Goldfarb NI, Nettler S. Weights for scoring the quality of well-being instrument among

62

63

64 65 66 67 68

69 70 71 72

73

74

75

76

rheumatoid arthritics. A comparison to general population weights. Med Care 1986;24:973–80. Jenkinson C, Gray A, Doll H, et al. Evaluation of index and profile measures of health status in a randomized controlled trial. Comparison of the Medical Outcomes Study 36-Item Short Form Health Survey, EuroQol, and disease specific measures. Med Care 1997;35:1109–18. Dolders MG, Zeegers MP, Groot W, Ament A. A meta-analysis demonstrates no significant differences between patient and population preferences. J Clin Epidemiol 2006;59:653–64. Dolan P. Effect of age on health state valuations. J Health Serv Res Policy 2000;5:17–21. B is for bigotry. The Economist, November 16, 2006. Murray CJ, Chen LC. Understanding morbidity change. Popul Dev Rev 1992;18:481–503. Torrance GW. Social preferences for health states: an empirical evaluation of three measurement techniques. Socioecon Plann Sci 1976;10:128–36. Kaplan RM, Bush JW, Berry CC. Health status index: category rating versus magnitude estimation for measuring levels of well-being. Med Care 1979;17:501– 25. Read JL, Quinn RJ, Berwick DM, et al. Preferences for health outcomes. Comparison of assessment methods. Med Decis Making 1984;4:315–29. Haig TH, Scott DA, Wickett LI. The rational zero point for an illness index with ratio properties. Med Care 1986;24:113–24. Tengs TO, Wallace A. One thousand health-related quality-of-life estimates. Med Care 2000;38:583–637. Wells CD, Murrill WB, Arguedas MR. Comparison of health-related quality of life preferences between physicians and cirrhotic patients: implications for costutility analyses in chronic liver disease. Dig Dis Sci 2004;49:453–8. Bonsel GJ, Klompmaker IJ, Essink-Bot ML, et al. Cost-effectiveness analysis of the Dutch liver transplantation programme. Transplant Proc 1990;22: 1481–4. Kim WR, Poterucha JJ, Hermans JE, et al. Costeffectiveness of 6 and 12 months of interferon-alpha therapy for chronic hepatitis C. Ann Intern Med 1997;127:866–74. Teran JC, Imperiale TF, Mullen KD, et al. Primary prophylaxis of variceal bleeding in cirrhosis: a costeffectiveness analysis. Gastroenterology 1997;112: 473–82. Owens DK, Cardinalli AB, Nease RF Jr. Physicians’ assessments of the utility of health states associated with human immunodeficiency virus (HIV) and hepatitis B virus (HBV) infection. Qual Life Res 1997; 6:77–86.