Health utilities measure patients' preferences for a health state.
Health utilities measure patients' preferences for a health state.
To assess health utilities for sofosbuvir-containing therapy for chronic hepatitis C.
The SF-6D utility scores were derived from the SF-36 instrument administered at baseline, during and post-treatment to participants of the previously reported clinical trials of sofosbuvir. EQ-5D utility scores were also approximated from the SF-36 using a regression model.
Nine hundred and ninety-four patients were enrolled. Baseline SF-6D and EQ-5D scores were 0.66 ± 0.13 and 0.71 ± 0.22, respectively (the POSITRON trial), 0.71 ± 0.16 and 0.76 ± 0.23 (FISSION), 0.70 ± 0.14 and 0.75 ± 0.22 (FUSION), 0.72 ± 0.15 and 0.79 ± 0.22 (NEUTRINO). In all studies, SF-6D and EQ-5D scores were highly correlated with each other. (r = 0.83–0.87, P < 0.0001). After 12 weeks, patients receiving sofosbuvir + ribavirin (POSITRON) had similar utility scores to placebo (P > 0.05). Patients receiving 12 and 16 weeks of sofosbuvir + ribavirin (FUSION) had similar utility scores (P > 0.05). In FISSION, patients receiving sofosbuvir + ribavirin had significantly better utilities compared to patients receiving interferon + ribavirin (P < 0.001). Patients receiving sofosbuvir + ribavirin + interferon (NEUTRINO) had a decrease in utilities during treatment (SF-6D: from 0.72 to 0.62, EQ-5D: 0.79 to 0.65; P < 0.0001) similar to that observed in patients receiving pegylated interferon + ribavirin for 24 weeks in FISSION (0.72 to 0.62 and 0.77 to 0.65, respectively, P < 0.0001). After 12 weeks post-treatment, patients with SVR (FUSION) had improvement in SF-6D (+0.026 from baseline, P = 0.013) and EQ-5D (+0.043, P = 0.013). In multivariate analyses, baseline depression, anxiety, fatigue, insomnia and treatment-related anaemia were the most consistent predictors of utilities.
Patients' health utilities are minimally impacted by sofosbuvir + ribavirin treatment, as compared to interferon-based, therapy regardless of treatment duration.
Clinical trials' numbers: NCT01542788 (POSITRON), NCT01497366 (FISSION), NCT01604850 (FUSION), NCT01641640 (NEUTRINO).
The health utility scores are based on patients' preference for a health status and are needed for assessment of the economic impact of interventions in patients with chronic conditions.[1, 2] Health utilities are used in various cost-effectiveness analyses to quality adjust the outcomes of interest. Policy makers rely on these analyses which involve calculation of quality-adjusted life years (QALYs). In fact, QALYs provide a measurement for the intervention-associated gained or lost years of life while taking into account the quality of these years of life.[2-4] Thus, this metric allows diverse programs to be compared with each other by policy makers and customers using a single unit that incorporates information about both quantity and quality of life impacted by a specific intervention or program.[2-4]
There are a number of ways to measure health utilities. Utilities can be measured directly through techniques such as time trade-off or standard gamble, or indirectly using validated instruments or questionnaires.[5-7] An indirect method to estimate health utilities is to use an extensively validated metric named SF-6D. These SF-6D scores can be derived from the widely used quality of life questionnaire Medical Outcome Study-Short Form 36 (SF-36) using utility weights elicited from a sample of the general population and previously described parametric or Bayesian nonparametric algorithm. Among other chronic diseases, SF-6D has been validated for use in chronic hepatitis.
Another instrument for indirect evaluation of health state preferences is EQ-5D which requires administering a specifically designed questionnaire. Regulatory agencies in Europe, such as National Institute for Health and Care Excellence of the UK and the European Medicines Agency have recently expressed preference for utility estimates measured using EQ-5D. However, using separate questionnaires in one trial to assess the HRQL and the health status (SF-36 and EQ-5D) adds to the total questionnaire burden and is often not practical.
An alternative strategy is to use mapping algorithms to approximate EQ-5D scores from SF-36 and SF-6D. One algorithm that uses an ordinary least square regression and the items of SF-36 has been presented by the authors of the SF-6D metric; the reported coefficient of determination for the method was 56%. Two other algorithms presented similarly designed linear relationships between EQ-5D and SF-6D based on observed high correlation between the metrics.[13, 14] In another article by Gray et al., two approaches have been reported: a two step approach that first predicted the values of individual items of EQ-5D using an ordered logit and then used them to calculate the total EQ-5D score, and a regression model with a coefficient of determination of 53%. In a review by Rowen et al., it was shown that algorithms for mapping of SF-36 to EQ-5D are generally reliable with the exception of extreme health states where more severe EQ-5D states seem to be over-predicted.
Chronic hepatitis C (CH-C) infection is a chronic condition that is estimated to affect 170 millions of people worldwide. A large proportion of the total economic burden of HCV infection is direct and indirect costs of management of HCV. In this context, the cost associated with treatment of HCV and the indirect costs associated with complications of HCV-related liver disease and treatment side effects could be tremendous. In addition, health states related to disease complication or treatment side effects can impair patients' quality of life and health utilities. Despite the adverse event profile and high costs, even earlier generations of anti-HCV therapies were found to be cost-effective.[20-22] Still, with newer emerging therapies being superior both in efficacy and safety profile, an opportunity for improvement of cost-utility balance is expected to open.
Treatment of CH-C involves the use of pegylated interferon and ribavirin with first generation protease inhibitors, and is associated with significant side effects including fatigue, anaemia, dizziness and nausea which usually result in compromised health status. Indeed, substantial decrements in health-related quality of life among patients receiving anti-HCV treatment have previously been reported. The majority of the side effects are associated with the use of interferon. Recently emerged direct anti-viral agents do not seem to directly contribute to HRQL impairment, but, as long as they are used in combination with interferon, will not eliminate any of interferon-associated side effects and the HRQL impairment either.[25-28] On the other hand, the newly emerging interferon-free regimens [29-34] are expected to result in less if any adverse events and, therefore, better health utility scores for patients undergoing anti-HCV treatment. However, the health utility scores that could be used in cost-effectiveness analyses of interferon-free anti-HCV therapies are yet to be reported.
Recently, four clinical 3 trials (FISSION, POSITRON, NEUTRINO and FUSION) were conducted studying sofosbuvir, an HCV NS5B inhibitor, with ribavirin with or without interferon for patients with HCV infection. The aim of this study is to evaluate the impact of different treatment strategies that involve sofosbuvir in different combinations and duration on patients' utility scores.
Subjects were enrolled in four phase 3 trials of sofosbuvir, namely, FISSION, POSITRON, FUSION and NEUTRINO, all described elsewhere.[29, 30] In all studies, patients were men and women at least 18 years old with chronic (at least 6 months) HCV infection and with serum HCV RNA ≥10 000 IU/mL during screening. Patients were excluded if they had evidence or prior history of hepatocellular carcinoma, decompensated liver disease, other chronic liver disease, co-infection with HIV or hepatitis B virus or other clinically significant abnormalities.
The FISSION trial was a randomized, open-label, active-control study in treatment-naïve patients with HCV genotype 2 and 3 infection comparing 12 weeks of treatment with sofosbuvir plus ribavirin to pegylated interferon alfa-2a plus ribavirin for 24 weeks. For details about the study design, please refer to original publication. The SF-6D scores were derived from the SF-36 questionnaire that was implemented at baseline, week 12, week 24 and week 36.
The POSITRON trial was a blinded, placebo-controlled study that compared 12 weeks of sofosbuvir and ribavirin with matching placebo in patients with a documented inability to receive interferon therapy due to prior intolerance, medical contraindications for interferon or unwillingness to be treated with interferon. For details about the study design, please refer to original publication. The SF-6D scores were calculated at baseline, week 12 and week 16.
The FUSION study was a blinded, active-control study that evaluated 12 weeks and 16 weeks of sofosbuvir and ribavirin in patients who had previously failed an interferon-containing regimen. For details about the study design, please refer to original publication. The SF-6D scores were derived from the SF-36 questionnaire that was implemented at baseline, weeks 4, 12, 16, 20, 24, 28 and 40 (only those with undetectable HCV RNA at week 20 were followed up at subsequent visits).
The NEUTRINO study was an open-label uncontrolled study that evaluated 12 weeks of triple sofosbuvir, ribavirin and pegylated interferon therapy in treatment-naive patients with HCV genotype 1, 4, 5 and 6. For details about the study design, please refer to original publication. The SF-6D scores were calculated at baseline, weeks 12, 16 and 24.
The health utility scores were assessed using the SF-6D metric derived from SF-36v2 questionnaire which was administered at each study time point to all subjects in their native language (English, Swedish, Dutch and Italian). The SF-6D score is widely used for estimating a preference-based single index measure for health from SF-36 data using general population values and is typically involved in calculation of QALYs in cost-utility and cost-effectiveness analyses. The Excel converter program for calculation of SF-6D scores from SF-36v2 questionnaires using a nonparametric Bayesian algorithm was provided by the University of Sheffield under the terms and conditions of noncommercial end-user license agreement.
Using five previously reported mapping algorithms,[12-15] we also evaluated EQ-5D scores for the same subjects. These algorithms use individual scales or summary scores of SF-36, or SF-6D values for approximation of EQ-6D values using linear, ordinal and logit regression techniques.
In three of the four studies (excluding NEUTRINO which was uncontrolled), screened patients were randomized into two arms as described above. In addition to collecting a number of clinico-demographical parameters and medical history prior treatment, we defined treatment-related anaemia as haemoglobin decrement of 2 g/dL or more from the baseline at any time point after the start of treatment. For all those parameters, as well as for the SF-6D utility scores, the prevalence in percents or a mean and a standard deviation were calculated within each study arm in each of the four studies separately. Furthermore, clinico-demographical parameters and SF-6D scores were compared between the study arms at all applicable time points using Pearson's chi-square test for independence or Wilcoxon nonparametric test. The decrements in SF-6D from the baseline were calculated for each patient at each subsequent time point, and Wilcoxon tests were applied to compare them to zero (sign rank) and between the study arms (rank sum) where applicable. The minimal clinically important difference (MCID) for SF-6D was 0.05.
Independent predictors of SF-6D scores and decrements in those were assessed using multiple linear regressions with the arm of the study being used as one of the potential predictors of the outcome in both each trial (POSITRON, FISSION, FUSION, NEUTRINO) separately, and in all four trials pooled together. In a pooled multivariate analysis, the following treatment regimens were considered to be potential predictors of utilities: SOF for 12 weeks, SOF for 16 weeks, IFN for 12 weeks, IFN for 24 weeks, placebo. Using this treatment coding, NEUTRINO subjects were considered to receive both SOF for 12 weeks and IFN for 12 weeks. Other potential SF-6D predictors in all studies were age, gender, ethnicity, BMI, location, baseline haemoglobin (at day 1) or treatment-related anaemia (after the start of treatment), pre-treatment history of psychiatric disorders self-reported at screening, baseline HCV viral load and ALT, presence or absence of liver cirrhosis, achieving SVR (at and after the end of treatment).
In each study at each time point, mean values of estimated EQ-5D score were also calculated. Pearson's correlations coefficients were calculated for SF-6D and EQ-5D values predicted by different algorithms.
P values of 0.05 or less were considered potentially significant. All statistical analyses were run in sas 9.1 (SAS Institute, Cary, NC, USA). The study was approved by each site's Institutional Review Board and Inova IRB.
The demographics, baseline clinical presentation and treatment outcomes of the studies participants have previously been published.[29-31]
In POSITRON study, 262 patients with HCV genotype 2 and 3 were randomized to receive sofosbuvir + ribavirin (n = 196) or the placebo (n = 66). As previously published,[29-31] no difference at baseline was observed for all parameters between those receiving active treatment and placebo controls (all P > 0.05). A total of 16% of patients had compensated cirrhosis. During treatment, a significant proportion of patients receiving active treatment developed anaemia (a decrement in haemoglobin of at least 2 g/dL) as compared to placebo (P < 0.0001).
In FISSION, of patients with completed SF-36 questionnaires, a total of 105 subjects received 12 weeks of sofosbuvir + ribavirin therapy as opposed to 110 who received 24 weeks of pegylated interferon + ribavirin. A total of 21% of patients had compensated cirrhosis. Similarly, no difference between the study arms was observed in any of the clinico-demographical parameters, the rates of treatment-related anaemia (approximately 70%) or SVR.[29-31]
In FUSION, 98 patients received 16 weeks of treatment with sofosbuvir + ribavirin and 103 patients received 12 weeks of sofosbuvir + ribavirin followed by 4 weeks of blinded matching placebo. The two cohorts were identical in every studied clinico-demographical parameter.[29, 30] It is important to note that in FUSION, 34% of patients had compensated cirrhosis. The rate of SVR (but not treatment-related anaemia) was higher in the 16 weeks arm.
In NEUTRINO, an open-label single arm study of 12-week long treatment with sofosbuvir + ribavirin + pegylated interferon, 326 participants were included. The rate of treatment-induced anaemia was 92.6%.
The rates of serious adverse events were: in the POSITRON trial, 5% in the active treatment arm and 3% in the placebo arm; in the FUSION trial, 5% in the 12 weeks arm and 3% in the 16 weeks arm; in the FISSION trial, 3% in the interferon-free arm and 1% in the interferon-containing arm; in the NEUTRINO trial, 1% of the study cohort.[29, 30]
The utility scores for POSITRON (Table 1, Figure 1A) were similar at all time points between those receiving active treatment and placebo. However, when compared to their own baseline, a significant average decrement of 0.051 (P < 0.0001; 44.8% experienced a decrement exceeding MCID of 0.05) was observed in the treatment arm, but not in the placebo arm (P = 0.35, 28.9% exceeded MCID). By week 4 of post-treatment follow-up, the trends sustained but statistical significance disappeared (both P > 0.05).
|SOF + RBV for 12 weeks||Placebo||P a||SOF + RBV for 12 weeks||IFN + RBV for 24 weeks||P|
|Baseline||0.671 ± 0.131||0.639 ± 0.136||0.21||0.707 ± 0.161||0.716 ± 0.160||0.60|
|End-of-treatment||0.632 ± 0.136||0.645 ± 0.149||0.42||0.690 ± 0.176||0.625 ± 0.147||0.042|
|Follow-up week 4||0.663 ± 0.137||0.646 ± 0.138||0.40||NA||NA||NA|
|Follow-up week 12||NA||NA||NA||0.695 ± 0.152||0.696 ± 0.163||0.66|
|Decrement from baseline byb|
|End-of-treatment||0.051 ± 0.118c||0.017 ± 0.100||0.082||0.018 ± 0.159||0.089±0.168c||0.023|
|Follow-up week 4||0.020 ± 0.119||−0.004 ± 0.114||0.47||NA||NA||NA|
|Follow-up week 12||NA||NA||NA||−0.006 ± 0.177||0.018 ± 0.138||0.20|
|SOF + RBV for 16 weeks||SOF + RBV for 12 weeks||P||An uncontrolled study of SOF + RBV + IFN|
|Baseline||0.695 ± 0.136||0.698 ± 0.152||0.58||0.723 ± 0.152|
|End-of-treatment||0.668 ± 0.154||0.656 ± 0.151||0.59||0.621 ± 0.130|
|Follow-up week 4||0.695 ± 0.147||0.688 ± 0.151||0.84||0.691 ± 0.145|
|Follow-up week 12||0.704 ± 0.151||0.734 ± 0.155||0.33||0.728 ± 0.158|
|Decrement from baseline byb|
|End-of-treatment||0.028 ± 0.128c||0.039 ± 0.130c||0.97||0.105 ± 0.149c|
|Follow-up week 4||0.001 ± 0.120||0.007 ± 0.134||0.84||0.032 ± 0.147c|
|Follow-up week 12||−0.027 ± 0.111c||−0.024 ± 0.128||0.93||−0.006 ± 0.150|
The utility scores for participants in FISSION (Table 1, Figure 1B) were similar at baseline between the study arms. At the end of treatment, however, the utility scores were significantly lower in those receiving interferon: 0.625 in the interferon arm vs. 0.690 in sofosbuvir arm (P = 0.042; the difference between the average utilities exceeds MCID). The decrement from baseline was also significant in the interferon arm (0.089, P < 0.0001, 53.9% of patients experienced a decrement exceeding MCID) but not in the sofosbuvir arm (0.018, P = 0.29, 40.5% above MCID). Despite this, by week 12 of follow-up, subjects in both arms of the study returned to their baseline utility values and were not different from each other (all P > 0.05) (Table 1).
The utility scores for participants in FUSION (Table 1, Figure 1C) were similar in both study arms at all time points. Also observed were significant decrements from patients' own baseline at the end-of-treatment (44.3–44.6% experienced a decrement above MCID, P > 0.05), which completely disappeared 4 weeks after, and partially significant trends towards improvement (negative decrements in the table) occurred at week 12 of follow-up in both arms. Furthermore, at week 12 post-treatment in FUSION, a statistically significant improvement in the utility scores compared to baseline was observed among those who achieved SVR: an average +0.026 (P = 0.0126). Indeed, 57.1% of participants experienced at least some improvement in their status after achieving SVR (34.3% experienced improvement exceeding MCID), with maximum improvement being from baseline of 0.61 to the resulting 0.94. In this study, only patients with SVR were followed up after week 20, so no conclusions about the causal effect of SVR can be made from these data.
The utility scores in NEUTRINO (Table 1, Figure 1D), where an interferon-containing regimen was studied, dropped substantially after 12 weeks of treatment: from 0.72 ± 0.15 to 0.62 ± 0.13 (paired P < 0.0001, exceeds MCID) (Table 1). The magnitude of this decrement, although still statistically significant (exceeds MCID in 63.9% of patients), substantially decreased by week 4 (the SF-6D values increased back to the average of 0.69 ± 0.15, P = 0.002) and completely disappeared by week 12 post-treatment (average 0.73 ± 0.16, P = 0.47 when compared to patients' own baseline).
In multivariate analysis (Table 2), baseline depression, fatigue, anxiety and insomnia were the major predictors of lower utility scores at all time points in all studies. Treatment-related anaemia was also associated with lower end-of-treatment scores in some of the studies. In addition, in FISSION, receiving sofosbuvir as opposed to pegylated interferon was associated with higher end-of-treatment score (β = 0.079 ± 0.024, P = 0.0015, the magnitude of beta exceeds MCID) while in other studies, the study arm was not found to be associated with SF-6D utility score at any time point, and neither was SVR at the end of treatment or at any time point after that. Furthermore, baseline cirrhosis was found to be both clinically and significantly associated with lower health utility scores in NEUTRINO only (treatment-naive genotype 1,4,5,6 subjects).
|β ± S.E.||P||β ± S.E.||P|
|POSITRON study||FISSION study|
|Depression||−0.070 ± 0.018||0.0002||Caucasian||0.080 ± 0.031||0.0097|
|Fatigue||−0.062 ± 0.029||0.0317||Anxiety||−0.067 ± 0.033||0.0433|
|HCV viral load >6 × 106||0.069 ± 0.020||0.0006||Depression||−0.104 ± 0.028||0.0003|
|End of treatment|
|Depression||−0.071 ± 0.021||0.0007||Receiving Sofosbuvir||0.079 ± 0.024||0.0015|
|Insomnia||−0.064 ± 0.023||0.0064||Age, per 1 year||−0.0024 ± 0.0011||0.0317|
|Depression||−0.135 ± 0.029||<0.0001|
|Anaemia||−0.068 ± 0.027||0.0118|
|Week 4 of follow-up|
|Depression||−0.061 ± 0.021||0.0041||Not applicable at this time point|
|Insomnia||−0.073 ± 0.023||0.0020|
|Week 12 of follow-up|
|Not applicable at this time point||Age, per year||−0.0036 ± 0.0010||0.0004|
|Caucasian||0.099 ± 0.033||0.0035|
|Depression||−0.110 ± 0.030||0.0003|
|Fatigue||−0.106 ± 0.033||0.0018|
|FUSION study||NEUTRINO study|
|Anxiety||−0.053 ± 0.027||0.0495||Depression||−0.084 ± 0.020||<0.0001|
|Depression||−0.071 ± 0.023||0.0027||Fatigue||−0.067 ± 0.028||0.0179|
|Fatigue||−0.063 ± 0.027||0.0213|
|End of treatment|
|Male gender||0.058 ± 0.023||0.0129||Anxiety||−0.041 ± 0.021||0.0479|
|Anxiety||−0.083 ± 0.029||0.0042||Fatigue||−0.057 ± 0.027||0.0345|
|Depression||−0.063 ± 0.025||0.0108||Cirrhosis||0.053 ± 0.021||0.0132|
|Fatigue||−0.065 ± 0.030||0.0324|
|Week 4 of follow-up|
|Anxiety||−0.062 ± 0.030||0.0384||Depression||−0.059 ± 0.020||0.0041|
|Depression||−0.055 ± 0.025||0.0304||Fatigue||−0.056 ± 0.028||0.0455|
|Insomnia||−0.052 ± 0.026||0.0468||Insomnia||−0.043 ± 0.021||0.0407|
|Week 12 of follow-up|
|Depression||−0.071 ± 0.033||0.0329||Anxiety||−0.052 ± 0.026||0.0488|
|Anaemia||−0.070 ± 0.032||0.0308||Depression||−0.077 ± 0.023||0.0012|
|Cirrhosis||−0.056 ± 0.026||0.0356|
In pooled multivariate analysis with all four studies merged together, after adjustment for demographics, medical and treatment history, receiving interferon for 12 or 24 weeks was independently associated with lower SF-6D scores during treatment: β = −0.038 ± 0.011 (P = 0.0005) and −0.052 ± 0.018 (P = 0.0034), respectively; however, this association disappeared post-treatment (P > 0.05). On the other hand, longer duration of treatment with sofosbuvir (16 weeks vs. 12 weeks) was not associated with SF-6D at any time point (all P > 0.05). Other predictors of lower SF-6D utility scores were similar to those reported above for the studies separately and included baseline depression, anxiety, fatigue, cirrhosis, treatment-related anaemia and being treatment-experienced (Table S1).
All five presented algorithms were used to calculate EQ-5D scores from either scales of SF-36 or directly from SF-6D. The correlation coefficients with SF-6D in different studies were as follows: 0.842–0.870 for the ordinal least square regression, 1.0 for the two linear models with SF-6D,[13, 14] 0.713–0.757 for the two step approach, and 0.827–0.850 for the linear regression model  (all P < 0.0001). Thus, the first and last algorithms demonstrated similarly high correlations with SF-6D while not directly using SF-6D values.
The EQ-5D scores for the four studies calculated using the linear regression algorithm by Gray et al.  are shown in Table 3. Predictors of EQ-5D scores were identical to those reported for SF-6D (data not shown).
|SOF + RBV for 12 weeks||Placebo||P||SOF + RBV for 12 weeks||IFN + RBV for 24 weeks||P|
|Baseline||0.717 ± 0.214||0.673 ± 0.227||0.22||0.740 ± 0.232||0.771 ± 0.236||0.35|
|End-of-treatment||0.664 ± 0.212||0.671 ± 0.238||0.74||0.737 ± 0.251||0.650 ± 0.224||0.0413|
|Follow-up week 4||0.708 ± 0.234||0.689 ± 0.242||0.56||NA||NA||NA|
|Follow-up week 12||NA||NA||NA||0.752 ± 0.231||0.743 ± 0.221||0.90|
|Decrement from baseline byb|
|End-of-treatment||0.075 ± 0.180a||0.029 ± 0.138||0.12||0.006 ± 0.201||0.115 ± 0.200a||0.0076|
|Follow-up week 4||0.026 ± 0.188||0.019 ± 0.172||0.84||NA||NA||NA|
|Follow-up week 12||NA||NA||NA||−0.035 ± 0.173||0.035 ± 0.156||0.0362|
|SOF + RBV for 16 weeks||SOF + RBV for 12 weeks||P||An uncontrolled study of SOF + RBV + IFN|
|Baseline||0.745 ± 0.211||0.753 ± 0.231||0.79||0.793 ± 0.219|
|End-of-treatment||0.724 ± 0.225||0.685 ± 0.225||0.25||0.645 ± 0.213|
|Follow-up week 4||0.745 ± 0.213||0.738 ± 0.239||0.94||0.750 ± 0.224|
|Follow-up week 12||0.769 ± 0.218||0.790 ± 0.233||0.55||0.791 ± 0.215|
|Decrement from baseline byb|
|End-of-treatment||0.020 ± 0.167||0.059 ± 0.191a||0.095||0.149 ± 0.210a|
|Follow-up week 4||0.005 ± 0.175||0.012 ± 0.177||0.72||0.044 ± 0.209a|
|Follow-up week 12||−0.054 ± 0.179a||−0.021 ± 0.184||0.26||−0.0003 ± 0.1874|
In this study, we evaluated the impact of anti-HCV therapy on health utility scores in patients with chronic hepatitis C infection before, during and soon after treatment. Various sofosbuvir-containing anti-HCV therapies were studied and included different combinations of medications, different treatment durations and different control strategies. In this study, we demonstrated the superiority in terms of health utility of interferon-free anti-HCV regimens over the standard treatment which includes at least 12 weeks of pegylated interferon and is known to result in substantial decrement in patients' well-being.
Being derived directly from SF-36, the SF-6D utility scores calculated in this study followed essentially the same temporal and treatment-related trends as previously reported. In particular, health utility scores in patients who were previously ineligible or unwilling to receive Interferon-based therapy and, thus, had no other option for treatment at the time of study, were similar to those receiving placebo at the same time. Another expected finding was that the health status of those receiving interferon was more severely impaired compared to an interferon-free regimen, although all treatment-related impairment resolved within 12 weeks after the end of treatment. Furthermore, the duration of treatment with an interferon-free regimen does not affect the health status of the patient during, at the end, or soon after treatment.
A moderate trend towards improvement of health utility scores in those who achieved SVR was found in one study, although not reproduced in other studies. More research is needed to evaluate the impact of achieving SVR to health utility scores.
Similarly to previously reported HRQL data,[31, 32, 36, 37] the major predictors of lower utility scores were pre-treatment depression and other well-being-related conditions (insomnia, fatigue, anxiety, hepatic cirrhosis) regardless of the study cohort, time point or treatment. However, no consistent predictors for the magnitude of health utility decrement during treatment were found: in POSITRON, it was high pre-treatment viral load (β = 0.041, P = 0.0354), in FISSION-receiving Interferon (0.072, P = 0.0081) and Caucasian race (0.082, P = 0.0335), in FUSION-female gender only (0.057, P = 0.0064), in NEUTRINO-Caucasian race (0.053, P = 0.0229), the absence of depression (β = 0.048, P = 0.0269) and the absence of cirrhosis (0.071, P = 0.0038). Using these findings, we suggest that more substantial impairment is expected in those who were initially in good health, but their health status will still be better than in those with pre-treatment cirrhosis and depression.
Hepatitis C infection is known to cause impairment in quality of life by itself.[6, 38] The major proportion of its impact onto health status of the patient is manifested at advanced stages when symptoms of severe liver damage or hepatitis C-associated metabolic disorders occur. Until then, hepatitis C infection is generally asymptomatic and minimally affects individual's day-to-day well-being. Since interferon-based therapy is expected to cause adverse event during treatment, many patients choose to postpone treatment unless their liver disease becomes more severe. In the nearest future, in the light of newly emerging therapies for anti-HCV treatment, the risk-benefit balance associated with anti-HCV treatment is expected to shift. Specifically, with less contraindications and higher success rates, more patients at early stages of liver disease and good health status will choose or will be eligible to start treatment. For these patients, even temporary impairment in their well-being will be important in making a decision about getting or postponing treatment. Thus, cost-utility analysis of any emerging anti-HCV therapy including prospective collection of health utility data is absolutely necessary.
The limitations of the study include the lack of direct measurement of health utilities (standard gamble, time trade-off), and also the absence of follow-up for those who failed to clear the virus at the end of treatment, so we could not make any causal implications about the effect of SVR on health utility score as opposed to failing treatment. The follow-up period was also short so no meaningful QALY calculations could be made. We also could not calculate EQ-5D scores directly by using the specifically designed EQ-5D questionnaire but used an approximation model to calculate these scores. Nevertheless, design of the initial studies guaranteed balanced cohorts with minimal confounding, while implementation of SF-36 at multiple time points allowed describing the temporal changes in the utility scores in patients receiving different anti-HCV treatment options. This study will provide investigators with rich historical data that have been obtained from patients with chronic hepatitis C together with SF-6D and EQ-5D health utility scores.
To conclude, we prospectively evaluated the effect of sofosbuvir-based anti-HCV therapy on health utility score in patients receiving this therapy. These findings can further be used in cost-utility and cost-effectiveness analyses of sofosbuvir-containing regimens by policy making agencies, health maintenance organizations, insurance companies and patients with chronic hepatitis C infection.
Guarantor of the article: Z. M. Younossi.
Author contributions: M. Stepanova run data analysis and wrote the first draft; F. Nader contributed to the data preparation; S. Cure and F. Bourhis run EQ-5D conversion analysis; S. Hunt prepared the source PRO data and critically reviewed the manuscript; Z. M. Younossi prepared the research study design and finalized the manuscript.
Declaration of personal interests: None.
Declaration of funding interests: This study was funded by Gilead Sciences.