Japanese value set for the EORTC QLU-C10D: A multi-attribute utility instrument based on the EORTC QLQ-C30 cancer-specific quality-of-life questionnaire

1. Why is this study needed?

The EORTC QLU-C10D is a preference-based multi-attribute utility instrument (MAUI) derived from the EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30), a health-related quality-of-life (HRQL) questionnaire widely used in cancer clinical trials internationally. The QLU-C10D enables quantification of utility from responses to the QLQ-C30, and hence enables HRQL data to be used in health policy decisions about cancer. Such decisions are typically made within a country, relating to the health budget of that country, or of regional and local health authorities. Therefore, country-specific ‘value sets’ based on the values and preferences of the general population of specific countries are needed.

2. What is the key problem/issue/question this manuscript addresses?

No value sets for the EORTC QLU-C10D existed for Japan prior to this study.

3. What is the main point of your study?

The valuation survey used to develop the Japanese QLU-C10D value set followed the standard protocol developed by the Multi-Attribute Utility in Cancer (MAUCa) Consortium for evaluating the EORTC QLU-C10D in general population samples. The valuation method used was an online discrete choice experiment. The resultant value set enables HRQL data from the EORTC QLQ-C30 to be used in Japanese health policy decisions and health technology assessment.

4. What are your main results and what do they mean?

A Japanese value set for the EORTC QLU-C10D was created. Physical functioning, role functioning, and pain were associated with the largest utility weights. The value of the worst health state was -0.221, lower than that seen in most other existing QLU-C10D country-specific value sets.

When economic evaluation of healthcare technologies is performed, quality-adjusted life years (QALYs) are standardly used for outcome measurement. QALYs can be calculated by weighting life years by the utility of the health state[1]. In Japan, since 2019, economic evaluation submissions are required for selected drug and medical device pricing before the Ministry of Health, Labour and Welfare (MHLW) can approve higher prices than for existing drugs[2]. As of December 2022, evaluations of 39 drugs and devices were completed or are in progress. The guideline for submission to the authority [3] indicates that “QALY should be used in principle” and “If Japanese quality-of-life (QOL) scores (utilities) are newly collected for a cost-effectiveness analysis, EQ-5D-5L is recommended as the first choice.” However, it does not preclude the use of alternative utility instruments.

For the purposes of economic evaluation, utility is anchored as 0 = dead and 1 = full health, which is necessary for construction of QALYs. To obtain scores on this utility scale, we typically use a preference-based measure (PBM). Many generic PBMs have been developed to measure utility, for example, the EuroQol 5 Dimensions (EQ-5D) [4, 5], Health Utilities Index (HUI)[6, 7], and Short Form 6 Dimensions (SF-6D) [8]. On the other hand, in clinical studies, disease-specific profile-type instruments are often used to measure patients’ HRQL. However, profile-type measures cannot be used for economic evaluation because they are not preference-based and therefore do not measure utility.

In collaboration with the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group, the Multi-Attribute Utility in Cancer (MAUCa) Consortium has developed the EORTC QLU-C10D, a multi-attribute utility instrument (MAUI) derived from the EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30) [9, 10]. The QLQ-C30 is the most widely used cancer-specific HRQL questionnaire [11]. But because the QLQ-C30 is a profile-type measure, it cannot be used to quality-adjust survival to calculate QALYs. The QLU-C10D was developed to enable quantification of utility from responses to the QLQ-C30. While mapping algorithms are available to derive utilities from QLQ-C30 responses through generic MAUIs [12], the QLU-C10D is potentially theoretically and empirically stronger because it comprises a descriptive system and a valuation method that complies with the Checklist for Reporting Valuation Studies [13], and aims to retain the cancer-specific sensitivity which is part of the QLQ-C30. Five of the 10 QLU-C10D dimensions capture symptoms and impacts of cancer and its treatments that are not explicitly included in generic instruments: nausea, fatigue, loss of appetite, and problems with sleep and bowel function. The other five dimensions are pain and four aspects of functioning (physical, role, social, and emotional). The QLU-C10D is not a stand-alone questionnaire; it is a MAUI that comprises a health state descriptive system plus country-specific preference weighting algorithms. Online Resource 1 shows the QLU-C10D descriptive system and explains how the 10 dimensions can be derived from 13 of the 30 items in the QLQ-C30.

The MAUCa Consortium has developed a standard protocol for evaluating the EORTC QLU-C10D in general population samples, as described. Using this method, value sets have been estimated for 11 countries so far, with more in progress [14‐22]. This study aimed to apply this valuation method in a Japanese general population sample to produce Japan-specific utility weights and value set for the QLU-C10D, and to compare the Japanese value set to those from other countries.

A cross-sectional population-based survey was designed to collect QLU-C10D valuation data from a representative sample of the Japanese general population; the study protocol was approved by the Japanese National Institute of Public Health ethics committee (approval number NIPH-IBRA #12272). The methods were consistent with previous QLU-C10D valuation studies [18, 19, 21, 23‐28].

The survey was implemented by SurveyEngine, a company specialized in online choice experiments. SurveyEngine managed sample recruitment (via a Japanese online panel), survey administration, and data collection. SurveyEngine and its panel provider complied with the International Code on Market, Opinion and Social Research and Data Analytics [29]. The survey opened on 5th February 2021 and closed on 15th March 2021. Online panel members were eligible if they were aged ≥ 18 years and able to read and understand Japanese. Online panelists received an e-mail invitation to participate, including a hyperlink to the study and survey. Panel members who attempted to enter the survey via mobile phones were screened out as the discrete choice experiment (DCE) was too complex for a small screen. Consent was sought from the remainder, who were screened for quota sampling to ensure the age and sex distributions of the sample matched those of the Japanese general population (Table 1). Participants who consented and were within quota proceeded to further survey questions.

A target sample size of ≥ 2000 respondents was determined to provide acceptable precision for model parameter estimates, based on the MAUCa consortium’s extensive experience with DCE valuation surveys and the number of health state comparisons in the QLU-C10D DCE [31‐34]. This sample size was larger than most similar studies [35], and meets the various rules of thumb outlined by de Bekker-Grob et al. [36].

This study provides the Japanese value set for the EORTC QLU-C10D, endorsed by the EORTC Quality of Life Group. The largest utility weights were associated with decrements in physical functioning, role functioning, and pain. Intermediate utility weights were associated with decrements in social functioning and nausea, while the remaining symptoms and emotional functioning were associated with smaller utility decrements. Compared with the QLU-C10D value sets from other countries, the Japanese decrements in social functioning, fatigue, and appetite were the largest of the 12 countries where QLU-C10D value sets have been established. The level 4 decrements in role function and nausea were the second largest among these countries. Generally, the Japanese weights of symptom-related items were larger than the average of the 12 countries, except for pain, where it was among the smaller. In addition, the comparison based on 500 randomly generated health states revealed considerable heterogeneity among countries, reflecting variations in dimension-specific preference weights in country-specific value sets. Different dimensions may play different roles in different cultures, but the observed variations may also be due in part to linguistic non-equivalence between countries; irrespective, these justify the need for country-specific value sets.

The value of the worst health state was -0.221, which was lower than that seen in most other existing QLU-C10D country-specific value sets, excluding France. This is a surprising result compared to the Japanese EQ-5D-5L value set. The worst Japanese EQ-5D-5L index [55555] was − 0.025, [49] which is the highest value in the world. This may be due to a key difference in the valuation methodologies used to generate the two value sets; the EORTC QLU-C10D was created by DCE with the duration method while the EQ-5D-5L was performed by composite time trade-off (cTTO) by the in-person interview. According to the Japanese EQ-5D-5L value set, the Japanese are reluctant to trade health states with death, suggesting a strong risk-aversion to death. By contrast, the international comparison of the EORTC QLU-C10D value set suggests that the Japanese willingly trade life-years with their health state. It may be caused by reflection of the Japanese preference; good health states are more preferable to long life years, but death is less acceptable, compared with Western people. Of course, it is possible that methodological artifacts may have contributed to the inconsistency. One of these is the method of preference elicitation: the QLU-C10D DCE was conducted as a self-complete survey while the EQ-5D-5L was interviewer administered. Another is translation effects in the source instrument (QLQ-C30 and EQ-5D-5L) and/or the preference elicitation DCE questionnaire for the QLU-C10D versus the cTTO for the EQ-5D-5L that somehow differentially distorted the Japanese preference task of the QLU-C10D relative to that of the EQ-5D-5L.

EQ-5D-5L is now a standard instrument for utility assessment in Japan. However, in clinical trial settings, the collection of EQ-5D-5L is sometimes omitted, and some studies include only disease-specific HRQL instruments. The QLQ-C30 and FACT-G are frequently used, particularly in cancer contexts [50]. Before the QLU-C10D was created, data obtained using the QLQ-C30 could not be used directly to calculate the QALY. Therefore, when QLQ-C30 data were used for cost-effectiveness analysis, mapping from the QLQ-C30 to PBMs was sometimes used. Although a mapping algorithm from the QLQ-C30 to the EQ-5D-5L has been established in Japan [51] mapping is not necessarily recommended for estimating utility, as there is considerable uncertainty around such calculations particularly at the extremes of the utility scale. In the Japanese HTA guidelines, mapping is only allowed if utility data cannot be obtained by other methods. As the QLU-C10D is now an established PBM, its use is more acceptable than that of the mapping algorithm. Also, because the EQ-5D-5L is a generic PBM, the QLQ-C30 is likely to be more sensitive to changes and differences in the health states of patients with cancer, and may therefore capture the utility of patients with cancer more appropriately and calculate the cost per QALY more precisely. Finally, many existing clinical trials have collected QLQ-C30 data in Japan. Such accumulated data can now be converted to utilities using the scoring algorithm generated by our research, and thereby provide HRQL weighting for QALY calculation. Given these advantages the Japanese value set for the EORTC QLU-C10D has many benefits for academics and the Japanese HTA system.

This study has several strengths. The Japanese value set was established in a large-sample representative of age and sex, enhancing generalisability of results. Second, only one inconsistency was observed in all the weights (the second and the third level of the “Trouble Sleeping” dimension). This is the lowest number of inconsistencies yet for QLU-C10D valuation studies, suggesting the Japanese survey was of high quality. Moreover, as our survey was based on the standard international protocol of the MAUCa Consortium, it facilitated international comparison with other country-specific QLU-C10D value sets. This study also has some limitations. Some respondents may not have engaged as fully in the online choice task as in face-to-face surveys. Also, respondents were not selected by random sampling from the entire Japanese population but by quota sampling from an online panel. Some characteristics of the respondents were statistically different from the Japanese population norms (e.g., region and work); we adjusted for most of these using raking, a form of sample weighting that allows weighting by several variables simultaneously. Further, the survey was conducted during the COVID-19 pandemic which had substantial impact on life in Japan. Other authors have noted that the pandemic did not impact on the ability to conduct online surveys such as this one during the pandemic, and indeed greater use and development of online research occurred during the pandemic [52]. However, it is unknown whether there was an impact on health preferences during the pandemic for the health attributes assessed in our study in comparison to pre- and post-pandemic preferences. There is limited evidence about the impacts of the COVID-19 pandemic on how people value health, and the policy implications of any such effects are unclear [53].

This study employed data from approximately 2,500 Japanese general population respondents who completed a DCE task based on an international valuation protocol developed for the EORTC QLU-C10D by the MAUCa Consortium and the EORTC Quality of Life Group. This produced the EORTC-endorsed Japanese value set for the EORTC QLU-C10D, which has some distinguishing characteristics compared to existing country-specific QLU-C10D value sets. Fundamentally, this study promotes economic evaluations in Japan and the development of HTA systems that produce transparent, consistent and defensible decisions around health and healthcare.