Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
PharmacoEconomics - Open

Open Access 02-05-2024 | Lung Cancer | Original Research Article

Cancer-Specific Health Utilities: Evaluation of Core Measurement Properties of the EORTC QLU-C10D in Lung Cancer Patients—Data from Four Multicentre LUX-Lung Trials, Applying Six Country Tariffs

Authors: Micha J. Pilz, Simone Seyringer, Imad Al-Naesan, Madeleine T. King, Andrew Bottomley, Richard Norman, Lisa Schlosser, Tobias Hell, Eva Maria Gamper, the EORTC Quality of Life Group

Published in: PharmacoEconomics - Open

Login to get access

Abstract

Background

Cost-utility analysis generally requires valid preference-based measures (PBMs) to assess the utility of patient health. While generic PBMs are widely used, disease-specific PBMs may capture additional aspects of health relevant for certain patient populations. This study investigates the construct and concurrent criterion validity of the cancer-specific European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility-Core 10 dimensions (QLU-C10D) in non-small-cell lung cancer patients.

Methods

We retrospectively analysed data from four multicentre LUX-Lung trials, all of which had administered the EORTC Quality of Life Questionnaire (QLQ-C30) and the EQ-5D-3L. We applied six country-specific value sets (Australia, Canada, Italy, the Netherlands, Poland, and the United Kingdom) to both instruments. Criterion validity was assessed via correlations between the instruments’ utility scores. Correlations of divergent and convergent domains and Bland-Altman plots investigated construct validity. Floor and ceiling effects were assessed.

Results

The comparison of the EORTC QLU-C10D and EQ-5D-3L produced homogenous results for five of the six country tariffs. High correlations of utilities (r > 0.7) were found for all country tariffs except for the Netherlands. Moderate to high correlations of converging domain pairs (r from 0.472 to 0.718) were found with few exceptions, such as the Social Functioning–Usual Activities domain pair (max. r = 0.376). For all but the Dutch tariff, the EORTC QLU-C10D produced consistently lower utility values compared to the EQ-5D-3L (x̄ difference from − 0.082 to 0.033). Floor and ceiling effects were consistently lower for the EORTC QLU-C10D (max. 4.67% for utilities).

Conclusions

The six country tariffs showed good psychometric properties for the EORTC QLU-C10D in lung cancer patients. Criterion and construct validity was established. The QLU-C10D showed superior measurement precision towards the upper and lower end of the scale compared to the EQ-5D-3L, which is important when cost-utility analysis seeks to measure health change across the severity spectrum.
Appendix
Available only for authorised users
Literature
1.
2.
3.
Migliorino MR, Santo A, Romano G, Cortinovis D, Galetta D, Alabiso O, Cartenì G, Vari S, Fasola G, Pazzola A, Giuffrida D, Zaniboni A, Caprioli A, Longo F, Acciai V, de Marinis F. Economic burden of patients affected by non-small cell lung cancer (NSCLC): the LIFE study. J Cancer Res Clin Oncol. 2017;143(5):783–91.PubMedCrossRef
4.
Gridelli C, Rossi A, Carbone DP, Guarize J, Karachaliou N, Mok T, Petrella F, Spaggiari L, Rosell R. Non-small-cell lung cancer. Nat Rev Dis Primers. 2015;21(1):15009.CrossRef
5.
6.
Eberhardt WE, De Ruysscher D, Weder W, Le Péchoux C, De Leyn P, Hoffmann H, Westeel V, Stahel R, Felip E, Peters S, Panel Members. 2nd ESMO Consensus Conference in Lung Cancer: locally advanced stage III non-small-cell lung cancer. Ann Oncol. 2015;26(8):1573-1588.
7.
Al Dayel F. EGFR mutation testing in non-small cell lung cancer (NSCLC). J Infect Public Health. 2012;5 Supplement:S31-34.CrossRef
8.
Zhang YL, Yuan JQ, Wang KF, Fu XH, Han XR, Threapleton D, Yang ZY, Mao C, Tang JL. The prevalence of EGFR mutation in patients with non-small cell lung cancer: a systematic review and meta-analysis. Oncotarget. 2016;48(7):78985–93.CrossRef
9.
Aguiar F, Fernandes G, Queiroga H, Machado JC, Cirnes L, Souto Moura C, Hespanhol V. Overall survival analysis and characterization of an EGFR mutated non-small cell lung cancer (NSCLC) population. Arch Bronconeumol. 2018;54(1):10–7.PubMedCrossRef
10.
Hsu WH, Yang JC, Mok TS, Loong HH. Overview of current systemic management of EGFR-mutant NSCLC. Ann Oncol. 2018;1(Suppl. 1):i3–9.CrossRef
11.
Ding PN, Lord SJ, Gebski V, Links M, Bray V, Gralla RJ, Yang JC, Lee CK. Risk of treatment-related toxicities from EGFR tyrosine kinase inhibitors: a meta-analysis of clinical trials of gefitinib, erlotinib, and afatinib in advanced EGFR-mutated non-small cell lung cancer. J Thorac Oncol. 2017;12(4):633–43.PubMedCrossRef
12.
Normando SR, Cruz FM, Del Giglio A. Cumulative meta-analysis of epidermal growth factor receptor-tyrosine kinase inhibitors as first-line therapy in metastatic non-small-cell lung cancer. Anticancer Drugs. 2015;26(9):995–1003.PubMedCrossRef
13.
Zhang Y, Sheng J, Yang Y, Fang W, Kang S, He Y, Hong S, Zhan J, Zhao Y, Xue C, Ma Y, Zhou T, Ma S, Gao F, Qin T, Hu Z, Tian Y, Hou X, Huang Y, Zhou N, Zhao H, Zhang L. Optimized selection of three major EGFR-TKIs in advanced EGFR-positive non-small cell lung cancer: a network meta-analysis. Oncotarget. 2016;12(7):20093–108.CrossRef
14.
Sequist LV, Yang JC, Yamamoto N, O’Byrne K, Hirsh V, Mok T, Geater SL, Orlov S, Tsai CM, Boyer M, Su WC, Bennouna J, Kato T, Gorbunova V, Lee KH, Shah R, Massey D, Zazulina V, Shahidi M, Schuler M. hase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J Clin Oncol. 2013;31(27):3327–34.PubMedCrossRef
15.
Wu YL, Zhou C, Hu CP, Feng J, Lu S, Huang Y, Li W, Hou M, Shi JH, Lee KY, Xu CR, Massey D, Kim M, Shi Y, Geater SL. Afatinib versus cisplatin plus gemcitabine for first-line treatment of Asian patients with advanced non-small-cell lung cancer harbouring EGFR mutations (LUX-Lung 6): an open-label, randomised phase 3 trial. Lancet Oncol. 2014;15(2):213–22.PubMedCrossRef
16.
Yang JC, Wu YL, Schuler M, Sebastian M, Popat S, Yamamoto N, Zhou C, Hu CP, O’Byrne K, Feng J, Lu S, Huang Y, Geater SL, Lee KY, Tsai CM, Gorbunova V, Hirsh V, Bennouna J, Orlov S, Mok T, Boyer M, Su WC, Lee KH, Kato T, Massey D, Shahidi M, Zazulina V, Sequist LV. Afatinib versus cisplatin-based chemotherapy for EGFR mutation-positive lung adenocarcinoma (LUX-Lung 3 and LUX-Lung 6): analysis of overall survival data from two randomised, phase 3 trials. Lancet Oncol. 2015;16(2):141–51.PubMedCrossRef
17.
Griebsch I, Palmer M, Fayers PM, Ellis S. Is progression-free survival associated with a better health-related quality of life in patients with lung cancer? Evidence from two randomised trials with afatinib. BMJ Open. 2014;4(10):1-9.
18.
Pratt-Chapman MBA. Patient-reported outcomes in health economic decision-making: a changing landscape in oncology. Recent Results Cancer Res. 2019;213:67–83.PubMedCrossRef
19.
Trippoli S, Vaiani M, Lucioni C, Messori A. Quality of life and utility in patients with non-small cell lung cancer. Quality-of-life Study Group of the Master 2 Project in Pharmacoeconomics. Pharmacoeconomics. 2001;19(8):855–63.PubMedCrossRef
20.
McDonough CMTA. Measuring preferences for cost-utility analysis: how choice of method may influence decision-making. Pharmacoeconomics. 2007;25(2):93–106.PubMedPubMedCentralCrossRef
21.
Brazier J, Usherwood T, Harper R, Thomas K. Deriving a preference-based single index from the UK SF-36 Health Survey. J Clin Epidemiol. 1998;51(11):1115–28.PubMedCrossRef
22.
King MT, Costa DS, Aaronson NK, Brazier JE, Cella DF, Fayers PM, Grimison P, Janda M, Kemmler G, Norman R, Pickard AS, Rowen D, Velikova G, Young TA, Viney R. QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30. Qual Life Res. 2016;25(3):625–36.PubMedCrossRef
23.
Roudijk B, Donders ART, Stalmeier PFM. Setting dead at zero: applying scale properties to the QALY model. Med Decis Making. 2016;38(6):627–34.CrossRef
24.
Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001;33(5):337–43.PubMedCrossRef
25.
Feeny D, Furlong W, Boyle M, Torrance GW. Multi-attribute health status classification systems. Health Utilities Index. Pharmacoeconomics. 1995;7(6):490–502.PubMedCrossRef
26.
Rowen D, Brazier J, Ara R, Azzabi ZI. The role of condition-specific preference-based measures in health technology assessment. Pharmacoeconomics. 2017;35(Suppl. 1):33–41.PubMedCrossRef
27.
Drummond M, Sculpher M. Common methodological flaws in economic evaluations. Med Care. 2005;43(Suppl. 7):5–14.PubMed
28.
Goodwin EGC. A systematic review of the literature on the development of condition-specific preference-Based Measures of Health. Appl Health Econ Health Policy. 2016;14(2):161–83.PubMedCrossRef
29.
Langworth L, Yang Y, Young T, Mulhern B, Hernández Alava M, Mukuria C, Rowen D, Tosh J, Tsuchiya A, Evans P, Devianee Keetharuth A, Brazier J. Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: a systematic review, statistical modelling and survey. Health Technol Assess. 2014;9(18):1–224.
30.
Versteegh MM, Leunis A, Uyl-de Groot CA, Stolk EA. Condition-specific preference-based measures: benefit or burden? Value Health. 2012;15(3):504–13.PubMedCrossRef
31.
Neumann PJ, Goldie SJ, Weinstein MC. Preference-based measures in economic evaluation in health care. Annu Rev Public Health. 2000;21:587–611.PubMedCrossRef
32.
Brazier JE, Rowen D, Mavranezouli I, Tsuchiya A, Young T, Yang Y, Barkham M, Ibbotson R. Developing and testing methods for deriving preference-based measures of health from condition-specific measures (and other patient-based measures of outcome). Health Technol Assess. 2016;16(32):1–114.
33.
Richardson J, Iezzi A, Khan MA, Chen G, Maxwell A. Measuring the sensitivity and construct validity of 6 utility instruments in 7 disease areas. Med Decis Making. 2016;36(2):147–95.PubMedCrossRef
34.
Pettitt D, Raza S, Naughton B, Roscoe A, Ramakrishnan A, Ali A, Davies B, Dopson S, Hollander G, Smith J, Brindley D. The limitations of QALY: a literature review. J Stem Cell Res Ther. 2016;6(4):1-7.
35.
Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, Bouter LM, de Vet HC. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42.PubMedCrossRef
36.
Miller VA, Hirsh V, Cadranel J, Chen YM, Park K, Kim SW, Zhou C, Su WC, Wang M, Sun Y, Heo DS, Crino L, Tan EH, Chao TY, Shahidi M, Cong XJ, Lorence RM, Yang JC. Afatinib versus placebo for patients with advanced, metastatic non-small-cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial. Lancet Oncol. 2013;13(5):528–38.CrossRef
37.
Sequist LV, Yang JC, Yamamoto N, O’Byrne K, Hirsh V, Mok T, Geater SL, Orlov S, Tsai CM, Boyer M, Su WC, Bennouna J, Kato T, Gorbunova V, Lee KH, Shah R, Massey D, Zazulina V, Shahidi M, Schuler M. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J Clin Oncol. 2013;31(27):3327–34.PubMedCrossRef
38.
Schuler M, Yang JC, Park K, Kim JH, Bennouna J, Chen YM, Chouaid C, De Marinis F, Feng JF, Grossi F, Kim DW, Liu X, Lu S, Strausz J, Vinnyk Y, Wiewrodt R, Zhou C, Wang B, Chand VK, Planchard D, LUX-Lung 5 Investigators. Afatinib beyond progression in patients with non-small-cell lung cancer following chemotherapy, erlotinib/gefitinib and afatinib: phase III randomized LUX-Lung 5 trial. Ann Oncol. 2016;27(3):417–23.PubMedCrossRef
39.
Soria JC, Felip E, Cobo M, Lu S, Syrigos K, Lee KH, Göker E, Georgoulias V, Li W, Isla D, Guclu SZ, Morabito A, Min YJ, Ardizzoni A, Gadgeel SM, Wang B, Chand VK, Goss GD, LUX-Lung 8 Investigators. Afatinib versus erlotinib as second-line treatment of patients with advanced squamous cell carcinoma of the lung (LUX-Lung 8): an open-label randomised controlled phase 3 trial. Lancet Oncol. 2015;16(8):897–907.PubMedCrossRef
40.
Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, Filiberti A, Flechtner H, Fleishman SB, de Haes JC, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;85(5):365–76.PubMedCrossRef
41.
42.
Finch AP, Gamper E, Norman R, Viney R, Holzner B, King M, Kemmler G, EORTC Quality of Life Group. Estimation of an EORTC QLU-C10 value set for Spain using a discrete choice experiment. Pharmacoeconomics. 2021;39(9):1085–98.PubMedPubMedCentralCrossRef
43.
Gamper EM, King MT, Norman R, Efficace F, Cottone F, Holzner B, Kemmler G. EORTC QLU-C10D value sets for Austria, Italy, and Poland. Qual Life Res. 2020;29(9):2485–95.PubMedPubMedCentralCrossRef
44.
Jansen F, Verdonck-de Leeuw IM, Gamper E, Norman R, Holzner B, King M, Kemmler G. Dutch utility weights for the EORTC cancer-specific utility instrument: the Dutch EORTC QLU-C10D. Qual Life Res. 2021;30(7):2009–19.PubMedPubMedCentralCrossRef
45.
Kemmler G, Gamper E, Nerich V, Norman R, Viney R, Holzner B, King M. German value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30. Qual Life Res. 2019;28(12):3197–211.PubMedPubMedCentralCrossRef
46.
King MT, Viney R, Simon Pickard A, Rowen D, Aaronson NK, Brazier JE, Cella D, Costa DSJ, Fayers PM, Kemmler G, McTaggart-Cowen H, Mercieca-Bebber R, Peacock S, Street DJ, Young TA, Norman R. Australian Utility Weights for the EORTC QLU-C10D, a multi-attribute utility instrument derived from the cancer-specific quality of life questionnaire, EORTC QLQ-C30. Pharmacoeconomics. 2018;36(2):225–38.PubMedCrossRef
47.
McTaggart-Cowan H, King MT, Norman R, Costa DSJ, Pickard AS, Regier DA, Viney R, Peacock SJ. The EORTC QLU-C10D: The Canadian Valuation Study and Algorithm to Derive Cancer-Specific Utilities From the EORTC QLQ-C30. MDM Policy Pract. 2019;4(1):1-11.
48.
Nerich V, Gamper EM, Norman R, King M, Holzner B, Viney R, Kemmler G. French value-set of the QLU-C10D, a cancer-specific utility measure derived from the QLQ-C30. Appl Health Econ Health Policy. 2021;19(2):191–202.PubMedCrossRef
49.
Norman R, Mercieca-Bebber R, Rowen D, Brazier JE, Cella D, Pickard AS, Street DJ, Viney R, Revicki D, King MT, European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group and the MAUCa Consortium. U.K. utility weights for the EORTC QLU-C10D. Health Econ. 2019;28(12):1385–401.PubMedCrossRef
50.
Revicki DA, King MT, Viney R, Pickard AS, Mercieca-Bebber R, Shaw JW, Müller F, Norman R. United States utility algorithm for the EORTC QLU-C10D, a multiattribute utility instrument based on a cancer-specific quality-of-life instrument. Med Decis Making. 2021;41(4):485–501.PubMedCrossRef
51.
EuroQol Group. EuroQol–a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(2):199–208.
52.
53.
R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, Vienna, Austria; 2021.
54.
Viney R, Norman R, King MT, Cronin P, Street DJ, Knox S, Ratcliffe J. Time trade-off derived EQ-5D weights for Australia. Value Health. 2011;14(6):928–36.PubMedCrossRef
55.
Bansback N, Tsuchiya A, Brazier J, Anis A. Canadian valuation of EQ-5D health states: preliminary value set and considerations for future valuation studies. PLoS ONE. 2012;7(2): e31115.PubMedPubMedCentralCrossRef
56.
Scalone L, Cortesi PA, Ciampichini R, Belisari A, D’Angiolella LS, Cesana G, Mantovani LG. Italian population-based values of EQ-5D health states. Value Health. 2013;16(5):814–22.PubMedCrossRef
57.
Lamers LM, McDonnell J, Stalmeier PF, Krabbe PF, Busschbach JJ. The Dutch tariff: results and arguments for an effective design for national EQ-5D valuation studies. Health Econ. 2006;15(10):1121–31.PubMedCrossRef
58.
Golicki D, Jakubczyk M, Niewada M, Wrona W, Busschbach JJ. Valuation of EQ-5D health states in Poland: first TTO-based social value set in Central and Eastern Europe. Value Health. 2010;13(2):289–97.PubMedCrossRef
59.
60.
61.
Devlin NJBR. EQ-5D and the EuroQol group: past, present and future. Appl Health Econ Health Policy. 2017;12(2):127–37.CrossRef
62.
63.
64.
Bulamu NB, Vissapragada R, Chen G, Ratcliffe J, Mudge LA, Smithers BM, Isenring EA, Smith L, Jamieson GG, Watson DI. Responsiveness and convergent validity of QLU-C10D and EQ-5D-3L in assessing short-term quality of life following esophagectomy. Health Qual Life Outcomes. 2021;19(1):233.PubMedPubMedCentralCrossRef
65.
Gamper EM, Cottone F, Sommer K, Norman R, King M, Breccia M, Caocci G, Patriarca A, Palumbo GA, Stauder R, Niscola P, Platzbecker U, Caers J, Vignetti M, Efficace F. The EORTC QLU-C10D was more efficient in detecting clinical known group differences in myelodysplastic syndromes than the EQ-5D-3L. J Clin Epidemiol. 2021;137:31–44.PubMedCrossRef
66.
Klapproth CP, Fischer F, Rose M, Karsten MM. Health state utility differed systematically in breast cancer patients between the EORTC QLU-C10D and the PROMIS Preference Score. J Clin Epidemiol. 2022;152:101–9.PubMedCrossRef
67.
Pan CW, He JY, Zhu YB, Zhao CH, Luo N, Wang P. Comparison of EQ-5D-5L and EORTC QLU-C10D utilities in gastric cancer patients. Eur J Health Econ. 2022;(9):885-893.
68.
Shaw JW, Bennett B, Trigg A, DeRosa M, Taylor F, Kiff C, Ntais D, Noon K, King MT, Cocks K. A comparison of generic and condition-specific preference-based measures using data from nivolumab trials: EQ-5D-3L, mapping to the EQ-5D-5L, and European Organisation for research and treatment of cancer quality of life utility measure-core 10 dimensions. Value Health. 2021;24(11):1651–9.PubMedCrossRef
69.
Soare IA, Leeuwenkamp O, Longworth L. Estimation of Health-Related Utilities for 177Lu-DOTATATE in GEP-NET Patients Using Utilities Mapped from EORTC QLQ-C30 to EQ-5D-3L and QLU-C10D Utilities. PharmacoEconomics Open. 2021;5(4):715–25.PubMedPubMedCentralCrossRef
70.
Jansen F, Coupé VMH, Eerenstein SEJ, Cnossen IC, van Uden-Kraan CF, de Bree R, Doornaert P, Halmos GB, Hardillo JAU, van Hinte G, Honings J, Leemans CR, Verdonck-de Leeuw IM. Cost-utility and cost-effectiveness of a guided self-help head and neck exercise program for patients treated with total laryngectomy: results of a multi-center randomized controlled trial. Oral Oncol. 2021;117:1-9.
71.
Pickard AS, Neary MP, Cella D. Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer. Health Qual Life Outcomes. 2007;21(5):70.CrossRef
72.
Cieza A, Ewert T, Ustün TB, Chatterji S, Kostanjsek N, Stucki G. Development of ICF Core Sets for patients with chronic conditions. J Rehabil Med. 2004;44 Suppl.:9–11.
73.
Pilz MJ, Rothmund M, Lidington E, Piccinin C, Arraras JI, Groenvold M, Holzner B, van Leeuwen M, Petersen MA, Schmidt H, Young T, Giesinger JM, EORTC Quality of Life Group. Content comparison of the EORTC CAT Core, SF-36, FACT-G, and PROMIS role and social functioning measures based on the International Classification of Functioning, Disability and Health. Psycho-oncology, 2023;32(9):1372–84. https://​doi.​org/​10.​1002/​pon.​6188
74.
Vanier A, Oort FJ, McClimans L, Ow N, Gulek BG, Böhnke JR, Sprangers M, Sébille V, Mayo N, Response Shift - in Sync Working Group. Response shift in patient-reported outcomes: definition, theory, and a revised model. Qual Life Res. 2021;30(12):3309–22.PubMedPubMedCentralCrossRef
75.
Pilz MJ, Seyringer S, Hallsson LR, Bottomley A, Jansen F, King MT, Norman R, Rutten MJ, Leeuw IMV, Siersema PD, Gamper EM. The EORTC QLU-C10D is a valid cancer-specific preference-based measure for cost-utility and health technology assessment in the Netherlands. Eur J Health Econ. 2024. https://​doi.​org/​10.​1007/​s10198-024-01670-6
76.
Koller M, Müller K, Nolte S, Schmidt H, Harvey C, Mölle U, Boehm A, Engeler D, Metzger J, Sztankay M, Holzner B, Groenvold M, Kuliś D, Bottomley A, EORTC Quality of Life Group. Investigating the response scale of the EORTC QLQ-C30 in German cancer patients and a population survey. Health Qual Life Outcomes. 2021;19(9):235.PubMedPubMedCentralCrossRef
77.
Scott NW, Fayers PM, Bottomley A, Aaronson NK, de Graeff A, Groenvold M, Koller M, Petersen MA, Sprangers MA, EORTC and the Quality of Life Cross-Cultural Meta-Analysis Group. Comparing translations of the EORTC QLQ-C30 using differential item functioning analyses. Qual Life Res. 2006;15(6):1103–15.PubMedCrossRef
78.
Sonntag M, König HH, Konnopka A. The estimation of utility weights in cost-utility analysis for mental disorders: a systematic review. Pharmacoeconomics. 2013;31(12):1131–54.PubMedCrossRef
79.
Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, Bonsel G, Badia X. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.PubMedPubMedCentralCrossRef
80.
Marra CA, Woolcott JC, Kopec JA, Shojania K, Offer R, Brazier JE, Esdaile JM, Anis AH. A comparison of generic, indirect utility measures (the HUI2, HUI3, SF-6D, and the EQ-5D) and disease-specific instruments (the RAQoL and the HAQ) in rheumatoid arthritis. Soc Sci Med. 2005;60(7):1571–82.PubMedCrossRef
81.
82.
83.
Metadata
Title
Cancer-Specific Health Utilities: Evaluation of Core Measurement Properties of the EORTC QLU-C10D in Lung Cancer Patients—Data from Four Multicentre LUX-Lung Trials, Applying Six Country Tariffs
Authors
Micha J. Pilz
Simone Seyringer
Imad Al-Naesan
Madeleine T. King
Andrew Bottomley
Richard Norman
Lisa Schlosser
Tobias Hell
Eva Maria Gamper
the EORTC Quality of Life Group
Publication date
02-05-2024
Publisher
Springer International Publishing
Published in
PharmacoEconomics - Open
Print ISSN: 2509-4262
Electronic ISSN: 2509-4254
DOI
https://doi.org/10.1007/s41669-024-00484-9