References
- Bray F, Ferlay J, Soerjomataram I. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.
- Feng RM, Zong YN, Cao SM, et al. Current cancer situation in China: good or bad news from the 2018 global cancer statistics? Cancer Commun (Lond). 2019;39:22.
- Wu C, Li M, Meng H, et al. Analysis of status and countermeasures of cancer incidence and mortality in China. Sci China Life Sci. 2019;62:640–647.
- Longworth L, Rowen D. Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value Health. 2013;16:202–210.
- Wang L, Shi JF, Zhu J, et al. Health-related quality of life and utility scores of patients with breast neoplasms in China: a multicenter cross-sectional survey. Breast. 2018;39:53–62.
- Acaster S, Pinder B, Mukuria C, et al. Mapping the EQ-5D index from the cystic fibrosis questionnaire-revised using multiple modelling approaches. Health Qual Life Outcomes. 2015;13:33.
- Shi JF, Kang DJ, Qi SZ, et al. Impact of genital warts on health related quality of life in men and women in mainland China: a multicenter hospital-based cross-sectional study. BMC Public Health. 2012;12:153.
- Dakin H, Gray A, Murray D. Mapping analyses to estimate EQ-5D utilities and responses based on Oxford knee score. Qual Life Res. 2013;22:683–694.
- Murasawa H, Sugiyama T, Matsuoka Y, et al. Health utility and health-related quality of life of Japanese prostate cancer patients according to progression status measured using EQ-5D-5L and FACT-P. Qual Life Res. 2019;28:2383–2391.
- Wu EQ, Mulani P, Farrell MH, et al. Mapping FACT-P and EORTC QLQ-C30 to patient health status measured by EQ-5D in metastatic hormone-refractory prostate cancer patients. Value Health. 2007;10:408–414.
- Liu GG, Wu H, Li M, et al. Chinese time trade-off values for EQ-5D health states. Value Health. 2014;17:597–604.
- Diels J, Hamberg P, Ford D, et al. Mapping FACT-P to EQ-5D in a large cross-sectional study of metastatic castration-resistant prostate cancer patients. Qual Life Res. 2015;24:591–598.
- Fang P, Tan KS, Troxel AB, et al. High body mass index is associated with worse quality of life in breast cancer patients receiving radiotherapy. Breast Cancer Res Treat. 2013;141:125–133.
- Meregaglia M, Borsoi L, Cairns J, et al. Mapping health-related quality of life scores from FACT-G, FAACT, and FACIT-F onto preference-based EQ-5D-5L utilities in non-small cell lung cancer cachexia. Eur J Health Econ. 2019;20:181–193.
- Askew RL, Swartz RJ, Xing Y, et al. Mapping FACT-melanoma quality-of-life scores to EQ-5D health utility weights. Value Health. 2011;14:900–906.
- Gray LA, Wailoo AJ, Hernandez Alava M. Mapping the FACT-B instrument to EQ-5D-3L in patients with breast cancer using adjusted limited dependent variable mixture models versus response mapping. Value Health. 2018;21:1399–1405.
- Teckle P, McTaggart-Cowan H, Van der Hoek K, et al. Mapping the FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D. Health Qual Life Outcomes. 2013;11:203.
- Cheung YB, Thumboo J, Gao F, et al. Mapping the English and Chinese versions of the functional assessment of cancer therapy-general to the EQ-5D utility index. Value Health. 2009;12:371–376.
- Young TA, Mukuria C, Rowen D, et al. Mapping functions in health-related quality of life: mapping from two cancer-specific health-related quality-of-life instruments to EQ-5D-3L. Med Decis Making. 2015;35:912–926.
- Longworth L, Yang Y, Young T, et al. 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;18:1–224.
- Nahvijou A, Safari H, Yousefi M, et al. Mapping the cancer-specific FACT-B onto the generic SF-6Dv2. Breast Cancer. 2021;28:130–136.
- Teckle P, Peacock S, McTaggart-Cowan H, et al. The ability of cancer-specific and generic preference-based instruments to discriminate across clinical and self-reported measures of cancer severities. Health Qual Life Outcomes. 2011;9:106.
- Norman R, Cronin P, Viney R, et al. International comparisons in valuing EQ-5D health states: a review and analysis. Value Health. 2009;12:1194–1200.
- Fayers PM, Hays RD. Should linking replace regression when mapping from profile-based measures to preference-based measures? Value Health. 2014;17:261–265.
- Brazier JE, Yang Y, Tsuchiya A, et al. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ. 2010;11:215–225.
- Thompson NR, Lapin BR, Katzan IL. Mapping PROMIS global health items to EuroQol (EQ-5D) utility scores using linear and equipercentile equating. Pharmacoeconomics. 2017;35:1167–1176.
- Lamu AN. Does linear equating improve prediction in mapping? Crosswalking macnew onto EQ-5D-5L value sets. Eur J Health Econ. 2020;21:903–915.
- Chen H, Li N, Ren J, et al. Participation and yield of a population-based colorectal cancer screening programme in China. Gut. 2019;68:1450–1457.
- Shi J-F, Huang H-Y, Guo L-W, et al. Quality-of-life and health utility scores for common cancers in China: a multicentre cross-sectional survey. Lancet. 2016;388.
- Versteegh MM, Rowen D, Brazier JE, et al. Mapping onto Eq-5 D for patients in poor health. Health Qual Life Outcomes. 2010;8:141.
- Luo N, Liu G, Li M, et al. Estimating an EQ-5D-5L value set for China. Value Health. 2017;20:662–669.
- Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol group. Ann Med. 2001;33:337–343.
- Tsuchiya A, Ikeda S, Ikegami N, et al. Estimating an EQ-5D population value set: the case of Japan. Health Econ. 2002;11:341–353.
- Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35:1095–1108.
- 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;5:70.
- Cheung YB, Tan HX, Luo N, et al. Mapping the Shah-modified Barthel index to the health utility index mark III by the mean rank method. Qual Life Res. 2019;28:3177–3185.
- Cheung YB, Luo N, Ng R, et al. Mapping the functional assessment of cancer therapy-breast (FACT-B) to the 5-level EuroQoL group’s 5-dimension questionnaire (EQ-5D-5L) utility index in a multi-ethnic Asian population. Health Qual Life Outcomes. 2014;12:180.
- Huang IC, Frangakis C, Atkinson MJ, et al. Addressing ceiling effects in health status measures: a comparison of techniques applied to measures for people with HIV disease. Health Serv Res. 2008;43:327–339.
- Hays RD, Revicki DA, Feeny D, et al. Using linear equating to map PROMIS(®) global health items and the PROMIS-29 V2.0 profile measure to the health utilities index mark 3. PharmacoEconomics. 2016;34:1015–1022.
- Walters SJ, Brazier JE. Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Qual Life Res. 2005;14:1523–1532.
- Hu X, Jing M, Zhang M, et al. Responsiveness and minimal clinically important difference of the EQ-5D-5L in cervical intraepithelial neoplasia: a longitudinal study. Health Qual Life Outcomes. 2020;18:324.
- Wailoo AJ, Hernandez-Alava M, Manca A, et al. Mapping to estimate health-state utility from non-preference-based outcome measures: an ISPOR good practices for outcomes research task force report. Value Health. 2017;20:18–27.
- Yang Q, Yu XX, Zhang W, et al. Mapping function from FACT-B to EQ-5D-5 L using multiple modelling approaches: data from breast cancer patients in China. Health Qual Life Outcomes. 2019;17:153.
- Ameri H, Yousefi M, Yaseri M, et al. Mapping the cancer-specific QLQ-C30 onto the generic EQ-5D-5L and SF-6D in colorectal cancer patients. Expert Rev Pharmacoecon Outcomes Res. 2019;19:89–96.
- Wang Y, Shi J, Du L, et al. Health-related quality of life in patients with esophageal cancer or precancerous lesions assessed by EQ-5D: a multicenter cross-sectional study. Thorac Cancer. 2020;11:1076–1089.
- Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15:155–163.
- Sullivan PW, Ghushchyan V. Mapping the EQ-5D index from the SF-12: US general population preferences in a nationally representative sample. Med Decis Making. 2006;26:401–409.
- Ara R, Brazier J. Deriving an algorithm to convert the eight mean SF-36 dimension scores into a mean EQ-5D preference-based score from published studies (where patient level data are not available). Value Health. 2008;11:1131–1143.
- Pickard AS, Ray S, Ganguli A, et al. Comparison of FACT- and EQ-5D-based utility scores in cancer. Value Health. 2012;15:305–311.
- Zhuo L, Xu L, Ye J, et al. Time trade-off value set for EQ-5D-3L based on a nationally representative Chinese population survey. Value Health. 2018;21:1330–1337.
- Jin X, Liu GG, Luo N, et al. Is bad living better than good death? Impact of demographic and cultural factors on health state preference. Qual Life Res. 2016;25:979–986.
- Brazier J, Roberts J, Tsuchiya A, et al. A comparison of the EQ-5D and SF-6D across seven patient groups. Health Econ. 2004;13:873–884.
- Orgeta V, Edwards RT, Hounsome B, et al. The use of the EQ-5D as a measure of health-related quality of life in people with dementia and their carers. Qual Life Res. 2015;24:315–324.
- Thompson AJ, Turner AJ. A comparison of the EQ-5D-3L and EQ-5D-5L. Pharmacoeconomics. 2020;38:575–591.
- Zhu J, Yan XX, Liu CC, et al. Comparing EQ-5D-3L and EQ-5D-5L performance in common cancers: suggestions for instrument choosing. Qual Life Res. 2021;30:841–854.
- Oppe M, Devlin NJ, van Hout B, et al. A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol. Value Health. 2014;17:445–453.