1
|
Wang Y, Shi J, Du L, Huang H, Wang L, Zhu J, Li H, Bai Y, Liao X, Mao A, Liu G, Ren J, Sun X, Gong J, Zhou Q, Mai L, Zhu L, Xing X, Liu Y, Ren Y, Song B, Lan L, Zhou J, Lou P, Sun X, Qi X, Wu S, Wei W, Zhang K, Dai M, Chen W, He J. 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. [PMID: 32130756 PMCID: PMC7113059 DOI: 10.1111/1759-7714.13368] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 02/09/2020] [Accepted: 02/10/2020] [Indexed: 12/24/2022] Open
Abstract
Background We aimed to obtain a set of health state utility scores of patients with esophageal cancer (EC) and precancerous lesions in China, and to explore the influencing factors of health‐related quality of life (HRQoL). Methods A hospital‐based multicenter cross‐sectional study was conducted. From 2013 to 2014, patients with EC or precancerous lesions were enrolled. HRQoL was assessed using a European quality of life‐5 dimension (EQ‐5D‐3L) instrument. Multivariable linear regression analysis was performed to explore the influencing factors of the EQ‐5D utility scores. Results A total of 2090 EC patients and 156 precancer patients were included in the study. The dimension of pain/discomfort had the highest rate of self‐reported problems, 60.5% in EC and 51.3% in precancer patients. The mean visual analog scale (VAS) score for EC and precancer patients were 68.4 ± 0.7 and 64.5 ± 3.1, respectively. The EQ‐5D utility scores for EC and precancer patients were estimated as 0.748 ± 0.009 and 0.852 ± 0.022, and the scores of EC at stage I, stage II, stage III, and stage IV were 0.693 ± 0.031, 0.747 ± 0.014, 0.762 ± 0.015, and 0.750 ± 0.023, respectively. According to the multivariable analyses, the factors of region, occupation, household income in 2012, health care insurance type, pathological type, type of therapy, and time points of the survey were statistically associated with the EQ‐5D utility scores of EC patients. Conclusions There were remarkable decrements of utility scores among esophageal cancer patients, compared with precancer patients. The specific utility scores of EC would support further cost‐utility analysis in populations in China.
Collapse
Affiliation(s)
- Youqing Wang
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences/Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences/Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, China
| | - Jufang Shi
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingbin Du
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences/Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences/Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, China
| | - Huiyao Huang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Le Wang
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences/Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences/Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, China
| | - Juan Zhu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Huizhang Li
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences/Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences/Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yana Bai
- Institute of Epidemiology and Health Statistics, Lanzhou University, Lanzhou, China
| | - Xianzhen Liao
- Hunan Office for Cancer Control and Research, Hunan Provincial Cancer Hospital, Changsha, China
| | - Ayan Mao
- Public Health Information Research Office, Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing, China
| | - Guoxiang Liu
- Department of Health Economics, School of Health Management, Harbin Medical University, Harbin, China
| | - Jiansong Ren
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaojie Sun
- Center for Health Management and Policy, Key Lab of Health Economics and Policy, Shandong University, Jinan, China
| | - Jiyong Gong
- Science and Education Department of Public Health Division, Shandong Tumor Hospital, Jinan, China
| | - Qi Zhou
- Chongqing Office for Cancer Control and Research, Chongqing Cancer Hospital, Chongqing, China
| | - Ling Mai
- Department of Institute of Tumor Research, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Lin Zhu
- Teaching and Research Department, Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, China
| | - Xiaojing Xing
- Liaoning Office for Cancer Control and Research, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - Yuqin Liu
- Cancer Epidemiology Research Center, Gansu Provincial Cancer Hospital, Lanzhou, China
| | - Ying Ren
- Urban Office of Cancer Early Detection and Treatment, Tieling Central Hospital, Tieling, China
| | - Bingbing Song
- Heilongjiang Office for Cancer Control and Research, Affiliated Cancer Hospital of Harbin Medical University, Harbin, China
| | - Li Lan
- Institute of Chronic Disease Prevention and Control, Harbin Center for Disease Control and Prevention, Harbin, China
| | - Jinyi Zhou
- Institute of Chronic Non-communicable Diseases Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Peian Lou
- Department of Control and Prevention of Chronic Non-Communicable Diseases, Xuzhou Center for Disease Control and Prevention, Xuzhou, China
| | - Xiaohua Sun
- Ningbo Clinical Cancer Prevention Guidance Center, Ningbo No.2 Hospital, Ningbo, China
| | - Xiao Qi
- Department of Occupational Medicine, Tangshan People's Hospital, Tangshan, China
| | - Shouling Wu
- Health Department of Kailuan Group, Kailuan General Hospital, Tangshan, China
| | - Wenqiang Wei
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kai Zhang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Min Dai
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wanqing Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie He
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| |
Collapse
|
2
|
Mukuria C, Rowen D, Harnan S, Rawdin A, Wong R, Ara R, Brazier J. An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2019; 17:295-313. [PMID: 30945127 DOI: 10.1007/s40258-019-00467-6] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
BACKGROUND Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values (HSUVs) from data obtained from another health-related quality of life (HRQoL) measure. There have been several methodological developments in this area since a previous review up to 2007. OBJECTIVE To provide an updated review of all mapping studies that map from HRQoL measures to target generic preference-based measures (EQ-5D measures, SF-6D, HUI measures, QWB, AQoL measures, 15D/16D/17D, CHU-9D) published from January 2007 to October 2018. DATA SOURCES A systematic review of English language articles using a variety of approaches: searching electronic and utilities databases, citation searching, targeted journal and website searches. STUDY SELECTION Full papers of studies that mapped from one health measure to a target preference-based measure using formal statistical regression techniques. DATA EXTRACTION Undertaken by four authors using predefined data fields including measures, data used, econometric models and assessment of predictive ability. RESULTS There were 180 papers with 233 mapping functions in total. Mapping functions were generated to obtain EQ-5D-3L/EQ-5D-5L-EQ-5D-Y (n = 147), SF-6D (n = 45), AQoL-4D/AQoL-8D (n = 12), HUI2/HUI3 (n = 13), 15D (n = 8) CHU-9D (n = 4) and QWB-SA (n = 4) HSUVs. A large number of different regression methods were used with ordinary least squares (OLS) still being the most common approach (used ≥ 75% times within each preference-based measure). The majority of studies assessed the predictive ability of the mapping functions using mean absolute or root mean squared errors (n = 192, 82%), but this was lower when considering errors across different categories of severity (n = 92, 39%) and plots of predictions (n = 120, 52%). CONCLUSIONS The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions.
Collapse
Affiliation(s)
- Clara Mukuria
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
| | - Donna Rowen
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Sue Harnan
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Andrew Rawdin
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Ruth Wong
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Roberta Ara
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - John Brazier
- School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| |
Collapse
|
3
|
Dakin H, Abel L, Burns R, Yang Y. Review and critical appraisal of studies mapping from quality of life or clinical measures to EQ-5D: an online database and application of the MAPS statement. Health Qual Life Outcomes 2018; 16:31. [PMID: 29433510 PMCID: PMC5810002 DOI: 10.1186/s12955-018-0857-3] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Accepted: 01/29/2018] [Indexed: 11/17/2022] Open
Abstract
Background The Health Economics Research Centre (HERC) Database of Mapping Studies was established in 2013, based on a systematic review of studies developing mapping algorithms predicting EQ-5D. The Mapping onto Preference-based measures reporting Standards (MAPS) statement was published in 2015 to improve reporting of mapping studies. We aimed to update the systematic review and assess the extent to which recently-published studies mapping condition-specific quality of life or clinical measures to the EQ-5D follow the guidelines published in the MAPS Reporting Statement. Methods A published systematic review was updated using the original inclusion criteria to include studies published by December 2016. We included studies reporting novel algorithms mapping from any clinical measure or patient-reported quality of life measure to either the EQ-5D-3L or EQ-5D-5L. Titles and abstracts of all identified studies and the full text of papers published in 2016 were assessed against the MAPS checklist. Results The systematic review identified 144 mapping studies reporting 190 algorithms mapping from 110 different source instruments to EQ-5D. Of the 17 studies published in 2016, nine (53%) had titles that followed the MAPS statement guidance, although only two (12%) had abstracts that fully addressed all MAPS items. When the full text of these papers was assessed against the complete MAPS checklist, only two studies (12%) were found to fulfil or partly fulfil all criteria. Of the 141 papers (across all years) that included abstracts, the items on the MAPS statement checklist that were fulfilled by the largest number of studies comprised having a structured abstract (95%) and describing target instruments (91%) and source instruments (88%). Conclusions The number of published mapping studies continues to increase. Our updated database provides a convenient way to identify mapping studies for use in cost-utility analysis. Most recent studies do not fully address all items on the MAPS checklist. Electronic supplementary material The online version of this article (10.1186/s12955-018-0857-3) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Helen Dakin
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK.
| | - Lucy Abel
- Nuffield Department of Primary Care Health Science, University of Oxford, Oxford, UK
| | - Richéal Burns
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Yaling Yang
- Nuffield Department of Primary Care Health Science, University of Oxford, Oxford, UK
| |
Collapse
|
4
|
Angulo J, Calderín M, Fernández Y, González M, Gómez E, Herreros M, Peñasco P, Zapatero M, Dorado J. Comparative study of the B-SAQ, OAB-V8 and OAB-V3 questionnaires as screening tools for overactive bladders in clinical practice. Actas Urol Esp 2017; 41:383-390. [PMID: 28268078 DOI: 10.1016/j.acuro.2016.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Revised: 12/10/2016] [Accepted: 12/12/2016] [Indexed: 10/20/2022]
Abstract
OBJECTIVE To compare the capacity shown by 3 self-assessment questionnaires validated in Spanish (B-SAQ, OAB-V8 and OAB-V3) for the screening of patients with overactive bladder (OAB) in clinical practice. MATERIAL AND METHOD A noninterventional observational study was conducted of men and women older than 30 years evaluated in primary care consultations. The clinical diagnosis of OAB was conducted through a case history review, physical examination, urine analysis, ultrasonography and voiding diary. The presence of coping strategies and discomfort was investigated. The differential diagnosis was established in patients with symptoms not due to OAB. We assessed the correlation between the clinical tests and diagnosis (kappa <.4 poor; .4-.6 moderate; >.6 good; >.8 excellent) and ROC curves to define the capacity to screen the assessed questionnaires. RESULTS A total of 411 patients were investigated. OAB was detected in 207 (50.4%) patients, other causes for the lower urinary tract symptoms were detected in 63 (15.3%), and 141 (34.3%) patients had no diagnosis. The voiding diary suggested OAB in 197 (47.9%) patients. The correlation between the clinical diagnosis and the diagnosis based on the voiding diary was .702. The correlation between the clinical diagnosis and B-SAQ, OAB-V8 and OAB-V3 was .59, .673 and .732, respectively. The area under the curve (AUC) was .799 for B-SAQ; .837 for OAB-V8 and .867 for OAB-V3 (OAB-V3 vs. OAB-V8, P=.02; OAB-V3 vs. B-SAQ, P<.0001). The AUC for the voiding diary was .852 (OAB-V3 vs. diary, P=.47). CONCLUSIONS OAB-V3 is a simple questionnaire with excellent performance for screening OAB in a specific population and that is superior to the OAB-V8 and B-SAQ. The accuracy of the voiding diary for the same indication is equivalent to that of the OAB-V3 in our setting.
Collapse
|
5
|
Peral C, Sánchez-Ballester F, García-Mediero JM, Ramos J, Rejas J. Cost-effectiveness analysis of fesoterodine flexible dose in newly diagnosed patients with overactive bladder in routine clinical practice in Spain. CLINICOECONOMICS AND OUTCOMES RESEARCH 2016; 8:541-550. [PMID: 27713646 PMCID: PMC5044989 DOI: 10.2147/ceor.s111646] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Objective To carry out cost-effectiveness analysis from the Spanish National Health System perspective, of treating overactive bladder (OAB), in newly diagnosed patients with two flexible doses of fesoterodine in routine clinical practice. Patients and methods Economic evaluation of flexible-dose fesoterodine in newly diagnosed patients, including two treatment groups: standard escalating from 4 to 8 mg or fast escalating to 8 mg. Costs were estimated from health care resources utilization related to OAB, and were expressed in 2015 Euros. Quality-adjusted life-years (QALYs) were obtained from overactive bladder questionnaire-short form. Univariate and probabilistic sensitivity analyses were carried out. Results Three hundred and ninety symptomatic OAB patients treated with fesoterodine and newly diagnosed (141 in fast escalating group and 249 in standard escalating) were analyzed. Adjusted health care total costs were not statistically different; difference −€4.1 (confidence interval: −153.3; 25.1) P=0.842. QALYs were higher in fast escalating to high dose vs standard escalating group, resulting in a cost of −€16,020/QALY gained for fast escalating vs standard escalating group. Conclusion When the cost-effectiveness threshold is set at a maximum value of €30,000/QALY gained, fesoterodine fast escalating group was cost-effective vs standard escalating group 67.6% of the time. The treatment with fesoterodine, in female patients newly diagnosed, fast escalating to 8 mg was a cost-effective option relative to escalating traditionally from 4 to 8 mg, in the management of OAB in routine clinical practice, from the Spanish National Health System perspective.
Collapse
Affiliation(s)
- Carmen Peral
- Health Economics & Outcomes Research Department, Pfizer, Alcobendas (Madrid)
| | | | | | - Jaime Ramos
- Health Economics & Outcomes Research Department, Pfizer, Alcobendas (Madrid)
| | - Javier Rejas
- Health Economics & Outcomes Research Department, Pfizer, Alcobendas (Madrid)
| |
Collapse
|