Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer

A Simon Pickard, Maureen P Neary, David Cella, A Simon Pickard, Maureen P Neary, David Cella

Abstract

Background: Understanding what constitutes an important difference on a HRQL measure is critical to its interpretation. The aim of this study was to provide a range of estimates of minimally important differences (MIDs) in EQ-5D scores in cancer and to determine if estimates are comparable in lung cancer.

Methods: A retrospective analysis was conducted on cross-sectional data collected from 534 cancer patients, 50 of whom were lung cancer patients. A range of minimally important differences (MIDs) in EQ-5D index-based utility (UK and US) scores and VAS scores were estimated using both anchor-based and distribution-based (1/2 standard deviation and standard error of the measure) approaches. Groups were anchored using Eastern Cooperative Oncology Group performance status (PS) ratings and FACT-G total score-based quintiles.

Results: For UK-utility scores, MID estimates based on PS ranged from 0.10 to 0.12 both for all cancers and for lung cancer subgroup. Using FACT-G quintiles, MIDs were 0.09 to 0.10 for all cancers, and 0.07 to 0.08 for lung cancer. For US-utility scores, MIDs ranged from 0.07 to 0.09 grouped by PS for all cancers and for lung cancer; when based on FACT-G quintiles, MIDs were 0.06 to 0.07 in all cancers and 0.05 to 0.06 in lung cancer. MIDs for VAS scores were similar for lung and all cancers, ranging from 8 to 12 (PS) and 7 to 10 (FACT-G quintiles).

Discussion: Important differences in EQ-5D utility and VAS scores were similar for all cancers and lung cancer, with the lower end of the range of estimates closer to the MID, i.e. 0.08 for UK-index scores, 0.06 for US-index scores, and 7 [corrected] for VAS scores.

References

    1. 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;85:365–376. doi: 10.1093/jnci/85.5.365.
    1. de Haes J, Curran D, Young T, Bottomley A, Flechtner H, Aaronson N, Blazeby J, Bjordal K, Brandberg Y, Greimel E, Maher J, Sprangers M, Cull A. Quality of life evaluation in oncological clinical trials - the EORTC model. The EORTC Quality of Life Study Group. Eur J Cancer. 2000;36:821–825. doi: 10.1016/S0959-8049(00)00007-1.
    1. Webster K, Cella D, Yost K. The Functional Assessment of Chronic Illness Therapy (FACIT) Measurement System: properties, applications, and interpretation. Health Qual Life Outcomes. 2003;1:79. doi: 10.1186/1477-7525-1-79.
    1. Pickard AS, Wilke CT, Lin HW, Lloyd A. Health Utilities Using the EQ-5D in Studies of Cancer. PharmacoEconomics. 2007;25:365–384. doi: 10.2165/00019053-200725050-00002.
    1. Revicki DA, Cella D, Hays RD, Sloan JA, Lenderking WR, Aaronson NK. Responsiveness and minimal important differences for patient reported outcomes. Health Qual Life Outcomes. 2006;4:70. doi: 10.1186/1477-7525-4-70.
    1. Lydick E, Epstein RS. Interpretation of quality of life changes. Qual Life Res. 1993;2:221–226. doi: 10.1007/BF00435226.
    1. Norman GR, Stratford P, Regehr G. Methodological problems in the retrospective computation of responsiveness to change: the lesson of Cronbach. J Clin Epidemiol. 1997;50:869–879. doi: 10.1016/S0895-4356(97)00097-8.
    1. Norman GR, Sridhar FG, Guyatt GH, Walter SD. Relation of distribution- and anchor-based approaches in interpretation of changes in health-related quality of life. Med Care. 2001;39:1039–1047. doi: 10.1097/00005650-200110000-00002.
    1. de Vet HC, Terwee CB, Ostelo RW, Beckerman H, Knol DL, Bouter LM. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Outcomes. 2006;4:54. doi: 10.1186/1477-7525-4-54.
    1. Eton DT, Cella D, Yost KJ, Yount SE, Peterman AH, Neuberg DS, Sledge GW, Wood WC. A combination of distribution- and anchor-based approaches determined minimally important differences (MIDs) for four endpoints in a breast cancer scale. J Clin Epidemiol. 2004;57:898–910. doi: 10.1016/j.jclinepi.2004.01.012.
    1. Wyrwich KW, Tierney WM, Babu AN, Kroenke K, Wolinsky FD. A comparison of clinically important differences in health-related quality of life for patients with chronic lung disease, asthma, or heart disease. Health Serv Res. 2005;40:577–591. doi: 10.1111/j.1475-6773.2005.0l374.x.
    1. Metz SM, Wyrwich KW, Babu AN, Kroenke K, Tierney WM, Wolinsky FD. A comparison of traditional and Rasch cut points for assessing clinically important change in health-related quality of life among patients with asthma. Qual Life Res. 2006;15:1639–1649. doi: 10.1007/s11136-006-0036-6.
    1. Steel JL, Eton DT, Cella D, Olek MC, Carr BI. Clinically meaningful changes in health-related quality of life in patients diagnosed with hepatobiliary carcinoma. Ann Oncol. 2006;17:304–312. doi: 10.1093/annonc/mdj072.
    1. Cella D, Eton DT, Fairclough DL, Bonomi P, Heyes AE, Silberman C, Wolf MK, Johnson DH. What is a clinically meaningful change on the Functional Assessment of Cancer Therapy-Lung (FACT-L) Questionnaire? Results from Eastern Cooperative Oncology Group (ECOG) Study 5592. J Clin Epidemiol. 2002;55:285–295. doi: 10.1016/S0895-4356(01)00477-2.
    1. Cella D, Eton DT, Lai JS, Peterman AH, Merkel DE. Combining anchor and distribution-based methods to derive minimal clinically important differences on the Functional Assessment of Cancer Therapy (FACT) anemia and fatigue scales. J Pain Symptom Manage. 2002;24:547–561. doi: 10.1016/S0885-3924(02)00529-8.
    1. 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. doi: 10.1007/s11136-004-7713-0.
    1. Pickard AS, De Leon MC, Kohlmann T, Cella D, Rosenbloom S. Psychometric Comparison of the Standard EQ-5D to a 5 Level Version in Cancer Patients. Med Care. 2007;45:259–263. doi: 10.1097/01.mlr.0000254515.63841.81.
    1. Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001;33:337–343.
    1. Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35:1095–1108. doi: 10.1097/00005650-199711000-00002.
    1. Shaw JW, Johnson JA, Coons SJ. US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Med Care. 2005;43:203–220. doi: 10.1097/00005650-200503000-00003.
    1. Oken MM, Creech RH, Tormey DC, Horton J, Davis TE, McFadden ET, Carbone PP. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982;5:649–655. doi: 10.1097/00000421-198212000-00014.
    1. Wyrwich KW, Nienaber NA, Tierney WM, Wolinsky FD. Linking clinical relevance and statistical significance in evaluating intra-individual changes in health-related quality of life. Med Care. 1999;37:469–478. doi: 10.1097/00005650-199905000-00006.
    1. Gunter OH, Matschinger H, Konig HH. An item response theory model analysis to evaluate the dimensionality of the EQ-5D across six countries (abstract #1656). Accessed October 30, 2006
    1. Johnson JA, Pickard AS. Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta, Canada. Med Care. 2000;38:115–121. doi: 10.1097/00005650-200001000-00013.

Source: PubMed

Sponsorit ja yhteistyökumppanit

Sairaudet

Huumeiden interventiot

3
Tilaa