Development of the Incontinence Utility Index: estimating population-based utilities associated with urinary problems from the Incontinence Quality of Life Questionnaire and Neurogenic Module

Jesús Cuervo, Nacho Castejón, Kristin M Khalaf, Catherine Waweru, Denise Globe, Donald L Patrick, Jesús Cuervo, Nacho Castejón, Kristin M Khalaf, Catherine Waweru, Denise Globe, Donald L Patrick

Abstract

Background: Generic utility instruments may not fully capture the impact and consequences of urinary problems. Condition-specific preference-based measures, developed from previously validated disease-specific patient-reported outcomes instruments, may add relevant information for economic evaluations. The aim of this study was to develop a condition-specific preference-based measure, the Incontinence Utility Index (IUI), for valuing health states associated with urinary problems.

Methods: A two-step process was implemented. First, an abbreviated health state classification system was developed from the Incontinence Quality of Life Questionnaire (I-QOL) and Neurogenic Module by applying Rasch modelling, classical psychometrical testing and expert criteria to data from two pivotal trials comprised of neurogenic detrusor overactivity (NDO) patients. Criterion, convergent validity and concordance with the original instrument was assessed in the abbreviated version. Then, a multi-attribute utility function (MAUF) was estimated from a representative sample of the UK non-institutionalized adult general population. Visual analogue and time-trade off (TTO) evaluations were applied in the elicitation process. Predictive validity of the MAUF was tested comparing estimated and direct utility scores.

Results: The abbreviated health state classification system generated from the NDO sample contained 5 attributes with 3 levels of response and had adequate psychometrical properties: significant differences in scores according to the reduction in the frequency of urinary incontinence episodes [UIE] (p < 0.001); Spearman correlation coefficient with number of daily UIE = -0.43; p < 0.01 and Intraclass Correlation Coefficient (ICC, 95% CI) with the original version = 0.90 (0.89-0.91; p < 0.001). Next, 442 participants were interviewed (398 cases were valid, generating 2,388 TTO evaluations) to estimate the social preferences for derived health states. Mean age was 44.75 years (interquartile range 33.5-55.5) and 60.1% were female. An overall algorithm for the IUI was estimated and transformed onto a dead = 0.00 and full health = 1.00 scale. Model fits were acceptable (R-squared = 0.923 and 0.978). Predictive validity was adequate: ICC (95% CI) = 0.928 (0.648-0.985) and Mean of Absolute Differences = 0.038.

Conclusions: The newly developed IUI is a preference-based measure for urinary problems related to NDO that provides general population-based utility scores with adequate predictive validity.

Trial registration: ClinicalTrials.gov: NCT00461292, NCT00311376.

Figures

Figure 1
Figure 1
Presentation diagram of the time trade-off technique. Life P= The most desirable health state/Full health/The best health state imaginable. Life A= A given health stated derived from the abbreviated health state classification system.

References

    1. Coyne KS, Sexton CC, Kopp ZS, Ebel-Bitoun C, Milsom I, Chapple C. The impact of overactive bladder on mental health, work productivity and health-related quality of life in the UK and Sweden: results from EpiLUTS. BJU Int. 2011;108:1459–1471. doi: 10.1111/j.1464-410X.2010.10013.x.
    1. Ganz ML, Smalarz AM, Krupski TL, Anger JT, Hu JC, Wittrup-Jensen KU, Pashos CL. Economic costs of overactive bladder in the United States. Urology. 2010;75:526–532. doi: 10.1016/j.urology.2009.06.096.
    1. Reeves P, Irwin D, Kelleher C, Milsom I, Kopp Z, Calvert N, Lloyd A. The current and future burden and cost of overactive bladder in five European countries. Eur Urol. 2006;50:1050–1057. doi: 10.1016/j.eururo.2006.04.018.
    1. Wu EQ, Birnbaum H, Marynchenko M, Mareva M, Williamson T, Mallett D. Employees with overactive bladder: work loss burden. J Occup Environ Med. 2005;47:439–446. doi: 10.1097/01.jom.0000161744.21780.c1.
    1. Abrams P, Artibani W, Cardozo L, Dmochowski R, van Kerrebroeck P, Sand P: Reviewing the ICS 2002 terminology report: the ongoing debate.Neurourol Urodyn 2009, 28:287.
    1. Schurch B, Denys P, Kozma CM, Reese PR, Slaton T, Barron R. Reliability and validity of the Incontinence Quality of Life questionnaire in patients with neurogenic urinary incontinence. Arch Phys Med Rehabil. 2007;88:646–652. doi: 10.1016/j.apmr.2007.02.009.
    1. Tapia CI, Khalaf K, Berenson K, Globe D, Chancellor M, Carr LK: Health-related quality of life and economic impact of urinary incontinence due to detrusor overactivity associated with a neurologic condition: a systematic review.Health Qual Life Outcomes 2013, 11:13. doi:10.1186/1477-7525-11-13. 13–11.
    1. The EuroQol Group EuroQol–a new facility for the measurement of health-related quality of life. Health Policy. 1990;16:199–208. doi: 10.1016/0168-8510(90)90421-9.
    1. Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35:1095–1108. doi: 10.1097/00005650-199711000-00002.
    1. Torrance GW, Feeny DH, Furlong WJ, Barr RD, Zhang Y, Wang Q. Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Med Care. 1996;34:702–722. doi: 10.1097/00005650-199607000-00004.
    1. Feeny D, Furlong W, Torrance GW, Goldsmith CH, Zhu Z, DePauw S, Denton M, Boyle M. Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Med Care. 2002;40:113–128. doi: 10.1097/00005650-200202000-00006.
    1. Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21:271–292. doi: 10.1016/S0167-6296(01)00130-8.
    1. 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;51:1115–1128. doi: 10.1016/S0895-4356(98)00103-6.
    1. Franks P, Hanmer J, Fryback DG. Relative disutilities of 47 risk factors and conditions assessed with seven preference-based health status measures in a national U.S. sample: toward consistency in cost-effectiveness analyses. Med Care. 2006;44:478–485. doi: 10.1097/01.mlr.0000207464.61661.05.
    1. O’Brien BJ, Spath M, Blackhouse G, Severens JL, Dorian P, Brazier J. A view from the bridge: agreement between the SF-6D utility algorithm and the Health Utilities Index. Health Econ. 2003;12:975–981. doi: 10.1002/hec.789.
    1. Conner-Spady B, Suarez-Almazor ME. Variation in the estimation of quality-adjusted life-years by different preference-based instruments. Med Care. 2003;41:791–801. doi: 10.1097/00005650-200307000-00003.
    1. Pinto AM, Kuppermann M, Nakagawa S, Vittinghoff E, Wing RR, Kusek JW, Herman WH, Subak LL. Comparison and correlates of three preference-based health-related quality-of-life measures among overweight and obese women with urinary incontinence. Qual Life Res. 2011;20:1655–1662. doi: 10.1007/s11136-011-9896-5.
    1. McDonough CM, Tosteson AN. Measuring preferences for cost-utility analysis: how choice of method may influence decision-making. Pharmacoeconomics. 2007;25:93–106. doi: 10.2165/00019053-200725020-00003.
    1. Papaioannou D, Brazier J, Parry G. How valid and responsive are generic health status measures, such as EQ-5D and SF-36, in schizophrenia? a systematic review. Value Health. 2011;14:907–920. doi: 10.1016/j.jval.2011.04.006.
    1. Haywood KL, Garratt AM, Lall R, Smith JF, Lamb SE. EuroQol EQ-5D and condition-specific measures of health outcome in women with urinary incontinence: reliability, validity and responsiveness. Qual Life Res. 2008;17:475–483. doi: 10.1007/s11136-008-9311-z.
    1. Oh SJ, Ku JH. Is a generic quality of life instrument helpful for evaluating women with urinary incontinence? Qual Life Res. 2006;15:493–501. doi: 10.1007/s11136-005-2487-6.
    1. Finkelstein MM, Skelly J, Kaczorowski J, Swanson G: Incontinence Quality of Life Instrument in a survey of primary care physicians.J Fam Pract 2002, 51:952.
    1. Davis S, Wailoo A: A review of the psychometric performance of the EQ-5D in people with urinary incontinence.Health Qual Life Outcomes 2013, 11:20.
    1. Coyne K, Revicki D, Hunt T, Corey R, Stewart W, Bentkover J, Kurth H, Abrams P. Psychometric validation of an overactive bladder symptom and health-related quality of life questionnaire: the OAB-q. Qual Life Res. 2002;11:563–574. doi: 10.1023/A:1016370925601.
    1. Kelleher CJ, Cardozo LD, Khullar V, Salvatore S. A new questionnaire to assess the quality of life of urinary incontinent women. Br J Obstet Gynaecol. 1997;104:1374–1379. doi: 10.1111/j.1471-0528.1997.tb11006.x.
    1. Wagner TH, Patrick DL, Bavendam TG, Martin ML, Buesching DP. Quality of life of persons with urinary incontinence: development of a new measure. Urology. 1996;47:67–71. doi: 10.1016/S0090-4295(99)80384-7.
    1. Patrick DL, Martin ML, Bushnell DM, Yalcin I, Wagner TH, Buesching DP. Quality of life of women with urinary incontinence: further development of the incontinence quality of life instrument (I-QOL) Urology. 1999;53:71–76. doi: 10.1016/S0090-4295(98)00454-3.
    1. Patrick DL, Khalaf KM, Dmochowski R, Kowalski JW, Globe DR. Psychometric performance of the incontinence quality-of-life questionnaire among patients with overactive bladder and urinary incontinence. Clin Ther. 2013;35:836–845. doi: 10.1016/j.clinthera.2013.04.013.
    1. Reese PR, Pleil AM, Okano GJ, Kelleher CJ. Multinational study of reliability and validity of the King’s Health Questionnaire in patients with overactive bladder. Qual Life Res. 2003;12:427–442. doi: 10.1023/A:1023422208910.
    1. Yang Y, Brazier J, Tsuchiya A, Coyne K. Estimating a preference-based single index from the Overactive Bladder Questionnaire. Value Health. 2009;12:159–166. doi: 10.1111/j.1524-4733.2008.00413.x.
    1. Brazier J, Czoski-Murray C, Roberts J, Brown M, Symonds T, Kelleher C. Estimation of a preference-based index from a condition-specific measure: the King’s Health Questionnaire. Med Decis Making. 2008;28:113–126. doi: 10.1177/0272989X07301820.
    1. Kay S, Tolley K, Colayco D, Khalaf K, Anderson P, Globe D. Mapping EQ-5D Utility Scores from the Incontinence Quality of Life Questionnaire among Patients with Neurogenic and Idiopathic Overactive Bladder. Value Health. 2013;16:394–402. doi: 10.1016/j.jval.2012.12.005.
    1. Torrance GW, Furlong W, Feeny D, Boyle M. Multi-attribute preference functions. health utilities index. Pharmacoeconomics. 1995;7:503–520. doi: 10.2165/00019053-199507060-00005.
    1. Brazier J, 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. 2012;16:1–114. doi: 10.3310/hta16320.
    1. Wright B, Masters G. Rating Scale Analysis. Rasch Measurement. Chicago: MESA Press; 1982.
    1. Young T, Yang Y, Brazier JE, Tsuchiya A, Coyne K. The first stage of developing preference-based measures: constructing a health-state classification using Rasch analysis. Qual Life Res. 2009;18:253–265. doi: 10.1007/s11136-008-9428-0.
    1. Mulhern B, Smith SC, Rowen D, Brazier JE, Knapp M, Lamping DL, Loftus V, Young TA, Howard RJ, Banerjee S. Improving the measurement of QALYs in dementia: developing patient- and carer-reported health state classification systems using Rasch analysis. Value Health. 2012;15:323–333. doi: 10.1016/j.jval.2011.09.006.
    1. Linacre JM. Detecting multidimensionality: which residual data-type works best? J Outcome Meas. 1998;2:266–283.
    1. Cruz F, Herschorn S, Aliotta P, Brin M, Thompson C, Lam W, Daniell G, Heesakkers J, Haag-Molkenteller C. Efficacy and safety of onabotulinumtoxinA in patients with urinary incontinence due to neurogenic detrusor overactivity: a randomised, double-blind, placebo-controlled trial. Eur Urol. 2011;60:742–750. doi: 10.1016/j.eururo.2011.07.002.
    1. Ginsberg D, Gousse A, Keppenne V, Sievert KD, Thompson C, Lam W, Brin MF, Jenkins B, Haag-Molkenteller C. Phase 3 efficacy and tolerability study of onabotulinumtoxinA for urinary incontinence from neurogenic detrusor overactivity. J Urol. 2012;187:2131–2139. doi: 10.1016/j.juro.2012.01.125.
    1. Torrance G. Social preferences for health states: an empirical evaluation of three measurement techniques. Socioecon Plann Sci. 1976;10:128–136. doi: 10.1016/0038-0121(76)90036-7.
    1. Montejo AL, Correas-Lauffer J, Maurino J, Villa G, Rebollo P, Diez T, Cordero L. Estimation of a multiattribute utility function for the Spanish version of the TooL questionnaire. Value Health. 2011;14:564–570. doi: 10.1016/j.jval.2010.11.016.
    1. The Market Research Society M: MRS Code of Conduct. 2010. .
    1. European Pharmaceutical Market Research Association E: EphMRA Code of Conduct. 2014. .
    1. The Association for Qualitative Research A: Qualitative research recruitment guidelines. 2002. .
    1. Stiggelbout AM, Eijkemans MJ, Kiebert GM, Kievit J, Leer JW, De Haes HJ. The ‘utility’ of the visual analog scale in medical decision making and technology assessment. is it an alternative to the time trade-off? Int J Technol Assess Health Care. 1996;12:291–298. doi: 10.1017/S0266462300009648.
    1. Deyo RA, Diehr P, Patrick DL. Reproducibility and responsiveness of health status measures. statistics and strategies for evaluation. Control Clin Trials. 1991;12:142S–158S. doi: 10.1016/S0197-2456(05)80019-4.
    1. Linacre J. Winsteps® Rasch measurement computer program. Beaverton, Oregon: ; 2012.
    1. StataCorp . Stata Statistical Software: Release 10. College Station, Tx: StataCorp LP; 2007.
    1. National Institute for Health and Clinical Excellence (NICE) Guide to the methods of technology appraisal. 2013. Process and methods guides. London: NICE; 2013.
    1. Young TA, Yang Y, Brazier JE, Tsuchiya A. The use of rasch analysis in reducing a large condition-specific instrument for preference valuation: the case of moving from AQLQ to AQL-5D. Med Decis Making. 2011;31:195–210. doi: 10.1177/0272989X10364846.
    1. Hatoum HT, Brazier JE, Akhras KS. Comparison of the HUI3 with the SF-36 preference based SF-6D in a clinical trial setting. Value Health. 2004;7:602–609. doi: 10.1111/j.1524-4733.2004.75011.x.
    1. Mulhern B, Meadows K: The construct validity and responsiveness of the EQ-5D, SF-6D and diabetes health profile-18 in type 2 diabetes.Health Qual Life Outcomes 2014, 12:42.
    1. Brazier JE, Kolotkin RL, Crosby RD, Williams GR. Estimating a preference-based single index for the Impact of Weight on Quality of Life-Lite (IWQOL-Lite) instrument from the SF-6D. Value Health. 2004;7:490–498. doi: 10.1111/j.1524-4733.2004.74012.x.
    1. 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:e31115.
    1. van Nooten FE, Koolman X, Brouwer WB. The influence of subjective life expectancy on health state valuations using a 10 year TTO. Health Econ. 2009;18:549–558. doi: 10.1002/hec.1385.
    1. Dolan P, Roberts J. To what extent can we explain time trade-off values from other information about respondents? Soc Sci Med. 2002;54:919–929. doi: 10.1016/S0277-9536(01)00066-1.

Source: PubMed

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