70 Discussion of resultsOur analyses revealed that the decrease in generic HRQoL <strong>for</strong> a clinically significantdeterioration in vision, as measured by BCVA, was small. The predicted decreases <strong>for</strong> a fiveletterdrop in BCVA in the better-seeing eye were 0.0058, 0.245 and 0.546 <strong>for</strong> the SF-6D, PCSand MCS respectively (all p < 0.0001). We also had CS data from a subset of participants andthere<strong>for</strong>e were able to estimate changes in HRQoL <strong>for</strong> both BCVA and CS and relate these tothe findings observed in the TAP trial. However, when interpreting these associations, it is veryimportant to recognise that the predicted HRQoL changes do not describe the aver<strong>age</strong> benefit ina representative sample of patients, given that a proportion (47% of the VPDT cohort) will havehad treatment to the first affected eye and had a normally sighted fellow eye.The gradient of change in visual functioning measured by the NEIVFQ instrument was notinfluenced by the duration of follow-up. Models predicting distance, near and compositeNEIVFQ scores from BCVA were quadratic. The predicted decreases <strong>for</strong> a five-letter drop inBCVA in the better-seeing eye were 5.08, 5.48 and 3.90 <strong>for</strong> the distance and near domains and<strong>for</strong> the composite instrument respectively. The Submacular Surgery Trials Research Groupquantified the association between BCVA and NEIVFQ scores using the change in BCVA. 65 Theobserved change in NEIVFQ composite score per 100 letters was 18 points, very much less thanour estimate of 55 letters. Their lower estimate may be due, in part, to the assumption of a linearrelationship or to their much smaller sample size. The VPDT cohort study has enabled moreprecise quantification of these relationships, particularly those between BCVA and HRQoL.These relationships constitute an important source of robust in<strong>for</strong>mation <strong>for</strong> modelling the costeffectivenessof current and future interventions <strong>for</strong> nAMD.The shape of the relationship between visual function and HRQoL had also not been previouslyinvestigated. Even in a study as large at the VPDT cohort study, the analyses had limited powerto detect departures from a linear relationship. The tendency <strong>for</strong> some functions to plateau withsevere loss of visual function is clearly not a floor effect and supports the prior hypothesis thatHRQoL decreases less steeply when visual function is very poor. Our failure to observe a plateauwhen vision is excellent may have arisen because few patients achieved BCVA < 0.0 logMAR(6/6 Snellen) in the best-seeing eye, either because patients could not achieve better acuity orbecause they were not encour<strong>age</strong>d to do so. However, this explanation is not consistent withthe observation that visually demanding tasks such as fluent reading and driving ability can beper<strong>for</strong>med with BCVA = 0.3 logMAR (6/12 Snellen) in the best-seeing eye.Previous researchers have investigated which of BCVA or CS in the better-seeing eye is thestronger predictor of HRQoL. Based on a multivariable regression, Bansback et al. 66 reported thatCS was a better predictor of HRQoL than BCVA and, using the Health Utilities Index mark 3 67(HUI3), estimated a change in utility of 0.14 per log unit. In contrast, we found that, in this largedata set, BCVA was a consistently stronger predictor of HRQoL than CS.Patients’ adaptation to loss of visual function was investigated by Brown. 31 In a sample of 237patients with mixed causes of visual loss there was a tendency <strong>for</strong> those who had had visual loss<strong>for</strong> longer (over a time frame of 5 years) to report better HRQoL. 31 In a sample of 72 patientswho had had AMD <strong>for</strong> up to 20 years (35 <strong>for</strong> < 1 year, 19 <strong>for</strong> 1–3 years and 18 <strong>for</strong> 3–20 years),patients with durations of visual loss ≥ 1 year had better HRQoL than those with durations< 1 year (p < 0.005). 18 This association was potentially affected by the small number of patientswith very longstanding disease. Also, these studies did not assess HRQoL longitudinally in thesame patients, so the observed finding is less confidently attributed to the duration of disease andit is not clear whether or not the differences in HRQoL with duration of visual loss were adjusted
DOI: 10.3310/hta16060Health Technology Assessment 2012; Vol. 16: No. 671<strong>for</strong> the extent of visual loss, that is BCVA. However, our data were obtained over relatively shortdurations of follow-up and it is possible that adaptation occurs only over longer periods of time.Narrative reviews have concluded that utility decreases with deteriorating visual function, 16,17,68but few studies have systematically quantified the relationships between these measures <strong>for</strong>patients with nAMD (Table 22). 18,64 Our estimate of ~0.1 change in utility per 100 lettersis consistent with utility estimates based on the SF-6D or the EQ-5D. It is lower than theestimates based on the HUI3 64 (see below) and those based on preferences elicited directlyfrom patients. 18,65 The distributions of preferences elicited directly from AMD patients weremarkedly skewed in contrast to scores on preference-based utility measures derived fromsocietal valuations (acknowledging that this contrast is both between source of valuation, i.e.patients vs society, and between measure, i.e. directly elicited preference by time trade-off vspreference-based utility measure). This observation is consistent with some patients refusing totrade years of life <strong>for</strong> improved vision, 18,31 and raises concern about the validity of the method.More fundamentally, as generic measures of HRQoL are used to make broad comparisonsacross interventions in different disease areas, it is more appropriate to value health states withpreference weights from the general population rather than specific groups. 13Is the Short Form questionnaire-6 Dimensions an appropriatemeasure of generic health-<strong>related</strong> quality of life?A generic HRQoL measure chosen <strong>for</strong> comparing health gain across disease areas should have adescriptive system that covers all the important dimensions of health. The SF-6D, like the EQ-5D,has a descriptive system that purports to meet the World Health Organization definition ofhealth: ‘complete physical, mental and social well-being and not merely the absence of disease orinfirmity’. 69 Utilities measured using the SF-6D are similar to those measured using the EQ-5D. 70By contrast, the HUI3 is based on a narrower, ‘within the skin’ definition of health focusingon impairment and not on the social context of the impairment. 71 Thus, the HUI3 consists ofitems that tap self-reported functioning more directly than the EQ-5D and SF-6D. The HUI3 is,there<strong>for</strong>e, likely to be ‘more sensitive’ 71 to visual loss than the SF-6D. 64 However, the HUI3 hasbeen criticised <strong>for</strong> using this relatively narrow description of health. 9TABLE 22 Estimates of utility from different studiesStudyInstrument/methodusedSource of utilityvaluesVisual acuity and utility observationsBrown et al.,2000 18 Time trade-off Patients 20/20 to 20/400 (0.0–1.3 logMAR or 70letters ≈ utility 0.89 to 0.52 ≈ 0.47 differenceEspallargues et al., EQ-5D General population ≤ 0.3 to > 2.0 logMAR or 120 letters ≈ utility2005 64 0.75–0.63 ≈ 0.12 differenceEspallargues et al., SF-6D General population ≤ 0.3 to > 2.0 logMAR or 120 letters ≈ utility2005 64 0.70–0.63 ≈ 0.07 differenceEspallargues et al., HUI3 General population ≤ 0.3 to > 2.0 logMAR or 120 letters ≈ utility2005 64 0.50–0.10 ≈ 0.40 differenceEspallargues et al., Visual analogue2005 64 scalePatients≤ 0.3 to > 2.0 logMAR or 120 letters ≈ utility0.71–0.59 ≈ 0.12 differenceTime trade-off Patients ≤ 0.3 to > 2.0 logMAR or 120 letters ≈ utilityEspallargues et al.,0.222005 64 0.73–0.47 ≈ 0.26 differenceVPDT cohort study SF-6D General population Regression coefficient, 0.0012 per letter 0.120.1 logMAR, i.e. five letters.Approximate utilitychange per 100 letters0.670.100.060.330.10© Queen’s Printer and Controller of HMSO 2012. This work was produced by Reeves et al. under the terms of a commissioning contract issued by theSecretary of State <strong>for</strong> Health.
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FeedbackThe HTA programme and the a