Measuring Responsiveness in Quality of Life ResearchAuthor(s): Kevin W. SmithSource: Quality of Life Research, Vol. 9, No. 3, Abstracts: 7th Annual Conference of theInternational Society for Quality of Life Research (ISOQOL) (Mar., 2000), p. 266Published by: SpringerStable URL: http://www.jstor.org/stable/4036180 .Accessed: 23/08/2011 11:16

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Abstract 1222

RESPONSIVENESS OF THE NATIONAL EYE INSTITUTE VISUAL FUNCTION QUESTIONNAIRE TO CHANGES IN VISION Paivi H. Miskala, Center for the Submacular Surgery Trials (SST) Patient Centered Outcomes Subcommittee and SST Pilot Study Investigators, The Johns Hopkins University, Baltimore, MD

The National Eye Institute Visual Function Questionnaire (NEI-VFQ) mea- sures vision-related quality of life in patients with vision impairment. Al- though the NEI-VFQ appears sensitive to between-patient vision differences, responsiveness to within-patient changes over time is unknown. This study investigated responsiveness of the NEI-VFQ subscales to changes in vi- sion in patients with subfoveal choroidal neovascularization secondary to selected eye conditions, primarily age-related macular degeneration, en- rolled in pilot Submacular Surgery Trials (SST). Data were combined from 3 pilot trials and correlation and regression methods were used to analyze changes in the NEI-VFQ scores and visual acuity from the 12-month to the 24-month visit using SAS. Eighty-seven of 327 patients enrolled in the pilot trials had an interview and visual acuities at 12 and 24 months. Median change in the overall NEI-VFQ score was a loss of 1.4 points (range - 28.0,20.3). Median better eye visual acuity change was 0.0 lines (range - 9.2,3.4). Eight of the 12 NEI-VFQ scales appeared responsive to changes in better eye visual acuity based on linear regression analysis (p<0.05), general vision, near activities, distance activities, mental health, role diffi- culties, dependency, driving and peripheral vision scales. General health, ocular pain, social functioning and color vision scales were not sensitive to changes in better eye visual acuity. Similar resuhls were obtained using weighted visual acuity of the 2 eyes wth lhe exception of peripheral vision scale. Change in the worse eye visual acuity was not associated with changes in NEI-VFQ scales. Since several NEI-VFQ scales appear to be responsive to both differences and changes in visual acuity, i may be pos- sible to extrapolate visual acuity and change in visual acuitywhen patients can be interviewed but visual acuity is not available. This analysis may help clinicians better understand which aspects of patients' lives are affected most by loss of central vision.

Abstract 1231

USING THE "SMALLEST REAL DiFFERENCE" AS A MEASURE OF SENSITIY TO CHANGE IN HEALTH-RELATED QUALITY OF LIFE SCALES: ADVANTAGES, PROBLEMS, AND SUGGESTED SOLUTIONS. Peter Schuck, FBK Research Institute, Bad EIster, Germany

Recently it was suggested to use the so-calted 'smallest real difference" (SRD) as a measure of sensitivity to change/responsiveness [1]. The SRD is a confidence limit of the standard error of measurement (SEM) of the difference scores. The absolute values of the SEM/SRD per se are an indi- cator of measurement error (and as such complementary to the concept of reliability) and not a measure of sensitivityo change. In head-to-head studies with e.g. an effective intervention to induce change however, the percent- age of patients, reaching the respective SRD criterion, could be used to compare the responsiveness of competitive instruments. In contrast to other sensitivity to change measures (e.g. "the" effect size) such an index would take the different reliabilities of the competitive instruments explicitly into account. The SRD concept is equivalent to the 'reliablechange index" (RCI), developed to assess 'clinical significance" of outcome data for single pa- tients in psychotherapy 121. However, a patient here must not only have a pre-post difference score which is statistically different from measurement error (the RCI/SRD-criterion, see above), s/he must have returned with the post-treatment score to values of 'normal functioning" of healthy people. Three different thresholds for the latter are discussed. Preferences for one or the other depends e.g. on the amount of overlapping of the two distribu- lions. This wvill be presented, with a special focus on the possibility to use this approach as a substitute of an external criterion for change, which is often difficult to find. References: I1l Pfennings LE, van der Ploeg HM, Cohen L, Potman CH. A comparison of responsiveness indices in multiple sclerosis patients. Qual Life Res 1999I8:481-9. (21 Jacobson NS, Roberts LJ, Bems SB, McGlinchey JB. Methods for defining and determining the clinical significance of treatment effects: description, application, and alter- natives. J Clin Consult Psychol 1999;67:300-7,

Abstract 1509

ABILITY OF THE CHILDREN HEALTH QUESTIONNAIRE (CHQ-CF87) TO DETECT DIFFERENCES IN QUALITY OF LIFE (QOL) BETWEEN CHILDREN ACCORDING TO THE TYPE OF CANCER C RODARY, J LANDGRAF, C KALIFA, G LEVERGER, JC GENTET BIOSTATISTICS AND EPIDEMIOLOGY, INSTITUT GUSTAVE ROUSSY, VILLEJUIF, FRANCE

OBJECTIVE: To answer the question: is the CHO able to identity patients (pts) who have specific needs following completion of their treatment (TT), according to the type of cancer ? INSTRUMENT: the 2nd French version of the CHO, thevalidation of which is ongoing, comprises 81 questions grouped into 8 dimensions: Physical Functioning (PF), Role/Social Limitations (RS), Self Esteem (SE), General Health Perception (GH), Bodily Pain (BP), Gen- eral Behavior (BE). Family Activities (FA), Mental Health (MH). It provides an 8-score profile, ranging from 0 (very bad OoL) to 100 (very good QoL). METHODS: Children aged 9 to 19, suffering from 8 types of cancer were included. The CHO was administered only once at the follow-up visit. Ac- crual of at least 300 children from 10 centers is expected. RESULTS: 261 pts have been included (May 2000). Compliance was high: 98%. The re- sults concem 4 types of cancer with at least 30 pts per malignancy at the time of the analysis: Leukemia (LE),62, Non Hodgkin's Lymphoma (NHL),34, Wilms'tumor (WT),31, Bone tumors (BT),35. The median age is 13.5 years and the median interval since the end of TT is 4.5 years (range: 1.5 - 16). There was a significant difference between the 3 dimensions (Kruskall- Wallis test): PF (respectively 90, 93, 97 and 81, pc.001), GH (respectively 64,69,72, and 59, p<01) and SE (respectively 77,81, 79, and 68, p<.001). For the type of cancer, the NB group had the highest scores and the BT group, the lowest. DISCUSSION: These results were expected but must be verified in a larger series of pts for the other 4 cancers. If this generic tool shows differences in QoL in pts, relaled to the cancer type, the next stage will be to evaluate the ability of CHO to detect meaningful changes over time, in order to validate its role as a criterion of efficacy in oncology.

Abstract 1672

MEASURING RESPONSIVENESS IN QUALITY OF LIFE RESEARCH Kevin W. Smith, New England Research Institutes, Watertown, MA

PURPOSE. Responsiveness, the degree to which an instrurnent measures change over lime, is an important psychometric characteristic of quality of life (QOL) questionnaires. Responsiveness hastraditionally been measured by an effect size. Effect sizes, however, have more to do with the efficacy of treatments than vwith the inherent properties of a QOL scale. The pur- pose of this research was to develop structural equation models (SEMs) to express responsiveness as the correlation between change in a QOL scale and change in a latent QOL variable. METHODS. Latent variable SEMs for the relationships among baseline, follow-up, and change scores were de- veloped. The models were applied to 6-month change data for 181 patients with cardiovascular disease who completed the Multidimensional Index of Life Quality (MILO) and for 89 HIVY adults completing the Multidimensional Quality of Life Questionnaire for Persons with HIV/AIDS (MQOL-HIV). Ret- rospective assessments of perceived change and other indicators were used to identity the models. RESULTS. An SEM linking latent variables of baseline, follow-up, and change scores to observed scores is unidentified. Additional indicators or parameter constraints are needed to identify these models. Three approaches for identifying models were found. 1) Collect three indicators of change to form a just-identified model. 2) Treat respon- siveness as the reliability of a change score and use the reliability formula to compute a responsiveness correlation. 3) Compute the correlation be- tween change in a QOL scale and retrospective perceived change (rated from much worse to much better). Identified models will not always ad- equately fit the data. Because responsiveness correlations are a type of reliability coefficient, they depend on the variation in change occurring in a particular sample and will therefore vary from study to study. While difficult to estimate in some situations, responsiveness correlations are more ac- curate than effect sizes for assessing an instrument's ability to measure change.

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