156 research outputs found

    Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

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    Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes

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

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    <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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).</p> <p>Discussion</p> <p>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 0.07 for VAS scores.</p

    Measuring Patient and Clinician Perspectives to Evaluate Change in Health-Related Quality of Life Among Patients with Chronic Obstructive Pulmonary Disease

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    CONTEXT: Many treatments aim to improve patients’ health-related quality of life (HRQoL), and many care guidelines suggest assessing symptoms and their impact on HRQoL. However, there is a lack of consensus regarding which HRQoL outcome measures are appropriate to assess, and how much change on those measures depict significant HRQoL improvement. OBJECTIVE: We used triangulation methods to identify and understand clinically important differences (CIDs) for the amount of change in HRQoL that reflects both health professionals and patients’ values, among patients with chronic obstructive pulmonary disease (COPD). DESIGN, SETTING, AND PARTICIPANTS: We incorporated three perspectives: (1) an expert panel of physicians familiar with the measurement of HRQoL in COPD patients; (2) 610 primary care COPD outpatients who completed baseline and bimonthly follow-up HRQoL interviews over the 12-month study; and (3) the primary care physicians (PCPs; n = 43) of these outpatients who assessed their patients’ disease at baseline and at subsequent PCP visits during the year long study. MEASUREMENTS: The Chronic Respiratory Disease Questionnaire (CRQ), the Medical Outcomes Study Short Form 36-item survey (SF-36, version 2.0), and global assessments of change from each of the three perspectives for all HRQoL domains. RESULTS: With few exceptions, the CRQ was able to detect small changes at levels reported by the patients (1–2 points) and their PCPs (1–5 points). These results confirm minimal important difference standards developed in 1989 by Jaeschke et al. anchored on patient-perceived changes in HRQoL. In general, the expert panel and PCP CIDs were larger than the patient CIDs. CONCLUSION: This triangulation methodology yielded improved interpretation, understanding, and insights on stakeholder perspectives of CIDs for patient-reported outcomes

    Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

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    Peer reviewedPublisher PD

    Health-related quality of life among general practice patients with differing chronic diseases in Germany: Cross sectional survey

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    Background This study was carried out to compare the HRQoL of patients in general practice with differing chronic diseases with the HRQoL of patients without chronic conditions, to evaluate the HRQoL of general practice patients in Germany compared with the HRQoL of the general population, and to explore the influence of different chronic diseases on patients HRQoL, independently of the effects of multiple confounding variables. Methods A cross-sectional questionnaire survey including the SF-36, the EQ-5D and demographic questions was conducted in 20 general practices in Germany. 1009 consecutive patients aged 15–89 participated. The SF-36 scale scores of general practice patients with differing chronic diseases were compared with those of patients without chronic conditions. Differences in the SF-36 scale/summary scores and proportions in the EQ-5D dimensions between patients and the general population were analyzed. Independent effects of chronic conditions and demographic variables on the HRQoL were analyzed using multivariable linear regression and polynomial regression models. Results The HRQoL for general practice patients with differing chronic diseases tended to show more physical than mental health impairments compared with the reference group of patients without. Patients in general practice in Germany had considerably lower SF-36 scores than the general population (P < 0.001 for all) and showed significantly higher proportions of problems in all EQ-5D dimensions except for the self-care dimension (P < 0.001 for all). The mean EQ VAS for general practice patients was lower than that for the general population (69.2 versus 77.4, P < 0.001). The HRQoL for general practice patients in Germany seemed to be more strongly affected by diseases like depression, back pain, OA of the knee, and cancer than by hypertension and diabetes. Conclusion General practice patients with differing chronic diseases in Germany had impaired quality of life, especially in terms of physical health. The independent impacts on the HRQoL were different depending on the type of chronic disease. Findings from this study might help health professionals to concern more influential diseases in primary care from the patient´s perspective

    An interdisciplinary intervention for older Taiwanese patients after surgery for hip fracture improves health-related quality of life

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    Abstract Background The effects of intervention programs on health-related quality of life (HRQOL) of patients with hip fracture have not been well studied. We hypothesized that older patients with hip fracture who received our interdisciplinary intervention program would have better HRQOL than those who did not. Methods A randomized experimental design was used. Older patients with hip fracture (N = 162), 60 to 98 years old, from a medical center in northern Taiwan were randomly assigned to an experimental (n = 80) or control (n = 82) group. HRQOL was measured by the SF-36 Taiwan version at 1, 3, 6, and 12 months after discharge. Results The experimental group had significantly better overall outcomes in bodily pain (&#946; = 9.38, p = 0.002), vitality (&#946; = 9.40, p &lt; 0.001), mental health (&#946; = 8.16, p = 0.004), physical function (&#946; = 16.01, p &lt; 0.001), and role physical (&#946; = 22.66, p &lt; 0.001) than the control group at any time point during the first year after discharge. Physical-related health outcomes (physical functioning, role physical, and vitality) had larger treatment effects than emotional/mental- and social functioning-related health outcomes. Conclusions This interdisciplinary intervention program may improve health outcomes of elders with hip fracture. Our results may provide a reference for health care providers in countries using similar programs with Chinese/Taiwanese immigrant populations. Trial registration NCT01052636http://deepblue.lib.umich.edu/bitstream/2027.42/78259/1/1471-2474-11-225.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78259/2/1471-2474-11-225.pdfPeer Reviewe

    EuroQol (EQ-5D) measure of quality of life predicts mortality, emergency department utilization, and hospital discharge rates in HIV-infected adults under care

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    BACKGROUND: Health-related quality of life (HR-QOL) is a relevant and quantifiable outcome of care. We implemented HR-QOL assessment at all primary care visits at UCSD Owen Clinic using EQ-5D. The study aim was to estimate the prognostic value of EQ-5D for survival, hospitalization, and emergency department (ED) utilization after controlling for CD4 and HIV plasma viral load (pVL). METHODS: We conducted a retrospective analysis of HIV clinic based cohort (1996–2000). The EQ-5D includes single item measures of: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each item is coded using 3-levels (1 = no problems; 2 = some problems; 3 = severe problems). The instrument includes a global rating of current health using a visual analog scale (VAS) ranging from 0 (worst imaginable) to 100 (best imaginable). An additional single item measure of health change (better, much the same, worse) was included. A predicted VAS (pVAS) was estimated by regressing the 5 EQ-5D health states on VAS using reference cell coding of health states and random effects linear models. Survival models were fit using Cox modelling. Hospitalization and ED rate models were estimated using population-averaged Poisson models. RESULTS: 965 patients met eligibility criteria. 12% were female; 42% were non-white. Median time-at-risk was 1.2 years. Median CD4 was 233. Median log(10)(pVL) was 4.6. 47 deaths occurred. In two Cox models controlling for CD4 and pVL, the adjusted hazard ratios (aHR) for VAS and pVAS as time-varying covariates were 0.73 (95% CI: 0.63–0.83) and 0.66 (95% CI: 0.56–0.77) respectively, for every 10 point increase in (p)VAS rating. In Poisson regression models predicting ED visit rates and hospital discharge rates controlling for current CD4 and pVL, each of the EQ-5D health dimensions, VAS, and health change items were significantly (p < 0.05) associated with the outcomes. For ED visit rates, the adjusted incidence rate ratios (aIRR) were 0.86 (0.83–0.89) and 0.79 (0.75–0.82) for VAS and pVAS, respectively. For hospital discharge rates, the aIRR's were 0.85 (0.82–0.88) and 0.79 (0.75–0.82) for VAS and pVAS, respectively. CONCLUSION: EQ-5D is a brief and prognostically useful predictor of mortality, hospitalization, and ED utilization among adults under care for HIV infection, even after adjusting for CD4 and HIV plasma viral load
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