Effects of comorbidity on health-related quality-of-life scores: an analysis of clinical trial data

Xuan, Jianwei; Kirchdoerfer, Leonard; Boyer, J. Gregory; Norwood, G. Joseph

doi:10.1016/s0149-2918(00)88295-8

Cited by 103 publications

(78 citation statements)

References 22 publications

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“…Although each condition may have its own effect, most studies focus on the index disease, whereas the confounding and/or modifying effect of other variables is given less attention, or even ignored, and this may threaten the validity of the results [30]. This is particularly important in chronic diseases in which mortality is the less likely outcome, and the ''With'' and ''Without,'' respectively, mean having and not having each comorbidity or complication * P \ 0.05, **P \ 0.01, ***P \ 0.001 according to independent samples t test objectives of treatment and care are controlling the course of the disease and maximizing HRQoL [31]. Subjects with diabetes and multiple co-existing chronic conditions such as cardiovascular diseases or coronary artery disease, peripheral sensory neuropathy and peripheral vascular diseases have reported poorer HRQoL than those without these conditions [32,33].…”

Section: Discussionmentioning

confidence: 99%

Comparing the sensitivity of EQ-5D, SF-6D and 15D utilities to the specific effect of diabetic complications

et al. 2010

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After removing the effect of background variables, 15D utilities remain sensitive to CHD and DR. The obvious explanation is its richer descriptive system, which provides increased discriminative ability compared to EQ-5D and SF-6D, and this might be evidence for preferring the 15D in economic evaluations of interventions for diabetics. However, the need remains for further testing in other diabetes complications and more diverse patient samples.

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Section: Discussionmentioning

confidence: 99%

Comparing the sensitivity of EQ-5D, SF-6D and 15D utilities to the specific effect of diabetic complications

et al. 2010

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“…Esto reafirma lo demostrado por otros estudios (30,31) que indican que este tipo de cuestionarios específicos son más sensibles a los cambios en el estado de salud de los pacientes. Igualmente, pudimos comprobar que tanto el efecto techo como el efecto suelo eran inferiores al 15%.…”

Section: Discussionunclassified

Propiedades psicométricas de un cuestionario específico de calidad de vida en trasplante hepático

Estraviz

Quintana

Valdivieso

et al. 2007

Rev. esp. enferm. dig.

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RESUMENObjetivo: traducir y evaluar las propiedades psicométricas de un cuestionario de calidad de vida específico para pacientes sometidos a trasplante hepático.Material y métodos: el cuestionario fue administrado a 60 pacientes en lista de espera de trasplante hepático de la Unidad de Trasplante del Hospital de Cruces, y a los 6 meses tras la intervención. Se estudió la fiabilidad, la validez, la sensibilidad al cambio y el mínimo cambio detectable (MCD). Para evaluar la validez convergente se utilizaron dos cuestionarios, SF-36 (Health Survey Short Form 36) y el HAD (Hospital Anxiety and Depression Scale).Resultados: el cuestionario específico presenta un coeficiente alfa de Cronbach superior a 0,7. El análisis factorial demuestra una única dimensión. Las correlaciones con las áreas del SF-36 oscilaron entre -0,34 y -0,71 en el preoperatorio, y entre -0,21 y -0,67 a los 6 meses. Respecto al HAD-ansiedad, los coeficientes eran 0,44 en el preoperatorio y 0,51 a los 6 meses, y para HADdepresión de 0,64 y 0,39 respectivamente. Los estudios de validez discriminante confirman que el cuestionario muestra diferencias entre pacientes con cirrosis de diversas etiologías o gravedad. En el estudio de la sensibilidad al cambio se obtuvieron unos valores para los índices TEE (tamaño del efecto estandarizado) y MRE (media de respuesta estandarizada) de 0,92 y 0,99 respectivamente. Además, un 58,33% de los pacientes superaba el MCD.Conclusiones: el cuestionario específico posee adecuadas propiedades psicométricas, lo cual puede aconsejar su utilización en estos pacientes, como otra medida más para evaluar los resultados de esta intervención. ABSTRACTObjective: to translate and evaluate the psychometric properties of a quality of life questionnaire specific to liver transplant patients.Material and methods: the questionnaire was administered to 60 patients on the waiting list for liver transplant in the Cruces Hospital Transplant Unit, and again at 6 months after the transplant. The reliability, validity, sensitivity to change, and minimum detectable change (MDC) were studied. Two questionnaires, the SF-36 (Health Survey Short Form 36) and HADS (Hospital Anxiety and Depression Scale), were used to evaluate the convergent validity.Results: the specific questionnaire presented a Cronbach's alpha coefficient of over 0.7. The factor analysis demonstrates a single dimension. Correlations with the areas of SF-36 varied between -0.34 and -0.71 in the preoperative phase, and between -0.21 and -0.67 at 6 months. With respect to the HAD-anxiety scale, the coefficients were 0.44 in the preoperative phase and 0.51 at 6 months, and for the HAD-depression scale these were 0.64 and 0.39, respectively. Discriminant validation studies confirm that the questionnaire shows differences between patients with cirrhosis of various etiologies and severities. In the study of sensitivity to change, values were obtained for the SES (standardised effect size) and SRM (standardised response mean) indices of 0.92 and 0.99, respectively. Furthermore, 58.3...

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“…Many research questions demand more than evaluation of an overall test statistic. When the focus of clinical trials extends to understanding the mechanisms responsible for group and individual di erences, and how these may interact with treatments [53][54][55], then LANOVA and the SEM heritage can represent incisive approaches. A univariate test statistic may answer the question 'Did the treatment work?'.…”

Section: Discussionmentioning

confidence: 99%

General linear contrasts on latent variable means: structural equation hypothesis tests for multivariate clinical trials

Donaldson

2003

Statistics in Medicine

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Structural equation models articulate the assumed measurement and causal relations among variables, imposing discipline on otherwise unstructured and redundant associations that arise in correlational studies. Biomedical research has eschewed such methods, relying on the generally superior causal inference afforded by randomized controlled trials. Increasingly, however, clinical trials incorporate numerous covariates that are measured but unmanipulated. Most clinical trials now also include multiple correlated endpoints, which can generate ambiguous outcome patterns refractory to simple statistical analysis and interpretation. Modern clinical trials are really multivariate longitudinal studies with at best a component of randomized control; as such, structural equation approaches can add rigour and clarity. The analysis of latent variance (LANOVA) conception combines structural equation and experimental analysis of variance legacies. It allows, for any design that can be decomposed into between-group and within-person models, tests on latent means (that is, the means of the unobserved factors) that are directly analogous to their analysis of variance counterparts. LANOVA variables are either outcomes (which may have a time structure), varying covariates (which may have a time structure), or background covariates (which are static). Allowable causal relations are set-recursive: background covariates can affect all other variables; varying covariates can affect current outcomes and later outcomes and covariates; outcomes can affect only later outcomes. All standard ANOVA and ANCOVA hypotheses can then be tested by proper restrictions among the means and intercepts of these latent variables. Structural equation modelling programs can be used to estimate the models and test the hypotheses. I demonstrate the approach by expressing and testing hypotheses appropriate for two clinical studies that evaluate patient-reported outcomes in populations with solid and haematological malignancies.

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Effects of comorbidity on health-related quality-of-life scores: an analysis of clinical trial data

Cited by 103 publications

References 22 publications

Comparing the sensitivity of EQ-5D, SF-6D and 15D utilities to the specific effect of diabetic complications

Comparing the sensitivity of EQ-5D, SF-6D and 15D utilities to the specific effect of diabetic complications

Propiedades psicométricas de un cuestionario específico de calidad de vida en trasplante hepático

General linear contrasts on latent variable means: structural equation hypothesis tests for multivariate clinical trials

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