US valuation of the EQ-5D health states: development and testing of the D1 valuation model.
ABSTRACT The EQ-5D is a brief, multiattribute, preference-based health status measure. This article describes the development of a statistical model for generating US population-based EQ-5D preference weights.
A multistage probability sample was selected from the US adult civilian noninstitutional population. Respondents valued 13 of 243 EQ-5D health states using the time trade-off (TTO) method. Data for 12 states were used in econometric modeling. The TTO valuations were linearly transformed to lie on the interval [-1, 1]. Methods were investigated to account for interaction effects caused by having problems in multiple EQ-5D dimensions. Several alternative model specifications (eg, pooled least squares, random effects) also were considered. A modified split-sample approach was used to evaluate the predictive accuracy of the models. All statistical analyses took into account the clustering and disproportionate selection probabilities inherent in our sampling design.
Our D1 model for the EQ-5D included ordinal terms to capture the effect of departures from perfect health as well as interaction effects. A random effects specification of the D1 model yielded a good fit for the observed TTO data, with an overall R of 0.38, a mean absolute error of 0.025, and 7 prediction errors exceeding 0.05 in absolute magnitude.
The D1 model best predicts the values for observed health states. The resulting preference weight estimates represent a significant enhancement of the EQ-5D's utility for health status assessment and economic analysis in the US.
SourceAvailable from: Arie Pieter KappeteinJournal of the American College of Cardiology 10/2012; 60(15):1438-1454. DOI:10.1016/j.jacc.2012.09.001 · 15.34 Impact Factor
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ABSTRACT: Many patients with incurable cancer inaccurately believe that chemotherapy may cure them. Little is known about how such beliefs affect choices for care at the end of life. This study assessed whether patients with advanced cancer who believed that chemotherapy might offer a cure were more likely to receive chemotherapy in the last month of life and less likely to enroll in hospice care before death. This study examined patients diagnosed with stage IV lung or colorectal cancer in the Cancer Care Outcomes Research and Surveillance consortium, a population- and health system-based prospective cohort study. Among 722 patients who completed a baseline survey and died during the study period, logistic regression was used to assess the association of understanding goals of chemotherapy with chemotherapy use in the last month of life and hospice enrollment before death; adjustments were made for patient and tumor characteristics. One-third of the patients (33%) recognized that chemotherapy was "not at all" likely to cure their cancer. After adjustments, such patients were no less likely than other patients to receive end-of-life chemotherapy (odds ratio [OR], 1.32; 95% confidence interval [CI], 0.84-2.09), but they were more likely than other patients to enroll in hospice (OR, 1.97; 95% CI, 1.37-2.82). An understanding of the purpose of chemotherapy for incurable cancer is a critical aspect of informed consent. Still, advanced cancer patients who were well informed about chemotherapy's goals received late-life chemotherapy at rates similar to those for other patients. An understanding of the incurable nature of cancer, however, is associated with increased hospice enrollment before death, and this suggests important care outcomes beyond chemotherapy use. Cancer 2015. © 2015 American Cancer Society. © 2015 American Cancer Society.Cancer 02/2015; DOI:10.1002/cncr.29250 · 5.20 Impact Factor
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ABSTRACT: BACKGROUND Health-related quality of life (HRQOL) heterogeneity among cancer survivors may mask subgroups (classes) with different limitations and long-term outcomes. The authors determined the HRQOL classes that exist among lung cancer survivors, examined transitions among those classes over time, and compared survival outcomes of patients according to the classes present in the initial phase of care.METHODS Lung cancer survivors in the Cancer Care Outcomes Research and Surveillance Consortium completed EuroQol 5-domain quality-of-life questionnaires 4.8 months (initial phase) and >1 year (survivorship phase) after diagnosis (n = 1396). Latent class analysis and latent transition analysis were used to determine HRQOL classes and transitions across time. Correlates of class membership were tested using multinomial logistic regression. Kaplan-Meier and Cox regression analyses were used to compare survival across class membership.RESULTSLatent class analysis identified 4 classes at diagnosis and follow-up: 1) poor HRQOL, 2) pain-dominant impairment, 3) mobility/usual activities impairment, and 4) good HRQOL. Probabilities of remaining in the same class were .87, .85, .82, and .73 for classes 4, 1, 3, and 2, respectively. Younger age, lower income, lower education, comorbidities, and a history of depression/emotional problems were associated with a greater likelihood of being in classes 1, 2, or 3 at follow-up. Patients in classes 1 and 3 had significantly lower median survival estimates than patients in class 4 (4.8 years, 3.8 years, and 5.5 years, respectively; P < .001).CONCLUSIONS Examining the heterogeneity of HRQOL in lung cancer populations allows the identification of classes with different limitations and long-term outcomes and, thus, guides tailored and patient-centered provision of supportive care. Cancer 2015. © 2015 American Cancer Society.Cancer 01/2015; DOI:10.1002/cncr.29232 · 5.20 Impact Factor