Search

The EQ-5D is the most popular generic preference-based instrument used for asthma patients. This study aims to explore the psychometric properties of the EQ-5D-5L instrument in patients with asthma and identify the EQ-5D-5L scores in these patients.PubMed, Scopus, Web of Science, Google Scholar and CEA Registry were searched with English language from 2009 until April 2020. Retrieved studies were checked against the inclusion criteria. Reference lists of the included articles were also reviewed. The quality of included articles was evaluated using Mitton checklist and the data were extracted by a reviewer and were checked by a second reviewer. Meta-analysis was done to calculate the overall scores based on type of asthma control.A total of 17 articles were included. The EQ-5D-5L scores ranged from 0.45 to 0.93 and the VAS scores ranged from 35.67 to 83.80. The EQ-5D-5L is higher in well-controlled (0.88, 95% CI: 0.81-0.96,Higher score of the EQ-5D-5L was consistent with well-controlled asthma patients and those with lower severity of asthma. The assessment of psychometric properties of the EQ-5D-5L needs further observations.

BackgroundCOVID-19 caused by severe acute respiratory syndrome coronavirus 2 appeared in December 2019 in Wuhan, China.ObjectiveWe aimed to investigate the clinical manifestation include signs and symptoms, laboratory results, and perinatal outcomes in pregnant women with COVID-19.Materials and MethodsWe searched PubMed via LitCovid hub, Embase, Scopus, Web of sciences, and Google scholar on 07 April 2020. Meta-analysis was performed via CMA software using the Mantel-Haenszel method. The event rate with 95% CI was calculated for each variable.ResultsTen studies were selected. The pooled prevalence for fever, post-partum fever, cough, myalgia, fatigue, dyspnea, sore throat, and diarrhea were 66.8 %, 37.1 %, 35.5 %, 24.6 %, 14.9%, 14.6 %, 11.5%, and 7.6 %, respectively. Laboratory test results were 49.8 % for lymphopenia, 47.7 % for leukocytosis, 83.7 % for elevated neutrophil ratio, 57 % for elevated C-reactive protein, and 71.4 % for decreased lymphocyte ratio. The rate of cesarean section for delivery in all cases was 84%. Only one case was the newborn of a mother with COVID-19 positive. Also, there was only one death due to Decreased lymphocyte ratio.ConclusionFever was the most common signs and symptoms in pregnant women with COVID-19. Among the laboratory tests, the highest amount was related to elevated neutrophil ratio. It seems that due to the differences between pregnant women and the general population, special measures should be considered to treat these patients.

Background: Short-Form Six-Dimension version 2 (SF-6Dv2) is a multi-attribute utility instrument that can be used in combination with the SF-36v2 (SF-6Dv2SF-36) or as an independent instrument in t...

Objectives Health-related quality of life (HRQoL) is one of the most important outcome measures for patients. The purpose of this study was to evaluate HRQoL and related factors in Coronavirus disease 2019 (COVID-19) patients. Methods A total of 420 COVID-19 patients who had been discharged from hospital were selected using a systematic sampling. The EuroQol 5-dimensional-5 levels (EQ-5D-5L) questionnaire along with medical records of the patients were used to gather the data. The t test and analysis of variance were employed to test the difference between mean EQ-5D-5L scores, and the BetaMix model was used to investigate factors associated with EQ-5D-5L scores. Results The mean score for the patients who completed the EQ-5D-5L questionnaire (n = 409) was 0.6125. The EQ-5D-5L scores were significantly higher in males, patients with younger age, those with a low level of education, the employed, patients who worked in uncrowded workplaces, patients without diabetes, and those who were not admitted to intensive care unit. The BetaMix model showed that gender, age, education, employment status, having diabetes, heart failure, and admission to the intensive care unit were significant independent predictors of the EQ-5D-5L index values. Conclusion The mean score for EQ-5D-5L in COVID-19 patients was low in this study. Some of the factors, especially aging and having diabetes, should be considered in the aftercare of patients to improve their HRQoL.

The EQ-5D-5L and two versions of the SF-6D version 2 (i.e., SF-6Dv2ind-10 that is derived from 10 items of the SF-36v2, and SF-6Dv2SF-36 that is derived from its combination with the full SF-36v2) are used to drive utilities. The study was prospected to compare the performance of these instruments in breast cancer patients. Data were gathered from 418 patients with breast cancer using three questionnaires including the EQ-5D-5L, SF-36v2, and SF-6Dv2ind-6. The differences between the mean utilities of instruments were tested by t-test. The correlation between the dimensions scores of instruments was estimated by Spearman’s correlation coefficient (ρ). The level of agreement between the instruments score was assessed by ICC and Bland–Altman plot. The correlations between theoretically related pairs of EQ-5D-5L and SF-6Dv2SF-36 were stronger than those of the EQ-5D-5L and SF-6Dv2ind-6. The ICC between EQ-5D-5L and SF-6Dv2ind-6 was 0.64, and between EQ-5D-5L and SF-6Dv2SF-36 was 0.48. The Bland–Altman plot showed that there was a poorer agreement on the lower values. The EQ-5D-5L had more similarity with the SF-6Dv2ind-6 in comparison with the SF-6Dv2SF-36. Nevertheless, there are still significant differences between them.

The health-related quality of life (HRQoL) data extracted from cancer-specific questionnaires are often non-preference based, while patient preference-based utility data are required for health economic evaluation. This study aimed to map Functional Assessment of Cancer Therapy-Breast (FACT-B) subscales onto the Short Form six Dimension as an independent instrument (SF-6Dv2ind-6) using the data gathered from patients with breast cancer. Data for 420 inpatient and outpatient patients with breast cancer were gathered from the largest academic center for cancer patients in Iran. The OLS and Tobit models were used to predict the values of the SF-6Dv2ind-6 with regard to the FACT-B subscales. Prediction accuracy of the models was determined by calculating the root mean square error (RMSE) and mean absolute error (MAE). The relationship between the fitted and observed SF-6Dv2ind-6 values was examined using the Intraclass Correlation Coefficients (ICC). Goodness of fit of models was assessed using the predicted R2 (Pred R2) and adjusted R2 (Adj R2). A tenfold cross-validation method was used for validation of models. Data of 416 patients with breast cancer were entered into final analysis. The model included main effects of FACT-B subscales, and statistically significant clinical and demographic variables were the best predictor for SF-6Dv2ind-6 (Model S3 of OLS with Adj R2 = 61.02%, Pred R2 = 59.25%, MAE = 0.0465, RMSE = 0.0621, ICC = 0.678, AIC = -831.324, BIC = -815.871). The best algorithm developed for SF-6Dv2ind-6 enables researchers to convert cancer-specific instruments scores into preference-based scores when the data are gathered using cancer-specific instruments.

Calculating utility values in colorectal cancer (CRC) patients under chemotherapy treatment is important for studies of economic evaluations. The EQ-5D-5L and composite time trade-off (cTTO) were used to calculate utility values in 105 patients with CRC in Iran. The mean EQ-5D-5L index and cTTO values were 0.45 ± 0.03 and 0.51 ± 0.02, respectively. Anxiety and pain were the most common problems reported by the patients. The BetaMix showed that lower mean utility values were significantly associated with females, aging, a low level of income, a greater number of comorbidities, and an advanced stage of cancer.

Direct and indirect preference-based methods are two main types of utility generating methods which are being frequently used in cost-utility analysis. However, a key question is how do these two methods perform in terms of validity? The aim of this study is to assess the utilities derived from EuroQol five-dimensional 5 level (EQ-5D-5L) as an indirect method and composite time trade-off (C-TTO) as a direct method in patients with colorectal cancer (CRC). A total of 223 patients with CRC were consecutively selected from three cancer centers in Tehran between May and September 2017. The EQ-5D-5L and C-TTO methods were used to estimate utilities in patients. Wilcoxon test was performed to compare utilities between C-TTO and EQ-5D-5L. In addition, intraclass correlation coefficient (ICC) and Bland–Altman plot were used to assess the agreement between the two methods. Bootstrapping quantile regression analysis was performed for comparison coefficient. The mean values of EQ-5D-5L (0.7186 ± 0.1275) for all stages were significantly higher than the C-TTO (0.4180 ± 0.4670) values. Stage 1 had the highest utility in both C-TTO (0.8167 ± 0.2332) and EQ-5D-5L (0.8339 ± 0.0535), whereas stage 4 had the lowest utility (0.1283 ± 0.5530 and 0.6001 ± 0.1220, respectively). As well, the C-TTO underestimates the values in low level of utilities and overestimates in high level of utilities. The overall ICC between the two methods was 0.50. Our study provides some tentative results about the differences between values of EQ-5D-5L and C-TTO, but clearly more work is needed to be done on this issue.

Patient-level utility data are needed for cost-utility analysis; in oncology, however, the data are commonly gathered using disease-specific questionnaires that are often not appropriate. Present study aimed to derive an algorithm which can map the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30 (EORTC QLQ-C30) scales and the Colorectal Cancer-Specific Quality Of Life Questionnaire (QLQ-CR29) scales onto the EuroQoL 5-Dimension 5-Level (EQ-5D-5L) values in patients with colorectal cancer (CRC). Using the Ordinary Least Square (OLS) model, a cross-sectional dataset of 252 patients with CRC were gathered from three academic centers of cancer treatment in Tehran in 2017. The predicted R2 (Pred R2) and adjusted R2 (Adj R2) are used to evaluate model goodness of fit. Additionally, mean absolute error (MAE), root mean square error (RMSE), Spearman’s correlation coefficients (ρ), and intraclass correlation (ICC) are applied to assess predictive ability of models. The tenfold cross-validation procedure was applied for validation models. According to the results of our study, the model C4 from EORTC QLQ-C30 was the best predictive model (Pred R2 = 66.57%, Adj R2 = 67.67%, RMSE = 0.10173, MAE = 0.07840). Also, the model R4 from QLQ-CR29 performed the best for EQ-5D-5L (Adj R2 = 48.42%, Pred R2 = 45.54%, MAE = 0.10051, RMSE = 0.12997). The mapping algorithm successfully mapped the EORTC QLQ-C30 and QLQ-CR29 scales onto the EQ-5D-5L values; therefore, it enables policymakers to convert cancer-specific questionnaires scores to the preference-based scores.

Health-state utility values of diabetic foot ulcer (DFU) patients are necessary for clinical praxis and economic modeling. The purpose of this study was to estimate utility values in DFU patients using the EuroQol-5-dimension-5-level (EQ-5D-5L) and composite time trade-off (cTTO). The EQ-5D-5L and cTTO were used for estimating utility values. Data were collected from 228 patients referred to the largest governmental diabetes center in the South of Iran, Yazd province. When appropriate, independent sample t-test or analysis of variance test was used to test the difference in the utility values in each of the demographic and clinical characteristics of the patients. Finally, the BetaMix was used to identify predictors of the utility values. The means of EQ-5D-5L and cTTO values were 0.55( SD 0.21) and 0.67( SD 0.23), respectively. Anxiety and pain were the most common problems reported by the patients. The difference between the mean EQ-5D-5L values was significant for age, grade of ulcer, number of comorbidities, and having complications. In addition, variables of gender, age, grade of ulcer, and having complications were significant predictors of the EQ-5D-5L. The difference between the mean cTTO values was significant for age, employment status, grade of ulcer, number of comorbidities, and having complications. Moreover, variables of gender, age, grade of ulcer, number of comorbidities, and developing complications were significant predictors of cTTO. The current study provided estimates of utility values for DFU patients for clinical praxis and economic modeling. These estimates, similar to utilities reported in other studies, were low. Identifying strategies to decrease anxiety/depression and pain in patients is important to improve the utility values.

Introduction: Economic evaluation of healthcare interventions usually needs accurate data on utility and health-related quality-of-life scores. The aim of this study is to map QLQ-C30 scale score onto EQ-5D-5L and SF-6D utility values in colorectal cancer (CRC) patients. Methods: EQ-5D-5L, SF-6D, and QLQ-C30 were completed by 252 patients with CRC who were referred to three cancer centers in Tehran between May and September 2017. Moreover, OLS, Tobit, and CLAD models were used to predict EQ-5D-5L and SF-6D values. The goodness of fit of models was evaluated using Pred R2 and Adj R2. In addition, their predictive performance was assessed by MAE, RMSE, ICC, MID, and Spearman’s correlation coefficients between observed and predicted EQ-5D-5L and SF-6D values. Models were validated using a 10-fold cross-validation method. Results: Considering the goodness of fit and predictive ability of models, the OLS Model 2 performed best for EQ-5D-5L (Adj R2 = 58.09%, Pred R2 = 58.93%, MAE = 0.0932, RMSE = 0.129) and the OLS Model 3 performed best for SF-6D (Adj R2 = 54.90%, Pred R2 = 55.62%, MAE = 0.0485, RMSE = 0.0634). Conclusion: Our results demonstrated that algorithms developed based on OLS Models 1 and 2 are the best for predicted EQ-5D-5L and SF-6D values, respectively.

Objectives Many studies have mapped the QLQ-C30 onto the EQ-5D or the SF-6D utilities; however, these studies were limited to developed countries. So this study aimed to map QLQ-C30 onto the SF-6D version 2 (SF-6D-v2) and EQ-5D-5L using the data collected from patients with colorectal and breast cancer in a developing country. Methods A cross-sectional data set of 668 inpatient and outpatient patients with cancer was gathered from 4 teaching hospitals of cancer treatment in Tehran and Yazd from May 2017 to November 2018. The ordinary least squares (OLS) and censored least absolute deviations (CLAD) models were applied to estimate the utility values of both EQ-5D-5L and SF-6D-V2 using the QLQ-C30. Predicted R2 and adjusted R2 were used to evaluate the goodness of fit of the models. Moreover, the predictive performance of 2 models was assessed through estimating the mean absolute error (MAE), root mean square error (RMSE), intraclass correlation coefficients (ICC), and Spearman’s rho. The 10-fold cross-validation method was also applied for validation of models. Results The OLS Model E4 was the best-performing model for EQ-5D-5L (Adj R2 = 71.7%, Pred R2 = 71.15%, MAE = 0.0770, RMSE = 0.1026), and the OLS Model S4 performed best for SF-6D-V2 (Adj R2 = 74.64%, Pred R2 = 73.86%, MAE = 0.0465, RMSE = 0.0621). Conclusion The OLS Model E4 for EQ-5D-5L and the OLS Model S4 for SF-6D-V2 were the best models for policy makers to have more accurate evaluation of the healthcare interventions when the data are gathered through non-preference-based instruments.