Asrul Akmal Shafie1,2, Irwinder Kaur Chhabra3,4, Jacqueline Hui Yi Wong3,5, Noor Syahireen Mohammed3,6. 1. Discipline of Social and Administrative Pharmacy, School of Pharmaceutical Science, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia. aakmal@usm.my. 2. Institutional Planning and Strategic Centre, Universiti Sains Malaysia, 11800, Penang, Malaysia. aakmal@usm.my. 3. Discipline of Social and Administrative Pharmacy, School of Pharmaceutical Science, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia. 4. Pharmacy Department, Sabah Women and Children's Hospital, Ministry of Health Malaysia, Karung Berkunci No.187, 88996, Kota Kinabalu, Sabah, Malaysia. 5. Pharmacy Department, Hospital Kuala Lumpur, Ministry of Health Malaysia, Jalan Pahang, 50586, Kuala Lumpur, Malaysia. 6. Clinical Research Center, Hospital Sultanah Bahiyah, Ministry of Health Malaysia, KM 6, Jalan Langgar, 05460, Alor Setar, Kedah Darul Aman, Malaysia.
Abstract
PURPOSE: To develop a mapping algorithm for generating EQ-5D-3L utility scores from the PedsQL Generic Core Scales (PedsQL GCS) in patients with transfusion-dependent thalassemia (TDT). METHODS: The algorithm was developed using data from 345 TDT patients. Spearman's rank correlation was used to evaluate the conceptual overlap between the instruments. Model specifications were chosen using a stepwise regression. Both direct and response mapping methods were attempted. Six mapping estimation methods ordinary least squares (OLS), a log-transformed response using OLS, generalized linear model (GLM), two-part model (TPM), Tobit and multinomial logistic regression (MLOGIT) were tested to determine the root mean squared error (RMSE) and mean absolute error (MAE). Other criterion used were accuracy of the predicted utility score, proportions of absolute differences that was less than 0.03 and intraclass correlation coefficient. An in-sample, leave-one-out cross validation was conducted to test the generalizability of each model. RESULTS: The best performing model was specified with three out of the four PedsQL GCS scales-the physical, emotional and social functioning score. The best performing estimation method for direct mapping was a GLM with a RMSE of 0.1273 and MAE of 0.1016, while the best estimation method for response mapping was the MLOGIT with a RMSE of 0.1597 and MAE of 0.0826. CONCLUSION: The mapping algorithm developed using the GLM would facilitate the calculation of utility scores to inform economic evaluations for TDT patients when EQ-5D data is not available. However, caution should be exercised when using this algorithm in patients who have poor quality of life.
PURPOSE: To develop a mapping algorithm for generating EQ-5D-3L utility scores from the PedsQL Generic Core Scales (PedsQL GCS) in patients with transfusion-dependent thalassemia (TDT). METHODS: The algorithm was developed using data from 345 TDT patients. Spearman's rank correlation was used to evaluate the conceptual overlap between the instruments. Model specifications were chosen using a stepwise regression. Both direct and response mapping methods were attempted. Six mapping estimation methods ordinary least squares (OLS), a log-transformed response using OLS, generalized linear model (GLM), two-part model (TPM), Tobit and multinomial logistic regression (MLOGIT) were tested to determine the root mean squared error (RMSE) and mean absolute error (MAE). Other criterion used were accuracy of the predicted utility score, proportions of absolute differences that was less than 0.03 and intraclass correlation coefficient. An in-sample, leave-one-out cross validation was conducted to test the generalizability of each model. RESULTS: The best performing model was specified with three out of the four PedsQL GCS scales-the physical, emotional and social functioning score. The best performing estimation method for direct mapping was a GLM with a RMSE of 0.1273 and MAE of 0.1016, while the best estimation method for response mapping was the MLOGIT with a RMSE of 0.1597 and MAE of 0.0826. CONCLUSION: The mapping algorithm developed using the GLM would facilitate the calculation of utility scores to inform economic evaluations for TDT patients when EQ-5D data is not available. However, caution should be exercised when using this algorithm in patients who have poor quality of life.
Authors: I-Chan Huang; Constantine Frangakis; Mark J Atkinson; Richard J Willke; Walter L Leite; W Bruce Vogel; Albert W Wu Journal: Health Serv Res Date: 2008-02 Impact factor: 3.402