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Rabiah Begum, Speaker at Dermatology Conferences
University of Leicester, United Kingdom
Title : Mapping the EQ-5D-5L to two condition specific measures in Vitiligo patients: the VITIQOL and the VNS: Results from the Hi-Light trial.



Vitiligo presents a significant health related quality of life (HRQoL) burden. The Viti-QoL is a 16 item condition specific measure. The Vitiligo Noticeability Scale (VNS) is a 5 point clinical measure of vitiligo. Neither instruments are suitable for economic evaluation. No mapping algorithm to convert between EQ-5D-5L and these instruments exist, at present. We present two mapping algorithms that can be used to convert responses into utilities using data from the HI-Light randomized control trial.   


Data from 181 patients were collected at screening and 6 months for Viti-QoL and at 3 and 6 months for VNS. For Viti-QoL, the total score across all 16 items was used through a linear mixed effects model as well as Beta Binomial (BB) Regression models. For VNS, a discrete ‘U’ shaped, a non-linear 4 parameter model was used to model mean utility over each VNS category. Several other model forms were also used.


For the Viti-QoL , the model identified was : 0.9736 -0.00216*Total VitiQoL score. The AIC was -583; and predicted vs observed mean (SD) utilities were 0.896 (0.158) vs 0.884 (0.029), respectively. For the VNS, the notable ‘U shape’ of the mean utilities resulted in a poor linear fit with an AIC of -9.1 and mean predicted vs observed utilities of 0.904 (0.153) vs 0.896 (0.050) respectively. The non-linear model was of the form: 0.91 +0.0566*VNS - 0.112*log(VNS+0.9). The 95% CI for each of the parameters were (0.82,1.19); (-0.052,0.164) , (-0.584,0.192) respectively. The predicted vs observed mean(SE) utilities were 0.918 (0.015) vs 0.917(0.014) respectively with an AIC of -25.6.   


We have shown the feasibility of mapping between EQ-5D-5L and VITIQOL and VNS. There remain challenges in modelling EQ-5D utilities with VNS due to the discrete nature of the distribution. 


Rabiah Begum is currently an experienced Medical Statistician specializing in Health Technology Assessment and working in collaboration with the University of Warwick and Leicester University. Rabiah is pursuing a PhD in Medical Statistics and specializes in designing clinical trials for Economic Modelling and Clinical Decision Making.