INTRODUCTION: The negative impact of hypoglycaemic events on health-related quality of life (HRQoL) may be evaluated by attaching published disutilities to these events. It is suggested that the marginal negative impact of individual hypoglycaemic events on HRQoL may decrease as the overall frequency increases. METHODS: Using disutility values from a large-scale (>8,000 respondents), time trade-off (TTO) study, nonlinear regression curves were fitted to the total disutility of different frequencies of non-severe daytime and nocturnal hypoglycaemic events. Nonparametric bootstrapping was applied to characterise the uncertainty of the marginal disutility. RESULTS: Power function regression curves were estimated at U d = 0.0141x (0.3393) and U d = 0.0221x (0.3277). An increase from 0 to 1 hypoglycaemic event per year produced a utility decrease of 0.0141 and 0.0221 for non-severe daytime and nocturnal events, respectively. An increase from 25 to 26 events per year produced a marginal impact of 0.0006 and 0.0008 for non-severe daytime and nocturnal events, respectively. DISCUSSION: These data concur with the noted phenomenon of "first being worst" as regards hypoglycaemic events. This finding may reflect a coping mechanism on the part of patients, a maximum limit for trading off remaining lifetime or the nature of the study. CONCLUSION: Applying nonlinear functions to the TTO data might improve the precision of the measured impact of hypoglycaemic events.
INTRODUCTION: The negative impact of hypoglycaemic events on health-related quality of life (HRQoL) may be evaluated by attaching published disutilities to these events. It is suggested that the marginal negative impact of individual hypoglycaemic events on HRQoL may decrease as the overall frequency increases. METHODS: Using disutility values from a large-scale (>8,000 respondents), time trade-off (TTO) study, nonlinear regression curves were fitted to the total disutility of different frequencies of non-severe daytime and nocturnal hypoglycaemic events. Nonparametric bootstrapping was applied to characterise the uncertainty of the marginal disutility. RESULTS: Power function regression curves were estimated at U d = 0.0141x (0.3393) and U d = 0.0221x (0.3277). An increase from 0 to 1 hypoglycaemic event per year produced a utility decrease of 0.0141 and 0.0221 for non-severe daytime and nocturnal events, respectively. An increase from 25 to 26 events per year produced a marginal impact of 0.0006 and 0.0008 for non-severe daytime and nocturnal events, respectively. DISCUSSION: These data concur with the noted phenomenon of "first being worst" as regards hypoglycaemic events. This finding may reflect a coping mechanism on the part of patients, a maximum limit for trading off remaining lifetime or the nature of the study. CONCLUSION: Applying nonlinear functions to the TTO data might improve the precision of the measured impact of hypoglycaemic events.
Authors: Craig J Currie; Christopher Ll Morgan; Chris D Poole; Peter Sharplin; Morten Lammert; Phil McEwan Journal: Curr Med Res Opin Date: 2006-08 Impact factor: 2.580
Authors: L A Donnelly; A D Morris; B M Frier; J D Ellis; P T Donnan; R Durrant; M M Band; G Reekie; G P Leese Journal: Diabet Med Date: 2005-06 Impact factor: 4.359
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Authors: David Russell-Jones; Simon R Heller; Sarah Buchs; Anna Sandberg; William J Valentine; Barnaby Hunt Journal: Diabetes Obes Metab Date: 2017-07-25 Impact factor: 6.577
Authors: Johannes Pöhlmann; Roberta Montagnoli; Giusi Lastoria; Witesh Parekh; Marie Markert; Barnaby Hunt Journal: Clinicoecon Outcomes Res Date: 2019-10-07