Conclusion Various methods have been used at all stages of CSPBM development .
The choice between developing a classification system de novo or from an existing instrument may depend on the availability of a suitable existing measure , while the choice between a decomposed or composite approach appears to be determined primarily by the purpose for which the instrument is design ed .
Background Health state utility values ( HSUVs ) are required to calculate quality -adjusted life-years ( QALYs ) .
They are frequently derived from generic preference-based measures of health .
However , such generic measures may not capture health attributes of relevance to specific conditions .
In such cases , a condition-specific preference-based measure ( CSPBM ) may be more appropriate .
Objective This systematic review aim ed to identify all published accounts of developing CSPBMs to describe and appraise the methods used .
Developing a utility index for the Aberrant Behavior Checklist (ABC-C) for fragile X syndrome
Purpose This study aim ed to develop a utility index ( the ABC-UI ) from the Aberrant Behavior Checklist-Community ( ABC-C ) , for use in quantifying the benefit of emerging treatments for fragile X syndrome ( FXS ) . Methods The ABC-C is a proxy-completed assessment of behaviour and is a widely used measure in FXS . A subset of ABC-C items across seven dimensions was identified to include in health state descriptions . This item reduction process was based on item performance , factor analysis and Rasch analysis performed on an observational study data set , and consultation with five clinical experts and a method ological expert . Dimensions were combined into health states using an orthogonal design and valued using time trade-off ( TTO ) , with lead-time TTO methods used where TTO indicated a state valued as worse than dead . Preference weights were estimated using mean , individual level , ordinary least squares and r and om-effects maximum likelihood estimation [ RE ( MLE ) ] regression models . Results A representative sample of the UK general public ( n = 349 ; mean age 35.8 years , 58.2 % female ) each valued 12 health states . Mean observed values ranged from 0.92 to 0.16 for best to worst health states . The RE ( MLE ) model performed best based on number of significant coefficients and mean absolute error of 0.018 . Mean utilities predicted by the model covered a similar range to that observed . Conclusions The ABC-UI estimates a wide range of utilities from patient-level FXS ABC-C data , allowing estimation of FXS health-related quality of life impact for economic evaluation from an established FXS clinical trial instrument
Conclusion Various methods have been used at all stages of CSPBM development .
The choice between developing a classification system de novo or from an existing instrument may depend on the availability of a suitable existing measure , while the choice between a decomposed or composite approach appears to be determined primarily by the purpose for which the instrument is design ed .
Background Health state utility values ( HSUVs ) are required to calculate quality -adjusted life-years ( QALYs ) .
They are frequently derived from generic preference-based measures of health .
However , such generic measures may not capture health attributes of relevance to specific conditions .
In such cases , a condition-specific preference-based measure ( CSPBM ) may be more appropriate .
Objective This systematic review aim ed to identify all published accounts of developing CSPBMs to describe and appraise the methods used .