Health‐related quality of life and upper‐limb impairment in children with cerebral palsy: developing a mapping algorithm

• Published in: Developmental medicine and child neurology Vol. 62; no. 7; pp. 854 - 860
• Main Authors: Tonmukayakul, Utsana, Imms, Christine, Mihalopoulos, Cathrine, Reddihough, Dinah, Carter, Rob, Mulhern, Brendan, Chen, Gang
• Format: Journal Article
• Language: English
• Published: England 01.07.2020
• ISSN: 0012-1622; 1469-8749; 1469-8749
• DOI: 10.1111/dmcn.14488

Aim To: (1) investigate the relationship between upper‐limb impairment and health‐related quality of life (HRQoL) for children with cerebral palsy and (2) develop a mapping algorithm from the Cerebral Palsy Quality of Life Questionnaire for Children (CPQoL‐Child) onto the Child Health Utility 9D (CHU9D) measure. Method The associations between physical and upper‐limb classifications and HRQoL of 76 children (40 females, 36 males) aged 6 to 15 years (mean age 9 years 7 months [SD 3y]) were assessed. Five statistical techniques were developed and tested, which predicted the CHU9D scores from the CPQoL‐Child total/domain scores, age, and sex. Results Most participants had mild impairments. The Manual Ability Classification System (MACS) level was significantly negatively correlated with CHU9D and CPQoL‐Child (r=−0.388 and r=−0.464 respectively). There was a negative correlation between the Neurological Hand Deformity Classification (NHDC) and CPQoL‐Child (r=−0.476, p<0.05). The generalized linear model with participation, pain domain, and age had the highest predictive accuracy. Interpretation The weak negative correlations between classification levels and HRQoL measures may be explained by the restricted range of impairment levels of the participants. The MACS and NHDC explained the impact of upper‐limb impairment on HRQoL better than the other classifications. The generalized linear model with participation, pain, and age is the suggested mapping algorithm. The suggested mapping algorithm will facilitate the use of CPQoL‐Child for economic evaluation and can be used to conduct cost–utility analyses. What this paper adds The Manual Ability Classification System and Neurological Hand Deformity Classification were the best predictors of health‐related quality of life measures. Age and Cerebral Palsy Quality of Life Questionnaire for Children participation and pain domain scores can predict Child Health Utility 9D scores. What this paper adds The Manual Ability Classification System and Neurological Hand Deformity Classification were the best predictors of health‐related quality of life measures. Age and Cerebral Palsy Quality of Life Questionnaire for Children participation and pain domain scores can predict Child Health Utility 9D scores.