Discussion
heterogenous, multimorbidity
SWEENEY
This is the first paper to externally validate the most recent PedsQL to CHU9D mappings using a sample of children and young people with chronic conditions from an ethnically diverse and deprived area in South London. After analysing these results, we determined whether improvements to the equations could be made for this diverse population. Our results indicate that, while existing mappings have an acceptable performance in the CYPHP sample, even better mappings can be built. The new CYPHP algorithms for mapping PedsQL onto CHU9D, particularly using OLS, yield superior goodness of fit compared previously published mappings.The new mappings are characterised by the presence of age as an important predictor, and more non-linear terms compared to previous work. Future research should assess the potential improvement to goodness of fit measures by adding variables such as socioeconomic status or medical information to model specifications. The importance of age, rather than sex, in the CYPHP mappings could be explained by the wider age range covered by the CYPHP sample (0–16 years) compared to previous mappings (e.g., 10–12 years in the Sweeney et al. mapping [Direct measurement of HRQoL for clinical use or for research purposes (e.g. evaluation and cost effectiveness analysis) may not always be possible. The ability to predict QALYs when only PedsQL scores and demographic characteristics are available becomes particularly useful. For example, this could allow the accurate prediction of missing values when a CHU9D response is not available. It could perhaps reduce the cost and time burden of filling out two separate HRQoL instruments, when one would suffice. Yet it is important to highlight the need to account for the uncertainty around the predicted CHU9D values. A caveat to the current study findings is that, although a population of children and young people across a wide age range was included, direct measurement, rather than use of mapping algorithms, may be particularly desirable among children below 5 years of age. This group was excluded from the item-level mapping as PedsQL items were considered too heterogenous to be pooled with the rest of the sample. Additionally, children under two years of age were removed from the dimension-level mapping as physical symptoms and cognitive function dimensions are not measured in older age groups, while school function is not relevant yet among the younger group. A strength of both HRQoL instruments is that they are self-completed. Children of a certain age or condition may require an adult or guardian to complete the questions introducing proxy biases. By completing two different HRQoL instruments, it may be possible to identify or reduce bias. The majority of the current population (77.4%) had one chronic condition only.Although the performance of mapping algorithms was acceptable for the multimorbid population, the evidence on the accuracy of existing and new mappings for this subpopulation is limited. As suggested by Sweeney et al., further research is required to determine if direct measurement compared to mapping algorithms are more appropriate to use for children with lower HRQoL. Additionally, further validations of the CYPHP mappings for children and young people with multimorbidity or with mental health conditions is needed.One of the strengths of this study is that it is the first to externally validate existing mappings with a sample of children and young people under 16 years of age with chronic conditions in a UK deprivated urban area. Previous mappings were based on an Australian sample with limited age coverage (15–17 years [Study limitations included a relatively low representation of children below 2 years of age, which requires further examination of existing and new mappings among this younger population. Second, the majority of our sample (77.4%) had one chronic condition only. Even though the performance of mapping algorithms was acceptable for the multimorbid population, the evidence on the accuracy of existing and new mappings for this subpopulation is limited.