Height in childhood can be negatively affected by various health conditions. Many of these health conditions are relatively rare and the first indication of a problem is the child’s slowed growth. Poor growth can also be a sign of more common problems, such as difficulties absorbing nutrients. The options for treatment and results of these treatments are better when children are diagnosed at a younger age. Although in the UK children are measured at least twice between the ages of 2 and 5 years, these measurements are not currently formally used to find children with conditions that could affect their growth.
As part of a larger project, we are proposing to look at how many children are diagnosed with seven growth-affecting conditions each year in England, as well as the average age at diagnosis, using Clinical Practice Research Datalink (CPRD) data. This will help us understand if the way we check healthy children’s growth can be improved, by comparing the number of conditions diagnosed and the age at diagnosis with other countries with formal screening programmes. We will also look at the impact of the Covid-19 pandemic by comparing the number of diagnoses and age at diagnosis before and after the pandemic.
We need to know how many children are normally diagnosed with these conditions and at what ages they are diagnosed to be able to see if a new way of checking children helps to increase diagnoses and lower the age at diagnosis.
Our overarching objective is to obtain evidence of the effectiveness of current practice for the identification of growth disorders in the UK. We will do this by estimating the national yearly incidence of growth disorder diagnoses for seven target conditions, as well as estimating the average age at which these diagnoses are given. The population of interest includes patients with a new diagnosis of any of the seven specified growth disorders.
We will use data from the Aurum and Gold datasets to obtain all available diagnoses. All new individual diagnoses in children aged <18 year for the following growth disorders will be counted in the target years (2017-2022):
a) Growth Hormone Deficiency
b) Turner Syndrome
c) Primary hypothyroidism
d) Crohn’s Disease
e) Coeliac Disease
f) Skeletal dysplasia
g) Noonan Syndrome
The average age at diagnosis will be estimated. We will compare the yearly number of diagnoses and age at diagnosis before and after the Covid-19 pandemic (2017-2019 vs 2020-2022), to assess any impact on access to routine healthcare and diagnostic abilities. Finally, we will assess inequalities in the number of diagnoses and age at diagnosis by sex, ethnicity and area-level Index of Multiple Deprivation.
Results from this research will provide a rationale for improvements of current growth-screening practice in the UK, by allowing direct comparisons in number and age at diagnosis with other countries that implement formal screening programmes. A large screening programme study is currently in planning. CPRD data will further provide a baseline comparator to assess the efficacy of the tested screening programme. The assessment of differences in outcomes in pre-and-post Covid years, and by sex, ethnicity and deprivation, will provide evidence of inequalities and opportunities to improve access to healthcare by understanding underlying patterns in the diagnosis of these conditions.
Primary analysis:
- Number of new yearly diagnoses for the following target conditions:
a) Growth Hormone Deficiency
b) Turner Syndrome
c) Primary hypothyroidism
d) Crohn’s Disease
e) Coeliac Disease
f) Skeletal dysplasia
g) Noonan Syndrome
- Average age at diagnosis for each target condition
Secondary analysis:
Outcomes for secondary analysis are the same as for the primary analyses. Secondary analyses used covariates to assess differences in these outcomes by IMD, ethnicity, sex and pre-post pandemic.
- Number of new yearly diagnoses for the target conditions.
- Average age at diagnosis for each target condition
Helen Storr - Chief Investigator - Barts and the London Queen Mary's School of Medicine and Dentistry
Joanna Orr - Corresponding Applicant - Queen Mary University of London
Andrew Prendergast - Collaborator - Queen Mary University of London
Helen Storr - Collaborator - Barts and the London Queen Mary's School of Medicine and Dentistry
Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation