Sickle cell disease (SCD) is an inherited condition that affects red blood cells. It is caused by unusual shaping of red blood cells which can cause blockages leading to severe pain and other health conditions. SCD is most common in people from Black African or Black Caribbean family origin but can affect people of other ethnic groups. The only cure for sickle cell is a stem cell or bone marrow transplant but these are rarely carried out as they are high risk procedures. Instead, people with severe sickle cell disease often have to manage pain and symptoms using medications.
It is believed that around 15,000 people in England have SCD with much more having sickle cell trait (SCT), meaning they carry the gene which can be passed on to their children. However, evidence to support this is dated and due to the growing population of Black and Mixed ethnicity individuals in the UK this is likely to be more. To date much of the evidence exploring how effective medications are at managing SCD comes from the US. In addition to this, it is unknown why some people with SCD suffer more than others and have poorer outcomes. This study aims to give an up-to-date estimate of the number of patients living with sickle cell in the UK and explore if specific characteristics or clinical events lead to some patients having poorer outcomes. Finally, it will explore how effective medications are at managing the disease in the UK.
Sickle cell disease (SCD) refers to a group of inherited blood disorders. It causes painful episodes (crises) and other comorbidities, with progression of the disease often heterogeneous. There is a fundamental knowledge gap in prediction of whom the disease is most severe; if filled this could transform the outcomes of patients with SCD. Using CPRD GOLD and Aurum this study will provide up-to-date estimates of the incidence of SCD and sickle cell trait (SCT) and assess the association with socio-economic status through linked data on deprivation. Using death dates recorded in CPRD we will additionally describe temporal trends of survival of SCD and SCT.
To provide insight into disease severity related to sickle cell crises, we will use linked hospital data to model sickle cell related hospital stays using a growth mixture model. A logistic regression model will be used to identify factors associated with most severe trajectories.
To explore disease progression of comorbidities, we will use process mining methods to identify clinical pathways of patients with SCD and SCT compared to the general population and identify factors associated with disease severity. This will help target therapeutic strategies to specific patient groups, reducing the incidence of stroke among other conditions and premature mortality. In addition, determining the risk factors associated with disease severity will also help targeting these individuals for delayed disease progression.
There is a scarcity in large-scale population-based studies that provide high-resolution insights into the effects of hydroxyurea treatment for SCD management. Therefore, our final aim will compare patients with SCD who received a prescription for hydroxyurea to those with SCD who have never received a prescription for this medication. We will use a propensity-score—matched Cox regression model to estimate the effects of this medication on all-cause mortality and other cardiovascular outcomes.
Sickle cell disease incidence; sickle cell trait incidence; sickle cell related hospitalisation; all-cause mortality; stroke; heart failure; chronic kidney disease; myocardial infarction; pneumonia
Jianhua Wu - Chief Investigator - Queen Mary University of London
Paris Baptiste - Corresponding Applicant - Queen Mary University of London
Harriet Larvin - Collaborator - Queen Mary University of London
Manh Thang Hoang - Collaborator - Queen Mary University of London
HES Admitted Patient Care;Patient Level Index of Multiple Deprivation;Practice Level Rural-Urban Classification