US scientists create tool to predict chronic ITP in children
Study IDs key risk factors, such as age and sex, for rare bleeding disorder
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U.S. researchers have created a prediction tool — one that uses laboratory tests collected at the time of diagnosis — to help identify which children with immune thrombocytopenia (ITP) are more likely to develop a chronic form of the bleeding disorder.
The tool was developed as part of a new study in which the team, using statistical models, identified key risk factors they said are “useful in predicting chronic ITP.” Among these factors were older age and female sex, as well as abnormal blood levels of white blood cells, platelets, and certain antibodies.
The presence of an underlying cause for a patient’s ITP was also linked to a higher risk of chronic disease, the research showed.
According to the team, “a chronicity prediction tool to use at the time of ITP diagnosis will better equip hematologists to counsel patients and families and engage in appropriate treatment strategies for individual patients earlier in their [disease] course.” Hematologists are doctors who specialize in diagnosing, treating, and managing diseases of the blood.
The study, “Predicting Development of Pediatric Chronic Immune Thrombocytopenia at Disease Onset Using a Statistical Risk Model,” was published in the journal Blood.
In ITP, the immune system attacks and destroys platelets, the cell fragments that help to clot blood and stop bleeding after an injury. Without enough platelets — a condition medically referred to as thrombocytopenia — people with ITP run a high risk of bruising and bleeding.
ITP can develop in children, but in most cases, the disease spontaneously resolves within about a year of onset.
Yet, in up to 30% of cases, ITP becomes chronic, meaning it persists beyond one year.
Doctors have no way to reliably predict chronic ITP risk
Doctors are currently unable, however, to reliably predict who may be at a higher risk of developing chronic ITP based on clinical data collected at the time of an ITP diagnosis.
“It is possible that patients at risk of developing chronic disease may benefit from intervention to prevent progression of disease and the consequences of disease,” the scientists wrote.
To address this problem, a team of researchers from institutions spanning the U.S. developed a multivariable statistical model using clinical data collected at ITP diagnosis to predict who may be at risk of developing chronic disease. The model was trained on data from 611 children with ITP and validated on an additional 161 youngsters with the condition.
Within the training group, ITP spontaneously resolved in 410 children (67%); the remaining 201 patients developed chronic ITP (33%).
Children who developed chronic disease were much older at diagnosis — with a median age of 9.1 versus 3.9 years — than those whose condition spontaneously resolved. Also, fewer boys than girls (43% vs. 54%) ended up with chronic disease.
Chronic patients also had a higher median platelet count at diagnosis, the data showed. Further, a higher proportion had secondary ITP (9.3% vs. 1.2%), when the disease is caused by a separate underlying condition.
Having secondary ITP increased risk by 6 times
After entering all the clinical data in the model, the researchers identified several key factors that may help predict which patients are most likely to develop chronic ITP.
Older age at the time of diagnosis was a strong predictor of chronic ITP, increasing by 13% per year, while boys had a 28% lower risk.
The data showed that abnormal levels of three types of antibodies, namely, immunoglobulin G (IgG), IgA, and IgM, were predictors of chronic disease, as were higher counts of platelets and lower levels of white blood cells.
The team noted that the association between chronic disease risk and white blood cell and platelet counts at diagnosis was nonlinear, meaning the risk plateaued at higher counts.
If ITP was secondary, or caused by another condition, the risk of chronic ITP increased nearly sixfold. Moreover, a positive direct antiglobulin test (DAT) at diagnosis, which looks for antibodies coating red blood cells, more than doubled the risk of chronic ITP.
We developed a prediction model for risk of developing chronic ITP at the time of ITP diagnosis. … The model performed well on internal and external validation, although larger validation studies are needed prior to widespread implementation into clinical practice.
The scientists then provided examples of predictions to illustrate the model’s outcomes.
The risk of developing chronic ITP was 19% if the patient was a 5-year-old boy with no underlying ITP cause, a negative DAT test, normal levels of antibodies (IgA, IgG, IgM) and white blood cells, but very low platelet counts (7 × 10⁹/L). In comparison, the risk rose to 45% if the boy was 15 years old with the exact same test results.
For the same 5-year-old boy, if his platelet count had been higher at 40 × 10⁹/L instead of 7 × 10⁹/L, his risk of chronic ITP would rise from 19% to about 33%.
When the team input data from validation datasets, the model’s overall accuracy in predicting chronic ITP ranged from 75% to 80%.
“Utilizing data from a large cohort of pediatric patients with ITP, we developed a prediction model for risk of developing chronic ITP at the time of ITP diagnosis,” the researchers concluded. “The model performed well on internal and external validation, although larger validation studies are needed prior to widespread implementation into clinical practice.”
The tool is now available for testing, with a website for clinicians on how to validate and implement it for “local use.”
