July 22: A new study led by Children’s Hospital Los Angeles may help answer a key question for physicians treating children with immune thrombocytopenia (ITP): Which patients will recover on their own, and which will develop chronic disease?
The multicenter study, published in the journal Blood- Opens in a new window, developed and validated a model that uses clinical and laboratory data to identify children at high risk for chronic ITP.
“The goal is to identify high-risk patients when they are first diagnosed with ITP,” says Taylor Kim, MD, a hematologist in the Cancer and Blood Disease Institute at Children’s Hospital Los Angeles and senior author of the study. “Knowing which children are likely to develop chronic disease would allow us to start treatment earlier, tailor therapy to the individual patient, and help mitigate bleeding risk.”
Predicting chronic ITP at diagnosis
ITP is an autoimmune blood disorder where the immune system attacks and destroys a patient’s platelets – the cells that help blood to clot – leading to bruising and bleeding.
Children can develop ITP following a virus, and most recover quickly without treatment. But some develop chronic ITP, which leads to long-term bleeding issues and is linked to an increased likelihood of other autoimmune diseases and immunodeficiency disorders. It also makes it difficult for children to participate in activities like sports.
A major challenge for doctors is not being able to determine at diagnosis which kids will recover quickly and which will develop chronic disease.
“When a child comes in with ITP, we usually just observe them and wait for their ITP to go away on its own, which happens in around 70% to 80% of cases,” Dr. Kim says. “But there’s a portion of patients who never get better or don’t get better for a long time, and it would be great if we could identify those patients in advance.”
This idea inspired the multi-site study. It began as a retrospective chart review that gathered clinical data from patients with ITP at several pediatric hospitals within the Pediatric ITP Consortium of North America, an organization dedicated to improving treatments and quality of life for individuals with ITP.
The clinical data gathered for each patient included gender, age, platelet count, levels of immunoglobulins or antibodies, direct antiglobulin test (DAT) results (which can sometimes be linked to other autoimmune disorders), and levels of lymphocytes.
Dr. Kim and her colleagues looked at these factors for each patient at the time of ITP diagnosis and identified patterns for the patients who then progressed to chronic ITP.
They found that:
- Older children were more likely to develop chronic ITP than younger children.
- Lower lymphocyte counts corresponded with a higher likelihood of chronic ITP.
- High levels of immunoglobulin G (IgG) were more associated with resolving ITP.
- Low levels of immunoglobulin M (IgM) and immunoglobulin A (IgA) were linked to chronic ITP.
- Higher platelet counts are associated with chronic ITP development.
These patterns were used to build the predictive model, a multivariate logistic regression model that Dr. Kim and her fellow investigators validated using clinical data from a separate cohort of patients.
Looking ahead
The prediction tool performed well in the study and is available online- Opens in a new window, although additional validation studies are needed before widespread clinical implementation.
To that end, Dr. Kim hopes to next further evaluate the model across a broader array of hospitals and clinics. She is also exploring the development of a mobile application to make it more easily accessible for clinicians.
Meanwhile, the team is exploring the creation of similar predictive models for specific ITP outcomes, such as major bleeding risk, as well as for autoimmune conditions such as lupus.
“I think the concept can be applied to a lot of different clinical questions,” she says. “That is what makes it so exciting.”