Children with cancer experience multiple symptoms due to their disease and as a result of treatment. The purpose of this study was to demonstrate the feasibility and potential utility of using latent profile analysis (LPA), a type of cluster analysis, in children with cancer to identify groups of patients who experience similar levels of symptom severity and impairment of physical function.Procedure.
We analyzed patient-reported symptom and functional data previously collected using the Pediatric Patient Reported Outcomes Measurement Information System (PROMIS). LPA was used to identify and characterize groups of patients who reported similar levels of symptom severity and functional impairment. We then used the multinomial logit model to examine demographic and disease characteristics associated with symptom/function profile membership.Results.
The analysis included 200 patients in treatment or in survivorship. We identified four symptom/function profiles; children currently receiving cancer treatment and those with at least one other medical problem were more likely to be members of the profile with the highest levels of symptom severity and functional impairment. Gender, age, race/ethnicity, and tumor type were not associated with profile membership.Conclusions.
LPA is a cluster research methodology that provides clinically useful results in pediatric oncology patients. Future studies of children with cancer using LPA could potentially lead to development of clinical scoring systems that predict patients' risk of developing more severe symptoms and functional impairments, allowing clinicians, patients, and parents to better anticipate and prevent the multiple symptoms that occur during and after treatment for childhood cancer.