A Clinical and Sociodemographic Risk Prediction Model Evaluating Adherence to Long-Term Care in Survivors of Childhood Leukemia

Background: Regular long-term follow-up care is important for surveillance and timely treatment of late effects after childhood leukemia therapy; however, structural barriers may disproportionately affect at-risk populations. Our objective was to evaluate factors associated with failure to utilize Long-Term Survivor (LTS) services following childhood leukemia treatment.

Methods: We electronically extracted and manually curated electronic health records to identify childhood leukemia cases diagnosed between 2011 and 2014 at Texas Children's Cancer and Hematology Center. Individuals treated with a stem cell transplant, or those that transferred to an outside hospital, relapsed, or died within two years of end of treatment (EOT) were excluded. Address at the EOT was geocoded using ArcGIS to estimate travel time to the clinic and Area Deprivation Index, a composite measure of 17 neighborhood-level social determinants of health (SDOH). Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between clinical factors and attending LTS Clinic. LTS Clinic attendance was defined as at least one visit with an LTS provider at any time following EOT. Predictive performance of the model was evaluated using area under the receiver operating characteristic curve (AUC-ROC).

Results: We identified 249 survivors of childhood leukemia that were eligible for LTS care in the designated time frame. Most were male (55%), non-Latino white (27%), Latino (57%), or non-Latino Black (10%) and were diagnosed at a median age of 5.7 years (range: 0.6-20). Overall, 41 survivors (16.5%) never attended LTS clinic. These included 15 survivors (6.0%) that were seen for initial disease follow-up after EOT but had no further contact with the hospital system beginning 2 years after EOT. In adjusted models, older age at EOT was associated with a higher likelihood of never attending LTS clinic (p<0.001). For example, survivors age 15 years and older at EOT were 7.4-times more likely to never attend LTS clinic (95% CI: 1.95-28.24). Additionally, compared with privately insured survivors, those with public insurance (OR=4.09, 95% CI: 1.67-9.99) and those that were uninsured (OR=4.68, 95% CI: 0.69-31.52) were more likely to never attend LTS clinic. LTS clinic attendance was largely comparable regardless of diagnosis, treatment exposures, sex, primary household language, and race/ethnicity, although Latinos were less likely to never attend an LTS visit compared with non-Latino whites (OR=0.36, 95% CI: 0.14-0.94). These observed associations were also independent of estimated travel time and neighborhood-level SDOH. Clinical and demographic factors provided reasonable predictive performance (AUC-ROC: 0.733, 95% CI: 0.655-0.821), e.g., categorizing survivors on their predicted probability of never attending LTS clinic based on observed clinical and demographic factors correctly identified 63.4% of survivors who never attend LTS clinic in the upper tertile of the risk prediction distribution.

Conclusions: Texas has the highest rates of uninsured children in the United States, comprising 12.7% of all children and 17.5% of Latino children living in the state (2019 American Community Survey data). Moreover, Medicaid eligibility in Texas is significantly limited for adults between the ages of 18 and 65 years. In this study, both older age at EOT and public insurance or uninsured status at EOT were strongly predictive of no documented LTS care among survivors of childhood leukemia, suggesting health insurance is major limiting factor to accessing survivorship services in Texas. Limiting predictive factors to race/ethnicity, age at EOT and payer status at EOT provides reasonable prediction of leukemia survivor that do not engage in LTS care (AUC-ROC: 0.711). Validation of a simple risk prediction model using information readily available in the electronic medical record at EOT may inform targeted interventions to augment access to survivorship services in this vulnerable population.

No relevant conflicts of interest to declare.