Purpose Evaluate the potential risk for long-term complications related to cancer therapy among childhood cancer survivors who completed treatment in Tanzania at Bugando Medical Centre (BMC), and compare the relative risk assessment of BMC survivor cohort and British Childhood Cancer Survivor Study (BCCSS) cohort. Methods Files of all patients age <18 yo with an oncologic diagnosis who received and completed their treatment at BMC from 2016 to 2022 were retrospectively reviewed. Extracted data included patient demographics, primary disease diagnosis and site, treatment received, and cumulative treatment doses. BCCSS risk assessment was assigned. Predicted long term follow up surveillance needs were extrapolated from published Children’s Oncology Group Long-Term Follow-Up Guidelines. Results A total of 173 patients were included in the survivor cohort (47% female, average age =7). The most common diagnoses were Burkitt lymphoma (26%, n=45) and Wilms (30%, n=52). Within the cohort, 98% received chemotherapy (n=170), 49% (n=73) underwent tumor resection, and 18% (n=32) received radiation. Distribution of BCCSS late effect risk assessment included 6% low risk (n=10), 80% moderate risk (n=139) and 14% (n=24) high risk. Based on treatment received, the late effects with highest potential risk were cardiomyopathy (57% of patients, n=98), bladder and urinary tract toxicity (50%, n=87), and ototoxicity (22%, n=38). Conclusion Childhood cancer survivors at BMC have a higher risk of late effects as compared to published survivor cohorts in high-income countries. There is a need to develop and improve long-term follow-up care for survivors by enhancing patient and provider education to promote early detection of late effects.[1](#fn-0002)

Background: Clinical informatics tools to integrate data from multiple sources have the potential to catalyze population health management of childhood cancer survivors at high risk for late heart failure through the implementation of previously validated risk calculators. Methods: The Oklahoma cohort (n=365) harnessed data elements from Passport for Care (PFC) and the Duke cohort (n=274) integrated cancer registry and electronic health record data, using standard query language, to automatically extract chemotherapy exposures for survivors <18 years old at diagnosis. The Childhood Cancer Survivor Study (CCSS) late cardiovascular risk calculator was implemented and risk groups for heart failure were compared to the Children’s Oncology Group (COG) Long-Term Follow-up Guidelines. Results: The Oklahoma and Duke cohorts both observed good overall concordance between the CCSS and COG risk groups for late heart failure with weighted Kappa statistics of 0.70 and 0.75, respectively. Low-risk groups showed excellent concordance (Kappa >0.9). Moderate and high-risk groups showed moderate concordance (Kappa 0.44-0.60 across both cohorts). In the Oklahoma cohort, adolescents at diagnosis were significantly less likely to receive guideline-adherent care for echocardiogram surveillance compared with survivors <13 years old at diagnosis (OR 0.22; 95% CI 0.10-0.49). Conclusions: Clinical informatics tools represent a feasible approach to leverage discrete data elements regarding key treatment exposures from PFC or the EHR to successfully implement previously validated late cardiovascular risk prediction models on a population health level. Real-world evidence on the concordance of CCSS, COG, and IGHG risk groups promises to refine current guidelines and identify inequities in guideline-adherent care.