Investigating Epidemiological Patterns in Pediatric Oncology Through Data Integration and Visualization
Abstract
This article describes a study that aimed to investigate epidemiological patterns in the DATASUS and RHC databases, based on the extraction and processing of data related to childhood cancer. From the collected, processed and integrated data, a web system was developed consisting of three dashboards, which present different types of interactive visual representations of pediatric oncology data. The system is available for public access, since the information collected from the aforementioned databases is already anonymized, and aims to assist, mainly, in strategic decision-making related to the treatment and prevention of childhood cancer.References
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Osterman, T. J., Terry, M., and Miller, R. S. (2020). Improving cancer data interoperability: The promise of the minimal common oncology data elements (mcode) initiative. JCO Clinical Cancer Informatics, (4):993–1001. PMID: 33136433.
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Rodriguez-Galindo, C., Friedrich, P., Morrissey, L., and Frazier, L. (2013). Global challenges in pediatric oncology. Current Opinion in Pediatrics, 25(1):3–15.
Batko, K. and Ślezak, A. (2022). The use of big data analytics in healthcare. Journal of Big Data, 9(1):3.
Bernardi, F. A., Alves, D., Crepaldi, N. Y., Yamada, D. B., Lima, V. C., and Lopes Rijo, R. P. C. (2022). Data quality in health research: a systematic literature review. medRxiv.
Chan, T., Sebok-Syer, S., Thoma, B., Wise, A., Sherbino, J., and Pusic, M. (2018). Learning analytics in medical education assessment: The past, the present, and the future. AEM Education and Training, 2(2):178–187.
Costantini, A., Michels, F., Ruhl, J., Hill, S., Kohler, B., and Negoita, S. (2023). The trajectory of pediatric cancer data and collection in the united states. Journal of Registry Management, 50(3):82–84.
Gazzarata, R., Almeida, J., Lindsköld, L., Cangioli, G., Gaeta, E., Fico, G., and Chronaki, C. E. (2024). Hl7 fast healthcare interoperability resources (hl7 fhir) in digital healthcare ecosystems for chronic disease management: Scoping review. International Journal of Medical Informatics, 189:105507.
INCA (2023). Estimativa 2023: incidência de câncer no Brasil. Instituto Nacional de Câncer José Alencar Gomes da Silva. Coordenação de Prevenção e Vigilância, Rio de Janeiro.
Jensen, P. B., Jensen, L. J., and Brunak, S. (2012). Mining electronic health records: towards better research applications and clinical care. Nature Reviews Genetics, 13(6):395–405.
Khan, S. S. and Qin, G. (2018). A review on healthcare data analytics: Recent advances and future directions. Journal of King Saud University-Computer and Information Sciences.
Linet, M. S., Ries, L. A. G., Smith, M. A., Tarone, R. E., and Devesa, S. S. (1999). Cancer surveillance series: Recent trends in childhood cancer incidence and mortality in the united states. JNCI: Journal of the National Cancer Institute, 91(12):1051–1058.
Mohammadzadeh, Z., Ghazisaeedi, M., Nahvijou, A., Rostam Niakan Kalhori, S., Davoodi, S., and Zendehdel, K. (2017). Systematic review of hospital based cancer registries (hbcrs): Necessary tool to improve quality of care in cancer patients. Asian Pacific Journal of Cancer Prevention, 18(8):2027–2033.
Obermeyer, Z. and Emanuel, E. J. (2016). Predicting the future - big data, machine learning, and clinical medicine. New England Journal of Medicine, 375(13):1216–1219.
Osterman, T. J., Terry, M., and Miller, R. S. (2020). Improving cancer data interoperability: The promise of the minimal common oncology data elements (mcode) initiative. JCO Clinical Cancer Informatics, (4):993–1001. PMID: 33136433.
Park, S., Bekemeier, B., Flaxman, A., and Schultz, M. (2022). Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review. Informatics for Health and Social Care, 47(2):175–193.
Rodriguez-Galindo, C., Friedrich, P., Morrissey, L., and Frazier, L. (2013). Global challenges in pediatric oncology. Current Opinion in Pediatrics, 25(1):3–15.
Published
2025-06-09
How to Cite
RIBEIRO, Felipe de Assis; SINIGAGLIA, Marialva; ÁVILA, Alexsandro Vargas de; SILVA, Isabel Cristina Siqueira da.
Investigating Epidemiological Patterns in Pediatric Oncology Through Data Integration and Visualization. In: BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTH (SBCAS), 25. , 2025, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 677-688.
ISSN 2763-8952.
DOI: https://doi.org/10.5753/sbcas.2025.7713.
