Targeted Enrollment in Pediatric Oncology Trials: A Vision for Just-in-Time Matching
Wyatt KD, Volchenboum SL. JCO Oncol Prac. 2024 Feb. doi: 10.1200/OP.23.00826
Standards-powered tools and innovative methods for trials administration and deployment can transform the clinical trials landscape, resulting in improved enrollment and, ultimately, better outcomes and improved care for children with cancer. Read more
Accelerating pediatric hodgkin lymphoma research: the hodgkin lymphoma data collaboration (NODAL)
Wyatt KD, Birz S, Castellino SM, et al. J Natl Cancer Inst. 2024. doi: 10.1093/jnci/djae013
We discuss the development of the Hodgkin Lymphoma Data Collaboration (NODAL) and foundational goals to advance pediatric Hodgkin lymphoma research. Read more
Using A Standardized Nomenclature to Semantically Map Oncology-Related Concepts from Common Data Models to a Pediatric Cancer Data Model
Carlson B, Watkins M, Li M, Furner B, Cohen E, Volchenboum SL. AMIA Annu Symp Proc. 2023;2023:874-883. PMID: 38222364
We describe an effort to utilize SSSOM, an emerging specification for semantically-rich data mappings, to provide a “hub and spoke” model of mappings from several common data models (CDMs) to the PCDC data model. Read more
Sociome Data Commons: A scalable and sustainable platform for investigating the full social context and determinants of health
Tilmon S, Nyenhuis S, Solomonides A, et al. J Clin Transl Sci. 2023;7(1):e255. doi:10.1017/cts.2023.670
Non-clinical aspects of life, such as social, environmental, behavioral, psychological, and economic factors, what we call the sociome, play significant roles in shaping patient health and health outcomes. This paper introduces the Sociome Data Commons, a new research platform that enables large-scale data analysis for investigating such factors. Read more
Data in pediatric oncology: Something old, something new
Wyatt KD. Pediatr Blood Cancer. Epub Nov 2023. doi:10.1002/pbc.30769
D4CG Senior Clinical Advisor Kirk Wyatt discusses the vital role of leveraging data to improve outcomes in pediatric cancer and the investments needed from the pediatric oncology community for these efforts to succeed. Read more
Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia
Kaskovich S, Wyatt KD, Oliwa T, et al. JCO Clin Cancer Inform. 2023;7:e2300009. doi: 10.1200/CCI.23.00009
We discuss the development of an automated tool for processing free-text clinical trial inclusion and exclusion criteria and matching patients to relevant clinical trials. Read more
Creating a data commons: The INternational Soft Tissue SaRcoma ConsorTium (INSTRuCT)
Wyatt KD, Birz S, Hawkins DS, et al. Pediatr Blood Cancer. 2022;69(11):e29924. doi: 10.1002/pbc.29924
We discuss the genesis, evolution, and progress of INSTRuCT, including challenges and research priorities, the development of the consortium, and how INSTRuCT aims to address key research priorities. Read more
Mapping Pediatric Oncology Clinical Trial Collaborative Groups on the Global Stage
Major A, Palese M, Ermis E, et al. JCO Glob Oncol. 2022;8:e2100266. doi: 10.1200/GO.21.00266
We describe pediatric cancer clinical trial groups on the international stage, with the goal of identifying the structure and function of these consortia, as well as the clinical data sources they collect, to reveal opportunities for collaborative efforts within these regions. Read more
Pediatric Cancer Data Commons: Federating and Democratizing Data for Childhood Cancer Research
Plana A, Furner B, Palese M, et al. JCO Clin Cancer Inform. 2021;5:1034-1043. doi: 10.1200/CCI.21.00075
We present our experience constructing the Pediatric Cancer Data Commons to highlight the significance of developing a rich and robust data ecosystem for pediatric oncology and to provide essential information to those creating resources in other disease areas. Read more
Using big data in pediatric oncology: Current applications and future directions
Major A, Cox SM, Volchenboum SL. Sem Oncol. 2020;47(1):56-64. doi: 10.1053/j.seminoncol.2020.02.006
We discuss the uses of big data in pediatric cancer, existing pediatric cancer registry initiatives and research, the challenges in harmonizing data to improve accessibility for study, and the future opportunities we see for innovation in this area. Read more
Data Commons to Support Pediatric Cancer Research
Volchenboum SL, Cox SM, Heath A, Resnick A, Cohn SL, Grossman R. Am Soc Clin Oncol Educ Book. 2017;37:746–752. doi: 10.1200/EDBK_175029
We describe current data commons and how they operate in the oncology landscape, and offer a practical paradigm for developing new commons. By centralizing data, processing power, and tools, there is a valuable opportunity to share resources and thus increase the efficiency, power, and impact of research. Read more
Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and Future
Liang WH, Federico SM, London WB, et al. JCO Clin Cancer Inform. 2020;4:895-905. doi: 10.1200/CCI.20.00074
In this review, the authors discuss the history of neuroblastoma risk classification in North America and Europe and highlight efforts by the International Neuroblastoma Risk Group (INRG) Task Force to develop a consensus approach for pretreatment stratification using seven risk criteria including an image-based staging system—the INRG Staging System. Read more