Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia
Kaskovich S, Wyatt KD, Oliwa T, Graglia L, Furner B, Lee J, et al. JCO Clin Cancer Inform. 2023;e2300009.
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. Full text
Creating a data commons: The INternational Soft Tissue SaRcoma ConsorTium (INSTRuCT)
Wyatt KD, Birz S, Hawkins DS, Minard-Colin V, Rodeberg DA, Sparber-Sauer M, et al. Pediatr Blood Cancer. 2022;e29924.
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. Full text
Mapping Pediatric Oncology Clinical Trial Collaborative Groups on the Global Stage
Major A, Palese M, Ermis E, James A, Villarroel M, Klussmann FA, et al. JCO Glob Oncol. 2022;8:e2100266.
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. Full text
Pediatric Cancer Data Commons: Federating and Democratizing Data for Childhood Cancer Research
Plana A, Furner B, Palese M, Dussault N, Birz S, Graglia L, et al. JCO Clin Cancer Inform. 2021;5:1034-1043.
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. Full text
Using big data in pediatric oncology: Current applications and future directions
Major A, Cox SM, Volchenboum SL. Sem Oncol. 2020;47(1):56-64.
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. Full text
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.
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. Full text
Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and Future
Liang WH, Federico SM, London WB, Naranjo A, Irwin MS, Volchenboum SL, Cohn SL. JCO Clin Cancer Inform. 2020;4:895-905.
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. Full text