The international pediatric oncology community has a long history of research collaboration. In the United States, the 2019 launch of the Children's Cancer Data Initiative puts the focus on developing a rich and robust data ecosystem for pediatric oncology. In this spirit, we present here our experience in constructing the Pediatric Cancer Data Commons (PCDC) to highlight the significance of this effort in fighting pediatric cancer and improving outcomes and to provide essential information to those creating resources in other disease areas. The University of Chicago's PCDC team has worked with the international research community since 2015 to build data commons for children's cancers. We identified six critical features of successful data commons design and implementation: (1) establish the need for a data commons, (2) develop and deploy the technical infrastructure, (3) establish and implement governance, (4) make the data commons platform easy and intuitive for researchers, (5) socialize the data commons and create working knowledge and expertise in the research community, and (6) plan for longevity and sustainability. Data commons are critical to conducting research on large patient cohorts that will ultimately lead to improved outcomes for children with cancer. There is value in connecting high-quality clinical and phenotype data to external sources of data such as genomic, proteomics, and imaging data. Next steps for the PCDC include creating an informed and invested data-sharing culture, developing sustainable methods of data collection and sharing, standardizing genetic biomarker reporting, incorporating radiologic and molecular analysis data, and building models for electronic patient consent. The methods and processes described here can be extended to any clinical area and provide a blueprint for others wishing to develop similar resources.

In this article, we will discuss the genesis, evolution, and progress of the INternational Soft Tissue SaRcoma ConsorTium (INSTRuCT), which aims to foster international research and collaboration focused on pediatric soft tissue sarcoma. We will begin by highlighting the current state of clinical research for pediatric soft tissue sarcomas, including rhabdomyosarcoma and non‐rhabdomyosarcoma soft tissue sarcoma. We will then explore challenges and research priorities, describe the development of INSTRuCT, and discuss how the consortium aims to address key research priorities.

PURPOSE Severe and febrile neutropenia present serious hazards to patients with cancer undergoing chemotherapy. We seek to develop a machine learning–based neutropenia prediction model that can be used to assess risk at the initiation of a chemotherapy cycle. MATERIALS AND METHODS We leverage rich electronic medical records (EMRs) data from a large health care system and apply machine learning methods to predict severe and febrile neutropenic events. We outline the data curation process and challenges posed by EMRs data. We explore a range of algorithms with an emphasis on model interpretability and ease of use in a clinical setting. RESULTS Our final proposed model demonstrates an out-of-sample area under the receiver operating characteristic curve of 0.865 (95% CI, 0.830 to 0.891) in the prediction of neutropenic events on the basis of only 20 clinical features. The model validates known risk factors and offers insight into potential novel clinical indicators and treatment characteristics that elevate risk. It relies on factors that are directly extractable from EMRs, provided a tool can be easily integrated into existing workflows. A cost-based analysis provides insight into optimal risk thresholds and offers a framework for tailoring algorithms to individual hospital needs. CONCLUSION A better understanding of neutropenic risk on an individual level enables a more informed approach to patient monitoring and treatment decisions.

Introduction: Despite substantial progress in the treatment of HL, older pts remain an unmet treatment need. Methods: We sought to identify the treatment patterns and outcomes in HL pts ≥ 60 y/o included in the Brazilian HL registry. Results: A total of 141 pts with HIV negative classical HL aged ≥ 60, diagnosed from January 2009 to December 2018, were identified. Five pts were excluded, leaving 136 pts available for analysis. The median age was 66 years old (60-90), 49% were female, PS >1 in 21%, advanced stage in 72%, anemia in 38%, high-risk IPS score in 62% and nodular sclerosis (NS) in 49%. In comparison to younger pts, pts ≥ 60 y/o were more likely to have a high-risk IPS score (63% vs 38%, P<.0001), and histopathology other than NS (51% vs 23%, P<.0001). Also, older pts were more likely to have a lower socioeconomic status (SES, 47% vs 30%, P< .0001) and a lower educational level (25% vs 3%, P<.0001). Median follow-up was 45 months (0-144) for all pts and 64 months (14-144) for pts alive. ABVD was the first-line treatment in 96% of pts. Twenty-one pts (15%) died during the first treatment. In 18 (86%) of these pts, the cause of death was an infection or a complication of treatment. The 5-year PFS and 5-year OS were 55% and 59%. The 5-year PFS in localized and advanced disease were 72% and 47% (P=0.013). The 5-year OS in localized and advanced disease were 81% and 51% (P=0.013). Among 131 pts treated with ABVD, 5% presented cardiac toxicity, 11% lung toxicity and 12% severe infection. 65% of pts used bleomycin for > 2 cycles and 44% for > 4 cycles. In comparison with 2009-2014, there was a decrease in the use of bleomycin for > 2 cycles in 2015-2018 (88% x 45%, P<0.0001). The impact of (SES) on outcomes was studied in pts treated with ABVD. The fatality ratio during treatment was 9% and 21% for higher and lower SES (P=0.10). The 5-year PFS for higher and lower SES were 71% and 46% (P = .005), and the 5-year OS 72% and 55% (P = .027), respectively. After adjustments for potential confounders, lower SES remained independently associated with poorer survival for ] for PFS). Conclusion: Advanced stage and poor-risk pts predominated. Inferior outcomes are in part due to advanced disease at diagnosis and to an excess of deaths during treatment. SES is an independent factor for shorter survival. The use of bleomycin remains high, despite a substantial decrease in recent years.