(@anngraham)

Data Sharing

Standardize Sharing

Challenges: There needs to be standardization of data reporting and sharing across institutions. Patients need their data accessible and available to share at will. One portal available by all researchers - such as cBio - where individuals could ensure that their redacted data was uploaded into Data needs to live in treating institution as well as made available for all researchers with an interest in a given area. ...more »

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(@anngraham)

Engagement

Ask - Activate - Update

To collect data of any kind from the pediatric cancer community is as easy as asking for it. This community is anxious for innovation toward kinder treatments, and they are ready to help. The next step is to make it easy to do. Engage nonprofit organizations who share research, are engaged with the wider community, are trusted and can activate their members to participate. Commit to updating participants on the impact ...more »

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(@erin.barthel)

Data Collection

Prospective data collection of late effects

I would love to see a way to prospectively collect data on late effects. We have so many new drugs coming out and it would be great to initiate this now so we can start collecting late effect data. So much of our knowledge comes from retrospective research collections. This database could be great way to more accurately learn when these late effects develop and what are patients are at risk for with new drugs.

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(@jaguillot)

Data Collection

Overall Success Metrics Dashboard

HOW DO WE MEASURE SUCCESS? It seems that we are currently lacking centralized, accurate, high-level progress metrics in childhood cancer. How do we know, year over year, if our countless programs/projects are actually moving the needle? Unless I'm missing something, I believe we need a centralized, easy to read, childhood cancer DASHBOARD, that counts EVERY child diagnosed, and includes very basic but highly accurate ...more »

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(@sfshih)

Data Collection

Multi-level data and longitudinal data collection: identifying the root causes for child cancer

From the prevention perspective, we should collect both family-level and also environmental-level data to help us identify the determinants of child cancers. On the family level, I would suggest that we collect the data from at least three years before the mother's pregnancy to the time of her child being diagnosed as cancers. Environmental-level includes the family social environment for both pregnant women and children ...more »

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(@snydercharlie)

Research Questions

Li–Fraumeni syndrome

Gain a better understanding of how p53 tumor suppression could potentially be restored in those with Li–Fraumeni syndrome using gene editing techniques or other mechanisms.

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(@duanyf)

Data Collection

The advantages of patient-derived orthotopic xenograft (PDOX) models for individualized osteosarcoma treatment and drug discover

Osteosarcoma is the most common primary malignant bone tumor which occurs mainly in children and adolescents. Due to rarity, heterogeneity, metastatic potency, and poor response rates to conventional systemic therapy, individualized precision oncology and novel drug discovery in osteosarcoma are warranted. Toward this goal, our laboratory has established the patient-derived orthotopic xenograft (PDOX) model using surgical ...more »

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(@nicolevasilevsky)

Data Analysis Tools

Mondo Disease Ontology: harmonizing disease concepts around the world

We will present our work on the Mondo Disease Ontology during the poster session at the Childhood Cancer Data Initiative Symposium. The Mondo ontology is a structured representation of cross-species diseases, and provides a logic-based structure for unifying multiple disease resources, which can be used for annotation and computational integration of disease data. The poster and abstract are shared at the link below. ...more »

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(@phillipsca)

Data Infrastructure

Common data model

Currently, large amounts of data exist for childhood cancer. The biggest of these is the data generated by the Children's Oncology Group. In order for data to be used, it must be formatted and structured appropriately. This starts with a common data model. Incorporating something similar to the data model used by PCORnet and applying it to childhood cancer data (COG and others) would maximize its utility.

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(@amanda.haddock)

Data Infrastructure

Quality Control Standards

There should be stringent standards in place, starting with data creation, to ensure that only high quality data (physical and digital) is submitted and stored. The Children's Brain Tumor Tissue Consortium has developed a set of data standards for each type of data to shepherd the collection and submission process so that researchers know they can count on a reliable resource, which speeds the research process. Data ...more »

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(@susanmcgovern)

Research Questions

Image-guided evaluation of the late effects of therapeutic childhood radiation

Parents of children who receive radiation for cancer treatment want to know about the long term effects of radiation on growth and development; robust data to answer these important questions are lacking. To address these questions, serial standard of care imaging could be collected from children undergoing radiation therapy at baseline and in followup. Using RTSTRUCT data in DICOM format, radiation dose to tumor volumes ...more »

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(@algustafson)

Data Infrastructure

Avoid redundancy of effort, look to CBBTC as a proven structure to build upon

Swifty Foundation encourages CCDI to build on the successes of CBTTC rather than beginning at ground zero. In 2014, just three years after its launch, CBTTC became the first and largest clinically annotated biospecimens repository with real time querablilty. With the launch of CAVATICA, its genomics analytic platform, it became the first brain tumor consortia to solve cloud-based, global WGS analysis, and was recognized ...more »

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