The proposed work aims to use Data collection and data analytics tools with machine learning algorithms to analyse the incidence of cases of retinoblastoma in Indian children. The aim is to study the trend in incidence , recurrence and survival prediction in these cases.
Patients who are undergoing treatment can submit their spoken queries in their preferred language and these queries can be evaluated to find emergency situations or remote assistance to the patients.
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 »
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 »
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.
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 »
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 »
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.
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 »
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 »
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.
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 »
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 »
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 »