Abstract A023 Establishment of the consortium for childhood cancer predisposition and the childhood cancer predisposition study
Bibliographic record
Abstract
Abstract Background: Genetic predisposition contributes to a much higher proportion of cancer in children than previously appreciated. This creates a unique opportunity to develop improved methods to identify children at increased risk for cancer, enable early detection or prevention of tumors, and improve cure rates with decreased morbidity. However, several challenges have impeded successful research and systematic approaches to the care of children with cancer predisposition. Methods: We established the Consortium for Childhood Cancer Predisposition (C3P), currently comprised of seven large pediatric institutions in North America. The long-term goal of C3P is to improve outcomes for children with genetic susceptibility to cancer through collaborative research and data sharing. To this end, we have developed the Childhood Cancer Predisposition Study (CCPS), a multicenter registry and biorepository, to achieve three main aims: 1) Establish and maintain the infrastructure for recruitment, participation, collection and sharing of clinical data and biological samples for children with cancer predisposition syndromes (CPS); 2) Define the spectrum of disease in children with CPS and explore the unique characteristics and management approaches of CPS-related tumors compared to their sporadic counterparts; and 3) Evaluate the clinical impact and effectiveness of standard and emerging tumor surveillance strategies. Results: The CCPS opened to enrollment in May, 2021 and is currently recruiting at 5 member sites. To date, 316 primary subjects and 64 family members have been enrolled, 193 in the last year. In total, more than 40 different cancer predisposition diagnoses are represented among participants, including those that are more prevalent, e.g., Li-Fraumeni syndrome (n=44), DICER1 syndrome (n=27), and PTEN Hamartoma Syndrome (n=23), and those which are very rare, e.g., Rothmund-Thomson syndrome (n=2). There is excellent uptake on obtaining samples, with the CCPS Biorepository at Emory University receiving biospecimens from 261 subjects to date, including constitutional DNA (n=261), frozen peripheral blood mononuclear cells (n=37), and plasma samples for ctDNA analysis (n= 34). Conclusions: C3P has established the infrastructure to facilitate comprehensive collaborative work to improve outcomes for children with cancer predisposition, which represent a wide variety of disorders. Future efforts will include the development of innovative strategies to promote recruitment beyond the primary C3P sites and the support of additional clinical and biological studies of specific CPS. Citation Format: Christopher C. Porter, Garrett M. Brodeur, Lisa Diller, Chloe Edgerton, Junne Kamihara, Wendy Kohlmann, Suzanne P. MacFarland, Luke Maese, David Malkin, Kim E. Nichols, Melissa R. Perrino, Sharon E. Plon, Surya Rednam, Anita Villani. Establishment of the consortium for childhood cancer predisposition and the childhood cancer predisposition study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A023.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".