Abstract 6385: St. Jude Survivorship Portal: Sharing and analyzing large clinical and genomic datasets from pediatric cancer survivors
Bibliographic record
Abstract
Abstract Survivors of childhood cancer are at risk for developing various adverse health conditions as adults that are attributable to the cancer and treatments they were exposed to as children. Cancer survivorship research relies on large-scale, longitudinal studies that generate a wide range of demographic, clinical, and genetic data on cancer survivors. Nevertheless, the absence of cancer survivorship data portals has made it challenging to broadly share cancer survivorship data. We have created the St. Jude Survivorship Portal (https://survivorship.stjude.cloud), the first data portal for sharing, analyzing, and visualizing childhood cancer survivorship data. The portal hosts data from two large cohorts of pediatric cancer survivors: the St. Jude Lifetime Cohort Study (SJLIFE) and the Childhood Cancer Survivor Study (CCSS). Over 1,600 clinical variables and over 400 million genetic variants from over 7,700 childhood cancer survivors are stored on the portal. The data can be explored using an interactive data dictionary and a genome browser specialized for population genetics analysis. Summary statistics of variables and genetic variants are computed on-the-fly and visualized through interactive and customizable charts. Survivor cohorts can be filtered or customized and may also be divided into groups for comparative analysis. Tools for performing cumulative incidence and regression analyses have been integrated into portal environment, allowing users to perform real-time statistical analyses on the stored survivorship data. Finally, users may also download individual-level clinical and genotype data from the portal using the controlled-access data download feature. Through various use-cases of survivorship research, we used the portal to explore the ototoxic effects of platinum-based chemotherapy, uncover a novel association between limb amputation, age, and long-term mental health, and identify a novel haplotype in MAGI3 strongly associated with cardiomyopathy specifically in survivors of African ancestry. The St. Jude Survivorship Portal provides a comprehensive, powerful, and easy-to-use interface for sharing and analyzing childhood cancer survivorship data that will serve as a valuable research tool for the broader survivorship research community. Citation Format: Gavriel Matt, Edgar Sioson, Jian Wang, Congyu Lu, Airen Zaldívar Peraza, Karishma Gangwani, Robin Paul, Colleen Reilly, Aleksandar Acić, Kyla Shelton, Qi Liu, Stephanie Sandor, Clay McLeod, Weiyu Qiu, Jaimin Patel, Fan Wang, Cindy Im, Zhaoming Wang, Carmen L. Wilson, Nickhill Bhakta, Kirsten Ness, Gregory T. Armstrong, Melissa M. Hudson, Leslie L. Robison, Jinghui Zhang, Yutaka Yasui, Xin Zhou. St. Jude Survivorship Portal: Sharing and analyzing large clinical and genomic datasets from pediatric cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6385.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.069 | 0.029 |
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".