Abstract 1296: Family history of cancer and rhabdomyosarcoma in children: a report from the Children's Oncology Group
Bibliographic record
Abstract
Abstract Introduction: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. In the United States, about 350 children are diagnosed with RMS per year. The two major histologic subtypes of RMS are embryonal (ERMS; approximately 70% of cases) and alveolar (ARMS; approximately 30% of cases). A small percentage of RMS cases are associated with germline mutations in TP53, HRAS, and NF1. However, it has been difficult to show if inherited susceptibility may play a role in sporadic cases due to the rarity of these tumors and the potential etiologic heterogeneity between subtypes. Objective: In order to better characterize genetic susceptibility to childhood RMS, we evaluated the role of family history of cancer using data from the largest case-control study of RMS to date. Methods: Cases (n=322) were enrolled from the third trial run by the Intergroup Rhabdomyosarcoma Study Group. Population-based controls (n=322) were pair matched to cases on race, sex, and age. Conditional logistic regression was used to evaluate cancer history among first- and second-degree relatives and the association with childhood RMS by generating adjusted odds ratios (aOR) and 95% confidence intervals (CI). Stratified analyses were conducted to independently evaluate the association of family cancer history and childhood RMS for children who had relatives diagnosed with a cancer before the age of 40 years and those with relatives diagnosed when older than 40 years. The association of family cancer history and childhood RMS was also assessed separately for children diagnosed with ERMS and those diagnosed with ARMS. Results: While there were no statistically significant associations, three patterns appeared to emerge: 1) having any first degree relative with a history of cancer was more common in RMS cases than controls (aOR=1.46, 95% CI: 0.72-2.97); 2) having a first degree relative who was younger at diagnosis (<40 years of age) appeared to convey a greater risk of RMS (aOR=1.55, 95% CI: 0.96-2.51); and 3) having a first degree relative with cancer was more common for those with ERMS compared to ARMS (aOR=1.58, 95% CI: 0.61-4.10 vs. aOR=1.01, 95% CI: 0.29-3.50, respectively). Conclusions: In the largest analysis of its kind to date, we found that family history of cancer appeared to increase the risk of childhood RMS. While the associations were not statistically significant, this is likely due to the low prevalence of family cancer history in this population (i.e., 6.6% overall). Ultimately, these findings tentatively support the role of inherited genetic susceptibility in the development of childhood RMS. Citation Format: Philip J. Lupo, Heather E. Danysh, Sharon E. Plon, David Malkin, Simone Hettmer, Douglas S. Hawkins, Stephen X. Skapek, Logan G. Spector, Karin Papworth, Beatrice Melin, Erik B. Erhardt, Seymour Grufferman. Family history of cancer and rhabdomyosarcoma in children: a report from the Children's Oncology Group. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1296. doi:10.1158/1538-7445.AM2014-1296
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".