Pediatric oncologist willingness to offer germline <i>TP53</i> testing in osteosarcoma
Bibliographic record
Abstract
BACKGROUND: Li-Fraumeni syndrome (LFS) is a cancer predisposition syndrome caused by mutations in the tumor-suppressor gene TP53. Osteosarcoma is a sentinel cancer in LFS. Prior studies using Sanger sequencing platforms have demonstrated that 3% of individuals with osteosarcoma harbor a mutation in TP53. New data from next-generation sequencing have demonstrated that 3.8% of patients with osteosarcoma have a known pathogenic variant, and an additional 5.7% carry exonic variants of unknown significance in TP53. METHODS: Pediatric oncologists were e-mailed an anonymous 18-question survey assessing their willingness to offer TP53 germline testing to a child with osteosarcoma with or without a family history, and they were evaluated for changes in their choices with the prior data and the new data. RESULTS: One hundred seventy-seven pediatric oncologists (22%) responded to the survey. Respondents were more likely to offer TP53 testing to a patient with a positive family history (77.4% vs 12.4%; P < .0001). Significantly more providers responded that they would offer TP53 testing once they were provided with the new data (25.4% vs 12.4%; P = .0038). The proportion of providers who responded that they were unsure increased significantly when they were presented with the new data (25.4% vs 10.2%; P = .0002). Potential implications for other family members and the possibility that surveillance imaging would detect new malignancies at an earlier stage were important factors influencing a provider's decision to offer TP53 testing. CONCLUSIONS: Recent data increase the proportion of providers willing to offer testing, and this suggests concern on the part of pediatric oncologists that variants of unknown significance may be disease-defining in rare cancers. Cancer 2018;124:1242-50. © 2018 American Cancer Society.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".