Current state of diagnostic genetic testing in pediatric sarcoma: Survey and review by the Cancer Genomics Consortium Sarcoma Working Group
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The genomic landscape of pediatric sarcomas is constantly expanding, and the utilization of integrated cytogenetic and molecular evaluation of these tumors for diagnosis, prognostication, and therapeutic implications continues to evolve. As a result, there are diverse approaches to the clinical practice of genomic testing in pediatric sarcomas. The Cancer Genomics Consortium Sarcoma Working Group conducted a survey to understand the current state of diagnostic genetic testing for pediatric sarcomas and assess the challenges faced in the field. Among 46 respondents across the United States and Canada, most utilized conventional karyotyping (61 %) and/or fluorescence in situ hybridization (87 %). Molecular methodologies, such as chromosomal microarray (30 %), targeted RT-PCR (22 %), gene fusion sequencing panels (35 %), pan-cancer sequencing panels (37 %), exome sequencing (11 %), and genome sequencing (7 %) were less frequently implemented clinically. When asked about challenges in the field of pediatric sarcoma, a scarcity of standard practice testing guidelines was noted most commonly, especially in the setting of limited tissue availability. Systematic evidence reviews and guidelines are needed for pediatric sarcomas with a consideration for multidisciplinary and international collaboration of individuals representing both high- and low-resource settings. As a resource in the interim, three case-based testing workflow scenarios are presented based on working group member experience to illustrate how differing technologies could be applied during evaluation considering diagnostic, prognostic and/or therapeutic needs. Finally, emerging technologies that are being applied to the diagnostic genetic evaluation of pediatric sarcomas are described, which upon implementation, may serve to streamline the work-up and further optimize patient care.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it