Epidemiology, Incidence, and Survival of Rhabdomyosarcoma Subtypes: SEER and ICES Database Analysis
Bibliographic record
Abstract
analysis. Survival was modeled with Kaplan-Meier survival curves and Cox proportional hazards models were used to assess the effect of age and gender on survival. Pleomorphic subtype had higher grade and larger sized tumors compared to other subtypes (p < 0.05). Pleomorphic and alveolar rhabdomyosarcoma had the worst overall survival with a 26.6% and 28.9% 5-year survival, respectively. Embryonal rhabdomyosarcoma had the highest 5-year survival rate (73.9%). Tumor size was negatively correlated with survival months, indicating patients with larger tumors had shorter survival times (p < 0.05). Presence of higher-grade tumors and metastatic disease at presentation were negatively correlated with survival months (p < 0.05). No significant differences in the survival were found between gender or race between all of the subtypes (p > 0.05). This study highlights key differences in the demographic and survival rates of the different types of rhabdomyosarcoma that can be used for more tailored patient counseling. We also demonstrate that large, population-level databases provide sufficient data that can be used in the analysis of rare tumors. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:2226-2230, 2019.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".