Role of Surgery in Rhabdomyosarcoma of the Head and Neck in Children
Bibliographic record
Abstract
OBJECTIVES: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. The goal of this research is to analyze the role of surgery in the management of pediatric parameningeal (PM) and non-PM head and neck RMS (HNRMS). STUDY DESIGN: Retrospective review. METHODS: Retrospective chart review of patients <20 years of age treated for HNRMS between 1970 and 2015. Clinical presentation, tumor characteristics, treatment, recurrence, follow-up, and outcome data were collected. RESULTS: Of 97 patients with HNRMS, 56% were male. Overall median (IQR: interquartile range) age at diagnosis was 5.8 (3.3-9.8) years. Sixty-five patients (67%) had PM tumors. Of 75 patients with histologic subtype identified, 51 (53%) had embryonal and 20 (21%) alveolar RMS. Almost all patients received chemotherapy (99%) and radiotherapy (95%). Forty-four patients (45%) underwent surgery. Surgery was more likely to be conducted in patients with lesions of a non-PM site. Median follow-up time was 3.4 years (IQR: 1.1-10.8). In 5 years of follow-up, 20% (17 of 85) died and 29% (20 of 70) had recurrence. The estimated 5-year survival rate was 72% (95% CI, 57.8, 81.5%). Surgery was associated with a reduced risk of mortality after accounting for TNM stage 4 and tumor site (adjusted HR 0.24; 95% CI, 0.07, 0.79; P = .02). The association between surgery and risk of mortality was similar in PM and non-PM tumors. CONCLUSION: A multimodal protocol for treatment including chemotherapy, surgery, and radiotherapy is the mainstay for management of children with HNRMS. While surgery is more commonly used to treat non-PM HNRMS, patients who are able to undergo surgery have significantly higher 5-year survival. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:E984-E992, 2021.
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 | 0.001 | 0.002 |
| 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".