Curative intent Stereotactic Ablative Radiation Therapy (SABR) for treatment of lung oligometastases from head and neck squamous cell carcinoma (HNSCC): a multi-institutional retrospective study
Bibliographic record
Abstract
OBJECTIVES: The aim of this retrospective study was to assess outcomes of SABR for metachronous isolated lung oligometastases from HNSCC. METHODS: For patients who developed isolated, 1 or 2 lungs lesions (<5cm) consistent with metastases from HNSCC, the indication of SABR was validated in a multidisciplinary tumor board. All patients were monitored by CT or PET CT after SABR (Stereotactic Ablative Body Radiation) for HNSCC. RESULTS: Between November 2007 and February 2018, 52 patients were treated with SABR for metachronous lung metastases. The median time from the treatment of the primary HNSCC to the development of lung metastases was 18 months (3-93). The cohort's median age was 65.5 years old (50-83). The vast majority (94.2%) received 60 Gy in three fractions. Forty-one patients (78.5%) presented a solitary lung metastasis, while 11 patients (21.5%) had two lung metastases. With a median follow-up of 45.3 months, crude local and metastatic control rates were 74 and 38%, respectively. 1 year and 2 year Overall Survival (OS) were 85.8 and 65.9%, respectively. The median OS was 46.8 months. About one-fourth of patients were retreated by SABR for distant pulmonary recurrence. The treatment was well tolerated with only one patient who reported ≥ grade 3 toxicity (1.9%). CONCLUSION: In selected metastatic HNSCC patients, early detection and treatment of lung metastases with SABR is effective and safe. Prospective studies are required to validate this potential shift. ADVANCES IN KNOWLEDGE: Patients with oligometastases and controlled primary HNSCC seem to benefit from metastasis directed therapies.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".