Radiation-Induced Oropharyngeal Squamous Cell Carcinoma: Case Report and Review of the Literature
Bibliographic record
Abstract
BACKGROUND: Radiation therapy (RT) is a mainstay for the treatment of head and neck (HN) cancers, with 80% of patients receiving such treatment. Radiation-induced malignancies represent a life-threatening long-term effect of RT, with an incidence of 0.5% to 15%. CASE DESCRIPTION: After 13 years, a 33-year-old woman treated with chemo-radiotherapy for nasopharyngeal carcinoma developed a locally advanced, radiation-induced, p16-negative oropharyngeal squamous cell carcinoma (SCC) at the base of the tongue. Chemo/immunotherapy was administered as a first-line treatment. Given the optimal response and the feasibility of surgery, after three cycles, the patient underwent a total glossectomy, bilateral neck dissection, and reconstruction with a thoraco-dorsal free flap. A histological examination found SCC with a residual cancer burden of 70% and free margins. DISCUSSION: The mechanisms responsible for carcinogenesis after RT are still not completely clear. Diagnosis may be challenging due to the previous treatment; growth patterns are unusual, and lymphotropism is lower. Prognosis is usually poor since surgical resectability is often not achievable. CONCLUSIONS: Radiation-induced malignancies are difficult to treat. Patient management should always be discussed at a multidisciplinary level. Future research is needed to assess whether the promising results of clinical studies with pre-operative immunotherapy in locally advanced HN SCC patients may be translated into radiation-induced cancers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".