Orthovoltage radiotherapy in the management of medial canthal basal cell carcinoma
Bibliographic record
Abstract
AIMS: To report the local control and complication rates of orthovoltage radiotherapy in the management of medial canthal basal cell carcinoma (BCC). METHODS: The medical records of all patients treated with medial canthal BCC between 1998 and 2010, with orthovoltage radiotherapy as primary treatment, adjuvant treatment after incomplete surgical excision, or for tumour recurrence following surgical excision, were retrospectively studied. The actuarial rates of tumour control and complications were calculated using Kaplan-Meier estimates. Main outcome measures were rates of tumour control and radiation complications. RESULTS: 90 patients were included with a median follow-up of 80 months. Tumour control rate at 10 years for the entire cohort was 94% (95% CI 84% to 98%). Tumour control rates showed no statistically significant differences among different treatment intents or treatment radiation energies. Radiation-related complication rates included loss of eyelashes in 59% (95% CI 48% to 66%), epiphora 51% (95% CI 39% to 62%), dry eye 14% (95% CI 3% to 35%) and conjunctival scarring 11% (95% CI 1% to 33%). No patient developed long-term corneal complications. CONCLUSIONS: Orthovoltage radiotherapy can be a reliable therapeutic alternative for selected medial canthal BCCs, which can be contained within the prescribed radiation field, with anticipated radiation-related toxicities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".