Sentinel Lymph Node Biopsy in Patients With Conjunctival and Eyelid Cancers
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Bibliographic record
Abstract
PURPOSE: To assess lymph node invasion through the use of sentinel lymph node biopsy (SLNB) in conjunctival and eyelid tumor patients and ascertain the impact of this technique in therapeutic management recommended by the multidisciplinary consensus committee. METHODS: A single center prospective nonrandomized clinical study was conducted between January 2008 and January 2010. Seventeen patients were included: 4 (2 conjunctiva and 2 eyelid) melanomas, 4 eyelid Merkel cell tumors, 8 (2 conjunctiva, 2 eyelid, 2 eyelid and conjunctiva, 2 cornea and conjunctiva) squamous cell tumors, and 1 eyelid meibomian carcinoma. Preoperative lymphoscintigraphy was done the day before surgery to label lymph node(s). The surgical biopsy was then performed along with an extemporaneous pathological examination followed by secondary complete lymph node dissection only in instances of positive histology. RESULTS: In all cases, one or more sentinel lymph nodes were identified (3-13). Two biopsies (1 Merkel cell carcinoma and 1 squamous cell carcinoma) revealed neoplastic invasion and led to complete cervical node dissection. Adjunct regional treatment was indicated for 1 melanoma, for 4 Merkel cell tumors, and for 2 squamous cell carcinomas. One false negative result was noted in the group of squamous cell carcinomas after 6 months, and it was treated. No relapse or death was observed for the other 16 patients. The mean overall follow-up was 18.2 months. CONCLUSION: As in previous studies, we found that SLNB for eyelid and conjunctival tumors is safe and effective in identifying microscopically positive SLNs. This procedure may also revive interest in the study of cervicofacial lymphatic drainage. Our current investigation is to be expanded and extended to other medical teams.
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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) | 0.000 | 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) | 0.000 | 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 it