Metastatic Melanoma in Sentinel Node–Negative Patients: The Ottawa Experience
Bibliographic record
Abstract
BACKGROUND: Lymph node involvement is a major independent prognostic factor for survival in patients with malignant melanoma. Sentinel lymph node biopsy (SLNB) detection of microscopic nodal melanoma has been shown to improve both 5-year survival and 5-year disease-free survival. OBJECTIVE: To determine the rate of metastatic melanoma in SLNB-negative patients at long-term follow-up. METHODS: Study subjects include all 152 patients who had a negative SLNB and were followed at the Ottawa Regional Cancer Centre (ORCC) between 1999 and 2004. Patients with a follow-up period less than 6 months, more than 1 primary melanoma, and metastatic melanoma at diagnosis were excluded. Age at diagnosis, sex, Breslow thickness, ulceration, mitoses, regression, Clark level, anatomical location, development of metastatic melanoma, time to detection of metastatic disease, and time to death from melanoma were studied. RESULTS: In this retrospective study at the ORCC, 40 of 140 (28.6%) patients with a single primary melanoma developed metastatic melanoma following negative SLNB at a mean follow-up of 63 months. CONCLUSION: The rate of metastatic melanoma following negative SLNB at long-term follow-up at the ORCC is higher than the upper limit of rates reported in the literature (6%-24%). The reason for this is multifactorial, and the long follow-up period of 5 years allowed for detection of metastatic disease at a mean of 3.9 years. Long-term prognosis may be guarded in node-negative patients with a primary cutaneous melanoma, and surveillance by a multidisciplinary team is crucial.
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 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 | 0.001 | 0.003 |
| 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".