Sentinel Lymph Node Biopsy in Patients With Thick Primary Cutaneous Melanoma
Bibliographic record
Abstract
Background: The clinical value of sentinel lymph node biopsy (SLNB) in patients with thick melanoma is uncertain. The purpose of this study was to investigate the correlations between survival and lymph node status in thick melanomas. Methods: Of a total of 736 melanoma patients registered between 2000 and 2016, 50 presented with thick melanomas (>= 4.0 mm) without distant metastatic disease. All patients were examined with a whole-body magnetic resonance imaging, or computed tomography, and positron emission tomography-computed tomography depending on the incorporation of the new technology in our medical institutions. They were studied according to the following procedure: 1) preoperative determination of regional lymph node along with the estimation and localization of sentinel lymph node (SLN) (dynamic isotope lymphography); 2) intraoperative localization and SLNB (lymphatic mapping); and 3) histopathology. Patient and tumor features were collected. Results: Mean follow-up was 40 months, and 37% had a follow-up >= 5 years. A positive SLN was identified in 28 patients (56%). No significant difference in melanoma-specific overall survival was observed in terms of the primary tumor site. Hazard ratios (HRs) were statistically significant for SLNB-positive group and mitotic rate (MR) > 3 mm 2 , but not for presence of ulceration. Mortality risk in the SLN-positive group was almost fourfold greater than that in the SLN-negative group at any time of follow-up. Conclusions: SLN status, along with MR, can provide valuable prognostic information in patients with thick primary cutaneous melanoma. World J Oncol. 2019;10(2):112-117 doi: https://doi.org/10.14740/wjon1181
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 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".