Re-evaluation of a Scoring System to Predict Nonsentinel-Node Metastasis and Prognosis in Melanoma Patients
Bibliographic record
Abstract
BACKGROUND: We previously developed a scoring system based on patient age and total sentinel node (SN) tumor size to predict nonsentinel node (NSN) metastasis. The score relied on the cutoff values of 55 years for age and 5 mm total SN tumor size to stratify SN-positive patients into 3 categories. Its validity, however, remains in doubt given that it was developed by retrospective review of a single, relatively small cohort of SN-positive melanoma patients. The purpose of this study was to validate this scoring system and to determine its value in predicting patient survival. STUDY DESIGN: A review of melanoma patients who had undergone sentinel node biopsy and completion lymph node dissection (CLND) at the Melanoma Institute Australia from June 1992 until April 2009 was undertaken. The significance of the correlation of each of the score variables (age and total SN tumor size) with NSN metastasis, melanoma-specific survival, and overall survival was tested. Cox logistic regression analysis was used to determine the degree of correlation of the score system to each of the 3 outcomes. RESULTS: Six hundred six SN-positive patients were identified and included in this study. The score system did not significantly correlate with NSN metastasis (p = 0.1049). However, it did significantly correlate with both overall survival (p < 0.0001) and disease-specific survival (p = 0.0014). CONCLUSIONS: Our results revealed that the previously developed scoring system does not predict NSN metastasis; however, it was found to be a powerful predictive tool for overall and disease-free survival in SN-positive melanoma patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".