Impact of the time interval between lymph node recurrence and lymphadenectomy on melanoma patient survival
Bibliographic record
Abstract
Lymphadenectomy is currently the standard treatment for melanoma patients with palpable lymph node (LN) metastasis. There is no recommendation as to the time when surgery should be performed in France. The aim of this retrospective study was to assess the impact of the time interval preceding lymphadenectomy on patient outcomes. Patients who underwent lymphadenectomy for LN macrometastasis (Stage IIIB/C AJCC) between 2005 and 2012 were included. Both the time interval between the first suspicion of LN recurrence (physical examination and imaging) and lymphadenectomy and the time interval between the multidisciplinary team meeting and lymphadenectomy were recorded. The impact of these time intervals on patient relapse-free survival (RFS) and overall survival (OS) were analysed. The regression optimized (ROP) model was used to identify ghost factors for the Cox model. A total of 154 patients were included. The median time interval between the multidisciplinary team meeting and lymphadenectomy was 22 days (IQR: 6 to 66). The median time interval between the first suspicion of LN recurrence and lymphadenectomy was 59 days (IQR: 15 to 676). Taking into account the effect identified by the regression optimized (ROP) model, these times were associated with an increased risk of recurrence and mortality (p<0.001 and p = 0.01, respectively). Our study demonstrates that increasing the time interval preceding lymphadenectomy significantly reduces patient RFS and OS.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".