Sentinel Lymph Node Biopsy Versus Pelvic Lymphadenectomy in Early Stage Cervical Cancer: Is It Time to Change the Gold Standard?
Bibliographic record
Abstract
The use of the sentinel lymph node (SLN) biopsy is a promising method to assess pelvic lymph nodes in early stage cervical cancer. Its use may avoid much of the morbidity associated with complete pelvic lymphadenectomy, the standard assessment procedure in early cervical cancer. Despite evidence suggesting that use of SLN biopsy in assessment of pelvic lymph nodes for metastases has a high detection rate and low false-negative rate, many clinicians are concerned about the potential false-negative rate. The aim of this study was to compare the incidence of pelvic, lymph node metastases in early-stage cervical cancer patients among a cohort of patients undergoing SLN biopsy and a matched cohort undergoing pelvic lymphadenectomy. The study group was comprised of 81 patients with FIGO stage IA/B1 cervical cancer, who underwent SLN detection followed by surgical treatment of the primary tumor. The control group consisted of 218 matched patients who underwent complete pelvic lymphadenectomy. All pathological and other cohort data on radical surgery for stage IA and IB cervical cancer were recorded prospectively and entered into a database. The two cohorts were matched for tumor characteristics known to be associated with lymph node metastases: tumor size (±5 mm), histology, depth of invasion (±2 mm), and the presence of capillary lymphatic space invasion. Using these parameters, 81 of the study group patients were matched with first control, 72 patients with a second control, and 65 patients with a third control. Conditional logistic regression analysis assessed the association between pelvic lymph node metastases and the surgical procedure, which was the primary study outcome. Pelvic lymph nodes metastases were found in 17% (14/81) of the study group compared to 7% (15/218) of the control group (odds ratio, 2.8; 95% confidence interval, 1.3–5.9; P = 0.006). There were no SLN false-negatives. Of the 14 cases of metastases in the SLN group, 11 were detected on frozen section and 3 on the permanent H and E stained sections. With respect to size, all of the SLN metastases were smaller than 1 cm and 6 were less than 2 mm. The investigators conclude from these findings that the high detection rate of the SLN procedure and its low false-negative rate, together with a presumed reduction of morbidity, makes the procedure of choice for pelvic lymph node assessment in early cervical cancer.
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 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".