Molecular Detection of Tumor Cells in Regional Lymph Nodes Is Associated With Disease Recurrence and Poor Survival in Node-Negative Colorectal Cancer: A Systematic Review and Meta-Analysis
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: Up to 25% of patients with node-negative colorectal cancer (CRC) on conventional histopathologic analysis ultimately die of recurrent disease. We performed a systematic review with meta-analyses to clarify whether molecular detection of isolated tumor cells or micrometastases in regional lymph nodes indicates high risk of disease recurrence and poor survival in node-negative CRC. METHODS: The following databases were searched in August 2011 to identify studies on the prognostic significance of molecular tumor-cell detection in regional lymph nodes of node-negative CRC: MEDLINE, BIOSIS, Science Citation Index, EMBASE, CCMed, and publisher databases. We extracted hazard ratios (HRs) and associated 95% CIs from the identified studies and performed random-effects model meta-analyses on overall survival, disease-specific survival, and disease-free survival. RESULTS: A total of 39 studies with a cumulative sample size of 4,087 patients were included. Immunohistochemistry, reverse transcriptase polymerase chain reaction, and both techniques were applied in 30, seven, and two studies, respectively. Thirteen studies were graded with low risk of bias. Meta-analyses revealed that molecular tumor-cell detection in regional lymph nodes was associated with poor overall survival (HR, 2.20; 95% CI, 1.43 to 3.40), disease-specific survival (HR, 3.37; 95% CI, 2.31 to 4.93), and disease-free survival (HR, 2.24; 95% CI, 1.57-3.20). Subgroup analyses showed the prognostic significance of molecular tumor-cell detection of being independent of the applied detection method, molecular target, and number of retrieved lymph nodes. CONCLUSION: Molecular detection of occult disease in regional lymph nodes is associated with an increased risk of disease recurrence and poor survival in patients with node-negative CRC.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.002 |
| 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 | 0.001 |
| 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 it