Comparison of histopathology and RT-qPCR amplification of guanylyl cyclase C for detection of colon cancer metastases in lymph nodes
Bibliographic record
Abstract
AIMS: In colorectal cancer (CRC), the presence of lymph node (LN) metastases is an important prognostic factor. Approximately 20% of patients diagnosed as having node-negative (pN0) CRC will relapse. Pathological nodal stage misclassification due to sampling error resulting from the small volume of tissue tested has been proposed to explain this recurrence rate in pN0 patients. The authors compared the assessment of node positivity by histopathology (HP) with a molecular method which can accommodate larger tissue volumes. METHODS: Detection rate of guanylyl cyclase C (GCC) mRNA was determined in 1,495 LNs from 99 CRC patients. Using a subset of 647 LNs, multiple levels of HP analysis were compared with GCC mRNA molecular detection. Finally, clinicopathological factors were correlated with the molecular detection of GCC and clinical outcome in 123 patients with pN0 colon cancer. RESULTS: GCC mRNA was detected in 8.0% of the 560 nodes initially identified as HP-negative, whereas two repeat HP examinations detected 3.0% of these cases. In HP-positive LNs, the GCC mRNA detection rate was 90% (78/87) when half-LN were tested. Testing the entire LN remaining after HP by GCC increased the detection rate of HP-positive LNs to 95% (p=0.027). In comparison, 75% (65/87) and 92% (80/87) of the LN positive by clinical HP remained positive when one or two subsequent sections were examined by HP. Finally, patients with pN0 disease who were GCC-positive exhibited an earlier time of recurrence (hazard ratio, 3.54; 95% CI 1.40 to 8.98; p=0.0077). CONCLUSIONS: Molecular detection of tumour cells in LNs may have prognostic value in identifying patients diagnosed as having pN0 colon cancer who will relapse following surgery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".