Association Between Interleukin-6 Levels and Lymph Node Metastasis in Bladder Cancer Patients
Bibliographic record
Abstract
Background: Bladder cancer (BC) is one of the urological cancers with high prevalence, mortality, morbidity, and expenditure rates. Urothelial malignancies account for about 90% cases of BC, with squamous and adenocarcinomas making up the remaining 10%. Lymph node metastasis (LNM), the most common type of BC metastasis, is generally found in the pelvic lymph nodes. LNM significantly affects the chances of survival and prognosis for patients with BC. It is feasible to stratify and assess the malignancy of the tumor and its response to therapies using potential tumor markers. Interleukin-6 (IL-6) has been observed to be a predictor of metastasis in lymph nodes in BC. The aim of this study was to evaluate the relationship between IL-6 levels and lymph node metastases in BC patients. Methods: Thirty-two BC patients between August 2021 and January 2022 were admitted to this study. Data on patient characteristics, clinical data, TNM staging, and IL-6 levels were collected. Univariate analysis was used in the characteristics of the patients. Results: The total subjects were 32 with 15 results in LNM. The difference in IL-6 levels between the LNM (+) group and the LNM (-) was statistically significant by Fisher's exact test (P = 0.041) and Mann-Whitney U tests (P = 0.003). Conclusions: The BC patients who had lymph node metastases also had higher serum levels of IL-6.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".