Bioactive Interleukin-6 Levels in Serum and Ascites as a Prognostic Factor in Patients with Epithelial Ovarian Cancer
Bibliographic record
Abstract
Interleukin-6 (IL-6) is a multifunctional cytokine displaying diverse biologic functions that can be produced by a broad variety of normal and malignant cell types (1). In vivo, high levels of bioactive IL-6 have been detected in the ascites of patients with epithelial ovarian cancer, suggesting abundant local production of this cytokine at the tumor site (2-6). We found IL-6 levels in ascites to correlate significantly with the volume of ascites and nearly so with the size of tumor found at initial surgery (2). Notably, IL-6 levels in malignant ascites also correlated with reactive thrombocytosis, and maximum IL-6 bioactivity in ascites and highest platelet counts occurred in patients with undifferentiated ovarian adenocarcinoma or advanced disease (7). Patients who responded to chemotherapy tended to have lower ascites IL-6 levels compared with patients who failed to respond to chemotherapy (4). Berek et al. concluded that bioactive IL-6 in serum may be a useful tumor marker for ovarian cancer, because in their study it correlated with tumor burden, clinical disease status, and survival time (3). Performing a multivariate analysis, Scambia et al. (6) found serum IL-6 to have an independent prognostic value, but appeared to be less sensitive than CA-125. In conclusion, most investigators found serum and ascitic IL-6 to be of prognostic value in ovarian cancer. In the following section, the B9-bioassay for the detection of IL-6 in body fluids is described in detail.
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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) | 0.000 | 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".