C-Reactive Protein Concentrations and Subsequent Ovarian Cancer Risk
Bibliographic record
Abstract
OBJECTIVE: To estimate the association between prediagnostic levels of C-reactive protein (CRP), a marker of chronic systemic inflammation, and subsequent development of ovarian cancer. METHODS: A multicenter, nested, case-control study was conducted, including women who developed ovarian cancer (case patients) and women who were cancer-free (controls) from the following cohorts: CLUE ("Give us a CLUE to cancer and heart disease") cohorts of Washington County, Maryland, the Columbia, Missouri Serum Bank, and the Island of Guernsey Prospective Study, United Kingdom. A total of 167 incident invasive epithelial ovarian cancer cases were identified and each matched to an average of two controls on cohort, age, race, menopausal status, time since last menstrual period, current hormone use, date of recruitment, and time of day of blood draw. Baseline serum samples were assayed for CRP concentrations, and estimates of risk associated with CRP levels were assessed using conditional logistic regression. RESULTS: Ovarian cancer risk was positively associated with increasing CRP concentrations. The risk of developing ovarian cancer among women in the highest third of the distribution of CRP compared with those in the lowest third was 1.72 (95% confidence interval 1.06-2.77), with evidence of an increasing risk with increasing concentration of CRP (P trend=0.02). Similar associations were observed using established clinical CRP cutpoints for heart disease risk (odds ratio 2.03, 95% confidence interval 1.20-3.47 for 3-10 mg/L compared with less than 1 mg/L, P trend=.008). If this association is causal, roughly 23% of ovarian cancer cases are attributed to chronic inflammation as indicated by elevated CRP concentrations. CONCLUSION: Higher circulating CRP concentrations in women who subsequently developed ovarian cancer support the hypothesized role of chronic inflammation in ovarian carcinogenesis. LEVEL OF EVIDENCE: II.
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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 | 0.003 |
| 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".