Prediagnosis Plasma Adiponectin in Relation to Colorectal Cancer Risk According to<i>KRAS</i>Mutation Status
Bibliographic record
Abstract
BACKGROUND: Low levels of adiponectin (ADIPOQ; HGNC ID; HGNC:13633), an adipokine, are associated with obesity, adiposity, excess energy balance, and increased risk of colorectal neoplasia. Given the reported association of increased body mass index (BMI) and low-level physical activity with KRAS-mutated colorectal tumor, we hypothesized that low-level plasma adiponectin might be associated with increased risk of KRAS-mutant colorectal carcinoma but not with risk of KRAS wild-type carcinoma. METHODS: We conducted molecular pathological epidemiology research using a nested case-control study design (307 incident rectal and colon cancer case patients and 593 matched control individuals) within prospective cohort studies, the Nurses' Health Study (152 case patients and 297 control individuals, with blood collection in 1989-1990) and the Health Professionals Follow-up Study (155 case patients and 296 control individuals, with blood collection in 1993-1995). Multivariable conditional logistic regression models and two-sided likelihood ratio tests were used to assess etiologic heterogeneity of the associations. RESULTS: The association of low-level plasma adiponectin with colorectal cancer risk statistically significantly differed by KRAS mutation status (P heterogeneity = .004). Low levels of plasma adiponectin were associated with KRAS-mutant colorectal cancer (for the lowest vs highest tertile: multivariable odds ratio [OR] = 2.83, 95% confidence interval [CI] = 1.50 to 5.34, P trend = .002) but not with KRAS wild-type cancer (for the lowest vs highest tertile: multivariable OR = 0.83, 95% CI = 0.49 to 1.43, P trend = .48). In secondary analyses, the association between plasma adiponectin and colorectal cancer did not appreciably differ by BRAF or PIK3CA oncogene mutation status. CONCLUSIONS: Low-level plasma adiponectin is associated with KRAS-mutant colorectal cancer risk but not with KRAS wild-type cancer risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".