Association between IGFBP1 expression and cancer risk: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: The results regarding the association between insulin-like growth factor binding protein 1 (IGFBP1) expression and cancer risk were controversial. We performed a meta-analysis to provide novel evidence on relationship between IGFBP1 expression and cancer risk. Methods: PubMed, Embase, Cochrane library and Web of science were searched for relevant cohort and case-control studies exploring the relationship between IGFBP1 expression and cancer risk. Odds ratios (ORs) were pooled in this meta-analysis using random model. Subgroup analyses were performed based on ethnicity, tumor types, publication year, study type, Newcastle-Ottawa Scale (NOS) score and sex. Results: A total of 27 studies including 16 cohort and 11 case-control studies were identified by literature search. No significant association was found between IGFBP1 expression and risk of various cancers [0.90, 95% confidence interval (CI): 0.79, 1.03]. The overall results showed that the pooled ORs were 0.71 (95% CI: 0.57, 0.88] for prostate cancer risk and 0.66 (95%CI: 0.44, 0.99) for colorectal cancer (CRC) risk. However, there is no significant association between IGFBP1 expression and risk for ovarian cancer (1.70, 95%CI: 0.41, 6.99), breast cancer (1.02, 95%CI: 0.85, 1.23), endometrial cancer (1.19, 95%CI: 0.64, 2.21), colorectal adenoma (0.93; 95%CI: 0.81, 1.07), lung cancer (0.81, 95%CI: 0.39, 1.68) or multiple myeloma (1.20, 95%CI: 0.98, 1.47). Conclusion: In this study, compared with individuals at low IGFBP1 expression adjusted for age, smoking status, alcohol intake and so on, risk of the prostate cancer and CRC were decreased among individuals of high IGFBP1 expression. There needs further study to confirm this issue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".