The Role of Crohn Disease on Breast Cancer Incidence: A Clinical Analysis
Bibliographic record
Abstract
Background: Crohn disease is a chronic inflammatory disease that can affect the entire gastrointestinal tract. The pathophysiology of this disease characteristically involves transmural inflammation, which predisposes patients to various gastrointestinal cancers such as colon cancer. Although the increased risk of gastrointestinal cancers in Crohn disease has been well established, the risk of extra-gastrointestinal cancers remains unknown. We sought to study the risk of breast cancer in patients with Crohn disease. Methods: The data for this retrospective study were compiled using the International Classification of Disease Ninth Revision (ICD-9) and ICD 10th Revision (ICD-10) codes from the national Health Insurance Portability and Accountability Act (HIPAA)-compliant PearlDiver database from 2010 to 2019. Patients were matched for age, sex, and Charlson Comorbidity Index (CCI). Statistical analyses were implemented to assess Chi-squared, logistic regression, and odds ratio. Results: and the odds ratio was 0.15 (95% confidence interval (CI)). Patients without Crohn disease had an increased prevalence of breast cancer throughout all age ranges compared to patients with Crohn disease. Additionally, patients without Crohn disease had higher rates of breast cancer throughout the four major regions of the United States. In terms of healthcare costs, patients with breast cancer and a history of Crohn disease paid $23.87 more per hospital visit compared to patients with breast cancer and no history of Crohn disease. Conclusions: The results of this study indicate a statistically significant correlation between Crohn disease and a reduced incidence of breast cancer. This finding is true across all age groups and across the United States. Further study is required to investigate a possible mechanism between the pathophysiology of Crohn disease ultimately leading to reduced tumorigenesis in the breast.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".