Colon Cancer Risk Following Intestinal <i>Clostridioides difficile</i> Infection: A Longitudinal Cohort Study
Bibliographic record
Abstract
Background: The gut microbiome may play an important role in the etiology and progression of colon cancer. The present hypothesis-testing study compared the colon cancer incidence rate among adults diagnosed with intestinal Clostridioides (formerly Clostridium) difficile (Cdiff) (the Cdiff cohort) to adults not diagnosed with intestinal Cdiff infection (the non-Cdiff cohort). Methods: De-identified eligibility and claim healthcare records within the Independent Healthcare Research Database (IHRD) from a longitudinal cohort of adults (the overall cohort) enrolled in the Florida Medicaid system between 1990 through 2012 were examined. Adults with ? 8 outpatient office visits over 8 years of continuous eligibility were examined. There were 964 adults in the Cdiff cohort and 292,136 adults in the non-Cdiff cohort. Frequency and Cox proportional hazards models were utilized. Results: Colon cancer incidence rate in the non-Cdiff cohort remained relatively uniform over the entire study period, whereas a marked increase was observed in the Cdiff cohort within the first 4 years of a Cdiff diagnosis. Colon cancer incidence was significantly increased (about 2.7-fold) in the Cdiff cohort (3.11 per 1,000 person-years) compared to the non-Cdiff cohort (1.16 per 1,000 person-years). Adjustments for gender, age, residency, birthdate, colonoscopy screening, family history of cancer, and personal history of tobacco abuse, alcohol abuse/dependence, drug abuse/dependence, and overweight/obesity, as well as consideration of diagnostic status for ulcerative and infection colitis, immunodeficiency, and personal history of cancer did not significantly change the observed results. Conclusions: This is the first epidemiological study associating Cdiff with an increased risk for colon cancer. Future studies should further evaluate this relationship. J Clin Med Res. 2023;15(6):310-320 doi: https://doi.org/10.14740/jocmr4919
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".