P074 Comparative Risk of Clostridioides Difficile Infection in Vedolizumab vs anti-TNFa Agents in Biologic-Naïve Patients With Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND: Clostridioides difficile infection (CDI) is associated with adverse outcomes in ulcerative colitis (UC). There is concern that vedolizumab, which inhibits lymphocyte trafficking to the intestines, may increase the risk of gastrointestinal infections such as CDI when compared to other biologics. We conducted a retrospective cohort study to determine if vedolizumab is associated with an increased risk of CDI compared to anti-TNFa agents in UC. METHODS: Retrospective cohort study of adult patients with UC initiating infliximab, adalimumab, or vedolizumab 6/1/14-12/31/20 at a large academic health system. Electronic records were manually reviewed. Patients with Crohn's disease, indeterminate colitis, prior biologic exposures, prior colectomy, and non-UC indications for biologics were excluded. Patients were followed until CDI, colectomy, biologic discontinuation/switch, or last gastroenterology encounter through 8/1/21. The primary outcome was time from biologic initiation to first CDI, defined as positive stool C. difficile toxin or toxigenic C. difficile polymerase chain reaction (PCR) with associated CDI antibiotic prescriptions. Secondary outcomes included CDI-related hospitalization, colectomy, or death within 30 days of CDI. The primary exposure was vedolizumab vs anti-TNFa therapy. Other independent variables included demographics and UC history/severity factors. Propensity scores (PSs) were calculated using logistic regression of vedolizumab vs anti-TNFa on the following covariates: age, sex, Caucasian, body mass index (BMI), disease duration, current systemic corticosteroid use, UC-related hospitalization within prior 12 months, last Mayo endoscopic subscore, Montreal disease extent, albumin, and malignancy history. Inverse probability of treatment weighting (IPTW) was performed using PSs. An univariable Cox proportional hazards model was fit to calculate the unadjusted hazard ratio (HR) of CDI for vedolizumab vs anti-TNFa. A multivariable, IPT-weighted Cox model was then fit with two additional covariates extrinsic to the PS: pre-biologic CDI and immunomodulator exposure (time-varying covariate). Patients were censored at loss of follow-up, biologic discontinuation, or colectomy. RESULTS: 805 UC patients initiated vedolizumab (n = 195) or anti-TNFa agents (n = 610). Vedolizumab patients were older and less commonly received systemic corticosteroids or had UC-related hospitalization within 12 months pre-biologic initiation. There were 43 CDIs over 1,436 patient-years follow-up. CDI and CDI hospitalization occurred less commonly with vedolizumab vs anti-TNFa (CDI: 1.0% vs 6.7%, p = 0.001; CDI hospitalization: 1.0% vs 3.8%, p = 0.042 by log-rank test). There were no differences in colectomies or deaths or exposure to antibiotics/corticosteroids during follow-up or within 30 days preceding CDI. The unadjusted Cox model demonstrated a lower hazard of CDI for vedolizumab vs anti-TNFa (HR 0.17, 95% CI 0.04-0.71). The multivariable IPT-weighted Cox model demonstrated no difference in hazard of CDI for vedolizumab vs anti-TNFa (HR 0.33, 95% CI 0.05-2.03) or immunomodulator exposure (HR 1.01, 95% CI 0.41-2.40). Pre-biologic CDI was associated with an increased hazard of CDI (HR 5.95, 95% CI 2.93-12.09). Among patients who developed CDI, 17/43 (39.5%) had pre-biologic CDI a median of 227 days (IQR 160-550 days) preceding CDI. CONCLUSION: Our study did not identify an increased risk of CDI associated with vedolizumab vs anti-TNFa agents after controlling for UC severity. We hope that these findings will reassure UC providers considering vedolizumab as a first-line biologic agent in the context of gastrointestinal infectious risks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".