S894 Burden of Herpes Zoster Among Patients With Ulcerative Colitis and Crohn’s Disease in the United States: A Retrospective Cohort Study Using a Large Administrative Claims Database
Bibliographic record
Abstract
Introduction: Herpes zoster (HZ) is a disease characterized by a painful dermatomal rash caused by reactivation of the varicella-zoster virus. HZ incidence is higher in patients (pts) with ulcerative colitis (UC) and Crohn’s disease (CD) than in the general population. This study examined the burden associated with HZ in pts with UC and CD in the United States. Methods: This was a retrospective cohort study using administrative claims data (10/2015-02/2020). Separate cohorts of pts with UC+HZ or CD+HZ were identified with International Classification of Diseases, 10th Revision, Clinical Modification codes in medical claims. The 1st HZ diagnosis was the index date and at least 1 UC or CD diagnosis was required within 12 months prior to index (baseline). Control cohorts of pts with UC or CD but no HZ during the study period were identified and randomly assigned an index date based on the distribution of the durations of pre-index eligibility in the HZ cohorts (i.e., UC+HZ or CD+HZ cohorts, respectively). All pts were required to have 12 months of continuous enrollment before (baseline) and after (follow-up) index. Adjusted incidence rate ratios of all-cause healthcare resource use (HRU) and adjusted differences of all-cause costs were estimated using multivariable modeling, adjusting for propensity scores and key baseline variables. Outcomes were reported comparing pts with UC+HZ to UC only and, separately, pts with CD+HZ to CD only. Results: The study included 431 and 10,285 pts with UC+HZ and UC only, and 435 and 9,797 pts with CD+HZ and CD only, respectively. Mean ages for the cohorts ranged between 56-65 years. Comorbidity burden and baseline costs were slightly higher in the HZ vs control cohorts (Table 1). Adjusted incidence rates of HRU over 12 months were higher in the cohorts with HZ vs those without (Table 1). Mean (95% confidence interval [CI]) adjusted cost differences were $8,393 (-468;17,350) and $5,299 (-3,019;14,966) for the UC+HZ vs UC only and for the CD+HZ vs CD only cohorts, respectively, over 12-month follow-up. During the 1st quarter following HZ, the mean (95% CI) adjusted cost differences were $2,574 (415;5,062) and $5,497 (2,300;11,487) for the UC+HZ vs UC only and for the CD+HZ vs CD only cohorts, respectively (Table 1). Conclusion: These results suggest that HZ poses a significant burden in UC and CD pts, being associated with higher HRU and costs even after adjusting for baseline differences. These findings highlight the need for interventions to reduce this burden.Table 1.: Baseline Characteristics and Study Outcomes a) Standardized differences of 20%, 50%, and 80% suggest small, medium, and large differences, respectively (Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Ed. New Jersey: Lawrence Erlbaum Associates; 1988). b) Measured using different observation windows prior to index date for various medications. Ustekinumab, Vedolizumab, Anti-TNF biologics, and JAK inhibitors were identified based on a window up to 3 months prior to index allowing for an additional 30 days at discontinuation. All others reported were identified based on a prescription or refill within 6 months prior to index with days supply covering index. c) All costs are reported in 2020 US dollars. d) IRRs were calculated using the PROC GENMOD procedure for generalized linear models assuming a negative binomial distribution and log link, accounting for the propensity score of being in UC+HZ or CD+HZ cohort and relevant baseline characteristics as covariates. e) Cost differences were estimated using the two-part modeling approach: (1) In the first part, the probability of observing a positive cost was modeled using logistic regression; (2) in the second part, a generalized linear model with a gamma distribution and log link was used to predict costs among patients with positive costs. Both models included the patients’ propensity scores and relevant baseline characteristics as covariates. The 95% CIs were estimated from nonparametric bootstrap procedures with 499 replications. CD, Crohn’s disease; CI, confidence interval; HZ, herpes zoster; IBD, inflammatory bowel disease; IRR, incidence rate ratio; JAK, Janus kinase; n, number of patients; PPPY, per patient per year; SD, standard deviation; TNF, tumor necrosis factor; UC, ulcerative colitis.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".