Summary Background Following induction therapy with a calcineurin inhibitor (CNI) in severe ulcerative colitis, transitioning to vedolizumab as maintenance therapy could be an option. Aim To report on the largest cohort of patients successfully induced with CNIs who were transitioned to vedolizumab maintenance therapy. Methods This is a retrospective observational study of adult patients with severe steroid‐refractory ulcerative colitis. Patients were included if they were induced with a CNI followed by maintenance therapy with vedolizumab between January 2014 and December 2018. The primary endpoint was colectomy‐free survival. Secondary endpoints included survival without vedolizumab discontinuation as well as clinical, steroid‐free and biochemical remission at week 14. Results A total of 71 patients (59% male) were treated with vedolizumab after induction therapy with CNIs for severe steroid‐refractory colitis. Patients were followed for a median time of 25 months (IQR 16‐36). Colectomy‐free survival rates from vedolizumab initiation were 93% at 3 months, 67% at 1 year and 55% at 2 years. At the end of induction with vedolizumab at week 14, 50% of patients were in clinical remission, and 62% of patients had a normal CRP. At 1 and 2 years following vedolizumab initiation, 43% and 28% of patients were still on vedolizumab respectively. Vedolizumab was dose escalated to infusions every 4 weeks in 44% of patients. The median time to dose escalation was 5.6 months (IQR 4.1‐8.2). No serious adverse events were recorded in our patient cohort. Conclusions Transitioning to vedolizumab following induction of remission with CNIs is effective and safe.
Background Inpatient management of severe ulcerative colitis is complicated by the use of prior immunosuppressant therapies. Our aim was to determine the rate of 1-year colectomy among individuals receiving inpatient calcineurin inhibitor (CNI)-based therapy stratified by prior biologic therapy. Methods A retrospective cohort study was performed between January 1, 2013 and April 1, 2018. Only individuals requiring inpatient administration of intravenous cyclosporine or oral tacrolimus were included in the analysis. Individuals were stratified according to prior biologic therapy exposure. The primary outcome of interest was 1-year risk of colectomy. Kaplan-Meier curves were generated for time-to-event data, and regression models were performed to examine the effects of covariates on the clinical endpoint. Results Sixty-nine (62.3% male) patients were treated with an inpatient CNI-based therapy and were included in the analysis. Fifteen (21.7%) patients were biologic-naïve, 42 (60.9%) patients had prior exposure to 1 class of biologic therapy, and 12 (17.4%) patients had prior exposure to 2 classes of biologic therapy (third-line CNI therapy). Third-line CNI therapy showed a greater risk of 1-year colectomy risk when compared with the risk for patients who were biologic-naïve (hazard ratio, 3.63; 95% confidence interval, 1.17-13.45; P = 0.025). In a multivariate proportional hazards model, third-line CNI therapy remained significantly associated with 1-year colectomy risk (hazard ratio, 7.94; 95% confidence interval, 1.97-39.76; P = 0.003). Conclusions The use of CNI-based therapy in individuals exposed to multiple classes of prior biologic therapies leads to a significantly increased risk of 1-year colectomy. Future studies will be required to compare inpatient management strategies with the expanding novel therapies in UC.
Background Models to predict colectomy in ulcerative colitis (UC) are valuable for identification, clinical management, and follow-up of high-risk patients. Our aim was to develop a clinical predictive model based on admission data for one-year colectomy in adults hospitalized for severe UC. Methods We performed a retrospective analysis of patients hospitalized at a tertiary academic center for management of severe UC from 1/2013 - 4/2018. Multivariate regression was performed to identify individual predictors of one-year colectomy. Outcome probabilities of colectomy based on the prognostic score were estimated using a bootstrapping technique. Results Two hundred twenty-nine individuals were included in the final analytic cohort. Four independent variables were associated with one-year colectomy which were incorporated into a point scoring system: (+) 1 for single class biologic exposure prior to admission; (+) 2 for multiple classes of biologic exposure; (+) 1 for inpatient salvage therapy with cyclosporine or a TNF-alpha inhibitor; (+) 1 for age < 40. The risk probabilities of colectomy within one year in patients assigned scores 1, 2, 3 and 4 were 9.4% (95% CI 1.7 – 17.2%), 33.7% (95% CI 23.9 – 43.5%), 58.5% (95% CI 42.9 – 74.1%), 75.0% (95% CI 50.5 – 99.5%). An assigned score of zero was a perfect predictor of no colectomy. Conclusion Risk factors most associated with one-year colectomy for severe UC included: prior biologic exposure, need for inpatient salvage therapy and younger age. We developed a simple scoring system using these variables to identify and stratify patients during their index hospitalization.
INTRODUCTION: Acute ulcerative colitis (UC) is associated with significant morbidity and comes with a high risk of surgery. Prior clinical predictors have often included Day 3 laboratory values to assess risk of colectomy. Utilization of readily available data on admission may expedite medical decisions allowing for prompt initiation of therapies. Our aim was to identify early laboratory predictors of colectomy at the time of admission. METHODS: We designed a retrospective study including patients >18 years old with an admission for acute UC at a single academic center between 1/1/2013 and 4/1/2018. Cases were identified using the ICD-9 code 556.X and ICD-10 code K51.X and separately manually verified. Clinical variables of interest and laboratory values were obtained via chart review or extracted from the electronic medical record. Statistical analysis was conducted using JMP ® 13.1.0. Data was analyzed using Wilcoxon rank-sum test for continuous variables, Fischer's exact test for categorical variables, followed by multivariate logistic regression for predictive modeling of in-hospital colectomy. RESULTS: 262 patients admitted with acute UC were reviewed. 59 (22.5%) required inpatient colectomy. 188 of these patients had complete platelet and albumin laboratory data. Basic demographic variables and significant predictors of colectomy in univariate analysis are described in Table 1. Platelet to Albumin ratio (PAR) was found to be the strongest assessed univariate predictor of colectomy (AUC = 0.72, P-value < 0.0001). The optimal PAR cutoff to predict colectomy was 129 (Sensitivity = 70%, Specificity = 72%). Final multivariate logistic regression model with only significant covariates included PAR score (categorical), outside hospital transfer, and number of prior biologics with an area under curve (AUC) = 0.84. PAR remained statistically significant in this model (OR: 6.48, 95% CI: 2.73-15.34). Admission platelet count and admission albumin were also predictors of colectomy in both univariate and separate multivariate analyses, whereas CRP on admission, CRP on Day 3, and CRP to Albumin ratio were not predictive of colectomy (Table 2). CONCLUSION: PAR ratio was found to be a robust predictor of in-hospital colectomy in acute UC. This simple laboratory tool may provide a means to quantify early risk of in-hospital colectomy. As such, an elevated PAR identified on admission can help guide therapeutic strategies aimed at mitigating risk for colectomy in high risk groups.
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