Dataset Information

A Clinical Predictive Model for One-year Colectomy in Adults Hospitalized for Severe Ulcerative Colitis.

ABSTRACT:

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 to 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.

SUBMITTER: Zafer M

PROVIDER: S-EPMC9802419 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Publications

A Clinical Predictive Model for One-year Colectomy in Adults Hospitalized for Severe Ulcerative Colitis.

Zafer Maryam M Zhang Hui H Dwadasi Sujaata S Goens Donald D Paknikar Raghavendra R Dalal Sushila S Cohen Russell D RD Pekow Joel J Rubin David T DT Sakuraba Atsushi A Micic Dejan D

Crohn's & colitis 360 20211221 1

<h4>Background</h4>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.<h4>Methods</h4>We performed a retrospective analysis of patients hospitalized at a tertiary academic center for management of severe UC from 1/2013 to 4/2018. Multivariate regression was performed to ...[more]

PMID: 36777555

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Project description:Background & aimsHospitalized patients with acute severe ulcerative colitis (ASUC) often require surgery. Although the tumor necrosis factor antagonist infliximab is an effective salvage therapy to prevent colectomy in patients with ASUC, optimal dosing is unclear. Calculated infliximab clearance has been associated with important outcomes in patients with ulcerative colitis, but its utility in patients with ASUC has not been established. We assessed the relationship between calculated the baseline infliximab clearance before infliximab salvage therapy and the requirement for colectomy in patients hospitalized for ASUC.MethodsWe obtained data from hospitalized patients with ASUC who initiated infliximab therapy. We then calculated the baseline infliximab drug clearance in these patients based on an existing formula. The primary aim was to compare clearance between patients who required colectomy 6 months later and patients who did not require colectomy. Receiver operating characteristic curve analyses evaluated clearance thresholds for colectomy. Multivariable logistic regression analysis evaluated factors associated with colectomy.ResultsIn 39 patients with ASUC, the median baseline calculated clearance was higher in patients requiring colectomy at 6 months than in patients without colectomy (0.733 vs 0.569 L/d; P = .005). An infliximab clearance threshold of 0.627 L/d identified patients who required colectomy with 80.0% sensitivity and 82.8% specificity (area under the curve, 0.80). A higher proportion of patients with infliximab clearance of 0.627 L/d or more underwent colectomy within 6 months (61.5%) than patients with lower infliximab clearance values (7.7%) (P = .001). Multivariable analysis identified baseline infliximab clearance as the only factor associated with colectomy. The infliximab dose in the hospital was higher in patients who required colectomy. Results were similar at 30 days and 1 year.ConclusionsIn patients hospitalized with ASUC, higher values of calculated infliximab clearance before infliximab administration is associated with higher rates of colectomy. Although patients who required colectomies received higher doses, data on infliximab concentrations are lacking. Infliximab pharmacokinetic models are needed for patients with ASUC to allow comparative trials on clearance-based vs standard dosing.

Project description:BackgroundA gap remains in documenting the impact of anti-tumor necrosis factor therapy on disease burden in ulcerative colitis (UC) patients treated in a real-world setting. The use of patient-reported outcomes (PROs) has been discussed as a primary endpoint in the context of the FDA PRO Guidance, for labelling purposes. Specifically, the efficacy and safety of adalimumab have been demonstrated in pivotal trials; however, data are needed to understand how clinical results translate into improvements in key aspects of the daily lives of UC patients, such as symptoms, health-related quality of life (HRQoL), and disability.AimTo assess real-world effectiveness of adalimumab on PRO measures in patients with moderate-to-severe UC.MethodsUCanADA was a single arm, prospective, 1-year multicenter Canadian post-marketing observational study in which multiple PRO questionnaires were completed-with psychologic distress/depression symptoms as the primary endpoint-by patients with moderate-to-severe UC. Assessments were performed during patients' routine care visit schedule, which was at the initiation of adalimumab (baseline), after induction (approximately 8 wk), and 52 wk after baseline. Additional optional assessments between weeks 8 and 52 were collected at least once but no more than two times during this period. Serious safety events and per-protocol adverse events were collected.ResultsFrom 23 Canadian centres, 100 patients were enrolled and 48 completed the study. Measured with the Patient Health Questionnaire-9 items at week 52, 61.5% (40/65) [95% confidence interval (CI): 49.7%-73.4%] of the patients improved in psychologic distress/depression symptoms, which was slightly higher in completers [65.9% (29/44); 95%CI: 51.9%-79.9%)]. At week 52, clinical response and clinical remission were achieved respectively by 65.7% (44/73) and 47.8% (32/73) of the patients. The odds of improving depressive symptoms for those achieving a clinical remission at week 52 was 7.94 higher compared with those not achieving a clinical remission (CI: 1.42, 44.41; P = 0.018). Significant changes from baseline to weeks 8 and 52 were observed in disability, HRQoL, and fatigue. Meaningful improvement was reported in work impairment.ConclusionAt week 52, over 60% of the UCanADA patients had depressive symptoms significantly reduced, as well as HRQoL, fatigue symptoms, and work impairment improved. No new safety signals were detected.

Dataset Information

A Clinical Predictive Model for One-year Colectomy in Adults Hospitalized for Severe Ulcerative Colitis.

Background

Methods

Results

Conclusion

Publications

A Clinical Predictive Model for One-year Colectomy in Adults Hospitalized for Severe Ulcerative Colitis.

Similar Datasets

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