A User-Friendly Prediction Tool to Identify Colectomy Risk in Patients With Ulcerative Colitis

被引:8
作者
Dalal, Rahul S. [1 ]
Osterman, Mark T. [2 ]
Buchner, Anna M. [2 ]
Praestgaard, Amy [3 ]
Lewis, James D. [2 ]
Lichtenstein, Gary R. [2 ]
机构
[1] Hosp Univ Penn, Dept Med, Philadelphia, PA 19104 USA
[2] Hosp Univ Penn, Dept Med, Div Gastroenterol, Philadelphia, PA 19104 USA
[3] Univ Penn, Ctr Clin Epidemiol & Biostat, Perelman Sch Med, Philadelphia, PA 19104 USA
关键词
surgery; colectomy; inflammatory bowel disease; multivariate model; INFLAMMATORY-BOWEL-DISEASE; RANDOMIZED CONTROLLED-TRIAL; POSTOPERATIVE COMPLICATIONS; CLINICAL-COURSE; OF-LIFE; THERAPY; HOSPITALIZATION; PARAMETERS; LYMPHOMA; OUTCOMES;
D O I
10.1093/ibd/izz014
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Background: Many patients with ulcerative colitis (UC) fear the potential side effects of immunosuppressive therapies. However, those with medically refractory disease often require total proctocolectomy (TPC) with a permanent ostomy or pouch, which may reduce quality of life. Prior studies have identified TPC predictors; however, no clinically useful prognostic tools exist to guide shared therapeutic decision-making. We therefore sought to develop a prediction tool of future TPC risk in UC patients. Methods: In this retrospective study, clinic charts of UC patients were reviewed from January 1, 2017, to December 31, 2017. Cases had TPC performed for refractory UC after January 1, 2008. Controls had no prior UC surgery. Clinical data were assessed 1-12 months preceding TPC or clinic visit for cases and controls, respectively. We randomly selected two-thirds of patients to develop a TPC prediction model using multivariable logistic regression. One-third was reserved for model validation. Results: We identified 115 cases and 325 controls. TPC predictors included albumin, 9-point Mayo score >5, Mayo endoscopic subscore >1, and corticosteroid use within 6 months. The areas under the receiver operating characteristic curve for the multivariable model were 0.94 (95% confidence interval [CI], 0.92-0.95) and 0.92 (95% CI, 0.89-0.95) for the test and validation cohorts, respectively. The validation cohort demonstrated a significant difference in calculated probability distributions between patients who did and did not have TPC (P < 0.01). We incorporated our model into a web-based application to allow convenient calculation of a patient's TPC risk. Conclusions: We created a user-friendly tool to assess TPC risk in UC. Prospective assessment will determine its utility for shared therapeutic decision-making.
引用
收藏
页码:1550 / 1558
页数:9
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