The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease

Abstract

Background Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies may also provide prognostic opportunities. We evaluated machine learning models incorporating routinely collected laboratory studies to predict surgical outcomes in U.S. Veterans with CD. Methods Adults with CD from a Veterans Health Administration, Veterans Integrated Service Networks (VISN) 10 cohort examined between 2001 and 2015 were used for analysis. Patient demographics, medication use, and longitudinal laboratory values were used to model future surgical outcomes within 1 year. Specifically, data at the time of prediction combined with historical laboratory data characteristics, described as slope, distribution statistics, fluctuation, and linear trend of laboratory values, were considered and principal component analysis transformations were performed to reduce the dimensionality. Lasso regularized logistic regression was used to select features and construct prediction models, with performance assessed by area under the receiver operating characteristic using 10-fold cross-validation. Results We included 4950 observations from 2809 unique patients, among whom 256 had surgery, for modeling. Our optimized model achieved a mean area under the receiver operating characteristic of 0.78 (SD, 0.002). Anti-tumor necrosis factor use was associated with a lower probability of surgery within 1 year and was the most influential predictor in the model, and corticosteroid use was associated with a higher probability of surgery. Among the laboratory variables, high platelet counts, high mean cell hemoglobin concentrations, low albumin levels, and low blood urea nitrogen values were identified as having an elevated influence and association with future surgery. Conclusions Using machine learning methods that incorporate current and historical data can predict the future risk of CD surgery.

Impact of artificial intelligence on prognosis, shared decision-making, and precision medicine for patients with inflammatory bowel disease: a perspective and expert opinion

“…Two ML models were developed for predicting the risk of surgical intervention in patients with CD [ 31 , 35 ]. Stidham et al.…”

Cystitis glandularis with concomitant Crohn’s disease leading to a paroxysm of Crohn’s disease with ulcerated external iliac vessels

“…Clinical complications such as intestinal fistulas and intestinal obstructions are common [ 4 ], and when chronic intestinal inflammation is inadequately controlled, progressive and irreversible bowel damage occurs. The potential complications of this progressive damage, such as bowel perforation, are serious [ 5 ]. Cystitis glandularis is a more common inflammatory disease in urology [ 6 ] and most often requires cystoscopy and pathological examination for diagnosis [ 7 ].…”

Adenocystitis with concomitant Crohn's disease leading to an outbreak of Crohn's disease with ulcerated external iliac vessels

“…Crohn's disease is a major type of in ammatory bowel disease [1] that is characterized by unknown pathogenesis, lack of a diagnostic gold standard, unsatisfactory treatment, and poor prognosis [2] and is easily missed by nongastroenterologists in patients with atypical clinical symptoms [3]. Clinical complications such as intestinal stula and intestinal obstruction are easily complicated [4], and once intestinal stula occurs, the digestive juices lead to self-digestion of other organs, with a high rate of death and disability [5]. Adenocystitis is a more common type of in ammatory disease in urology [6] and mostly requires cystoscopy and pathological diagnosis for clarity [7].…”