Evidence-based clinical practice guidelines for inflammatory bowel disease 2020

Nakase, Hiroshi; Uchino, Motoi; Shinzaki, Shinichiro; Matsuura, Minoru; Matsuoka, Katsuyoshi; Kobayashi, Taku; Saruta, Masayuki; Hirai, Fumihito; Hata, Keisuke; Hiraoka, Sakiko; Esaki, Motohiro; Sugimoto, Ken; Fuji, Toshimitsu; Watanabe, Kenji; Nakamura, Shirô; Inoue, Nagamu; Itoh, Toshiyuki; Naganuma, Makoto; Hisamatsu, Tadakazu; Watanabe, Mamoru; Miwa, Hiroto; Enomoto, Nobuyuki; Shimosegawa, Tooru; Koike, Kazuhiko

doi:10.1007/s00535-021-01784-1

Cited by 282 publications

(378 citation statements)

References 397 publications

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“…As an extra-facility cohort, 35 patients with UC at Toho University Sakura Medical Center who (1) started VDZ between January 2019 and June 2020 for the induction of remission, (2) underwent blood testing at week 0, and (3) underwent examination at Toho University Sakura Medical Center at week 22 were analyzed (Cohort 2). The diagnosis of UC was confirmed using the clinical practice guidelines for IBD of The Japanese Society of Gastroenterology 12 . VDZ treatment for the induction of remission was defined as VDZ started for active UC (Lichtiger index 13 was ≥ 5).…”

Section: Methodsmentioning

confidence: 99%

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis

Miyoshi

Maeda

Matsuoka

et al. 2021

Sci Rep

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Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (VDZ) before administration is an unmet need for optimizing individual patient treatment. We hypothesized that the machine-learning approach with daily clinical information can be a new, promising strategy for developing a drug-efficacy prediction tool. Random forest with grid search and cross-validation was employed in Cohort 1 to determine the contribution of clinical features at baseline (week 0) to steroid-free clinical remission (SFCR) with VDZ at week 22. Among 49 clinical features including sex, age, height, body weight, BMI, disease duration/phenotype, treatment history, clinical activity, endoscopic activity, and blood test items, the top eight features (partial Mayo score, MCH, BMI, BUN, concomitant use of AZA, lymphocyte fraction, height, and CRP) were selected for logistic regression to develop a prediction model for SFCR at week 22. In the validation using the external Cohort 2, the positive and negative predictive values of the prediction model were 54.5% and 92.3%, respectively. The prediction tool appeared useful for identifying patients with UC who would not achieve SFCR at week 22 during VDZ therapy. This study provides a proof-of-concept that machine learning using real-world data could permit personalized treatment for UC.

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Section: Methodsmentioning

confidence: 99%

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis

Miyoshi

Maeda

Matsuoka

et al. 2021

Sci Rep

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“…The etiology of IBD is unclear. Genetic susceptibility, environmental factors, and intestinal bacteria are implicated to be involved in the pathophysiology of IBD [ 2 ]. Inflammatory bowel diseases are generally divided into two types: ulcerative colitis (UC) and Crohn's disease (CD).…”

Section: Introductionmentioning

confidence: 99%

Epidemiology of Inflammatory Bowel Diseases in Nepal

Paudel¹,

Khanal²,

Shrestha³

et al. 2021

Cureus

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IntroductionInflammatory bowel diseases (IBD) comprise ulcerative colitis (UC) and Crohn's disease (CD). These are diseases of the gastrointestinal tract without a clear etiology but have strong relationships with underlying factors like genetic susceptibility, environmental factors, and intestinal bacteria. In the east, inflammatory bowel diseases predominantly affect the younger population and have an almost equal gender distribution. With urbanization and the adoption of the western lifestyle, the incidence and prevalence of IBD are increasing in Asia. In this study, we describe the epidemiology of IBD in Nepal. MethodsThis was an observational study conducted in nine endoscopy centers within Nepal. Two years of data of colonoscopies in these centers were collected retrospectively. IBD was diagnosed by endoscopic examination. The incidence of IBD was calculated as the number of patients with IBD per 1000 colonoscopies per year. The demographic profiles of the patients were also collected. ResultsA total of 7526 colonoscopies were done in nine centers within the two years study period. IBD was seen in 479 patients (6.3%). The incidence of UC was 23.7 per 1000 colonoscopies per year and the incidence of CD was 1.6 per 1000 colonoscopies per year. UC (87%) was more common than CD (13%). Both UC and CD were mostly seen in the 30 to 40 years age group. In patients with UC, the rectum was the most commonly affected site. DiscussionIBD in Nepal affects young males in their thirties. Younger age of affliction with a chronic disease and lack of awareness regarding the symptoms and diagnostic modalities of IBD may result in a delayed diagnosis. The target population must be made aware of the presenting symptoms of IBD and a need for colonoscopic examination for diagnosis. There is also a need for creating a national IBD registry for Nepal.

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“…However, 10–30% of patients with IBD have reported no response to the initial anti-TNF-α treatment, and an additional 23–46% of patients with IBD may lose their response to the treatment ( 16 ). Patients with inadequate therapeutic response may require surgical intervention, which may further increase the economic burden ( 17 , 18 ).…”

Section: Introductionmentioning

confidence: 99%

Cost-Effectiveness Analysis of Vedolizumab Compared With Infliximab in Anti-TNF-α-Naïve Patients With Moderate-to-Severe Ulcerative Colitis in China

Zhou

Sheng²,

Guan

et al. 2021

Front. Public Health

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Objective: To evaluate the cost effectiveness of vedolizumab vs. infliximab in the treatment of anti-tumor necrosis factor-alpha (TNF-α)-naïve patients with moderate-to-severe active ulcerative colitis (UC) in China.Methods: The costs and effectiveness of vedolizumab and infliximab in the treatment of anti-TNF-α naïve patients with moderate-to-severe active UC were compared using a hybrid decision tree model and a Markov model. From the perspective of the Chinese healthcare system, this study simulated the lifetime health benefits [quality-adjusted life-years (QALYs)] and costs (USD) for patients with UC from the induction phase to the maintenance phase, with an annual discount rate of 5%. The clinical efficacy and transition probability data were based on a previously published network meta-analysis. The health utility, surgical risk, biologic drug discontinuation rate, and mortality were derived from previous literature and the Chinese statistical yearbook. The cost data were based on China's drug purchase and biding platform and the results of a survey sent to clinicians in 18 tertiary hospitals. One-way and probabilistic sensitivity analyses (PSAs) were performed to validate the robustness of the models' assumptions and specific parameter estimates.Results: The results of the base-case analyses showed that compared with infliximab, vedolizumab led to a gain of 0.25 QALYs (9.56 vs. 9.31 QALYs) and was less expensive by $7,349 ($180,138 vs. 187,487), indicating that the use of vedolizumab was a dominant strategy. The results of one-way sensitivity analyses suggested that the annual discount rate and health-state costs had the greatest impact, but the results were otherwise consistent with those of the base-case analyses. The PSAs suggested that vedolizumab had a 98.6% probability of being effective at a threshold of 3 times the gross domestic product (GDP) per capita in China in 2020.Conclusion: Compared with infliximab, vedolizumab appears to be a more cost-effective option in the treatment of anti-TNF-α naïve adult patients with moderate-to-severe, active UC in China.

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Evidence-based clinical practice guidelines for inflammatory bowel disease 2020

Cited by 282 publications

References 397 publications

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis

Epidemiology of Inflammatory Bowel Diseases in Nepal

Cost-Effectiveness Analysis of Vedolizumab Compared With Infliximab in Anti-TNF-α-Naïve Patients With Moderate-to-Severe Ulcerative Colitis in China

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