[Economic burden and factors associated with Crohn's disease]

Prediction of the Short-Term Effectiveness of Ustekinumab in Patients with Moderate to Severe Crohn's Disease

Background

Ustekinumab (UST) is recommended as the first-line treatment for patients with moderate to severe Crohn's disease (CD). However, the efficacy of certain patients may be suboptimal and necessitate intensive treatment or modification of the treatment regimen. We sought to establish a nomogram model to predict the short-term effectiveness of UST in moderate to severe CD patients.

Methods

We established a derivation cohort comprising patients diagnosed with CD and treated with UST at the Sixth Affiliated Hospital of Sun Yat-sen University from May 2020 to July 2023. The patient data, including demographic and clinical characteristics as well as treatment details, were systematically collected. The achievement of clinical remission (defined as Crohn's Disease Activity Index, CDAI < 150, without corticosteroid usage) after induction therapy was the endpoint observed during follow-up. Potential predictors were identified through the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Subsequently, a multivariate logistic regression analysis was conducted to construct a nomogram model. The predictive accuracy and discriminative power of the model were assessed by Receiver Operating Characteristics (ROC) curves and calibration curves. Decision curve analysis (DCA) was employed to assess the clinical application value of the model.

Results

162 patients were included in the derivation cohort. The predictor's selection was according to the minimum criteria. Prognostic factors, including duration, body mass index (BMI), smoking, extraintestinal manifestations (EIMs), perianal lesions (P), history of Vedolizumab therapy, and albumin levels (ALB), were identified and included in the nomogram. The model showed good discrimination and calibration on internal validation based on the bootstrap method (C-index: 0.843, 95% confidence interval: 0.768-0.903). Moreover, DCA demonstrated that the nomogram was clinically beneficial.

Conclusion

We constructed a practical tool to assist clinicians in identifying moderate to severe CD patients who are expected to have a good clinical response to UST, promoting personalized treatment and the development of precision medicine.

Resveratrol for inflammatory bowel disease in preclinical studies: a systematic review and meta-analysis

Background: Inflammatory bowel disease (IBD) is a chronic condition that can be managed with treatment, but it is challenging to get IBD cured. Resveratrol, a non-flavonoid polyphenolic organic compound derived from various plants, has a potential effect on IBD. The current research was set out to investigate the therapeutic effects of resveratrol on animal models of IBD. Methods: A comprehensive search of PubMed, Embase, Web of Science, and Chinese databases was performed. The literature search process was completed independently by two people and reviewed by a third person. The risk of bias in the included literature was assessed using the Collaborative Approach to Meta Analysis and Review of Animal Data from Experimental Stroke (CAMARADES) 10-point quality checklist. The meta-analysis utilized Review Manager 5.4 software to evaluate the efficacy of resveratrol, with histopathological index as the primary outcome measure. Subgroup analysis was conducted based on this indicator. Additionally, meta-analyses were carried out on different outcomes reported in the literature, including final disease activity index, final body weight change, colon length, splenic index, and inflammatory factors. Results: After conducting a thorough literature search and selection process, a total of 28 studies were ultimately included in the analysis. It was found that over half of the selected studies had more than five items with low risk of bias in the bias risk assessment. Relevant datas from included literature indicated that the histopathological index of the resveratrol group was significantly lower than that of the control group (WMD = -2.58 [-3.29, -1.87]). Subgroup analysis revealed that higher doses of resveratrol (>80 mg/kg) had a better efficacy (WMD = -3.47 [-4.97, -1.98]). Furthermore, The data summary and quantitative analysis results of SI and colon length also showed that resveratrol was effective in alleviating intestinal mucosal pathological injury of IBD. In terms of biochemical indicators, the summary analysis revealed that resveratrol affected interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), interferon-γ (IFN-γ), malondialdehyde (MDA), myeloperoxidase (MPO), superoxide dismutase (SOD), and prostaglandin E2 (PGE2) significantly. These effects may be attributed to the mechanism of resveratrol in regulating immune response and inhibiting oxidative stress. Conclusion: This review suggests that resveratrol demonstrated a notable therapeutic impact in preclinical models of IBD, particularly at doses exceeding 80 mg/kg. This efficacy is attributed to the protective mechanisms targeting the intestinal mucosa involved in the pathogenesis of IBD through various pathways. As a result, resveratrol holds promising prospects for potential clinical use in the future.

Assessment of influencing factors of hospitalization expenses for Crohn's disease patients: Based on LASSO and linear mixed model

Aims

Crohn's disease (CD) is a global disease that is dramatically increasing. This study aimed to identify the primary drivers of hospitalization expenses for CD patients to provide guidance on the allocation and control of health care costs.

Methods

This study retrospectively collected the homepage data of the electronic medical records of CD patients in two tertiary hospitals in Zhejiang Province, China, from January 2016 to December 2021. The influencing factors of hospitalization expenses for CD were analyzed. A linear mixed model with least absolute shrinkage (LASSO-LMM) was used to develop a predictive model for hospitalization expenses for CD patients.

Results

A total of 4,437 CD patients were analyzed in this study. CD patients' age, length of hospital stay, admission route, comorbidities, and main treatment were found to be statistically significant variables for CD patients' hospitalization expenses. The AIC and BIC of LASSO-LMM model were 319.033 and 306.241, respectively. Patients who were older, had a longer hospital stay, and had comorbidities had higher hospitalization expenses. The hospitalization expenses of outpatients were lower than those of emergency patients. The weight of surgical treatment was the highest among three treatments (0.602).

Conclusions

Identifying and examining factors that influence hospitalization expenses for CD patients can help to control healthcare expenditures. Treatment mode was the most important impact on CD hospitalization expenses. Medical security departments can consider implement personalized and precise hospitalization expense compensation scheme base on LASSO-LMM prediction model in the future.