We developed myIBDcoach, which enables integrated care for all patients with IBD, regardless of disease severity or medication use. The feasibility study showed high satisfaction and compliance of patients and health care providers. To study myIBDcoach's efficacy, a multicenter randomized controlled trial has been initiated.

Background Cachexia, highly prevalent in patients with non-small cell lung cancer (NSCLC), impairs quality of life and is associated with reduced tolerance and responsiveness to cancer therapy and decreased survival. MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in post-transcriptional gene regulation. Changes in intramuscular levels of miRNAs have been implicated in muscle wasting conditions. Here, we aimed to identify miRNAs that are differentially expressed in skeletal muscle of cachectic lung cancer patients to increase our understanding of cachexia and to allow us to probe their potential as therapeutic targets. Methods A total of 754 unique miRNAs were profiled and analysed in vastus lateralis muscle biopsies of newly diagnosed treatment-naïve NSCLC patients with cachexia (n = 8) and age-matched and sex-matched healthy controls (n = 8). miRNA expression analysis was performed using a TaqMan MicroRNA Array. In silico network analysis was performed on all significant differentially expressed miRNAs. Differential expression of the top-ranked miRNAs was confirmed using reverse transcriptionquantitative real-time PCR in an extended group (n = 48) consisting of NSCLC patients with (n = 15) and without cachexia (n = 11) and healthy controls (n = 22). Finally, these miRNAs were subjected to univariate and multivariate Cox proportional hazard analysis using overall survival and treatment-induced toxicity data obtained during the follow-up of this group of patients. Results We identified 28 significant differentially expressed miRNAs, of which five miRNAs were up-regulated and 23 were down-regulated. In silico miRNA-target prediction analysis showed 158 functional gene targets, and pathway analysis identified 22 pathways related to the degenerative or regenerative processes of muscle tissue. Subsequently, the expression of six topranked miRNAs was measured in muscle biopsies of the entire patient group. Five miRNAs were detectable with reverse transcription-quantitative real-time PCR analysis, and their altered expression (expressed as fold change, FC) was confirmed in muscle of cachectic NSCLC patients compared with healthy control subjects: miR-424-5p (FC = 4.5), miR-424-3p (FC = 12), miR-450a-5p (FC = 8.6), miR-144-5p (FC = 0.59), and miR-451a (FC = 0.57). In non-cachectic NSCLC patients, only miR-424-3p was significantly increased (FC = 5.6) compared with control. Although the statistical support was not sufficient to imply these miRNAs as individual predictors of overall survival or treatment-induced toxicity, when combined in multivariate analysis, miR-450-5p and miR-451a resulted in a significant stratification between short-term and long-term survival. Conclusions We identified differentially expressed miRNAs putatively involved in lung cancer cachexia. These findings call for further studies to investigate the causality of these miRNAs in muscle atrophy and the mechanisms underlying their differential expression in lung cancer cachexia.

Background It is not well known to what extent effectiveness of treatment with immune checkpoint inhibitors in stage IV non‐small‐cell lung cancer (NSCLC) is influenced by weight loss and changes in body composition. Therefore, the goal of this study was to evaluate body composition changes in relation to early weight change and overall survival (OS) in stage IV NSCLC patients treated with second‐line nivolumab. Methods All patients with stage IV NSCLC, who were treated with second‐line nivolumab between June 2015 and December 2018 at Maastricht University Medical Center, were evaluated. Skeletal muscle mass (SMM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were assessed at the first lumbar level on computed tomography images obtained before initiation of nivolumab and at week 6 of treatment. The contribution of changes in body weight (defined as >2% loss), SMM, VAT, and SAT to OS was analysed by Kaplan–Meier method and adjusted for clinical confounders in a Cox regression analysis. The results from the study cohort were validated in another Dutch cohort from Erasmus Medical Center, Rotterdam. Results One hundred and six patients were included in the study cohort. Loss of body weight of >2% at week 6 was an independent predictor for poor OS (hazard ratio 2.39, 95% confidence interval 1.51–3.79, P < 0.001) when adjusted for gender, >1 organ with metastasis, pretreatment hypoalbumenaemia, and pretreatment elevated C‐reactive protein. The result was confirmed in the validation cohort (N = 62). Loss of SMM as a feature of cancer cachexia did not significantly predict OS in both cohorts. Significant (>2%) weight loss during treatment was reflected by a significant loss of VAT and SAT, while loss of SMM was comparable between weight‐stable and weight‐losing patients. Conclusions Weight loss, characterized by loss of subcutaneous and visceral adipose tissues, at week 6 of treatment with nivolumab, is a significant poor prognostic factor for survival in patients with Stage IV NSCLC.

To evaluate the relationship between early changes in muscle and adipose tissue during chemotherapy and overall survival (OS) in stage IV non-small cell lung cancer (NSCLC). Materials and methods: In this post-hoc analysis of the first line NVALT12 trial (NCT01171170) in stage IV NSCLC, skeletal muscle (SM), radiation attenuation (RA), subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) were assessed at the third lumbar level on CT-images obtained before initiation of chemotherapy and shortly after administration of the second cycle. The contribution of changes in different body compartments to overall survival was assessed. Results: CT scans of 111 patients were included. Analysis of body composition changes between the baseline and the follow-up scan, revealed that overall SM cross sectional area (CSA), radiation attenuation and SAT CSA decreased respectively by −1.2 ± 2.9 cm 2 /m 2 (p < 0.001), −0.7 ± 3.3 HU (p = 0.026) and −1.9 ± 8.7 cm 2 /m 2 (p = 0.026), while no significant changes in VAT tissue were observed. Longitudinally, median OS was significantly shorter among patients losing SM compared to patients with preserved SM (9.4 versus 14.2 months; HR 1.9, 95% CI: 1.23, 2.79, p = 0.003). Multivariate analyses showed that proportional loss of muscle mass was associated with poor OS (HR 0.949, 95% CI: 0.915, 0.985, p = 0.006) independent from important clinical prognostic factors including WHO-PS, gender, age and Charlson comorbidity index. Conclusion: Early loss of SM during first line chemotherapy is a poor prognostic factor in stage IV NSCLC patients. Future studies have to reveal whether early supportive intervention guided by initial CT muscle response to chemotherapy can influence the wasting process and related mortality risk.

Background Computed tomography (CT) is increasingly used in clinical research for single-slice assessment of muscle mass to correlate with clinical outcome and evaluate treatment efficacy. The third lumbar level (L3) is considered as reference for muscle, but chest scans generally do not reach beyond the first lumbar level (L1). This study investigates if pectoralis muscle and L1 are appropriate alternatives for L3. Methods CT scans of 115 stage IV non-small cell lung cancer patients were analyzed before and during tumor therapy. Skeletal muscle assessed at pectoralis and L1 muscle was compared to L3 at baseline. Furthermore, the prognostic significance of changes in muscle mass determined at different locations was investigated. Results Pearson’s correlation coefficient between skeletal muscle at L3 and L1 was stronger ( r =0.90, P <0.001) than between L3 and pectoralis muscle ( r =0.71, P <0.001). Cox regression analysis revealed that L3 (HR 0.943, 95% CI: 0.92–0.97, P <0.001) and L1 muscle loss (HR 0.954, 95% CI: 0.93–0.98, P <0.001) predicted overall survival, whereas pectoralis muscle loss did not. Conclusion L1 is a better alternative than pectoralis muscle to substitute L3 for analysis of muscle mass from regular chest CT scans.