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Background: Most patients with cystic fibrosis (CF) suffer from pancreatic insufficiency, leading to fat malabsorption, malnutrition and abdominal discomfort. Until recently, no specific tool was available for assessing gastro-intestinal related quality of life (GI QOL) in patients with CF. As the Horizon2020 project MyCyFAPP aims to improve GI QOL by using a newly designed mobile application, a sensitive and reliable outcome measure was needed. We aimed to study the applicability of the existing child-specific Pediatric Quality of Life Inventory, Gastrointestinal Symptoms Scales and Module (PedsQL GI) in children with CF. Methods: A multicenter, prospective observational study was performed in 6 European centers to validate the PedsQL GI in children with CF during 3 months. Results: In total, 248 children and their parents were included. Within-patient variability of PedsQL GI was low (24.11), and there was reasonable agreement between children and parents (ICC 0.681). Nine of 14 subscales were informative (no ceiling effect). The PedsQL GI and the median scores for 4 subscales were significantly lower in patients compared to healthy controls. Positive associations were found between PedsQL GI and age (OR = 1.044, p = 0.004) and between PedsQL GI and BMI z-score (OR = 1.127, p = 0.036). PedsQL GI correlated with most CFQ-R subscales (r 0.268 to 0.623) and with a Visual Analogue Scale (r = 0.20). Conclusions: PedsQL GI is a valid and applicable instrument to assess GI QOL in children with CF. Future research efforts should examine the responsiveness of the CF PedsQL GI to change in the context of clinical interventions and trials.

Background Expressing anthropometric parameters (height, weight, BMI) as z-score is a key principle in the clinical assessment of children and adolescents. The Centre for Disease Control and Prevention (CDC) growth charts and the CDC-LMS method for z-score calculation are widely used to assess growth and nutritional status, though they can be imprecise in some percentiles. Objective To improve the accuracy of z-score calculation by revising the statistical method using the original data used to develop current z-score calculators. Design A Gaussian Process Regressions (GPR) was designed and internally validated. Z-scores for weight-for-age (WFA), height-for-age (HFA) and BMI-for-age (BMIFA) were compared with WHO and CDC-LMS methods in 1) standard z-score cut-off points, 2) simulated population of 3000 children and 3) real observations 212 children aged 2 to 18 yo. Results GPR yielded more accurate calculation of z-scores for standard cut-off points (p&type=&type=0.001) with respect to CDC-LMS and WHO approaches. WFA, HFA and BMIFA z-score calculations based on the 3 different methods using simulated and real patients, showed a large variation irrespective of gender and age. Z-scores around 0 +/- 1 showed larger variation than the values above and below +/- 2. Conclusion The revised z-score calculation method was more accurate than CDC-LMS and WHO methods for standard cut-off points. On simulated and real data, GPR based calculation provides more accurate z-score determinations, and thus, a better classification of patients below and above cut-off points. Statisticians and clinic