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INTRODUCTION Following body mass index (BMI) percentiles, BMI declines after infancy and then there is a second rise in BMI between the age of 3 and 7 years until adulthood. [...], BACKGROUND/OBJECTIVES: Adiposity rebound (AR) is defined as the nadir or the inflexion point of body mass index (BMI) percentiles between the age of 3 and 7 years. An early rebound is seen as a risk of obesity and, thus, AR is considered as a suitable time period for prevention. As BMI does not reflect body composition, we aimed to examine the rebounds of fat mass index (FMI) and fat-free mass index (FFMI) together with BMI. SUBJECTS/METHODS: Cross-sectional data of 19 264 children aged 3-11 years were pooled from three German studies (Kiel Obesity Prevention Study, the project 'Better diet. More exercise. KINDERLEICHT-REGIONS' and regular examinations of Jena children). Height and weight were measured. Fat mass (FM) and fat-free mass (FFM) were obtained from bioelectrical impedance analysis and analysed using a population-specific algorithm. Percentiles of BMI, FMI and FFMI were constructed by the LMS method. RESULTS: Both BMI and FMI percentiles showed a rebound, whereas FFMI percentiles steadily increased with age. On P90, FMI rebound was about 1.6-1.8 years later compared with that of BMI, that is, at ages 4.2 years (BMI) and 5.8 years (FMI) in boys and at 4.2 years (BMI) and 6.0 years (FMI) in girls. At AR, the slope of the BMI-P90 was explained by increases in FFMI rather than FMI. By contrast, at FMI rebound, the slope of BMI was strongly related to FMI. CONCLUSIONS: BMI rebound does not equal the rebound of FM. At AR, the slope in BMI is determined by the increase in FFMI. AR should be defined as FMI rebound rather than BMI rebound. European Journal of Clinical Nutrition (2013) 67, 984-989; doi: 10.1038/ejcn.2013.131; published online 17 July 2013 Keywords: BMI; fat mass index; adiposity rebound; obesity

Purpose: We report an analysis of minimal residual/detectable disease (MRD) as a predictor of outcome in previously untreated patients with follicular lymphoma (FL) from the randomized, multicenter GALLIUM (ClinicalTrials.gov identifier: NCT01332968) trial., Patients and Methods: Patients received induction with obinutuzumab (G) or rituximab (R) plus bendamustine, or cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP) or cyclophosphamide, vincristine, prednisone (CVP) chemotherapy, followed by maintenance with the same antibody in responders. MRD status was assessed at predefined time points (mid-induction [MI], end of induction [EOI], and at 4-6 monthly intervals during maintenance and follow-up). Patients with evaluable biomarker data at diagnosis were included in the survival analysis., Results: MRD positivity was associated with inferior progression-free survival (PFS) at MI (hazard ratio [HR], 3.03 [95% CI, 2.07 to 4.45]; P < .0001) and EOI (HR, 2.25 [95% CI, 1.53 to 3.32]; P < .0001). MRD response was higher after G- versus R-chemotherapy at MI (94.2% v 88.9%; P = .013) and at EOI (93.1% v 86.7%; P = .0077). Late responders (MI-positive/EOI-negative) had a significantly poorer PFS than early responders (MI-negative/EOI-negative; HR, 3.11 [95% CI, 1.75 to 5.52]; P = .00011). The smallest proportion of MRD positivity was observed in patients receiving bendamustine at MI (4.8% v 16.0% in those receiving CHOP; P < .0001). G appeared to compensate for less effective chemotherapy regimens, with similar MRD response rates observed across the G-chemo groups. During the maintenance period, more patients treated with R than with G were MRD-positive (R-CHOP, 20.7% v G-CHOP, 7.0%; R-CVP, 21.7% v G-CVP, 9.4%). Throughout maintenance, MRD positivity was associated with clinical relapse., Conclusion: MRD status can determine outcome after induction and during maintenance, and MRD negativity is a prerequisite for long-term disease control in FL. The higher MRD responses after G- versus R-based treatment confirm more effective tumor cell clearance.

We report assessment of minimal residual disease (MRD) status and its association with outcome in rituximab-refractory follicular lymphoma (FL) in the randomized GADOLIN trial (NCT01059630). Patients received obinutuzumab (G) plus bendamustine (Benda) induction followed by G maintenance, or Benda induction alone. Patients with a clonal marker (t[14;18] translocation and/or immunoglobulin heavy or light chain rearrangement) detected at study screening were assessed for MRD at mid-induction (MI), end of induction (EOI), and every 6-24 months post-EOI/discontinuation by real-time quantitative PCR. At MI, 41/52 (79%) patients receiving G-Benda were MRD-negative vs. 17/36 (47%) patients receiving Benda alone (p = 0.0029). At EOI, 54/63 (86%) patients receiving G-Benda were MRD-negative vs. 30/55 (55%) receiving Benda alone (p = 0.0002). MRD-negative patients at EOI had improved progression-free survival (HR, 0.33, 95% CI, 0.19-0.56, p < 0.0001) and overall survival (HR, 0.39, 95% CI, 0.19-0.78, p = 0.008) vs. MRD-positive patients, and maintained their MRD-negative status for longer if they received G maintenance than if they did not. These results suggest that the addition of G to Benda-based treatment during induction can significantly contribute to the speed and depth of response, and G maintenance in MRD-negative patients potentially delays lymphoma regrowth.

Background and Aim of the Study: Successful preventive measures can stop a further increase in the prevalence of overweight in children and adolescents. However, up to now, the required effect sizes of interventions for reducing childhood overweight remain unclear. The calculation of the energy gap (excess calories consumed over calories expended) offers the possibility to estimate the required effect sizes. In this work 2 approaches to calculate the energy gap will be compared., Methods: Longitudinal data of 1690 children and adolescents of the Kiel Obesity Prevention Study (KOPS) on measured height, weight, fat mass and fat-free mass (using bioelectrical impedance analysis) at age 6 and 10 years will be used to calculate energy gap with 2 different approaches: (i) using age-independent changes in fat mass and fat-free mass (old approach) and (ii) using a mathematic model of weight dynamic (new approach)., Results: Energy gap according to the old approach was 140 kcal/day; by contrast, new modeling resulted in an energy gap between 270 and 370 kcal/day. Both, BMI and fat mass were suitable to calculate energy gap and led to nearly same results. Exceeding the 90(th) percentile of BMI or fat mass (incidence approach) as well as large changes within the normal range (i.e. between the 10(th) and the 90(th) percentile) led to large energy gaps. Thus, all children with large energy gaps have to be characterized as at risk for overweight., Conclusion: The new approach seems to be convincing because it considered the additional energy expenditure for building fat-free mass due to increasing age and weight.Calculating energy gap offers a new approach for prevention of overweight. It shows that the required effect sizes of prevention measures have to be in a region of 140 to 400 kcal/day. This differs clearly from energy reduction of diets in the therapy of obesity., (© Georg Thieme Verlag KG Stuttgart · New York.)

Objective: Calculation of attributable risks (ARs) of childhood overweight to estimate effectiveness of prevention strategies., Methods: We used pooled data of 4 population-based German studies including 34240 children and adolescents aged 3 to 18 years to calculate the impact of familial, social, "early life", and lifestyle factors on overweight. ARs (joint for all determinants as well as partial risks) were calculated., Results: The prevalence of childhood overweight was 13.4%. Successfully tackling all determinants can reduce overweight by 77.7% (ie, from 13.4% to 3.0%; = joint AR) with partial effects of treating parental overweight (42.5%); improving social status (14.3%); reducing media time to <1 hour per day (11.4%); and not smoking during pregnancy, low weight gain during pregnancy, and breastfeeding (together 9.5%), respectively. Improving all preventable risk factors (ie, early life factors and lifestyle) the effect is 9.2%. Media time has the strongest effect., Conclusions: The determinants identified explained 78% of the prevalence of overweight. Taking into account the partial ARs, the effectiveness of lifestyle interventions to prevent overweight in children is limited. Our data argue in favor of interventions aimed at families and social environments, with a major focus on promoting a lower screen time and computer use in children.

Objective: The aim of this study was to define body fat percentiles for German children and adolescents aged 3-16 years using the largest German database., Methods: The study population included 11,632 girls and 11,604 boys. Data were pooled from: i) Kiel Obesity Prevention Study (KOPS), acquisition period: 1996-2008, n = 12,237; ii) 'Better diet. More exercise. KINDERLEICHT-REGIONS', acquisition period: 2007, n = 9,405; and iii) examination of Jena schoolchildren, acquisition period: 2005, n = 1,594. Body fat mass was measured by bioelectrical impedance analysis using a population-specific algorithm. Data were weighted to achieve a representative sample for Germany. Percentile curves were constructed by the LMS method and proved by Worm plots and Q-statistic., Results: In both genders, the higher body fat percentile curves sloped downwards to age 7 years, whereas the lower percentiles declined up to 8.5 years. Thereafter fat mass remained nearly constant with age in boys and increased in girls. The 10th percentile achieved a minimum of 10-11% body fat in both genders, whereas the 90th percentile curve fluctuated between 29 and 44% in boys or 30-43% in girls. The association between fat mass and blood pressure was too weak to define disease-related cut-offs., Conclusion: These body fat percentiles are suitable reference values for German children and adolescents., (Copyright © 2012 S. Karger GmbH, Freiburg.)