Influence of total sugar intake on metabolic blood markers at 8 years of age in the Childhood Obesity Project

PURPOSE We aimed to characterize the association of dietary sugar intake with blood lipids and glucose-related markers in childhood. METHODS Data from the multicentric European Childhood Obesity Project Trial were used. Three-day weighed dietary records were obtained at 8~years of age along with serum concentrations of triglycerides, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), glucose, and insulin. Total sugar intake comprised all mono- and disaccharides; different sugar sources were defined. Linear regression models were applied to investigate the cross-sectional association of total sugar intake with blood lipids and glucose-related markers with adjustment for total energy intake using the residual method. RESULTS Data were available for 325 children. Children consumed on average 332~kcal (SD 110) and 21% (SD 6) of energy from total sugar. In an energy-adjusted model, an increase of 100~kcal from total sugar per day was significantly associated with a z score HDL-C decrease (-~0.14; 95% CI -~0.01, -~0.27; p value = 0.031). Concerning different food groups of total sugar intake, 100~kcal total sugar from sweetened beverages was negatively associated with z score HDL-C (-~1.67; 95% CI -~0.42, -~2.91; p value = 0.009), while total sugar from milk products was positively related to z score HDL-C (1.38, 95% CI 0.03, 2.72; p value = 0.045). None of the other blood lipids or glucose-related markers showed a significant relationship with total sugar intake. CONCLUSION Increasing dietary total sugar intake in children, especially from sweetened beverages, was associated with unfavorable effects on HDL-C, which might increase the long-term risk for dyslipidemia and cardiovascular disease. CLINICAL TRIAL REGISTRY ClinicalTrials.gov Identifier: NCT00338689; Registered: June 19, 2006. URL: https://clinicaltrials.gov/ct2/show/NCT00338689?term=NCT00338689&rank=1

Concordance in measurable residual disease result after first and second induction cycle in acute myeloid leukemia : An outcome- and cost-analysis

Peer reviewe

Associations of sugar intake with anthropometrics in children from ages 2 until 8 years in the EU Childhood Obesity Project

Purpose: We determined the association of total sugar intake with body weight and fat mass in children on an energy-equivalent basis and potential changes in the association from 2 to 8 years of age. Methods: Data were available from the Childhood Obesity Project Trial initiated in 2002. Sugar intake was measured by 3-day weighed food protocols at 2, 3, 4, 5, 6, and 8 years of age. Body mass index (BMI) and fat mass index (FMI) were available at the same time points. To investigate the association of sugar intake with anthropometrics over time, linear mixed models were applied. Odds ratios for having a high BMI or FMI (above one standard deviation) were estimated by logistic random-effects models. To control for total energy intake, the residual method was chosen and models were additionally adjusted for total energy intake. Results: Data were available for 809 children with in total 2846 observations. In an isocaloric model, an increase of 100 kcal from sugar per day was significantly associated with lower zBMI ( 12 0.033; 95% CI 120.061, 12 0.005) and zFMI ( 12 0.050; 95% CI 12 0.089, 12 0.011). In addition, a 100 kcal higher sugar intake was related to lower odds of having a high zBMI (OR 0.743; 95% CI 0.611, 0.903). Conclusion: This study provides no indication that increased total sugar intake positively affects BMI on an energy-equivalent basis. Whether the negative association of sugar is due to physiological effects or points more to macronutrient preferences or a reporting bias (lower sugar intake) in children with higher BMI can be debated. Clinical trial registry: ClinicalTrials.gov Identifier: NCT00338689; Registered: June 19, 2006. URL: http://clinicaltrials.gov/ct2/show/NCT00338689?term=NCT00338689&rank=1

Commercial complementary food use amongst European infants and children: results from the EU Childhood Obesity Project

Purpose: The objective of this secondary analysis is to describe the types of commercial complementary foods (CCF) consumed by infants and young children enrolled in the European Childhood Obesity Project (CHOP), to describe the contribution of CCF to dietary energy intakes and to determine factors associated with CCF use over the first 2 years of life. Methods: The CHOP trial is a multicenter intervention trial in Germany, Belgium, Italy, Poland and Spain that tested the effect of varying levels of protein in infant formula on the risk for childhood obesity. Infants were recruited from October 2002 to June 2004. Dietary data on CCF use for this secondary analysis were taken from weighted, 3-day dietary records from 1088 infants at 9 time points over the first 2 years of life. Results: Reported energy intakes from CCF during infancy (4\u20139\ua0months) was significantly higher (p 64 0.002) amongst formula-fed children compared to breastfed children. Sweetened CCF intakes were significantly higher (p 64 0.009) amongst formula-fed infants. Female infants were fed significantly less CCF and infant age was strongly associated with daily CCF intakes, peaking at 9\ua0months of age. Infants from families with middle- and high-level of education were fed significantly less quantities of CCF compared to infants with parents with lower education. Sweetened CCF were very common in Spain, Italy and Poland, with over 95% of infants and children fed CCF at 9 and 12\ua0months of age consuming at least one sweetened CCF. At 24\ua0months of age, 68% of the CHOP cohort were still fed CCF. Conclusions: CCF comprised a substantial part of the diets of this cohort of European infants and young children. The proportion of infants being fed sweetened CCF is concerning. More studies on the quality of commercial complementary foods in Europe are warranted, including market surveys on the saturation of the Western European market with sweetened CCF products

Association of early protein intake and pre-peritoneal fat at five years of age : Follow-up of a randomized clinical trial

BACKGROUND AND AIMS: The double-blind randomized European Childhood Obesity Project (CHOP) demonstrated that reduced protein content in infant formula leads to a lower body mass index (BMI) up to six years of age. Here we aimed at assessing pre-peritoneal fat, a marker of visceral fat, in children participating in the CHOP trial. METHODS AND RESULTS: Healthy term formula-fed infants in five European countries were randomized either to higher (n = 550) or lower (n = 540) protein formulas in the first year of life. Infants who were exclusively breastfed for at least three months (n = 588) were enrolled as an observational (non randomized) group. At age 5 years, subcutaneous fat (SC) and pre-peritoneal fat (PP) were measured by ultrasound in a subgroup of 275 children. The PP fat layer was thicker in the higher compared to the lower protein group (adjusted estimated difference: 0.058 cm, 95%CI 0.002; 0.115; p = 0.043), while SC fat was not different. Girls showed a thicker SC fat layer than boys. CONCLUSIONS: Higher protein intake in formula-fed infants appears to enhance pre-peritoneal fat tissue accumulation at the age of 5 years, but not of subcutaneous fat, which may trigger adverse metabolic and health consequences

Bayesian Inference for Optimization of Interim Analysis in Clinical Trials By Incorporation of Historical Data:Reanalysis of the HOVON AML 132 Clinical Trial

Background:Prospective randomized trials remain pivotal to evaluate the benefit of new therapies. Primary endpoints typically focus on long-term endpoints after study completion, whereas interim analyses are monitoring safety and toxicity. Although the traditional or frequentist approach is widely used to analyze endpoints and anticipate the number of events needed upon trial completion, it is limited by the need for prior assumptions of the expected treatment effect, long-term follow-up, and conservative stopping rules. Bayesian inference might overcome these limitations, for which prior knowledge is combined with new data to compute the posterior distribution, enhancing the strength of the ongoing trial. This study aims to evaluate whether a Bayesian approach using historical data as prior knowledge might support decision-making at interim time points of the HO132 phase 3 clinical trial for patients with acute myeloid leukemia (AML), that was recently reported (Löwenberg et al, 2021).Methods:In the HO132 trial, 927 patients aged 18 to 65 years with newly diagnosed AML were randomized between intensive induction ± lenalidomide. The primary endpoint EFS was not different between experimental and control treatment (HR 0.99, p=0.96). After excluding 64 patients for lenalidomide dose selection, three interim analyses were retrospectively introduced after inclusion of 150, 300 and 600 patients to assess whether the lack of efficacy emerged early during conduct of the trial. The control treatment arm was reinforced using 445 historical control treatment patients from the preceding AML trial (HO102). Patients of both control arms were matched 1:1 using propensity scores based on age and leukemia risk. At each interim analysis, posterior distributions were calculated for endpoints including complete remission (CR) after induction, minimal residual disease (MRD) in CR, early death within 2 months, and EFS. The posterior distributions were summarized to provide point estimates and 95% credible intervals (CI) on the treatment difference and hazard ratio (HR) between both arms. For binary outcomes, the probability of success (range 0-100%) of the control versus the experimental treatment was computed. For EFS, the probability of the HR being below 0.76 was calculated, which was the assumed effect size in the HO132 statistical plan. A probability of <10% was considered as the futility threshold.Results:We compared HO132 experimental treatment with control treatment reinforced with matched historical patients for the previously mentioned endpoints. The proportion of patients obtaining CR was lower with experimental compared with control treatment at interim analysis 1 (Fig 1A, treatment difference: -9.0% [95% CI -19.9 to 1.4]) and the probability for demonstrating a superior CR rate with experimental treatment was 4%. At interim analysis 2 and 3 the treatment difference was -8.1% [95% CI -16.3 to 0.001] and -9.8% [95% CI -18.6 to -4.1] with a probability of success of 3% and 0%, respectively.Patients in CR and assigned to the experimental treatment arm were less often MRDneg compared with control at every interim analysis (treatment difference: -10.3% [95% CI -28.7 to 8.0]; -8.1% [95% CI -21.5 to 5.6]; -5.6% [95% CI -14.5 to 3.4], respectively), with a respective probability not meeting the futility stopping rule of 13%, 12% and 11%.Early deaths were more frequently observed with experimental treatment versus control (treatment difference: 5.5% [95% CI -0.7 to 12.8]), with 4% probability of fewer early deaths with experimental treatment than control at interim analysis 1. The treatment differences for early death at interim analyses 2 and 3 were 3.5% (95% CI -1.7 to 9.2) and 2.0% (95% CI -1.9 to -6.0) with a probability of 10% and 15%, respectively.EFS was similar between both arms at interim analysis 2 and 3 (HR 1.00, and HR 1.04, respectively, Fig 1B), with a median follow-up time of 10 and 16 months, respectively. At interim analysis 2, this resulted in a probability of 4% reaching the anticipated HR of 0.76, which probability was 0% at interim analysis 3.Conclusion:Reanalyzing the prospective conduct of the HO132 study using Bayesian inference identified a low probability of success of the experimental treatment at three successive putative interim analyses based on important efficacy markers. Consequently, a low probability of efficacy during trial conduct might support early termination of the trial

Bayesian Inference for Optimization of Interim Analysis in Clinical Trials By Incorporation of Historical Data:Reanalysis of the HOVON AML 132 Clinical Trial

Background:Prospective randomized trials remain pivotal to evaluate the benefit of new therapies. Primary endpoints typically focus on long-term endpoints after study completion, whereas interim analyses are monitoring safety and toxicity. Although the traditional or frequentist approach is widely used to analyze endpoints and anticipate the number of events needed upon trial completion, it is limited by the need for prior assumptions of the expected treatment effect, long-term follow-up, and conservative stopping rules. Bayesian inference might overcome these limitations, for which prior knowledge is combined with new data to compute the posterior distribution, enhancing the strength of the ongoing trial. This study aims to evaluate whether a Bayesian approach using historical data as prior knowledge might support decision-making at interim time points of the HO132 phase 3 clinical trial for patients with acute myeloid leukemia (AML), that was recently reported (Löwenberg et al, 2021).Methods:In the HO132 trial, 927 patients aged 18 to 65 years with newly diagnosed AML were randomized between intensive induction ± lenalidomide. The primary endpoint EFS was not different between experimental and control treatment (HR 0.99, p=0.96). After excluding 64 patients for lenalidomide dose selection, three interim analyses were retrospectively introduced after inclusion of 150, 300 and 600 patients to assess whether the lack of efficacy emerged early during conduct of the trial. The control treatment arm was reinforced using 445 historical control treatment patients from the preceding AML trial (HO102). Patients of both control arms were matched 1:1 using propensity scores based on age and leukemia risk. At each interim analysis, posterior distributions were calculated for endpoints including complete remission (CR) after induction, minimal residual disease (MRD) in CR, early death within 2 months, and EFS. The posterior distributions were summarized to provide point estimates and 95% credible intervals (CI) on the treatment difference and hazard ratio (HR) between both arms. For binary outcomes, the probability of success (range 0-100%) of the control versus the experimental treatment was computed. For EFS, the probability of the HR being below 0.76 was calculated, which was the assumed effect size in the HO132 statistical plan. A probability of <10% was considered as the futility threshold.Results:We compared HO132 experimental treatment with control treatment reinforced with matched historical patients for the previously mentioned endpoints. The proportion of patients obtaining CR was lower with experimental compared with control treatment at interim analysis 1 (Fig 1A, treatment difference: -9.0% [95% CI -19.9 to 1.4]) and the probability for demonstrating a superior CR rate with experimental treatment was 4%. At interim analysis 2 and 3 the treatment difference was -8.1% [95% CI -16.3 to 0.001] and -9.8% [95% CI -18.6 to -4.1] with a probability of success of 3% and 0%, respectively.Patients in CR and assigned to the experimental treatment arm were less often MRDneg compared with control at every interim analysis (treatment difference: -10.3% [95% CI -28.7 to 8.0]; -8.1% [95% CI -21.5 to 5.6]; -5.6% [95% CI -14.5 to 3.4], respectively), with a respective probability not meeting the futility stopping rule of 13%, 12% and 11%.Early deaths were more frequently observed with experimental treatment versus control (treatment difference: 5.5% [95% CI -0.7 to 12.8]), with 4% probability of fewer early deaths with experimental treatment than control at interim analysis 1. The treatment differences for early death at interim analyses 2 and 3 were 3.5% (95% CI -1.7 to 9.2) and 2.0% (95% CI -1.9 to -6.0) with a probability of 10% and 15%, respectively.EFS was similar between both arms at interim analysis 2 and 3 (HR 1.00, and HR 1.04, respectively, Fig 1B), with a median follow-up time of 10 and 16 months, respectively. At interim analysis 2, this resulted in a probability of 4% reaching the anticipated HR of 0.76, which probability was 0% at interim analysis 3.Conclusion:Reanalyzing the prospective conduct of the HO132 study using Bayesian inference identified a low probability of success of the experimental treatment at three successive putative interim analyses based on important efficacy markers. Consequently, a low probability of efficacy during trial conduct might support early termination of the trial