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Objectives: The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations., Study Design and Setting: A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes. Different experimental designs were considered, and performances between designs were compared. One thousand clinical trials were simulated for each design based on an example of modeled disease., Results: According to simulation results, the number of patients needed to reach 80% power was 50 for crossover, 60 for parallel or randomized withdrawal, 65 for drop the loser (DL), and 70 for early escape or play the winner (PW). For a given sample size, each design had its own advantage: low duration (parallel, early escape), high statistical power and precision (crossover), and higher number of patients receiving the active treatment (PW and DL)., Conclusion: Our approach can help to identify the best experimental design, population, and outcome for future RCTs. This may be particularly useful for drug development in rare diseases, theragnostic approaches, or personalized medicine., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: Our main objective was to see whether the therapeutic benefit observed in placebo controlled randomized controlled trials (RCTs) is different between adults and children., Study Design and Setting: We searched three electronic databases for meta-analyses that included double-blind, placebo-controlled RCTs with separate results for adults and children. The selected reviews were classified according to disease and drug used. The heterogeneity of treatment response between adults and children was measured using ratio of odds ratios (RORs)., Results: We selected 89 meta-analyses and calculated RORs for 124 drugs. Heterogeneity in the direction of the treatment effect was observed in one drug and heterogeneity in the quantity of the treatment effect for 13 drugs, indicating significantly different treatment effect in adults when compared with children. RORs were not significantly different from 1 for 110 drugs. For 36 of these drugs, the treatment effect was confirmed in both populations., Conclusion: We found different treatment benefits estimated by clinical trials performed in adults compared with those performed in children for 14 of 124 drugs. Data on dose adjustment and child age groups from RCTs were not adequately reported to investigate their influence on the treatment benefit dissimilarities., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objectives: The aim of this survey was to quantify refusal rates and identify factors of refusal pertaining to studies and recruiting pediatricians in the research recruitment process., Study Design and Setting: We performed a cross-sectional survey on all clinical studies conducted in six pediatric Clinical Investigation Centers in France over an 18-month period. Data were retrieved using a data collection form for the characteristics of each of the studies included in the survey and a questionnaire addressed to recruiting pediatricians. Multilevel models were used for the statistical analysis., Results: Overall, 145 pediatricians approached the families of 999 children and adolescents for participation in 44 studies. In the 36 of the 44 studies that enrolled subjects, median refusal rate was 12.5% (Q1-Q3, 0-28%). Lower refusal rates were associated with therapeutic drug use as the focus of the study [odds ratio (OR), 0.51; 95% CI: 0.25, 1.05], additional hospital stays required for the study (OR, 0.53; 95% CI: 0.28, 0.99), longer duration of the inclusion visit (OR, 0.93/10 min; 95% CI: 0.87, 1), and recruitment by a pediatrician with university teaching responsibilities (OR, 0.26; 95% CI: 0.10, 0.68). Refusal rate was higher when the recruiting pediatrician perceived the study as generating heavy practical burden for the subject and/or its family (OR, 1.3; 95% CI: 1.17, 1.45)., Conclusion: Refusal to participate in clinical research was low and was influenced by factors associated to the objectives and conduct of the studies and factors related to the characteristics and perceptions of the recruiting pediatricians., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The absolute benefit (AB) is extensively used to summarize the results of clinical trials. As the AB depends directly on the patient's baseline risk, therapeutic decisions based on AB tend to favor patients at high risk. To evaluate the consequences of this decision's procedure for life-long therapy, we compare the AB with the gain in event-free life expectancy in a simulated hypertensive population. Our results show that the AB goes through a maximum and then declines as the duration of treatment increases. The amplitude of the variation of AB is independent of the baseline risks but the maximum is reached more quickly in the high-risk patients. Considering the gain in event-free life expectancy, low-risk patients benefit more than high-risk patients do, at the expense of a longer treatment exposure. The interpretation of the AB changes depending on follow-up.