Mean Dropout Rate Research Articles

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Dropout Rates in Placebo-Controlled and Active-Control Clinical Trials of Antipsychotic Drugs

Dropout rates in randomized clinical trials of antipsychotic drugs have consistently been reported to be high, and the use of a placebo-controlled design is hypothesized to be one of the reasons for this. To investigate this hypothesis in a meta-analysis of available data from pertinent clinical trials. Comprehensive search of PubMed- and MEDLINE-listed journals. Double-blind randomized controlled clinical trials of the second-generation antipsychotics risperidone, olanzapine, quetiapine, amisulpride, ziprasidone, and aripiprazole meeting the following criteria: unselected patient population with a diagnosis of schizophrenia or schizoaffective disorder, change in psychopathologic symptoms as the primary end point, and trial duration of 12 weeks or less. Sample size, mean age, baseline disease severity, dropout rate, trial design, trial duration, and publication year. Thirty-one trials meeting the inclusion criteria were found, comprising 10 058 subjects. Weighted mean dropout rates in the active treatment arms were significantly higher in placebo-controlled trials (PCTs) than in active-control trials: 48.1% (PCTs) vs 28.3% (active-control trials) for second-generation antipsychotics (odds ratio, 2.34; 95% confidence interval, 1.58-3.47) and 55.4% (PCTs) vs 37.2% (active-control trials) for classical antipsychotics (odds ratio, 2.10; 95% confidence interval, 1.29-3.40). Within PCTs, attrition rates were significantly higher in the placebo arms than with second-generation antipsychotics (60.2% vs 48.1%; odds ratio, 1.63; 95% confidence interval, 1.37-1.94). Within the subset of trials in which both second-generation and classical antipsychotics were used, dropout rates were significantly higher with classical antipsychotics. Use of a placebo-controlled design had a major effect on the dropout rates observed. Because high dropout rates affect the generalizability of such studies, it is suggested that, in addition to the PCTs, studies with alternative designs need to be considered when evaluating an antipsychotic's clinical profile.

The outcome of childhood obesity management depends highly upon patient compliance.

Over the last 20 years, obesity in childhood and adolescence has become a major public health concern due to dramatically increasing prevalence rates. We evaluated the outcome of 294 children (135 girls, 159 boys) aged 6-16 years (median 10.9 years) enrolled in a single centre outpatient obesity intervention programme consisting of periodical visits to the outpatient unit with regular medical and dietetic counselling aiming at a modification of dietary and activity patterns of patients and parents. The average number of visits to the outpatient unit was 3.6 (SD 2.7) with a mean visit interval of 62.1 days. A mean drop-out rate of 27.5% between each scheduled appointment occurred. In a stepwise regression model, neither reduction of the standard deviation score of patients' body mass index (BMI-SDS) nor dietary counselling contributed to the total number of visits. The only significant contributor was the patients' initial BMI-SDS explaining 4.6% of the variance of attended visits adjusted for age and sex. Segregation of the patients into an "obesity" (initial BMI-SDS >/=90th percentile, at least three visits attended, n=59) and an "excessive obesity" (initial BMI-SDS >/=99th percentile, at least four visits attended, n=75) subgroup showed a mean reduction of BMI-SDS in the "obesity" group at visit three of 0.14 (SD 0.21, P<0.0001), and in the "excessive obese" group at visit four of 0.17 (SD 0.22, P<0.001). In a stepwise regression model, the mean interval between visits and regular dietary counselling explained 11.7% of the variance of BMI-SDS reduction at visit three in both subgroups. there is an urgent need for efficient strategies to improve adherence of outpatients to obesity treatment since, in terms of reduction in body mass index standard deviation score, a beneficial outcome can be achieved for compliant obese children and adolescents.

Efficacy and safety of neuroleptics in behavioral disorders associated with dementia.

Neuroleptics are commonly used to treat behavioral disorders associated with dementia. However, their safety and efficacy have not been well established in these patients. A meta-analysis of randomized, controlled (either placebo or active drug), double-blind trials published since 1966 (N = 16; 499 treated, 112 active controls, and 123 placebo) was conducted. Data were collected on proportion of patients with clinically significant improvement, significant side effects, and dropout rates. Pooled mean percentages of patients who improved (95% CI): all neuroleptics, 64% (54% to 74%); low potency, 63% (54% to 72%); moderate potency, 70% (56% to 85%); moderate-high potency, 62% (49% to 75%); and high potency, 69% (49% to 90%). Thus, no differences in efficacy existed between different potencies of neuroleptics. Therapeutic effect (neuroleptic minus placebo) was only 26% (14% to 38%). Treatment-emergent side effects were more common for neuroleptics vs. placebo (mean difference = 25%, 13% to 37%), but pooled mean dropout rates were not different (mean difference = 4%, -7% to 14%). Neither weighting by clinical trial quality (3 raters; weighted agreement, 83% to 92%) nor exclusion of poor quality trials changed the results. Neuroleptics have small but significant efficacy over placebo in this population, and the efficacy rate is equivalent to the side effect rate. Comparing different neuroleptics shows they have similar efficacy, side effects, and dropout rates. Further study to determine more specific drug-responsive behaviors is needed to maximize benefits of these drugs.

Dropping Out of Middle School: A Multilevel Analysis of Students and Schools

Prior research on dropouts has often focused on high schools and examined the issue from either the individual perspective or the institutional perspective. Using data from the National Educational Longitudinal Survey of 1988 and a new form of hierarchical linear modeling (HLM), this study focuses on dropouts from middle school and examines the issue from both individual and institutional perspectives. At the individual level, the results identified a number of family and school experience factors that influence the decision to leave school, with grade retention being the single most powerful predictor. But disaggregating the analysis also revealed that there are widespread differences in the effects of these factors on White, Black, and Hispanic students. At the institutional level, the results revealed that mean dropout rates vary widely between schools and that most of the variation can be explained by differences in the background characteristics of students. But restricting the analysis to lower SES schools shows widespread differences in both mean dropout rates and social class differentiation among such schools. Moreover, much of the variation among those schools can be explained by social composition of students and by several structural features of schools and school climate.

Dropping out of Middle School: A Multilevel Analysis of Students and Schools

Prior research on dropouts has often focused on high schools and examined the issue from either the individual perspective or the institutional perspective. Using data from the National Educational Longitudinal Survey of 1988 and a new form of hierarchical linear modeling (HLM), this study focuses on dropouts from middle school and examines the issue from both individual and institutional perspectives. At the individual level, the results identified a number of family and school experience factors that influence the decision to leave school, with grade retention being the single most powerful predictor. But disaggregating the analysis also revealed that there are widespread differences in the effects of these factors on White, Black, and Hispanic students. At the institutional level, the results revealed that mean dropout rates vary widely between schools and that most of the variation can be explained by differences in the background characteristics of students. But restricting the analysis to lower SES schools shows widespread differences in both mean dropout rates and social class differentiation among such schools. Moreover, much of the variation among those schools can be explained by social composition of students and by several structural features of schools and school climate.