Single-agent versus combination chemotherapy in patients with advanced non-small cell lung cancer and a performance status of 2 : prognostic factors and treatment selection based on two large randomized clinical trials

Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.

Missing data in randomized clinical trials for weight loss: scope of the problem, state of the field, and performance of statistical methods.

BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis.

Maintaining Tissue Perfusion in High-Risk Surgical Patients: A Systematic Review of Randomized Clinical Trials

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mislabeling controlled clinical trials (CCTs) as "randomized clinical trials (RCTs)" in dental specialty journals

This study aimed to investigate whether studies published in dental journals with the highest impact factor, representing the 5 major dental specialties and titled as randomized clinical trials (RCTs) are truly RCTs. A second objective was to explore the association of journal type and other publication characteristics on correct classification.

Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

Bayesian doubly optimal group sequential designs for randomized clinical trials

When conducting a randomized comparative clinical trial, ethical, scientific or economic considerations often motivate the use of interim decision rules after successive groups of patients have been treated. These decisions may pertain to the comparative efficacy or safety of the treatments under study, cost considerations, the desire to accelerate the drug evaluation process, or the likelihood of therapeutic benefit for future patients. At the time of each interim decision, an important question is whether patient enrollment should continue or be terminated; either due to a high probability that one treatment is superior to the other, or a low probability that the experimental treatment will ultimately prove to be superior. The use of frequentist group sequential decision rules has become routine in the conduct of phase III clinical trials. In this dissertation, we will present a new Bayesian decision-theoretic approach to the problem of designing a randomized group sequential clinical trial, focusing on two-arm trials with time-to-failure outcomes. Forward simulation is used to obtain optimal decision boundaries for each of a set of possible models. At each interim analysis, we use Bayesian model selection to adaptively choose the model having the largest posterior probability of being correct, and we then make the interim decision based on the boundaries that are optimal under the chosen model. We provide a simulation study to compare this method, which we call Bayesian Doubly Optimal Group Sequential (BDOGS), to corresponding frequentist designs using either O'Brien-Fleming (OF) or Pocock boundaries, as obtained from EaSt 2000. Our simulation results show that, over a wide variety of different cases, BDOGS either performs at least as well as both OF and Pocock, or on average provides a much smaller trial. ^

Pronounced reduction of postprandial glucagon by lixisenatide:a meta-analysis of randomized clinical trials

Glucagon-like peptide-1 (GLP-1) receptor agonists improve islet function and delay gastric emptying in patients with type 2 diabetes mellitus (T2DM). This meta-analysis aimed to investigate the effects of the once-daily prandial GLP-1 receptor agonist lixisenatide on postprandial plasma glucose (PPG), glucagon and insulin levels. Methods: Six randomized, placebo-controlled studies of lixisenatide 20μg once daily were included in this analysis: lixisenatide as monotherapy (GetGoal-Mono), as add-on to oral antidiabetic drugs (OADs; GetGoal-M, GetGoal-S) or in combination with basal insulin (GetGoal-L, GetGoal-Duo-1 and GetGoal-L-Asia). Change in 2-h PPG and glucose excursion were evaluated across six studies. Change in 2-h glucagon and postprandial insulin were evaluated across two studies. A meta-analysis was performed on least square (LS) mean estimates obtained from analysis of covariance (ANCOVA)-based linear regression. Results: Lixisenatide significantly reduced 2-h PPG from baseline (LS mean difference vs. placebo: -4.9mmol/l, p<0.001) and glucose excursion (LS mean difference vs. placebo: -4.5mmol/l, p<0.001). As measured in two studies, lixisenatide also reduced postprandial glucagon (LS mean difference vs. placebo: -19.0ng/l, p<0.001) and insulin (LS mean difference vs. placebo: -64.8 pmol/l, p<0.001). There was a stronger correlation between 2-h postprandial glucagon and 2-h PPG with lixisenatide than with placebo. Conclusions: Lixisenatide significantly reduced 2-h PPG and glucose excursion together with a marked reduction in postprandial glucagon and insulin; thus, lixisenatide appears to have biological effects on blood glucose that are independent of increased insulin secretion. These effects may be, in part, attributed to reduced glucagon secretion. © 2014 John Wiley and Sons Ltd.

Effectiveness of inulin intake on indicators of chronic constipation; a meta-analysis of controlled randomized clinical trials

Background: Constipation is an intestinal dysfunction. Prebiotics, such as inulin, can improve bowel function by positively influencing intestinal biota. Aim: To analyze the scientific evidence for the role of inulin in improving bowel function in patients with chronic constipation. Methods: A meta-analysis of randomized controlled clinical trials was conducted, grounded on a literature search for the period 1995-2013 (descriptors: inulin & constipation) on PubMed, ScieLo and Central Trials Register Cochrane databases. A total of 24 articles were found, 5 of them were selected for this meta-analysis, involving 252 subjects (experimental group: n = 144, control group: n = 108). The quality of the studies was assessed using the Jadad scale. Results: We found a significant overall effect of inulin on stool frequency (DEM = 0.69, 95%CI: 0.04, 1.34), stool consistency (Bristol scale) (DEM = 1.07, 95% CI: 0.70, 1.45), transit time (DEM = -0.57, 95% CI: -0.99, -0.15) and hardness of stool (RR = 0.42, 95% CI: 0.26, 0.70). Pain and bloating do not improve with inulin intake. Conclusions: inulin intake has a positive effect on bowel function.

Randomization in clinical trials in orthodontics: its significance in research design and methods to achieve it

Randomization is a key step in reducing selection bias during the treatment allocation phase in randomized clinical trials. The process of randomization follows specific steps, which include generation of the randomization list, allocation concealment, and implementation of randomization. The phenomenon in the dental and orthodontic literature of characterizing treatment allocation as random is frequent; however, often the randomization procedures followed are not appropriate. Randomization methods assign, at random, treatment to the trial arms without foreknowledge of allocation by either the participants or the investigators thus reducing selection bias. Randomization entails generation of random allocation, allocation concealment, and the actual methodology of implementing treatment allocation randomly and unpredictably. Most popular randomization methods include some form of restricted and/or stratified randomization. This article introduces the reasons, which make randomization an integral part of solid clinical trial methodology, and presents the main randomization schemes applicable to clinical trials in orthodontics.

Effect of platform switching on peri-implant bone levels: a randomized clinical trial

The concept of platform switching has been introduced to implant dentistry based on observations of reduced peri-implant bone loss. However, randomized clinical trials are still lacking. This study aimed to test the hypothesis that platform switching has a positive impact on crestal bone-level changes.

Publication and non-publication of clinical trials: longitudinal study of applications submitted to a research ethics committee

BACKGROUND: Not all clinical trials are published, which may distort the evidence that is available in the literature. We studied the publication rate of a cohort of clinical trials and identified factors associated with publication and nonpublication of results. METHODS: We analysed the protocols of randomized clinical trials of drug interventions submitted to the research ethics committee of University Hospital (Inselspital) Bern, Switzerland from 1988 to 1998. We identified full articles published up to 2006 by searching the Cochrane CENTRAL database (issue 02/2006) and by contacting investigators. We analyzed factors associated with the publication of trials using descriptive statistics and logistic regression models. RESULTS: 451 study protocols and 375 corresponding articles were analyzed. 233 protocols resulted in at least one publication, a publication rate of 52%. A total of 366 (81%) trials were commercially funded, 47 (10%) had non-commercial funding. 346 trials (77%) were multi-centre studies and 272 of these (79%) were international collaborations. In the adjusted logistic regression model non-commercial funding (Odds Ratio [OR] 2.42, 95% CI 1.14-5.17), multi-centre status (OR 2.09, 95% CI 1.03-4.24), international collaboration (OR 1.87, 95% CI 0.99-3.55) and a sample size above the median of 236 participants (OR 2.04, 95% CI 1.23-3.39) were associated with full publication. CONCLUSIONS: In this cohort of applications to an ethics committee in Switzerland, only about half of clinical drug trials were published. Large multi-centre trials with non-commercial funding were more likely to be published than other trials, but most trials were funded by industry.