scholarly journals An Individual Patient Data Meta-Analysis with Colombian Studies on the Effect of Dark Chocolate Consumption on Cardiovascular Risk Parameters

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Leidy Alvarez ◽  
Javier Contreras ◽  
Mónica Giraldo
Keyword(s):  
Body Mass Index ◽  
Clinical Trials ◽  
Lipid Profile ◽  
Body Mass ◽  
Meta Analysis ◽  
Abdominal Circumference ◽  
Two Stage ◽  
One Stage ◽  
Study Results ◽  
The One

Background. It is postulated that cocoa solids possess cardioprotective capacity by various mechanisms. In the different cocoa studies evaluating cardiovascular disease, there are no conclusive data on the role it plays in controlling the lipid profile and anthropometric variables, perhaps because the concentration of cocoa, the geographical origin of the population, and the different concentrations supplied lead to a high heterogeneity of results. This study aims to estimate the effect of consuming cocoa-rich chocolate compared to placebo on the lipid profile and anthropometric variables based on data from three clinical trials conducted in Colombia. Methods. Meta-analysis of individual data from three randomized clinical trials conducted in Colombia. The entire population of the primary studies was included, which was reassigned into intervention groups if they consumed 50 grams of 70% concentrated cocoa or placebo, which was considered to be cocoa-free or with a concentration less than 50 grams. The variables at the beginning of the study were analyzed with medians, interquartile ranges, means, and deviations according to whether they met the normality assumption. Multiple imputations were used to manage missing data and were analyzed using the two approaches proposed for this type of study, that of one and two stages. In the two-stage approach, the data were weighted on a conventional Forrest plot, while in the one-stage approach, linear regressions with mixed models were applied. This study is governed by the regulations described in the 2013 Declaration of Helsinki and by article 11 of Resolution 8430 of 1993, which classifies it as a risk-free study. Results. A total of 275 participants were included, who consumed cocoa or placebo for 81 days on average; 52.7% were female and few smoked at the time of the intervention (31/275). Physical activity performed in number of hours per week was comparable between the intervention groups. When evaluating total cholesterol, low-density cholesterol (LDL), high-density cholesterol (HDL), triglycerides, abdominal circumference, and final body mass index with both the one-stage and two-stage approaches, there were no significant differences between the two groups. Conclusions. According to the results obtained in the meta-analysis, the consumption of cocoa in the Colombian population does not seem to significantly modify variables such as lipid profile, abdominal circumference, and body mass index. This conclusion according to the quality of the evidence has a weak recommendation and a low-to-moderate certainty. However, the analysis through the two proposed approaches yielded similar results.

One-Stage vs Two-Stage Laparoscopic Roux-en-Y Gastric Bypass in Obese Patients with Body Mass Index >55 Kg/m2; 5-YEAR FOLLOW UP

2016 ◽  
Vol 27 (4) ◽  
pp. 955-960 ◽  
Author(s):  
María Díaz-Tobarra ◽  
Norberto Cassinello Fernández ◽  
Pablo Jordá Gómez ◽  
Mohammad Nebih Nofal ◽  
Raquel Alfonso Ballester ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Gastric Bypass ◽  
Body Mass ◽  
Obese Patients ◽  
Two Stage ◽  
One Stage

scholarly journals Pattern-mixture model in network meta-analysis of binary missing outcome data: one-stage or two-stage approach?

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Loukia M. Spineli ◽  
Katerina Papadimitropoulou ◽  
Chrysostomos Kalyvas
Keyword(s):  
Mixture Model ◽  
Simulation Study ◽  
Meta Analysis ◽  
Credible Interval ◽  
Outcome Data ◽  
Systematic Bias ◽  
Two Stage ◽  
Pattern Mixture Model ◽  
One Stage ◽  
The One

Abstract Background Trials with binary outcomes can be synthesised using within-trial exact likelihood or approximate normal likelihood in one-stage or two-stage approaches, respectively. The performance of the one-stage and the two-stage approaches has been documented extensively in the literature. However, little is known about how these approaches behave in the presence of missing outcome data (MOD), which are ubiquitous in clinical trials. In this work, we compare the one-stage versus two-stage approach via a pattern-mixture model in the network meta-analysis using Bayesian methods to handle MOD appropriately. Methods We used 29 published networks to empirically compare the two approaches concerning the relative treatment effects of several competing interventions and the between-trial variance (τ2), while considering the extent and level of balance of MOD in the included trials. We additionally conducted a simulation study to compare the competing approaches regarding the bias and width of the 95% credible interval of the (summary) log odds ratios (OR) and τ2 in the presence of moderate and large MOD. Results The empirical study did not reveal any systematic bias between the compared approaches regarding the log OR, but showed systematically larger uncertainty around the log OR under the one-stage approach for networks with at least one small trial or low event risk and moderate MOD. For these networks, the simulation study revealed that the bias in log OR for comparisons with the reference intervention in the network was relatively higher in the two-stage approach. Contrariwise, the bias in log OR for the remaining comparisons was relatively higher in the one-stage approach. Overall, bias increased for large MOD. For these networks, the empirical results revealed slightly higher τ2 estimates under the one-stage approach irrespective of the extent of MOD. The one-stage approach also led to less precise log OR and τ2 when compared with the two-stage approach for large MOD. Conclusions Due to considerable bias in the log ORs overall, especially for large MOD, none of the competing approaches was superior. Until a more competent model is developed, the researchers may prefer the one-stage approach to handle MOD, while acknowledging its limitations.

scholarly journals Association of Body Mass Index with Mortality in Peritoneal Dialysis Patients: A Systematic Review and Meta-Analysis

2016 ◽  
Vol 36 (3) ◽  
pp. 315-325 ◽  
Author(s):  
Seyed-Foad Ahmadi ◽  
Golara Zahmatkesh ◽  
Elani Streja ◽  
Rajnish Mehrotra ◽  
Connie M. Rhee ◽  
...  
Keyword(s):  
Systematic Review ◽  
Body Mass Index ◽  
Peritoneal Dialysis ◽  
Body Mass ◽  
Meta Analysis ◽  
Dialysis Patients ◽  
Risk Of Death ◽  
Study Results ◽  
Meta Analyses

Background Although higher body mass index (BMI) is associated with better outcomes in hemodialysis patients, the relationship in peritoneal dialysis (PD) patients is less clear. We aimed to synthesize the results from all large and high-quality studies to examine whether underweight, overweight, or obesity is associated with any significantly different risk of death in peritoneal dialysis patients. Methods We searched MEDLINE, EMBASE, Web of Science, CINAHL, and Cochrane CENTRAL, and screened 7,123 retrieved studies for inclusion. Two investigators independently selected the studies using predefined criteria and assessed each study's quality using the Newcastle-Ottawa Quality Assessment Scale. We meta-analyzed the results of the largest studies with no overlap in their data sources. Results We included 9 studies ( n = 156,562) in the systematic review and 4 studies in the meta-analyses. When examined without stratifying studies by follow-up duration, the results of the studies were inconsistent. Hence, we pooled the study results stratified based upon their follow-up durations, as suggested by a large study, and observed that being underweight was associated with higher 1-year mortality but had no significant association with 2- and 3- to 5-year mortalities. In contrast, being overweight or obese was associated with lower 1-year mortality but it had no significant association with 2-, and 3- to 5-year mortalities. Conclusion Over the short-term, being underweight was associated with higher mortality and being overweight or obese was associated with lower mortality. The associations of body mass with mortality were not significant over the long-term.

scholarly journals Pattern-mixture model in network meta-analysis of binary missing outcome data: one-stage or two-stage approach?

2020 ◽  
Author(s):  
Loukia Maria Spineli ◽  
Katerina Papadimitropoulou ◽  
Chrysostomos Kalyvas
Keyword(s):  
Empirical Study ◽  
Mixture Model ◽  
Simulation Study ◽  
Meta Analysis ◽  
Outcome Data ◽  
Systematic Bias ◽  
Two Stage ◽  
Pattern Mixture Model ◽  
One Stage ◽  
The One

Abstract Background Trials with binary outcomes can be synthesised using within-trial exact likelihood or approximate normal likelihood in one-stage or two-stage approaches, respectively. The advantages of the one-stage over the two-stage approach have been documented extensively in the literature. Little is known how these approaches behave in the presence of missing outcome data (MOD) which are ubiquitous in trials. In this work, we compare the one-stage versus two-stage approach via a pattern-mixture model in the network meta-analysis Bayesian framework to handle MOD appropriately. Methods We used 29 published networks to empirically compare the two approaches with respect to the relative treatment effects of several competing interventions and the between-trial variance ( {\tau }^{2} ). We categorised the networks according to the extent and balance of MOD in the included trials. To complement the empirical study, we conducted a simulation study to compare the competing approaches regarding bias and width of the 95% credible interval of the (summary) log odds ratios (OR) and {\tau }^{2} in the presence of moderate and large MOD. Results The empirical study did not reveal any systematic bias between the compared approaches regarding the log OR, but showed systematically larger uncertainty around the log OR under the one-stage approach for networks with at least one small trial or low event risk and moderate MOD. For these networks, the simulation study revealed that the bias in log OR for comparisons with the reference intervention in the network was relatively higher in the two-stage approach. Contrariwise, the bias in log OR for the remaining comparisons was relatively higher in the one-stage approach. Overall, bias increased for large MOD. Furthermore, in these networks, the empirical results revealed slightly higher {\tau }^{2} estimates under the one-stage approach irrespective of the extent of MOD. The one-stage approach also led to less precise log OR and {\tau }^{2} when compared with the two-stage approach for large MOD. Conclusions Due to considerable bias in the log ORs overall, especially for large MOD, none of the competing approaches was superior. Until a more competent model is developed, the researchers may prefer the one-stage approach to handle MOD, while acknowledging its limitations.

scholarly journals Inositol supplementation and body mass index: A Systematic Review and meta‐analysis of randomized clinical trials

2021 ◽  
Author(s):  
Meysam Zarezadeh ◽  
Azadeh Dehghani ◽  
Amir Hossein Faghfouri ◽  
Nima Radkhah ◽  
Mohammad Naemi Kermanshahi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Body Mass Index ◽  
Clinical Trials ◽  
Body Mass ◽  
Randomized Clinical Trials ◽  
Meta Analysis

One-stage dose–response meta-analysis for aggregated data

2018 ◽  
Vol 28 (5) ◽  
pp. 1579-1596 ◽  
Author(s):  
Alessio Crippa ◽  
Andrea Discacciati ◽  
Matteo Bottai ◽  
Donna Spiegelman ◽  
Nicola Orsini
Keyword(s):  
Dose Response ◽  
Goodness Of Fit ◽  
Linear Mixed Model ◽  
Meta Analysis ◽  
Model Specification ◽  
Two Stage ◽  
Aggregated Data ◽  
One Stage ◽  
Non Linear ◽  
The One

The standard two-stage approach for estimating non-linear dose–response curves based on aggregated data typically excludes those studies with less than three exposure groups. We develop the one-stage method as a linear mixed model and present the main aspects of the methodology, including model specification, estimation, testing, prediction, goodness-of-fit, model comparison, and quantification of between-studies heterogeneity. Using both fictitious and real data from a published meta-analysis, we illustrated the main features of the proposed methodology and compared it to a traditional two-stage analysis. In a one-stage approach, the pooled curve and estimates of the between-studies heterogeneity are based on the whole set of studies without any exclusion. Thus, even complex curves (splines, spike at zero exposure) defined by several parameters can be estimated. We showed how the one-stage method may facilitate several applications, in particular quantification of heterogeneity over the exposure range, prediction of marginal and conditional curves, and comparison of alternative models. The one-stage method for meta-analysis of non-linear curves is implemented in the dosresmeta R package. It is particularly suited for dose–response meta-analyses of aggregated where the complexity of the research question is better addressed by including all the studies.

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