Guidelines for OBEsity Dietary Intervention Sharing
Obesity is a problem that represents a significant health and economic burden in Europe and throughout the world. The prevalence of obesity across European countries has tripled in the last several decades, making it one of the leading public health challenges.
A critical part of addressing this global epidemic is to improve the evidence base for more effective treatments for obesity; however, a challenge revealed in the randomized controlled trials (RCTs) of obesity interventions is the remarkable heterogeneity of inter-individual and intra-individual responses among adult patients—whether the intervention pertains to lifestyle (dietary, physical activity), or is a pharmacological or surgical intervention aiming at weight loss. Most obesity RCTs include a heterogeneous mixture of patients that, despite meeting the inclusion criteria for the study, vary remarkably that may drive the heterogeneous responses to the same intervention. Also, different trials take different approaches to measuring the same variable. This emphasizes the need to appropriately stratify patients according to precise phenotyping criteria, measured by using standardized methods, that might predict an individual’s response to an intervention: a paradigm shift in individually tailored obesity treatment, going from ‘one-size-fits-all’ to precision medicine.
Even for the largest and most comprehensive published clinical studies on obesity, stratification leads to subgroup analyses with reduced statistical power. Moreover, some trials do not report methods for measuring relevant obesity phenotypes in sufficient detail. Thus, it is necessary to harmonize and merge the data from multiple intervention studies—but data pooling is only possible with trials that include a common set of variables measured in the same way, including samples that are collected using consistent methods or procedures, described in enough detail.
@OBEDIS project aims to create a plan for helping shape future RCTs in the field of obesity by identifying the minimal set of variables that should be included in all trials with interventions on obesity, whatever the type and the endpoints of the intervention.
30 European experts have been invited to expand the working group. Based on an exhaustive scientific literature research but also on their expert opinions, they recommended minimal core set of variables to include in all future trials of adult obesity interventions, and sought to reach consensus on both these variables and the related assessment methods. They intend for this minimal core set to be adopted in future studies while acknowledging that in addition, RCTs or other trials will collect data on extra variables, depending on the specific area of focus.
@OBEDIS has given the research community a blueprint for designing future RCTs in order to allow the sharing and merging of datasets, and to enable meaningful subgroup analyses.
|Human Nutrition Research Center (CRNH-RA)
|Antwerp University Hospital
|Netherlands Organisation for Applied Scientific Research
The main outcome of the @OBEDIS project is the European consensus of core set of variables that should be systematically measured (using harmonized assessment methods) in each RCT involving obese adult patients, which will allow to precisely phenotype them. The wide adoption of this core set across Europe will be the first practical step to harmonize phenotype data collection in the field of obesity, facilitating in the future the merging of data at the European level, but also allowing to perform relevant and powerful subgroup analyses (patient stratification) based on their baseline phenotype, which will lead to the development of personalized medicine approaches. This minimal core set is detailed in the following link: https://www.force-obesity.org/sites/default/files/documents/obedis_minimal_core_set_of_variables_.pdf
The experts involved in the study group have followed a precise methodology. For a variable to be included in the minimal core set, it was required to fulfill the following criteria:
- A variable is defined as “a property with respect to which individuals in a sample differ in some ascertainable way” (“3 Most Important Types of Biological Variables,” 2019)
- It provided information that made it likely to impact treatment response, according to the relevant literature (especially studies that aimed to stratify patients).
- It was feasible: Given that each clinical trial has limits on budget and time as well as research team expertise, the @OBEDIS group aimed to minimize the burden of including each variable in future trials. The scientists paid considerable attention to factors that would encourage widespread adoption of these measures by the European obesity research community, especially the overall number of variables that should be systematically collected. The group preferred measures that were:
- Low-cost or free to utilize / able to be collected with minimal equipment or human resources
- Less invasive / quick to implement
- For questionnaires: available and/or validated in multiple languages or across cultures
The group provided an estimate of the average cost of including these measures in a European trial. While inclusion of these variables will in some cases introduce additional cost to individual clinical trials, they will also extend the insights made possible by each trial—making the overall research agenda proceed more purposefully and at a lower cost.
In addition to this main scientific outcome, another strong achievement was to have succeeded in unifying a large group of renowned experts from almost 10 different European countries with the support of EASO (European Association for the Study of Obesity) : Jildau Bouwman (NL), Helen Roche (IE), Ellen Blaak (NL), Olivier Ziegler (FR), André Scheen (BE), Antonio Palmeiras (ES), Chantal Simon (FR), Karine Clément (FR), Jean-Michel Oppert (FR), David Jacobi (FR), Jason Halford (UK), Martin Neovivus (SE), Paul Brunault (FR), Gema Frühbeck (ES), Luc Tappy (CH), Martine Laville (FR), Thorkild Sorensen (DK), Hans Hauner (DE), Uberto Pagotto (IT), Andrea Natali (IT), Gijs Goossens (NL), Hannele Yki-Järvinen (FI), Chantal Julia (FR), Dominique Langin (FR), Sadaf Farooqi (UK), Nathalie Farpour-Lambert (CH), Romain Barres (DK), Jorg Hager (CH), Yves Boirie (FR), Mikael Ryden (SE), Wim Saris (NL), Barend Mons (NL), Euan Woodward (UK), Kristina Campbell (CA).
During all the project duration, all the experts have been strongly motivated to contribute. Thanks to the EASO support, this fruitful join effort will continue beyond the @OBEDIS project. A dedicated symposium to the @OBEDIS outcomes is already scheduled at the next International Congress of Obesity (May 2020). A unique opportunity to widely disseminate the work done in @OBEDIS but also to extend the scope, by inviting new additional International experts from related and relevant disciplines such as metabolic surgery, diabetes....Moreover, representatives of ADOPT consortium (notably Dona Ryan, the president of World Obesity Federation) will be also invited. ADOPT consortium has conducted similar project as @OBEDIS by proposing a core set of variables but with only American experts (https://www.ncbi.nlm.nih.gov/pubmed/29575780). The ultimate aim of bridging the two consortia remains to propose a unique international core set of variables that could be used across the world for all the RCT involving obese patients, facilitating in the future the data pooling and sharing at the worldwide level.
Author: Alligier, Maud, et al.
The importance of sharing and reusing biomedical research data is well established. Sharing data facilitates research that allows for quicker translation of research findings into clinical practice, enhances scientific reproducibility and transparency, and increases collaboration and interdisciplinary research that helps advance science. In this rapidly evolving context, funding agencies but also publishers have recognized the importance of sharing data and have implemented policies and mandates that encourage researchers to share. However, despite the many arguments in favor of sharing and open science, researchers often do not share their data. A number of concerns may dissuade researchers, including practical concerns. The preparation of the data sets (including curation, harmonization of the collection (ontology, assessment methods, units...), quality assessment…) is a mandatory step but may present a roadblock especially because of lack of resources and time. Due to the lack of harmonization process in data collection, the data collected in a clinical study in the field of obesity and nutrition at the level of one centre is unlikely to be combined with another data set of the same field collected in another centre, even when it comes from the same country. Only an overall approach, as what has been done in @OBEDIS project, led by scientific experts of each of the fields in clinical research could contribute to alleviate the practical constraints and ensuring the biomedical research data sharing and reuse within Europe in the future.
OBEDIS initiative allowed to build a strong and motivated community of investigators across Europe, committed to advancing the state of the science needed to stratify obese adult patients, mandatory step towards the personalized medicine. The European minimal core set of variables developed, is a fundamental first step towards quality and harmonized data collection across Europe in the field of obesity. By improving high harmonized and quality data collection, the adoption of @OBEDIS outcomes by the scientific community, will facilitate the data pooling and sharing to conduct systematic reviews, meta-analytic syntheses, providing thus new evidence base on obese patient stratification leading to the development of more tailored and effective treatments.
The bridge with the ADOPT consortium (North American consortium) is a unique gateway to promote the work done in @OBEDIS but also to propose a unique international core set of variables that could be used across the world for all the RCT involving obese patients., facilitating in the future the data pooling and sharing at the worldwide level.