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Primary outcomes reporting in trials of paediatric type 1 diabetes mellitus: a systematic review.

ABSTRACT: Our objective was to systematically review randomised clinical trials (RCTs) of paediatric type 1 diabetes mellitus (T1DM) to assess reporting of (1) primary outcome, (2) outcome measurement properties and (3) presence or absence of adverse events.Electronic searches in MEDLINE, EMBASE, CINAHL, Cochrane SR and the Cochrane Central Register of Controlled Trials (CENTRAL) databases were undertaken. The search period was between 2001 and 2017. English-language RCTs on children younger than 21 years with T1DM were selected. We excluded studies of diagnostic or screening tools, multiple phase studies, protocols, and follow-up or secondary analysis of data.Of 11?816 unique references, 231?T1DM RCTs were included. Of total 231 included studies, 117 (50.6%) trials failed to report what their primary outcome was. Of 114 (49.4%) studies that reported primary outcome, 88 (77.2%) reported one and 26 (22.8%) more than one primary outcomes. Of 114 studies that clearly stated their primary outcome, 101 (88.6%) used biological/physiological measurements and 13 (11.4%) used instruments (eg, questionnaires, scales, etc) to measure their primary outcome; of these, 12 (92.3%) provided measurement properties or related citation. Of the 231 included studies, 105 (45.5%) reported that adverse events occurred, 39 (16.9%) reported that no adverse events were identified and 87 (37.7%) did not report on the presence or absence of adverse events.Despite tremendous efforts to improve reporting of clinical trials, clear reporting of primary outcomes of RCTs for paediatric T1DM is still lacking. Adverse events due to DM interventions were often not reported in the included trials. Transparent reporting of primary outcome, validity of measurement tools and adverse events need to be improved in paediatric T1DM trials.

SUBMITTER: Khanpour Ardestani S

PROVIDER: S-EPMC5743897 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

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Primary outcomes reporting in trials of paediatric type 1 diabetes mellitus: a systematic review.

Khanpour Ardestani Samaneh S Karkhaneh Mohammad M Yu Hai Chuan HC Hydrie Muhammad Zafar Iqbal MZI Vohra Sunita S

BMJ open 20171219 12

<h4>Objective</h4>Our objective was to systematically review randomised clinical trials (RCTs) of paediatric type 1 diabetes mellitus (T1DM) to assess reporting of (1) primary outcome, (2) outcome measurement properties and (3) presence or absence of adverse events.<h4>Methods</h4>Electronic searches in MEDLINE, EMBASE, CINAHL, Cochrane SR and the Cochrane Central Register of Controlled Trials (CENTRAL) databases were undertaken. The search period was between 2001 and 2017. English-language RCTs ...[more]

PMID: 29259053

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Project description:BackgroundSystematic reviews with or without meta-analyses (SR/MAs) are strongly encouraged to work from a protocol to facilitate high quality, transparent methodology. The completeness of reporting of a protocol (PRISMA-P) and manuscript (PRISMA) is essential to the quality appraisal (AMSTAR-2) and appropriate use of SR/MAs in making treatment decisions.ObjectivesThe objectives of this study were to describe the completeness of reporting and quality of SR/MAs, assess the correlations between PRISMA-P, PRISMA, and AMSTAR-2, and to identify reporting characteristics between similar items of PRISMA-P and PRISMA.MethodsWe performed a systematic review of Type 2 Diabetes Mellitus SR/MAs of hypoglycemic agents with publicly available protocols. Cochrane reviews, guidelines, and specific types of MA were excluded. Two reviewers independently, (i) searched PubMed and Embase between 1/1/2015 to 20/3/2019; (ii) identified protocols of included studies by searching the manuscript bibliography, supplementary material, PROSPERO, and Google; (iii) completed PRISMA-P, PRISMA, and AMSTAR-2 tools. Data analysis included descriptive statistics, Pearson correlation, and multivariable linear regression.ResultsOf 357 relevant SR/MAs, 51 had available protocols and were included. The average score for PRISMA-P was 15.8±3.3 (66%; maximum 24) and 25.2±1.1 (93%; maximum 27) for PRISMA. The quality of SR/MAs assessed using the AMSTAR-2 tool identified an overall poor quality (63% critically low, 18% low, 8% moderate, 12% high). The correlation between the PRISMA-P and PRISMA was not significant (r = 0.264; p = 0.06). Correlation was significant between PRISMA-P and AMSTAR-2 (r = 0.333; p = 0.02) and PRISMA and AMSTAR-2 (r = 0.555; p<0.01). Discrepancies in reporting were common between similar PRISMA-P and PRISMA items.ConclusionAdherence to protocol reporting guidance was poor while manuscript reporting was comprehensive. Protocol completeness is not associated with a completely reported manuscript. Independently, PRISMA-P and PRISMA scores were weakly associated with higher quality assessments but insufficient as a surrogate for quality. Critical areas for quality improvement include protocol description, investigating causes of heterogeneity, and the impact of risk of bias on the evidence synthesis.

Project description:BackgroundDiabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the transparency, replicability, biasedness, and overall validity of artificial intelligence studies in medicine.ObjectiveWe aimed to systematically review the reporting quality of machine learning (ML) studies of pediatric DM using the Minimum Information About Clinical Artificial Intelligence Modelling (MI-CLAIM) checklist, a general reporting guideline for medical artificial intelligence studies.MethodsWe searched the PubMed and Web of Science databases from 2016 to 2020. Studies were included if the use of ML was reported in children with DM aged 2 to 18 years, including studies on complications, screening studies, and in silico samples. In studies following the ML workflow of training, validation, and testing of results, reporting quality was assessed via MI-CLAIM by consensus judgments of independent reviewer pairs. Positive answers to the 17 binary items regarding sufficient reporting were qualitatively summarized and counted as a proxy measure of reporting quality. The synthesis of results included testing the association of reporting quality with publication and data type, participants (human or in silico), research goals, level of code sharing, and the scientific field of publication (medical or engineering), as well as with expert judgments of clinical impact and reproducibility.ResultsAfter screening 1043 records, 28 studies were included. The sample size of the training cohort ranged from 5 to 561. Six studies featured only in silico patients. The reporting quality was low, with great variation among the 21 studies assessed using MI-CLAIM. The number of items with sufficient reporting ranged from 4 to 12 (mean 7.43, SD 2.62). The items on research questions and data characterization were reported adequately most often, whereas items on patient characteristics and model examination were reported adequately least often. The representativeness of the training and test cohorts to real-world settings and the adequacy of model performance evaluation were the most difficult to judge. Reporting quality improved over time (r=0.50; P=.02); it was higher than average in prognostic biomarker and risk factor studies (P=.04) and lower in noninvasive hypoglycemia detection studies (P=.006), higher in studies published in medical versus engineering journals (P=.004), and higher in studies sharing any code of the ML pipeline versus not sharing (P=.003). The association between expert judgments and MI-CLAIM ratings was not significant.ConclusionsThe reporting quality of ML studies in the pediatric population with DM was generally low. Important details for clinicians, such as patient characteristics; comparison with the state-of-the-art solution; and model examination for valid, unbiased, and robust results, were often the weak points of reporting. To assess their clinical utility, the reporting standards of ML studies must evolve, and algorithms for this challenging population must become more transparent and replicable.

Project description:Integrated care interventions for chronic conditions can lead to improved outcomes, but it is not clear when and why this is the case. This study aims to answer the following two research questions: First, what are the context, mechanisms and outcomes of integrated care for people with type 2 diabetes? Second, what are the relationships between context, mechanisms and outcomes of integrated care for people with type 2 diabetes?A systematic literature search was conducted for the period 2003-2013 in Cochrane and PubMed. Articles were included when they focussed on integrated care and type 2 diabetes, and concerned empirical research analysing the implementation of an intervention. Data extraction was performed using a common data extraction table. The quality of the studies was assessed with the Mixed Methods Appraisal Tool. The CMO model (context + mechanism?=?outcome) was used to study the relationship between context factors (described by the barriers and facilitators encountered in the implementation process and categorised at the six levels of the Implementation Model), mechanisms (defined as intervention types and described by their number of Chronic Care Model (sub-)components) and outcomes (the intentional and unintentional effects triggered by mechanism and context).Thirty-two studies met the inclusion criteria. Most reported barriers to the implementation process were found at the organisational context level and most facilitators at the social context level. Due to the low number of articles reporting comparable quantitative outcome measures or in-depth qualitative information, it was not possible to make statements about the relationship between context, mechanisms and outcomes.Efficient resource allocation should entail increased investments at the organisational context level where most barriers are expected to occur. It is likely that investments at the social context level will also help to decrease the development of barriers at the organisational context level, especially by increasing staff involvement and satisfaction. If future research is to adequately inform practice and policy regarding the impact of these efforts on health outcomes, focus on the actual relationships between context, mechanisms and outcomes should be actively incorporated into study designs.

Project description:BackgroundAfter the publication of the CONSORT 2010 statement, few studies have been conducted to assess the reporting quality of randomized clinical trials (RCTs) on treatment of diabetes mellitus with Traditional Chinese Medicine (TCM) published in Chinese journals.ObjectiveTo investigate the current situation of the reporting quality of RCTs in leading medical journals in China with the CONSORT 2010 statement as criteria.MethodsThe China National Knowledge Infrastructure (CNKI) electronic database was searched for RCTs on the treatment of diabetes mellitus with TCM published in the Journal of Traditional Chinese Medicine, Chinese Journal of Integrated Traditional & Western Medicine, and the China Journal of Chinese Materia Medica from January to December 2011. We excluded trials reported as "animal studies", "in vitro studies", "case studies", or "systematic reviews". The CONSORT checklist was applied by two independent raters to evaluate the reporting quality of all eligible trials after discussing and comprehending the items thoroughly. Each item in the checklist was graded as either "yes" or "no" depending on whether it had been reported by the authors.ResultsWe identified 27 RCTs. According to the 37 items in the CONSORT checklist, the average reporting percentage was 45.0%, in which the average reporting percentage for the "title and abstract", the "introduction", the "methods", the "results", the "discussion" and the "other information" was 33.3%, 88.9%, 36.4%, 54.4%, 71.6% and 14.8%, respectively. In the Journal of Traditional Chinese Medicine, Chinese Journal of Integrated Traditional & Western Medicine, and the China Journal of Chinese Materia Medica the average reporting percentage was 42.2%, 56.8%, and 46.0%, respectively.ConclusionsThe reporting quality of RCTs in these three journals was insufficient to allow readers to assess the validity of the trials. We recommend that editors require authors to use the CONSORT statement when reporting their trial results as a condition of publication.

Project description:AimsTo reduce the burden of type 2 diabetes (T2DM), the disease decision model plays a vital role in supporting decision-making. Currently, there is no comprehensive summary and assessment of the existing decision models for T2DM. The objective of this review is to provide an overview of the characteristics and capabilities of published decision models for T2DM. We also discuss which models are suitable for different study demands.Materials and methodsFour databases (PubMed, Web of Science, Embase, and the Cochrane Library) were electronically searched for papers published from inception to August 2020. Search terms were: "Diabetes-Mellitus, Type 2", "cost-utility", "quality-of-life", and "decision model". Reference lists of the included studies were manually searched. Two reviewers independently screened the titles and abstracts following the inclusion and exclusion criteria. If there was insufficient information to include or exclude a study, then a full-text version was sought. The extracted information included basic information, study details, population characteristics, basic modeling methodologies, model structure, and data inputs for the included applications, model outcomes, model validation, and uncertainty.ResultsFourteen unique decision models for T2DM were identified. Markov chains and risk equations were utilized by four and three models, respectively. Three models utilized both. Except for the Archimedes model, all other models (n = 13) implemented an annual cycle length. The time horizon of most models was flexible. Fourteen models had differences in the division of health states. Ten models emphasized macrovascular and microvascular complications. Six models included adverse events. Majority of the models (n = 11) were patient-level simulation models. Eleven models simulated annual changes in risk factors (body mass index, glycemia, HbA1c, blood pressure (systolic and/or diastolic), and lipids (total cholesterol and/or high-density lipoprotein)). All models reported the main data sources used to develop health states of complications. Most models (n = 11) could deal with the uncertainty of models, which were described in varying levels of detail in the primary studies. Eleven studies reported that one or more validation checks were performed.ConclusionsThe existing decision models for T2DM are heterogeneous in terms of the level of detail in the classification of health states. Thus, more attention should be focused on balancing the desired level of complexity against the required level of transparency in the development of T2DM decision models.

Project description:Emerging research suggests whey protein (WP) supplementation may modify type 2 diabetes mellitus (T2DM) risk factors, including glucose control. As systematic reviews and/or meta-analyses of randomized controlled trials (RCTs) gain importance in nutrition literature, we conducted an umbrella systematic review to chronicle published systematic reviews and/or meta-analyses of RCTs pertinent to WP supplementation and T2DM modifiable risk factors. This review was conducted in accordance with Preferred Reporting Items for Overviews of Reviews standards. Potentially eligible articles were identified via a systematic search of 5 electronic health research databases (PubMed, Cochrane Library, CINAHL [EBSCO], Scopus, and SPORTDiscus [EBSCO]). Included articles were assessed for quality using the "A MeaSurement Tool to Assess systematic Reviews 2" critical appraisal tool. Thirteen articles, representing 109 unique RCTs, of the 2205 identified articles met the inclusion criteria. Nine articles (69%) were deemed high quality, 2 (15%) moderate quality, and 2 (15%) low quality. Findings from this umbrella review of 13 systematic reviews, including 12 meta-analyses, suggest WP may lower hemoglobin A1c, homeostasis model assessment of insulin resistance, and fasting insulin in groups classified as overweight/obese or at risk for or with metabolic syndrome; blood triglycerides in groups classified as overweight/obese or at risk for or with metabolic syndrome; and blood pressure in groups classified as overweight/obese. WP did not differentially affect C-reactive protein, body weight, body mass index, or waist circumference, nor did it adversely affect any T2DM risk factors. Insufficient evidence precluded assessing the influence of WP on glucose control-related outcomes in groups classified at lower risk for T2DM. Information regarding WP dose, duration, or types was insufficient to draw conclusions. Collectively, evidence suggests WP supplementation may improve multiple clinical indicators of glucose control, along with triglycerides and blood pressure, in groups of adults at increased risk of developing T2DM.

Dataset Information

Primary outcomes reporting in trials of paediatric type 1 diabetes mellitus: a systematic review.

Publications

Primary outcomes reporting in trials of paediatric type 1 diabetes mellitus: a systematic review.

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