Dataset Information

Comparison of autoantibody-positive and autoantibody-negative pediatric participants enrolled in the T1D Exchange clinic registry.

ABSTRACT: OBJECTIVE:To compare characteristics of autoantibody (aAb)-positive and -negative cases of type 1 diabetes (T1D) <18 years old in the T1D Exchange clinic registry. METHODS:An aAb-positive status (n = 6239) required at least one of the aAbs to be positive; an aAb-negative status (n = 485) required negative results on testing of at least two different aAbs. RESULTS:The percentage of males was higher (58% vs. 51%; P = 0.002) and total daily insulin dose lower (P = 0.003) in aAb-negative compared with aAb-positive groups, but both groups had similar distributions of race-ethnicity, diagnosis age, family history of T1D, ketoacidosis at diagnosis, body mass index at diagnosis and at most recent office visit, and current HbA1c. CONCLUSIONS:Male gender and lower total daily insulin dose were more likely in aAb-negative than aAb-positive children with T1D, but no other distinguishing characteristics were identified. Further examination of characteristics of aAb-negative cases may help characterize the heterogeneous nature of T1D.

SUBMITTER: Gerard-Gonzalez A

PROVIDER: S-EPMC6779047 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of autoantibody-positive and autoantibody-negative pediatric participants enrolled in the T1D Exchange clinic registry.

Gerard-Gonzalez Andrea A Gitelman Stephen E SE Cheng Peiyao P Dubose Stephanie N SN Miller Kellee M KM Olson Beth A BA Redondo Maria J MJ Steck Andrea K AK Beck Roy W RW

Journal of diabetes 20130601 2

<h4>Objective</h4>To compare characteristics of autoantibody (aAb)-positive and -negative cases of type 1 diabetes (T1D) <18 years old in the T1D Exchange clinic registry.<h4>Methods</h4>An aAb-positive status (n = 6239) required at least one of the aAbs to be positive; an aAb-negative status (n = 485) required negative results on testing of at least two different aAbs.<h4>Results</h4>The percentage of males was higher (58% vs. 51%; P = 0.002) and total daily insulin dose lower (P = 0.003) in aA ...[more]

PMID: 23368514

Similar Datasets

Project description:Objective: Post-randomisation exclusions in randomised controlled trials are common and may include participants identified as not meeting trial eligibility criteria after randomisation. We report how a decision might be reached and reported on, to include or exclude these participants. We illustrate using a motivating scenario from the BREATHE trial (Trial registration ClinicalTrials.gov, NCT02426112) evaluating azithromycin for the treatment of chronic lung disease in people aged 6-19?years with HIV in Zimbabwe and Malawi.Key points: Including all enrolled and randomised participants in the primary analysis of a trial ensures an unbiased estimate of the intervention effect using intention-to-treat principles, and minimises the effects of confounding through balanced allocation to trial arm. Ineligible participants are sometimes enrolled, due to measurement or human error. Of 347 participants enrolled into the BREATHE trial, 11 (3.2%) were subsequently found to be ineligible based on lung function criteria. We assumed no safety risk of azithromycin treatment; their inclusion in the trial and subsequent analysis of the intervention effect therefore mirrors clinical practice. Senior trial investigators considered diurnal variations in the measurement of lung function, advantages of retaining a higher sample size and advice from the Data Safety and Monitoring Board and Trial Steering Committee, and decided to include these participants in primary analysis. We planned and reported analyses including and excluding these participants, and in our case the interpretation of treatment effect was consistent.Conclusion: The decision, by senior investigators, on whether to exclude enrolled participants, should reflect issues of safety, treatment efficacy, statistical power and measurement error. As long as decisions are made prior to finalising the statistical analysis plan for the trial, the risk of exclusions creating bias should be minimal. The decision taken should be transparently reported and a sensitivity analysis can present the opposite decision.

Dataset Information

Comparison of autoantibody-positive and autoantibody-negative pediatric participants enrolled in the T1D Exchange clinic registry.

Publications

Comparison of autoantibody-positive and autoantibody-negative pediatric participants enrolled in the T1D Exchange clinic registry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure