Changes in diabetes medication regimens and glycemic control in adolescents and young adults with youth-onset type 2 diabetes: The SEARCH for diabetes in youth study

Pinto, Cathy Anne; Wang, Tongtong; Shankar, R. Ravi; Lawrence, Jean M.; Kim, Grace; Pihoker, Catherine; D’Agostino, Ralph B.; Dabelea, Dana

doi:10.1111/pedi.12691

Cited by 10 publications

(16 citation statements)

References 21 publications

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“…Diabetes prevalence has increased over time not only in adults; in the last two decades, T2DM has become increasingly more frequent among youth worldwide, a trend that seems to be especially related to obesity . The highest prevalence has been observed in the United States, where T2DM represents 10% to 50% of new cases of diabetes among adolescents and over 50% among minority groups, including Latin and Hispanic youth. In contrast, in Europe, T2DM is considered a rare disease, accounting for only 2% of new diabetes cases among youth .…”

Section: Introductionmentioning

confidence: 99%

Prevalence of type 2 diabetes among adolescents in Brazil: Findings from Study of Cardiovascular Risk in Adolescents (ERICA)

et al. 2019

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Background Type 2 diabetes mellitus (T2DM) in adolescents represents a clinical challenge related to lifestyle and obesity; however, only a few data are available in developing countries. Therefore, our aim was to investigate the prevalence of T2DM and prediabetes among Brazilian adolescents, as well as to describe the cardio‐metabolic profile according to the diagnosis. Methods This is a cross‐sectional school‐based multicenter study including youth aged 12 to 17 years from cities with more than 100 000 inhabitants in Brazil (n = 37 854 students). Fasting glucose, hemoglobin A1c (HbA1c) and other cardio‐metabolic risk factors were measured. Prediabetes was defined by glucose levels 100 to 125 mg/dL or HbA1c 5.7% to 6.4%. T2DM was defined by self‐report, glucose ≥126 mg/dL or HbA1c ≥ 6.5%. Multinomial logistic regression was used to estimate the odds ratio (OR) of prediabetes or T2DM according to covariates. Results Prevalences of prediabetes and T2DM were 22.0% (95% confidence interval [CI] 20.6%‐23.4%) and 3.3% (95% CI 2.9%‐3.7%), respectively. This estimates represented 213 830 adolescents living with T2DM and 1.46 million adolescents with prediabetes in Brazil. Prevalences of cardio‐metabolic risk factors were higher in adolescents with prediabetes and T2DM. In the multinomial logistic model, obesity (OR 1.59, 95% CI 1.20‐2.11), high waist circumference (OR 1.51, 95% CI 1.13‐2.01), and skipping breakfast (OR 1.48, 95% CI 1.21‐1.81) were associated with an increased OR for T2DM, while studying at rural area (OR 0.56, 95% CI 0.41‐0.78) was associated with a decreased OR for T2DM. Conclusions The prevalence of T2DM and prediabetes was high among Brazilian adolescents, which highlights that this disease became a public health challenge not only among adults in Brazil.

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Section: Introductionmentioning

confidence: 99%

Prevalence of type 2 diabetes among adolescents in Brazil: Findings from Study of Cardiovascular Risk in Adolescents (ERICA)

et al. 2019

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“…Instead, type 2 diabetes is aggregated into a class for "type 2 diabetes or unspecified type." Medications are also not infallible in helping to distinguish specific diabetes types, since some of the medications may be used for treating other conditions (e.g., metformin may be used to treat polycystic ovarian syndrome), and at least onethird of youth with type 2 diabetes are treated with insulin, a medication historically associated with the treatment of type 1 diabetes (8).…”

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confidence: 99%

Detection of Diabetes Status and Type in Youth Using Electronic Health Records: The SEARCH for Diabetes in Youth Study

et al. 2020

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Diabetes surveillance often requires manual medical chart reviews to confirm status and type. This project aimed to create an electronic health record (EHR)-based procedure for improving surveillance efficiency through automation of case identification. RESEARCH DESIGN AND METHODSYouth (<20 years old) with potential evidence of diabetes (N 5 8,682) were identified from EHRs at three children's hospitals participating in the SEARCH for Diabetes in Youth Study. True diabetes status/type was determined by manual chart reviews. Multinomial regression was compared with an ICD-10 rule-based algorithm in the ability to correctly identify diabetes status and type. Subsequently, the investigators evaluated a scenario of combining the rule-based algorithm with targeted chart reviews where the algorithm performed poorly. RESULTSThe sample included 5,308 true cases (89.2% type 1 diabetes). The rule-based algorithm outperformed regression for overall accuracy (0.955 vs. 0.936). Type 1 diabetes was classified well by both methods: sensitivity (Se) (>0.95), specificity (Sp) (>0.96), and positive predictive value (PPV) (>0.97). In contrast, the PPVs for type 2 diabetes were 0.642 and 0.778 for the rule-based algorithm and the multinomial regression, respectively. Combination of the rule-based method with chart reviews (n 5 695, 7.9%) of persons predicted to have non-type 1 diabetes resulted in perfect PPV for the cases reviewed while increasing overall accuracy (0.983). The Se, Sp, and PPV for type 2 diabetes using the combined method were ‡0.91. CONCLUSIONSAn ICD-10 algorithm combined with targeted chart reviews accurately identified diabetes status/type and could be an attractive option for diabetes surveillance in youth.The SEARCH observational study (SEARCH for Diabetes in Youth Study) has conducted population-based incidence and prevalence ascertainment of nongestational diabetes in youth since 2001 (1-6). The methods employed by SEARCH for the identification and typing of youth-onset diabetes are well established, but they rely on a time-consuming process of manually reviewing clinical records to verify diabetes presence, diabetes type, and date of diagnosis. The now widespread use

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“…After a mean of 7 years of follow-up, a significant proportion of participants changed their treatment regimen, adding or taking away metformin and/or insulin. A few took alternative glucoselowering drugs, primarily thiazolidinediones or sulfonylureas, and only 35% were meeting glycaemic targets (HbA 1c < 53.0 mmol/mol [<7%]) [28]. It is important to note that this follow-up time period occurred prior to publication of the TODAY study results.…”

Section: What Do We Know About Treatment Effects From Current Studies?mentioning

confidence: 99%

Youth-onset type 2 diabetes: translating epidemiology into clinical trials

Pyle

Kelsey

2021

Diabetologia

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Globally, the proportion of new diagnoses of youth-onset diabetes represented by type 2 diabetes is increasing, and youth with type 2 diabetes commonly have complications and comorbidities, as well as a higher rate of mortality. In this review, we summarise what is known about the natural progression of youth-onset type 2 diabetes from published clinical trials and large-scale prospective epidemiological studies. It is important to note that the robust pathophysiological and treatment data specifically related to individuals with a diabetes onset at ≤20 years of age largely hails from the USA. Youth-onset type 2 diabetes is characterised by pathophysiological heterogeneity and inadequate glycaemic control, highlighting the need for new treatment approaches and innovative study designs in populations of varied genetic and cultural backgrounds.

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Changes in diabetes medication regimens and glycemic control in adolescents and young adults with youth-onset type 2 diabetes: The SEARCH for diabetes in youth study

Abstract: Youth-onset T2D is still largely being treated with metformin and/or insulin. The majority treated were not at American Diabetes Association (ADA)-recommended goal 7 years after diagnosis.

Cited by 10 publications

References 21 publications

Prevalence of type 2 diabetes among adolescents in Brazil: Findings from Study of Cardiovascular Risk in Adolescents (ERICA)

Prevalence of type 2 diabetes among adolescents in Brazil: Findings from Study of Cardiovascular Risk in Adolescents (ERICA)

Detection of Diabetes Status and Type in Youth Using Electronic Health Records: The SEARCH for Diabetes in Youth Study

Youth-onset type 2 diabetes: translating epidemiology into clinical trials

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