Prognostic accuracy of immunologic and metabolic markers for type 1 diabetes in a high-risk population receiver operating characteristic analysis

Ping Xu, Craig A. Beam, David Cuthbertson, Jay M Sosenko, Jay S Skyler, Jeffrey P. Krischer

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

OBJECTIVE - To establish and compare the prognostic accuracy of immunologic and metabolic markers in predicting onset of type 1 diabetes in those with high risk in a prospective study. RESEARCH DESIGN AND METHODS - A total of 339 subjects from the Diabetes Prevention Trial-Type 1 (DPT-1) parenteral study, who were islet cell antibody (ICA)-positive, with low first-phase insulin response (FPIR) and/or abnormal glucose tolerance at baseline, were followed until clinical diabetes onset or study end (5-year follow-up). The prognostic performance of biomarkers was estimated using receiver operating characteristic (ROC) curve analysis and compared with nonparametric testing of ROC curve areas. Pearson correlation was used to assess the relationship between the markers. RESULTS - Individually, insulin autoantibody titer, ICA512A titer, peak C-peptide, 2-h glucose, FPIR, and FPIR/homeostasis model assessment of insulin resistance provided modest but significant prognostic values for 5-year risk with a similar level of area under ROC curve ranging between 0.61 and 0.67. The combination of 2-h glucose, peak C-peptide, and area under the curve C-peptide significantly improved the prognostic accuracy compared with any solitary index (P < 0.05) with an area under ROC curve of 0.76 (95% CI 0.70-0.81). The addition of antibody titers and/or intravenous glucose tolerance test (IVGTT) markers did not increase the prognostic accuracy further (P = 0.46 and P = 0.66, respectively). CONCLUSIONS - The combination of metabolic markers derived from the oral glucose tolerance test improved accuracy in predicting progression to type 1 diabetes in a population with ICA positivity and abnormal metabolism. The results indicate that the autoimmune activity may not alter the risk of type 1 diabetes after metabolic function has deteriorated. Future intervention trials may consider eliminating IVGTT measurements as an effective cost-reduction strategy for prognostic purposes.

Original languageEnglish
Pages (from-to)1975-1980
Number of pages6
JournalDiabetes Care
Volume35
Issue number10
DOIs
StatePublished - Oct 1 2012

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Type 1 Diabetes Mellitus
ROC Curve
C-Peptide
Glucose Tolerance Test
Biomarkers
Insulin
Glucose
Population
Autoantibodies
Area Under Curve
Insulin Resistance
Homeostasis
Research Design
Prospective Studies
Costs and Cost Analysis
Antibodies
islet cell antibody

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Advanced and Specialized Nursing

Cite this

Prognostic accuracy of immunologic and metabolic markers for type 1 diabetes in a high-risk population receiver operating characteristic analysis. / Xu, Ping; Beam, Craig A.; Cuthbertson, David; Sosenko, Jay M; Skyler, Jay S; Krischer, Jeffrey P.

In: Diabetes Care, Vol. 35, No. 10, 01.10.2012, p. 1975-1980.

Research output: Contribution to journalArticle

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abstract = "OBJECTIVE - To establish and compare the prognostic accuracy of immunologic and metabolic markers in predicting onset of type 1 diabetes in those with high risk in a prospective study. RESEARCH DESIGN AND METHODS - A total of 339 subjects from the Diabetes Prevention Trial-Type 1 (DPT-1) parenteral study, who were islet cell antibody (ICA)-positive, with low first-phase insulin response (FPIR) and/or abnormal glucose tolerance at baseline, were followed until clinical diabetes onset or study end (5-year follow-up). The prognostic performance of biomarkers was estimated using receiver operating characteristic (ROC) curve analysis and compared with nonparametric testing of ROC curve areas. Pearson correlation was used to assess the relationship between the markers. RESULTS - Individually, insulin autoantibody titer, ICA512A titer, peak C-peptide, 2-h glucose, FPIR, and FPIR/homeostasis model assessment of insulin resistance provided modest but significant prognostic values for 5-year risk with a similar level of area under ROC curve ranging between 0.61 and 0.67. The combination of 2-h glucose, peak C-peptide, and area under the curve C-peptide significantly improved the prognostic accuracy compared with any solitary index (P < 0.05) with an area under ROC curve of 0.76 (95{\%} CI 0.70-0.81). The addition of antibody titers and/or intravenous glucose tolerance test (IVGTT) markers did not increase the prognostic accuracy further (P = 0.46 and P = 0.66, respectively). CONCLUSIONS - The combination of metabolic markers derived from the oral glucose tolerance test improved accuracy in predicting progression to type 1 diabetes in a population with ICA positivity and abnormal metabolism. The results indicate that the autoimmune activity may not alter the risk of type 1 diabetes after metabolic function has deteriorated. Future intervention trials may consider eliminating IVGTT measurements as an effective cost-reduction strategy for prognostic purposes.",
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N2 - OBJECTIVE - To establish and compare the prognostic accuracy of immunologic and metabolic markers in predicting onset of type 1 diabetes in those with high risk in a prospective study. RESEARCH DESIGN AND METHODS - A total of 339 subjects from the Diabetes Prevention Trial-Type 1 (DPT-1) parenteral study, who were islet cell antibody (ICA)-positive, with low first-phase insulin response (FPIR) and/or abnormal glucose tolerance at baseline, were followed until clinical diabetes onset or study end (5-year follow-up). The prognostic performance of biomarkers was estimated using receiver operating characteristic (ROC) curve analysis and compared with nonparametric testing of ROC curve areas. Pearson correlation was used to assess the relationship between the markers. RESULTS - Individually, insulin autoantibody titer, ICA512A titer, peak C-peptide, 2-h glucose, FPIR, and FPIR/homeostasis model assessment of insulin resistance provided modest but significant prognostic values for 5-year risk with a similar level of area under ROC curve ranging between 0.61 and 0.67. The combination of 2-h glucose, peak C-peptide, and area under the curve C-peptide significantly improved the prognostic accuracy compared with any solitary index (P < 0.05) with an area under ROC curve of 0.76 (95% CI 0.70-0.81). The addition of antibody titers and/or intravenous glucose tolerance test (IVGTT) markers did not increase the prognostic accuracy further (P = 0.46 and P = 0.66, respectively). CONCLUSIONS - The combination of metabolic markers derived from the oral glucose tolerance test improved accuracy in predicting progression to type 1 diabetes in a population with ICA positivity and abnormal metabolism. The results indicate that the autoimmune activity may not alter the risk of type 1 diabetes after metabolic function has deteriorated. Future intervention trials may consider eliminating IVGTT measurements as an effective cost-reduction strategy for prognostic purposes.

AB - OBJECTIVE - To establish and compare the prognostic accuracy of immunologic and metabolic markers in predicting onset of type 1 diabetes in those with high risk in a prospective study. RESEARCH DESIGN AND METHODS - A total of 339 subjects from the Diabetes Prevention Trial-Type 1 (DPT-1) parenteral study, who were islet cell antibody (ICA)-positive, with low first-phase insulin response (FPIR) and/or abnormal glucose tolerance at baseline, were followed until clinical diabetes onset or study end (5-year follow-up). The prognostic performance of biomarkers was estimated using receiver operating characteristic (ROC) curve analysis and compared with nonparametric testing of ROC curve areas. Pearson correlation was used to assess the relationship between the markers. RESULTS - Individually, insulin autoantibody titer, ICA512A titer, peak C-peptide, 2-h glucose, FPIR, and FPIR/homeostasis model assessment of insulin resistance provided modest but significant prognostic values for 5-year risk with a similar level of area under ROC curve ranging between 0.61 and 0.67. The combination of 2-h glucose, peak C-peptide, and area under the curve C-peptide significantly improved the prognostic accuracy compared with any solitary index (P < 0.05) with an area under ROC curve of 0.76 (95% CI 0.70-0.81). The addition of antibody titers and/or intravenous glucose tolerance test (IVGTT) markers did not increase the prognostic accuracy further (P = 0.46 and P = 0.66, respectively). CONCLUSIONS - The combination of metabolic markers derived from the oral glucose tolerance test improved accuracy in predicting progression to type 1 diabetes in a population with ICA positivity and abnormal metabolism. The results indicate that the autoimmune activity may not alter the risk of type 1 diabetes after metabolic function has deteriorated. Future intervention trials may consider eliminating IVGTT measurements as an effective cost-reduction strategy for prognostic purposes.

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