Evidence for C-Peptide as a Validated Surrogate to Predict Clinical Benefits in Trials of Disease-Modifying Therapies for Type 1 Diabetes.

Type 1 diabetes is a chronic autoimmune disease in which destruction of pancreatic ß-cells causes life-threatening metabolic dysregulation. Numerous approaches are envisioned for new therapies, but limitations of current clinical outcome measures are significant disincentives to development efforts. C-peptide, a direct byproduct of proinsulin processing, is a quantitative biomarker of ß-cell function that is not cleared by the liver and can be measured in the peripheral blood. Studies of quantitative measures of ß-cell function have established a predictive relationship between stimulated C-peptide as a measure of ß-cell function and clinical benefits. C-peptide levels at diagnosis are often high enough to afford glycemic control benefits associated with protection from end-organ complications of diabetes, and even lower levels offer protection from severe hypoglycemia in type 1 diabetes, as observed in large prospective cohort studies and interventional trials of islet transplantation. These observations support consideration of C-peptide not just as a biomarker of ß-cell function but also as a specific, sensitive, feasible, and clinically meaningful outcome defining ß-cell preservation or restoration for clinical trials of disease-modifying therapies. Regulatory acceptance of C-peptide as a validated surrogate for demonstration of efficacy would greatly facilitate development of disease-modifying therapies for type 1 diabetes.

Validation of a Metabolite Panel for a More Accurate Estimation of Glomerular Filtration Rate Using Quantitative LC-MS/MS.

BACKGROUND: Clinical practice guidelines recommend estimation of glomerular filtration rate (eGFR) using validated equations based on serum creatinine (eGFRcr), cystatin C (eGFRcys), or both (eGFRcr-cys). However, when compared with the measured GFR (mGFR), only eGFRcr-cys meets recommended performance standards. Our goal was to develop a more accurate eGFR method using a panel of metabolites without creatinine, cystatin C, or demographic variables. METHODS: An ultra-performance liquid chromatography-tandem mass spectrometry assay for acetylthreonine, phenylacetylglutamine, pseudouridine, and tryptophan was developed, and a 20-day, multiinstrument analytical validation was conducted. The assay was tested in 2424 participants with mGFR data from 4 independent research studies. A new GFR equation (eGFRmet) was developed in a random subset (n = 1615) and evaluated in the remaining participants (n = 809). Performance was assessed as the frequency of large errors [estimates that differed from mGFR by at least 30% (1 - P30); goal <10%]. RESULTS: The assay had a mean imprecision (≤10% intraassay, ≤6.9% interassay), linearity over the quantitative range (r 2 > 0.98), and analyte recovery (98.5%-113%). There was no carryover, no interferences observed, and analyte stability was established. In addition, 1 - P30 in the validation set for eGFRmet (10.0%) was more accurate than eGFRcr (13.1%) and eGFRcys (12.0%) but not eGFRcr-cys (8.7%). Combining metabolites, creatinine, cystatin C, and demographics led to the most accurate equation (7.0%). Neither equation had substantial variation among population subgroups. CONCLUSIONS: The new eGFRmet equation could serve as a confirmatory test for GFR estimation.