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Novel time-saving OGTT sparing HbA1c-HOMA2 based algorithm for the diagnosis of cystic fibrosis-related diabetes
Fabian Lurquin1, Sophie Gohy2, Michel P Hermans1
1Department of Endocrinology and Nutrition, Cliniques universitaires Saint-Luc, Institut de recherche expérimentale et clinique, UCLouvain, Brussels, Belgium.
Insights
A new screening tool, the Diabetes Predicting Index in cystic fibrosis (DIPIc), combines HbA1c and HOMA-B to accurately screen for cystic fibrosis-related diabetes (CFRD). This method significantly reduces the need for oral glucose tolerance tests (OGTTs) in CF patients.
Area of Science:
- Endocrinology
- Metabolic Disorders
- Pulmonary Medicine
Background:
- Cystic fibrosis-related diabetes (CFRD) diagnosis presents challenges.
- Current diagnostic methods for CFRD can be burdensome for patients with cystic fibrosis (CF).
Purpose of the Study:
- To develop and validate a novel, less invasive screening algorithm for CFRD.
- To reduce the frequency of oral glucose tolerance tests (OGTTs) in CF patients.
Main Methods:
- Retrospective analysis of HbA1c and HOMA2 indices from OGTT data in 72 CF patients.
- Development of the Diabetes Predicting Index in cystic fibrosis (DIPIc) using HbA1c and HOMA-B.
- Evaluation of DIPIc accuracy and OGTT reduction potential using receiver-operating characteristics (ROC) curves.
Main Results:
- The DIPIc composite index demonstrated high diagnostic accuracy for CFRD.
- Established specific thresholds for DIPIc: exclusion cutoff < -1.7445 (98% sensitivity) and diagnostic threshold > 0.4543 (98% specificity).
- A stepwise algorithm incorporating DIPIc achieved 71% OGTT sparing.
Conclusions:
- The DIPIc composite index is an effective and less invasive screening tool for CFRD.
- Implementation of DIPIc can significantly decrease the need for annual OGTTs in CF patients.
Aims:
The diagnosis of cystic fibrosis-related diabetes (CFRD) faces several challenges. We propose a novel screening algorithm to alleviate the burden of cystic fibrosis (CF).
Methods:
Through a retrospective cross-sectional single-centre study, HbA1c and HOMA2 indices were assessed in multiple models as alternative diagnostic tools from OGTT data. We sought to establish specific thresholds for CFRD screening with oral glucose tolerance test (OGTT) as gold standard. We evaluated various straightforward or sequential approaches, in terms of diagnostic accuracy while also quantify the potential reduction in OGTTs through these different methods.
Results:
HOMA indices were recovered in 72 patients. We devised a composite index that combines HbA1c and HOMA-B: Diabetes Predicting Index in cystic fibrosis (DIPIc) = (HbA1c(%) × 3.455) - (HOMA-B(%) × 0.020) - 19.294. This index yields the highest screening accuracy according to receiver-operating characteristics curves. Using a stepwise algorithm that incorporates DIPIc decreases the requirement for annual OGTTs. A CFRD exclusion cutoff less than -1.7445 (sensitivity 98 %), in conjunction with a CFRD diagnostic threshold greater than 0.4543 (specificity 98 %) allows for 71 % OGTT sparing.
Conclusion:
The composite index DIPIc is a suitable, less invasive screening method for CFRD, which enables to avoid many OGTTs.
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