Xin-Yu Liang,1,* Li-yuan Mu,1,* Lei Hu,2,* Rui-ling She,1,* Chen-yu Ma,1,* Jun-han Feng,1,* Zhi-yu Jiang,1 Zhao-xing Li,1 Xiu-quan Qu,1 Bai-qing Peng,1 Kai-nan Wu,1 Ling-quan Kong1 

1Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 2Information Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Ling-quan Kong, Department of Breast and Thyroid Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China, Tel +8613101380893, Email huihuikp@163.com

Purpose: Glycated hemoglobin (HbA1c) is widely used in diabetes management and now recommended for diagnosis and risk assessment. Our research focused on investigating the optimal cutoff points of HbA1c for diagnosis of diabetes and prediabetes in Chinese breast cancer women, aiming to enhance early detection and tailor treatment strategies.
Patients and Methods: This study involved 309 breast cancer women without diabetes history in China. Patients were categorized into groups of newly diagnosed diabetes, prediabetes, and normal glucose tolerance using oral glucose tolerance test (OGTT) according to the 2010 ADA criteria. HbA1c data were collected from all patients. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the HbA1c screening.
Results: Among the 309 breast cancer women without diabetes history, 96 (31.0%) were identified with diabetes and 130 (42.1%) had prediabetes according to OGTT, and the incidence of normal glucose tolerance was only 26.9% (83). ROC curve analysis, using OGTT as a reference, revealed that the area under the curve of 0.903 (P< 0.001, 95% CI, 0.867– 0.938) for HbA1c alone, indicating high accuracy. The optimal HbA1c cutoff for identifying diabetes was determined to be 6.0%, with a sensitivity of 78.1% and specificity of 86.4%. For prediabetes, the ROC curve for HbA1c alone showed that the area under the ROC curve of 0.703 (P< 0.001, 95% CI, 0.632– 0.774), with an optimal cutoff of 5.5% (sensitivity of 76.9% and specificity of 51.8%).
Conclusion: The prevalence of undiagnosed diabetes is very high in breast cancer women without diabetes history in China. The optimal cutoff points of HbA1c for identifying diabetes and prediabetes are 6.0% and 5.5% in Chinese breast cancer women, respectively.

Keywords: breast cancer, diabetes, HbA1c, prediabetes