In recent years, with the aging of the population and the change of lifestyles, patients with type 2 diabetes mellitus (T2DM) have a high prevalence of malignancies, the duration of T2DM and the use of T2DM drugs may accelerate the occurrence of malignant tumor.
To analyze the risk of incidence and influencing factors of malignant tumors in patients with T2DM.
Patients with T2DM who were first treated or diagnosed at the Affiliated Hospital of Nantong University from October, 2011 to December, 2020 were prospectively included, with the follow-up termination date of September 30, 2021. The information of tumor incidence and full cause of death of patients were obtained by matching the ID information with the linkage records of the chronic disease tumor registration system and the cause of death registration system of Nantong City. The crudeincidence rate (CIR) and standardized incidence ratio (SIR) of malignant tumors among T2DM patients were calculated separately by gender. Cox proportional hazard regression model was used to explore the effects of the duration of T2DM and drug use on the incidence of malignant tumor in T2DM patients.
A total of 12 006 patients with T2DM were included in this study, involving 6 328 males (52.71%) and 5 678 females (47.29%). After 56 371 person-years of observation (29 543 person-years for males and 26 824 person-years for females), 601 patients with malignant tumor and 11 405 patients with T2DM alone were observed. The CIR of malignant tumor in T2DM patients was 1 093.24/100 000 in men and 1 032.51/100 000 in women, respectively. The top five combined tumors in T2DM patients are colorectal cancer, lung cancer, liver cancer, gastric cancer, and prostate cancer in male, while breast cancer, lung cancer, colorectal cancer, gastric cancer and pancreatic cancer in female. The incidences of colorectal cancer (SIR=2.03), prostate cancer (SIR=2.24), pancreatic cancer (SIR=1.75), kidney cancer (SIR=4.25), thyroid cancer (SIR=3.50) were higher in male T2DM patients than general population, while the incidences of lung cancer (SIR=0.61) and esophageal cancer (SIR=0.22) were lower than general population. The incidences of breast cancer (SIR=2.59), colorectal cancer (SIR=1.57), pancreatic cancer (SIR=2.10), endometrial cancer (SIR=2.83), kidney cancer (SIR=3.67), thyroid cancer (SIR=4.00) were higher in female T2DM patients than general population, while the incidence of esophageal cancer (SIR=0.27) was lower than general population. Compared with T2DM patients with disease duration of 1 to <3 years, the risk of malignant tumor was increased by 91% 〔HR=1.91, 95%CI (1.15, 3.20) 〕, 123%〔HR=2.23, 95%CI (1.37, 3.64) 〕 and 71%〔HR=1.71, 95%CI (1.04, 2.80) 〕in male with disease duration <1 year, 5 to <10 years and≥10 years, respectively, the risk of malignant tumor was increased by 79%〔HR=1.79, 95%CI (1.10, 2.92) 〕 and 99%〔HR=1.99, 95%CI (1.24, 3.19) 〕 in female with T2DM duration of 5 to <10 years and ≥10 years, respectively (P<0.05). Insulin use alone increased the risk of malignant tumor by 72%〔HR=1.72, 95%CI (1.25, 2.36) 〕and 116%〔HR=2.16, 95%CI (1.53, 3.05) 〕 in male and female, respectively (P<0.05). In addition, there was a significant interaction between insulin use and the duration of T2DM in male, the risk of malignant tumor was decreased by an average of 6% with the interaction over the years (Pinteraction=0.006) .
In addition to esophageal cancer in both sexes and lung cancer in male, the risk of colorectal cancer, prostate cancer, pancreatic cancer, kidney cancer, thyroid cancer, breast cancer and endometrial cancer increase by 57%-325% in patients with T2DM, and associated with the disease duration and insulin use, with the greatest risk of malignant tumor in male with disease duration of 5 to <10 years and in female with disease duration of ≥10 years. However, there is an antagonistic interaction between insulin use and increased duration of T2DM disease on the incidence of malignant tumor.
Diabetes mellitus has been a major concern as a common risk factor for cardiovascular disease. Glycated hemoglobin (HbA1c) variability is an indicator of long-term blood glucose fluctuation. Therefore, it is of great clinical significance to explore the correlation between HbA1c variability and new-onset atrial fibrillation (AF) in diabetic patients combined with heart failure with preserved ejection fraction (HFpEF) .
To investigate the correlation between HbA1c variability and new onset AF in type 2 diabetes mellitus (T2DM) patients combined with HFpEF.
The clinical data of 317 T2DM patients combined with HFpEF diagnosed in the Department of Cardiology, the Second Affiliated Hospital of Zhengzhou University from January 2018 to January 2019 were retrospectively analyzed. The follow-up was performed until February 2022, with a mean follow-up time of 3.4 years. The included patients were divided into the AF group (34 cases) and non-AF group (283 cases) based on the presence of new-onset AF during the follow-up period. The HbA1c variability was expressed as standard deviation of HbA1c measurement (HbA1c-SD) and HbA1c coefficient of variation (HbA1c-CV). Multivariate Cox regression analysis was used to explore the correlation between HbA1c variability and new-onset AF in T2DM patients combined with HFpEF. The survival curves were plotted by the Kaplan-Meier (K-M) method. The receiver operating characteristic (ROC) curve of HbA1c variability predicting new-onset AF in T2DM patients combined with HFpEF was plotted.
The HbA1c-SD and HbA1c-CV of patients in the AF group were higher than those in the non-AF group (P<0.05). The included patients were divided into the low HbA1c variability (HbA1c-SD≤0.34%, HbA1c-CV≤4.74%) and high HbA1c variability (HbA1c-SD>0.34%, HbA1c-CV>4.74%) groups according to the median of HbA1c variability. Log-rank test results showed higher incidence of new-onset AF in patients with high HbA1c variability (PHbA1c-SD<0.001, PHbA1c-CV=0.004). Multivariate Cox regression analysis showed that HbA1c-SD〔HR=2.22, 95%CI (1.37, 3.61), P=0.001〕 and HbA1c-CV〔HR=1.65, 95%CI (1.01, 2.67), P=0.001〕 were independent influencing factors for new-onset AF in T2DM patients combined with HFpEF. The AUC of HbA1c-SD for predicting AF in T2DM patients combined with HFpEF was 0.784 〔95%CI (0.713, 0.855), P=0.001〕, with the optimum cutoff value of 0.36%, sensitivity and specificity of 79.4% and 73.1%, respectively. The AUC of HbA1c-CV for predicting AF in patients with T2DM and HFpEF was 0.694 〔95%CI (0.591, 0.797), P<0.001〕, with the optimal cutoff value of 4.97%, sensitivity and specificity of 73.5% and 72.1%, respectively.
High HbA1c variability (HbA1c-SD>0.34%, HbA1c-CV>4.74%) is independently associated with an increased risk of new-onset AF in T2DM patients combined with HFpEF, with significant clinical value in predicting AF.
Metabolism-associated fatty liver disease (MAFLD) is considered as a major cause of increased morbidity and mortality from liver disease, type 2 diabetes mellitus (T2DM) is a driving factor in the progression of MAFLD. Estimated glucose processing rate (eGDR) is a simple evaluation indicator of insulin resistance in patients with T2DM, while its relationship with MAFLD has been rarely studied.
To investigate the correlation between eGDR and MAFLD in type 2 Diabetes and its predictive value.
A total of 1 434 patients with T2DM who were hospitalized in Hebei Provincial People's Hospital from 2019-01-01 to 2019-12-31 were selected as the study subjects. baseline data of the patients was collected, with their venous blood from the elbow collected for laboratory examination, and liver condition examined by abdominal ultrasound. According to the results of abdominal ultrasonography, T2DM patients were divided into MAFLD group (n=734) and non-MAFLD group (n=700). The subjects were divided into T1 group (eGDR≤5.09, n=477), T2 group (5.09<eGDR≤7.11, n=478) and T3 group (eGDR>7.11, n=479) according to the eGDR tertiles. Spearman rank correlation analysis was used to explore the correlation between eGDR and baseline data. Univariate and multivariate Logistic regression analysis was used to explore the influencing factors of combined MAFLD. The multiplicative interactions of eGDR with gender, age, hypertension, glycated hemoglobin A1c (HbA1c), BMI and glutamyl transferase (GGT) were evaluated. Receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of combined prediction model, FBG and HbA1c for MAFLD in T2DM and areas under curve (AUC) were calculated and compared by Delong test.
Age, disease course, HDL-C and eGDR of MAFLD group were lower than non-MAFLD group. BMI, alcohol consumption, proportions of hypertension and smoking, fasting blood glucose (FBG), uric acid (UA), total cholesterol (TC), TG, low density lipoprotein cholesterol (LDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST), GGT and ALB were higher than non-MAFLD group (P<0.05). The proportion of hypertension, age, BMI, FBG, HbA1c, Scr and TG in T3 group were lower than those in T1 and T2 groups, GGT was lower than that in T1 group, HDL-C and ALB were higher than those in T1 and T2 groups, the proportion of hypertension, BMI, FBG, HbA1c and TG in T2 group were lower than those in T1 group (P<0.05). eGDR was negatively correlated with age, FBG and ALB in patients with MAFLD (P<0.05). In patients without MAFLD, eGDR was negatively correlated with age, disease course, FBG, Scr, TG and ALB (P<0.05), and positively correlated with HDL-C, AST and GGT (P<0.05). Multivariate Logistic regression analysis showed that eGDR〔OR=0.814, 95%CI (0.772, 0.858), P<0.001〕, T1 group〔OR=1.310, 95%CI (1.003, 1.712), P=0.048〕and T2 group〔OR=2.554, 95%CI (1.941, 3.359), P<0.001〕 was an influencing factor of T2DM with MAFLD (P<0.05). BMI (Pinteraction<0.001), GGT (Pinteraction=0.033), hypertension (Pinteraction<0.001) had interaction with eGDR. The AUC of the combined prediction model was 0.743, which was greater than FBG (Z=3.227, P=0.001) and HbA1c (Z=1.877, P=0.061) .
The level of eGDR in T2DM patients with MAFLD is significantly lower than that in patients without MAFLD, and patients with low eGDR level have a higher risk of MAFLD. eGDR is a risk factor for MAFLD with T2MD. The combined prediction model of eGDR can be used as a predictor to evaluate the risk of MAFLD with T2MD.
The incidence of diabetic kidney disease (DKD) and the proportion of its related end-stage renal disease in dialysis patients in China are increasing. So it is urgent to take measures to prevent and control DKD. Intensified multifactorial interventions may prevent or delay the progression of DKD. Therefore, developing a personalized risk prediction model can effectively delay or even prevent the progression of DKD and be useful for the prevention and treatment of DKD.
The purpose of this study was to develop and validate a nomogram for the risk prediction of the progression from microalbuminuria (MAU) to macroalbuminuria (CAU) in type 2 diabetes mellitus (T2DM) patients.
A total of 1 263 T2DM patients with albuminuria who were hospitalized in Department of Endocrinology, the First Affiliated Hospital of Air Force Medical University from October 2016 to March 2020 were retrospectively recruited and divided into a development cohort of 906 cases and a validation cohort of 357 cases, according to the admission time. LASSO regression was used to screen the optimized variables measured at baseline for CAU. A Nomogram was constructed based on selected predictive factors identified by the multivariate logistic regression model of the development sub-cohort. The receiver operating characteristic (ROC) curve, calibration curve and Hosmer-Lemeshow (H-L) test were employed to assess the calibration and discrimination of the model. Decision curve analysis (DCA) was performed to evaluate the net clinical benefit of the Nomogram.
The diabetes duration, systolic blood pressure (SBP), glycosylated hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), cystatin C (Cys-C), estimated glomerular filtration rate (eGFR), and diabetic retinopathy (DR) were screened as predictive factors for progression from MAU to CAU by LASSO penalty regression. Multivariable Logistic regression analysis using these factors indicated that seven of those potential predictors were present in the final model, diabetes duration≥10 years, SBP≥140 mmHg, HbA1c≥7.0 mmol/L, LDL-C≥1.8 mmol/L, Cys-C>1.09 mg/L, and DR were risk factors for the progression from MAU to CAU in T2DM patients (P<0.05), while eGFR showed no statistically significant association with the progression in stratified analysis (P>0.05). External and internal validations of the nomogram indicated a good predictive performance. The AUC of the model was 0.814〔95%CI (0.782, 0.846) 〕 in the development cohort, and was 0.768〔95%CI (0.713, 0.823) 〕 in the validation cohort. The model was well fit according to the calibration curve and the H-L goodness of fit test (internal validation: P=0.065; external validation: P=0.451). DCA curve showed that the Nomogram's net benefit was higher than both extreme curves when the threshold probability set between 0.08 and 0.74 in the development cohort, and between 0.14 and 0.70 in the external validation cohort, suggesting potential clinical benefits provided by this Nomogram.
This study finally constructed a prediction model with seven indicators containing diabetes duration, SBP, HbA1c, LDL-C, Cys-C, eGFR, and DR, and will be a useful clinical predictive tool for the risk of progression from MAU to CAU in T2DM patients.
