scholarly journals Metabolomics Identifies Biomarker Signatures to Differentiate Pancreatic Cancer from Type 2 Diabetes Mellitus in Early Diagnosis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hongmin Xu ◽  
Lei Zhang ◽  
Hua Kang ◽  
Jie Liu ◽  
Jiandong Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Pancreatic Cancer ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Early Diagnosis ◽  
Regression Models ◽  
Pancreatic Tissue ◽  
Logistic Regression Models

Background and Purpose. Carbohydrate antigen 19-9 (CA19-9) based approaches differentiate less than 60% of cases of pancreatic cancer (PC) from those of pancreatic tissue damage caused by chronic pancreatitis and type 2 diabetes mellitus (DM). This study aims to identify potential blood-derived candidate biomarkers for improved diagnosis sensitivity. Methods. Plasma metabolic profiles in 26 PC patients, 27 DM patients, and 23 healthy volunteers were examined using an ultraperformance liquid chromatography coupled with tandem mass spectrometry platform. Differential metabolite ions were then identified using the principal component analysis (PCA) model and the orthogonal partial least-squares discrimination analysis (OPLS-DA) model. The diagnosis performance of metabolite biomarkers was validated by logistic regression models. Results. We established a PCA model (R2X = 23.5%, Q2 = 8.21%) and an OPLS-DA model (R2X = 70.0%, R2Y = 84.9%, Q2 = 69.7%). LysoPC (16 : 0), catelaidic acid, cerebronic acid, nonadecanetriol, and asparaginyl-histidine were found to identify PC, with a sensitivity of 89% and a specificity of 91%. Besides, lysoPC (16 : 0), lysoPC (16 : 1), lysoPC (22 : 6), and lysoPC (20 : 3) were found to differentiate PC from DM, with higher accuracy (68% versus 55%) and higher AUC values (72% versus 63%) than those of CA19-9. The diagnostic performance of metabolite biomarkers was finally validated by logistic regression models. Conclusion. We succeeded in screening differential metabolite ions among PC and DM patients and healthy individuals, thus providing a preliminary basis for screening the biomarkers for the early diagnosis of PC.

scholarly journals Secondary metformin monotherapy failure in individuals with type 2 diabetes mellitus

2021 ◽  
Vol 9 (1) ◽  
pp. e002127
Author(s):  
Tracey Weiss ◽  
Kristy Iglay ◽  
Tania Gulati ◽  
Swapnil Rajpathak ◽  
Lingfeng Yang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Glycemic Control ◽  
Treatment Change ◽  
Logistic Regression Models ◽  
Multivariable Logistic Regression ◽  
Metformin Monotherapy

IntroductionTo assess secondary metformin monotherapy (MM) failure in a real-world type 2 diabetes mellitus (T2DM) cohort.Research design and methodsUsing the IQVIA Electronic Medical Record (formerly GE Centricity) database, adults with T2DM who initiated MM between January 1, 2012 and June 30, 2016 and achieved glycemic control (hemoglobin A1c (HbA1c) <7% (53 mmol/mol); index date) were analyzed. Secondary MM failure was defined in two ways: loss of glycemic control (HbA1c ≥7% (53 mmol/mol)) and treatment change (addition or switch of antihyperglycemic agent). Multivariable logistic regression models assessed the association between secondary MM failure and sociodemographic and clinical factors.ResultsThe analysis included 4775 patients initiating MM. 32.9% and 19.2% experienced secondary MM failure at 24 months measured as loss of glycemic control and treatment change, respectively. Multivariable logistic regression found that women (OR=1.3, 95% CI 1.1 to 1.5) compared with men, lower Charlson Comorbidity Index (CCI) (OR=0.89, 95% CI 0.86 to 0.93), and lower baseline HbA1c (OR=0.93, 95% CI 0.88 to 0.98) were associated with increased likelihood of loss of glycemic control. Lower CCI was associated with increased likelihood of treatment change (OR=0.78, 95% CI 0.75 to 0.82).ConclusionsThe observed frequency of secondary MM failure underscores the importance of the American Diabetes Association’s recommendation for glycemic monitoring of at least every 6 months so that timely therapeutic adjustments can be made.

Cytokines as potential biomarkers for distinguishing patients with pancreatic cancer and type 2 diabetes mellitus

Pancreatology ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. S33
Author(s):  
Rohith Gopala Rao ◽  
Lucy Oldfield ◽  
Anthony Evans ◽  
Lavanya Sivapalan ◽  
Philip Schuler ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Pancreatic Cancer ◽  
Type 2 Diabetes Mellitus ◽  
Potential Biomarkers

scholarly journals Angiopoietin-like Protein 2 is a Useful Biomarker for Pancreatic Cancer that is Associated with Type 2 Diabetes Mellitus and Inflammation

2018 ◽  
Vol 9 (24) ◽  
pp. 4736-4741 ◽  
Author(s):  
Takuma Yoshinaga ◽  
Tatsuyuki Niou ◽  
Toru Niihara ◽  
Yoriko Kajiya ◽  
Emiko Hori ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Pancreatic Cancer ◽  
Type 2 Diabetes Mellitus

scholarly journals Comorbidity in an Older Population with Type-2 Diabetes Mellitus: Identification of the Characteristics and Healthcare Utilization of High-Cost Patients

2020 ◽  
Vol 11 ◽  
Author(s):  
Inmaculada Guerrero-Fernández de Alba ◽  
Valentina Orlando ◽  
Valeria M. Monetti ◽  
Sara Mucherino ◽  
Antonio Gimeno-Miguel ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Healthcare Database ◽  
Campania Region ◽  
Total Cost ◽  
T2dm Patient ◽  
Logistic Regression Models ◽  
Cost Distribution

Objectives: Little is known about the specific comorbidities contributing to higher costs in patients with type-2 diabetes mellitus (T2DM), particularly in older cases. We aimed to evaluate the prevalence, type, and cost of comorbidities occurring in older T2DM patients versus older non-T2DM patients, and the factors associated with high cost (HC) T2DM patients.Methods: Retrospective cohort study using information from the Campania Region healthcare database. People aged ≥65 years who received ≥2 prescriptions for antidiabetic drugs were identified as “T2DM patients.” Comorbidities among T2DM and non-T2DM groups were assessed through the RxRiskV Index (modified version). T2DM individuals were classified according to the total cost distribution as HC or “non-high cost.” Two sub-cohorts of HC T2DM patients were assessed: above 90th and 80th percentile of the total cost. Age- and sex-adjusted logistic regression models were created.Results: Among the T2DM cohort, concordant and discordant comorbidities occurred significantly more frequently than in the non-T2DM cohort. Total mean annual cost per T2DM patient due to comorbidities was €7,627 versus €4,401 per non-T2DM patient. Among T2DM patients identified as being above 90th and 80th percentiles of cost distribution, the total annual costs were &gt;€19,577 and &gt;€2,563, respectively. The hospitalization cost was higher for T2DM cases. Strongest predictors of being a HC T2DM patient were having ≥5 comorbidities and renal impairment.Conclusion: HC patients accrued &gt;80% of the total comorbidities cost in older T2DM patients. Integrated care models, with holistic and patient-tailored foci, could achieve more effective T2DM care.

scholarly journals Decreased serum C1Q/TNF-related protein 4 concentrations are associated with type 2 diabetes mellitus

2021 ◽  
Vol 12 ◽  
pp. 204201882110598
Author(s):  
Zheng Liu ◽  
Jinhua Lu ◽  
Daiyi Zhang ◽  
Lijuan Niu ◽  
Bimin Shi
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Stepwise Logistic Regression ◽  
Newly Diagnosed ◽  
Spearman Correlation ◽  
Related Protein ◽  
Multivariate Stepwise Logistic Regression

Objective: To detect serum C1Q/TNF-related protein 4 (CTRP4) concentrations in patients with newly diagnosed type 2 diabetes mellitus (T2DM) and evaluate the correlation between CTRP4 and other variables in T2DM. Method: Sixty-five patients with newly diagnosed T2DM and eighty-nine healthy volunteers were enrolled in this study. Anthropometric and biochemical data of the study participants was collected, and serum CTRP4 concentrations were detected by enzyme-linked immunosorbent assay (ELISA) kit. The correlation between serum CTRP4 and other indexes was analyzed by Spearman correlation analysis. Trend χ2 test and binary multivariate stepwise logistic regression were performed to assess the correlation between CTRP4 and the risk of T2DM. Results: Serum CTRP4 concentrations in the T2DM group were significantly lower than those in the control group ( P < .01). Spearman correlation analysis showed that CTRP4 concentrations were negatively correlated with BMI, hs-CRP, HOMA-IR, FBG and TG ( r = - 0.430, - 0.453, - 0.371, - 0.361, - 0.506, P < .05), and positively correlated with HDL-c ( r = 0.303, P < .05). Trend χ2 test indicated that with the increase of CTRP4 levels in the population, the risk of T2DM presented a general downward trend ( P < .01). Binary multivariate stepwise logistic regression suggested that serum CTRP4 was an independent impact factor for T2DM and high serum CTRP4 levels were related to the decreased risk of T2DM (P < .05). Conclusions: Serum CTRP4 concentrations decrease in patients with newly diagnosed T2DM. Serum CTRP4 levels are negatively associated with the risk of T2DM.

scholarly journals Association Between Transcription Factor 7-Like-2 Polymorphisms and Type 2 Diabetes Mellitus in a Ghanaian Population

2021 ◽  
Author(s):  
Christian Obirikorang ◽  
Evans Asamoah Adu ◽  
Enoch Odame Odame ◽  
Emmanuel Acheampong ◽  
Lawrence Quaye ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Lipid Analysis ◽  
Nucleotide Polymorphisms ◽  
Logistic Regression Models ◽  
Allele Specific ◽  
Amplification Assay ◽  
Glucose Estimation

Type-2 diabetes mellitus (T2DM) have been strongly associated with single nucleotide polymorphisms (SNPs) in the TCF7L2 gene. This study investigated the association between rs12255372, rs7903146 and T2DM in a Ghanaian population. A case-control study design was used for this study. A total of 106 T2DM patients and 110 control participants were selected. Basic data collected included body mass index, blood pressure and socio-demographics. Fasting blood samples were collected and used for serum lipid analysis, HbA1c, plasma glucose estimation and DNA extraction. Common and allele-specific primers were designed for genotyping using the Modified Tetra-Primer Amplification assay. Associations were evaluated using logistic regression models. The rs7903146 risk variant was significantly associated with 2.16 vs 4.06 increased odds for T2DM in patients

scholarly journals Early diagnosis of renal dysfunction in hypertensive patients with type 2 diabetes mellitus

2020 ◽  
Vol 11 (4) ◽  
pp. 102-109
Author(s):  
Oleksandr M Bilovol ◽  
Iryna I. Kniazkova ◽  
Oleksandr M. Kirienko ◽  
Vladyslav. I. Korniichuk ◽  
Denis A. Kirienko ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Early Diagnosis ◽  
Renal Dysfunction ◽  
Hypertensive Patients

scholarly journals The frailty syndrome in older adults with type 2 diabetes mellitus and associated factors

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
Bartolomeu Fagundes de Lima Filho ◽  
Antônia Gilvanete Duarte Gama ◽  
Vanessa da Nóbrega Dias ◽  
Eliza Mikaele Tavares da Silva ◽  
Fabricia Azevedo da Costa Cavalcanti ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Older Adults ◽  
Type 2 Diabetes Mellitus ◽  
Logistic Regression ◽  
Logistic Regression Model ◽  
Lower Limbs ◽  
Frailty Syndrome ◽  
Frail Phenotype

Abstract Objective: To compare clinical-functional factors among groups in relation to the frailty syndrome (pre-frail and frail) phenotype profile in older adults with type 2 diabetes mellitus (DM 2). Methods: A descriptive, analytical, cross-sectional study with a quantitative approach was performed. A total of 113 diabetic older adults of both sexes were evaluated in terms of their personal, socio-demographic, clinical-functional, mental, cognitive and fragility phenotype data. The Chi-square test and a logistic regression model were used. Results: The mean age was 68.66±6.62 years, and the sample was mostly female (61.9%), illiterate or with an incomplete primary education (60.2%), pre-frail (52.2%), sedentary (79.6%), and had been diagnosed with DM2 for more than 5 years (58.3%). There was a significant association between “pre-frail and frail” individuals and schooling (p=0.004), social participation (p=0.004), a subjective perception of vision (p=0.004), glycated hemoglobin (p=0.036), limb pain (p=0.012), depressive symptoms (p=0.002) and mobility (p=0.004). The logistic regression model showed an accuracy of 93.6% and the significant variables were education (p=0.039), pain in the lower limbs (p=0.025) and risk of falls (p=0.033). Conclusion: among all the factors related to the “pre-frail” and “frail” phenotype, schooling, pain in the lower limbs and mobility were most related to the worsening of the syndrome and its progress.

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