scholarly journals Detection of High Risk People for Diabetes by American Diabetes Association Risk Score in PERSIAN Guilan Cohort Study

2020 ◽  
Author(s):  
Tolou Hasandokht ◽  
Farahnaz Joukar ◽  
Saman Marroufizadeh ◽  
Sahar Sibevey ◽  
Mohammadreza Naghipour ◽  
...  
Keyword(s):  
Cohort Study ◽  
High Risk ◽  
Risk Score ◽  
Operating Characteristic ◽  
American Diabetes Association ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Diagnostic Value ◽  
Anthropometric Indices ◽  
Online Calculator

Abstract Background: To determine prevalence of high risk individuals for diabetes mellitus (DM) and pre DM based on American Diabetes Association (ADA) risk score among Iranian people. Methods: Present study was based on 7989 non diabetic subjects aged 35–70 years from 10520 PERSIAN Guilan Cohort Study (PGCS) participants. ADA risk score was calculated for every individual through online calculator. Receiver operating characteristic (ROC) curves was used to study diagnostic accuracy of the anthropometric indices for detecting individuals with high risk ADA score for developing DM, represented by area under the curve (AUC).Results: From 7989 study subjects, ADA risk score found 3874 (48.5%) and 19122 (23%) at risk for developing PreDM and DM, respectively. The results of ROC curve analyses showed the highest diagnostic value was related to waist circumference (WC) followed by Body Mass Index (BMI) (0.695 and 0.693, respectively). The cut-points of WC and BMI for identifying high risk people for DM were 97 and 29, respectively.Conclusions: A large number of our participants had high ADA risk score for developing DM and PreDM that provide the importance of prevention strategies. WC seems to be highest diagnostic value in identifying people (men and women) with DM.

scholarly journals Inflammatory Breast Carcinoma: Elevated microRNA miR-181b-5p and Reduced miR-200b-3p, miR-200c-3p, and miR-203a-3p Expression as Potential Biomarkers with Diagnostic Value

Biomolecules ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1059
Author(s):  
Sarah Atef Fahim ◽  
Mahmoud Salah Abdullah ◽  
Nancy A. Espinoza-Sánchez ◽  
Hebatallah Hassan ◽  
Ayman M. Ibrahim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Diagnostic Accuracy ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Diagnostic Value ◽  
Differentially Expressed Mirnas ◽  
E Box ◽  
Aggressive Breast Cancer ◽  
Potential Biomarkers

Inflammatory breast cancer (IBC) is a rare yet aggressive breast cancer variant, associated with a poor prognosis. The major challenge for IBC is misdiagnosis due to the lack of molecular biomarkers. We profiled dysregulated expression of microRNAs (miRNAs) in primary samples of IBC and non-IBC tumors using human breast cancer miRNA PCR array. We discovered that 28 miRNAs were dysregulated (10 were upregulated, while 18 were underexpressed) in IBC vs. non-IBC tumors. We identified 128 hub genes, which are putative targets of the differentially expressed miRNAs and modulate important cancer biological processes. Furthermore, our qPCR analysis independently verified a significantly upregulated expression of miR-181b-5p, whereas a significant downregulation of miR-200b-3p, miR-200c-3p, and miR-203a-3p was detected in IBC tumors. Receiver operating characteristic (ROC) curves implied that the four miRNAs individually had a diagnostic accuracy in discriminating patients with IBC from non-IBC and that miR-203a-3p had the highest diagnostic value with an AUC of 0.821. Interestingly, a combination of miR-181b-5p, miR-200b-3p, and miR-200c-3p robustly improved the diagnostic accuracy, with an area under the curve (AUC) of 0.897. Intriguingly, qPCR revealed that the expression of zinc finger E box-binding homeobox 2 (ZEB2) mRNA, the putative target of miR-200b-3p, miR-200c-3p, and miR-203a-3p, was upregulated in IBC tumors. Overall, this study identified a set of miRNAs serving as potential biomarkers with diagnostic relevance for IBC.

scholarly journals Evaluation of alpha-l-fucosidase for the diagnosis of hepatocellular carcinoma based on meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Lei Xi ◽  
Chunqing Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Value ◽  
Receiver Operating Characteristic Curves ◽  
Sensitivity Specificity ◽  
Review Manager

AbstractObjectivesThe main aim of the present study was to assess the diagnostic value of alpha-l-fucosidase (AFU) for hepatocellular carcinoma (HCC).MethodsStudies that explored the diagnostic value of AFU in HCC were searched in EMBASE, SCI, and PUBMED. The sensitivity, specificity, and DOR about the accuracy of serum AFU in the diagnosis of HCC were pooled. The methodological quality of each article was evaluated with QUADAS-2 (quality assessment for studies of diagnostic accuracy 2). Receiver operating characteristic curves (ROC) analysis was performed. Statistical analysis was conducted by using Review Manager 5 and Open Meta-analyst.ResultsEighteen studies were selected in this study. The pooled estimates for AFU vs. α-fetoprotein (AFP) in the diagnosis of HCC in 18 studies were as follows: sensitivity of 0.7352 (0.6827, 0.7818) vs. 0.7501 (0.6725, 0.8144), and specificity of 0.7681 (0.6946, 0.8283) vs. 0.8208 (0.7586, 0.8697), diagnostic odds ratio (DOR) of 7.974(5.302, 11.993) vs. 13.401 (8.359, 21.483), area under the curve (AUC) of 0.7968 vs. 0.8451, respectively.ConclusionsAFU is comparable to AFP for the diagnosis of HCC.

scholarly journals A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Susanne F. Awad ◽  
Soha R. Dargham ◽  
Amine A. Toumi ◽  
Elsy M. Dumit ◽  
Katie G. El-Nahas ◽  
...  
Keyword(s):  
High Risk ◽  
Sensitivity And Specificity ◽  
Risk Score ◽  
Area Under The Curve ◽  
Diabetes Risk ◽  
Predictive Values ◽  
Predictive Variables ◽  
Comparable Performance ◽  
Representative Random Sample ◽  
Diabetes Risk Score

AbstractWe developed a diabetes risk score using a novel analytical approach and tested its diagnostic performance to detect individuals at high risk of diabetes, by applying it to the Qatari population. A representative random sample of 5,000 Qataris selected at different time points was simulated using a diabetes mathematical model. Logistic regression was used to derive the score using age, sex, obesity, smoking, and physical inactivity as predictive variables. Performance diagnostics, validity, and potential yields of a diabetes testing program were evaluated. In 2020, the area under the curve (AUC) was 0.79 and sensitivity and specificity were 79.0% and 66.8%, respectively. Positive and negative predictive values (PPV and NPV) were 36.1% and 93.0%, with 42.0% of Qataris being at high diabetes risk. In 2030, projected AUC was 0.78 and sensitivity and specificity were 77.5% and 65.8%. PPV and NPV were 36.8% and 92.0%, with 43.0% of Qataris being at high diabetes risk. In 2050, AUC was 0.76 and sensitivity and specificity were 74.4% and 64.5%. PPV and NPV were 40.4% and 88.7%, with 45.0% of Qataris being at high diabetes risk. This model-based score demonstrated comparable performance to a data-derived score. The derived self-complete risk score provides an effective tool for initial diabetes screening, and for targeted lifestyle counselling and prevention programs.

scholarly journals Expression Analysis of Circulating miR-22, miR-122, miR-217 and miR-367 as Promising Biomarkers of Acute Lymphoblastic Leukemia

2021 ◽  
Author(s):  
Fatemeh hosseinpour-soleimani ◽  
Gholamreza Khamisipour ◽  
Zahra Derakhshan ◽  
Bahram Ahmadi
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Lymphoblastic Leukemia ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Healthy Individuals ◽  
Quantitative Real Time Pcr ◽  
Expression Levels

Abstract Background Currently, the role of serum-based biomarkers such as microRNAs in cancer diagnosis has been extensively established. This study aimed to determine expression levels of bioinformatically selected miRNAs and whether they can be used as biomarkers or a new therapeutic target in patients with Acute Lymphoblastic Leukemia (ALL). Materials and Methods The expression levels of serum miR-22, miR-122, miR-217, and miR-367 in 21 ALL patients and 21 healthy controls were measured using quantitative real-time PCR. The receiver operating characteristic (ROC) curve and the associated area under the curve (AUC) was used to assess candidate miRNAs' diagnostic value as a biomarker. Results The results showed that miR-217 was markedly decreased in patients with ALL compared to controls. Moreover, miR-22, miR-122, and miR-367 were found to be upregulated. Furthermore, ROC analysis showed that serum miR-217 and miR-367 could differentiate ALL patients from the healthy individuals, while miR-22 has approximate discriminatory power that requires further investigation. Conclusion Collectively, the results suggested that miR-217 may play a tumor suppressor role in ALL, whereas miR-22, miR-122, and miR-367 could function as an oncogene. Overall, miR-22, miR-217, and miR-367 could be considered possible biomarkers for the early diagnosis of ALL.

scholarly journals Serum Exosomal MicroRNAs as Potential Circulating Biomarkers for Endometriosis

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Lu Zhang ◽  
Huihui Li ◽  
Ming Yuan ◽  
Dong Li ◽  
Chang Sun ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Roc Curves ◽  
Diagnostic Value ◽  
Pcr Analysis ◽  
Go Annotation ◽  
Qrt Pcr ◽  
Noninvasive Biomarker ◽  
Novel Biomarkers ◽  
Negative Controls ◽  
Exosomal Mirna

Background. A reliable noninvasive biomarker is not yet available for endometriosis diagnosis. Novel biomarkers for the diagnosis of endometriosis are urgently needed. The molecular constituents of exosomes, especially exosomal microRNAs (miRNAs), have considerable potential as novel biomarkers for clinical diagnosis. This study is aimed at exploring aberrant exosomal miRNA profiles by using miRNA microarray and at providing more accurate molecular biomarkers of endometriosis. Methods. Exosomes were isolated from the serum of patients with endometriosis and negative controls and identified by electron microscopy, nanoparticle tracking analysis, and Western blot. Exosomal miRNAs were profiled by miRNA microarrays. The expression of selective serum exosomal miRNA was validated by qRT-PCR. Receiver operating characteristic (ROC) curves were established to explore the diagnostic value of selective miRNAs. Finally, GO annotation and KEGG pathway enrichment analyses were used to display possible functions associated with the two miRNAs. Results. A total of 24 miRNAs showed differential levels of enrichment with P<0.05 and log2 fold change>1 by miRNA microarrays. Among the six selective miRNAs (i.e., miR-134-5p, miR-197-5p, miR-22-3p, miR-320a, miR-494-3p, and miR-939-5p), qRT-PCR analysis revealed that miR-22-3p and miR-320a were significantly upregulated in serum exosomes from patients with endometriosis compared with negative individuals. ROC curve revealed that the serum exosomal miR-22-3p and miR-320a yielded the area under the curve values of 0.855 and 0.827, respectively. Conclusion. Our results demonstrated that exosomal miR-22-3p and miR-320a were significantly increased in the sera of patients with endometriosis. The two miRNAs may be useful potential biomarkers for endometriosis diagnosis.

scholarly journals Sequence-Based Discovery of Antibacterial Peptides Using Ensemble Gradient Boosting

Proceedings ◽  
2020 ◽  
Vol 66 (1) ◽  
pp. 6
Author(s):  
Ehdieh Khaledian ◽  
Shira L. Broschat
Keyword(s):  
Operating Characteristic ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Gradient Boosting ◽  
Support Vector ◽  
Antibacterial Peptides ◽  
Therapeutic Approaches ◽  
Laboratory Procedures ◽  
Feature Selection Techniques ◽  
Better Than

Antimicrobial resistance is driving pharmaceutical companies to investigate different therapeutic approaches. One approach that has garnered growing consideration in drug development is the use of antimicrobial peptides (AMPs). Antibacterial peptides (ABPs), which occur naturally as part of the immune response, can serve as powerful, broad-spectrum antibiotics. However, conventional laboratory procedures for screening and discovering ABPs are expensive and time-consuming. Identification of ABPs can be significantly improved using computational methods. In this paper, we introduce a machine learning method for the fast and accurate prediction of ABPs. We gathered more than 6000 peptides from publicly available datasets and extracted 1209 features (peptide characteristics) from these sequences. We selected the set of optimal features by applying correlation-based and random forest feature selection techniques. Finally, we designed an ensemble gradient boosting model (GBM) to predict putative ABPs. We evaluated our model using receiver operating characteristic (ROC) curves, calculating the area under the curve (AUC) for several different models for comparison, including a recurrent neural network, a support vector machine, and iAMPpred. The AUC for the GBM was ~0.98, more than 3% better than any of the other models.

A novel risk score for prediction of hypersensitivity reactions in cancer patients receiving carboplatin: Retrospective observational analysis.

2016 ◽  
Vol 34 (3_suppl) ◽  
pp. e282-e282
Author(s):  
Orawan Suppramote ◽  
Prapatsara Pongpunpisand ◽  
Kanlaya Ladkam ◽  
Somkiat Rujirawat
Keyword(s):  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Scoring System ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Cancer Type ◽  
Hypersensitivity Reactions ◽  
Risk Patients ◽  
Carboplatin Hypersensitivity

e282 Background: Hypersentitivity reactions (HSRs) from carboplatin are high incidence and most severity in Chulabhorn hospital. These reactions are associated with several causes including patient factors and experience in drug used. A reliable and valid tool for evaluated risk of HSRs before started carboplatin infusion should lead to prevent or decrease severity of the reactions. We innovated risk score to screen patient at high risk of HSRs. Methods: From October 2013 to September 2014, all cancer patients who received carboplatin in Chulabhorn hospital were included. A retrospective study design to developed risk scoring system for prediction of patients at high risk of carboplatin hypersensitivity called “Hypersensitivity risk score”. The hypersensitivity risk score was calculated for all patients receiving carboplatin and data for carboplatin hypersensitivity were obtained from medical records. Expected and observed HSRs were analyzed by using receiver operating characteristic (ROC) curve. Results: Seventy-three cancer patients received carboplatin and five (7%) patients had HSRs. Our scoring algorithm based on cancer type, number of carboplatin retreatment, duration between each retreatment, and number of carboplatin infusions prior to first reaction. All significant predictors were weighted into points and categorized to risk group which ranged from 0 to 8 . The ROC analysis for hypersensitivity risk score indicated good predictive accuracy with an area under the curve of 0.96 (95 %CI: 0.91-1.00). Data showed high sensitivity (80%) and specificity (94.85%) for a risk score cut-off of 4. The hypersensitivity risk score clearly differentiated the low (0-1), intermediate (2-3) and intermediate-high (4-5) and high (6-8) risk patients. Conclusions: The hypersensitivity risk score is a simple scoring system with high predictive value and differentiates low versus high risk patients. This score should be used for screen high risk of hypersensitivity reactions in patients receiving carboplatin.

Predictors of thromboprophylaxis in hospitalised medical patients

2015 ◽  
Vol 113 (05) ◽  
pp. 1127-1134 ◽  
Author(s):  
David Spirk ◽  
Mathieu Nendaz ◽  
Drahomir Aujesky ◽  
Daniel Hayoz ◽  
Jürg H. Beer ◽  
...  
Keyword(s):  
Cohort Study ◽  
Venous Thromboembolism ◽  
High Risk ◽  
Risk Score ◽  
Low Risk ◽  
Medical Patients ◽  
Clinical Factors ◽  
Thromboembolic Risk ◽  
Factors Associated ◽  
Risk Patients

summaryBoth, underuse and overuse of thromboprophylaxis in hospitalised medical patients is common. We aimed to explore clinical factors associated with the use of pharmacological or mechanical thromboprophylaxis in acutely ill medical patients at high (Geneva Risk Score ≥ 3 points) vs low (Geneva Risk Score < 3 points) risk of venous thromboembolism. Overall, 1,478 hospitalised medical patients from eight large Swiss hospitals were enrolled in the prospective Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE) cohort study. The study is registered on ClinicalTrials. gov, number NCT01277536. Thromboprophylaxis increased stepwise with increasing Geneva Risk Score (p< 0.001). Among the 962 high-risk patients, 366 (38 %) received no thromboprophylaxis; cancer-associated thrombocytopenia (OR 4.78, 95 % CI 2.75–8.31, p< 0.001), active bleeding on admission (OR 2.88, 95 % CI 1.69–4.92, p< 0.001), and thrombocytopenia without cancer (OR 2.54, 95 % CI 1.31–4.95, p=0.006) were independently associated with the absence of prophylaxis. The use of thromboprophylaxis declined with increasing severity of thrombocytopenia (p=0.001). Among the 516 low-risk patients, 245 (48 %) received thromboprophylaxis; none of the investigated clinical factors predicted its use. In conclusion, in acutely ill medical patients, bleeding and thrombocytopenia were the most important factors for the absence of thromboprophylaxis among highrisk patients. The use of thromboprophylaxis among low-risk patients was inconsistent, without clearly identifiable predictors, and should be addressed in further research.

scholarly journals Circular RNA FUNDC1 improves prediction of stroke associated infection in acute ischemic stroke patients with high risk

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Lei Zuo ◽  
Cai Li ◽  
Juan Zu ◽  
Honghong Yao ◽  
Fuling Yan
Keyword(s):  
Ischemic Stroke ◽  
High Risk ◽  
Acute Ischemic Stroke ◽  
Risk Model ◽  
Area Under The Curve ◽  
Preventive Treatment ◽  
Roc Curves ◽  
Circular Rna ◽  
Diagnosis And Prognosis ◽  
Sensitivity Specificity

Abstract Identifying those patients who were at high risk of stroke associated infection (SAI) for preventive antibiotic therapy was imperative for patients’ benefits, thus improving prediction of SAI was critical for all acute ischemic stroke (AIS) patients. Circular RNA FUNDC1 (circFUNDC1) has been reported to be the diagnosis and prognosis biomarker of AIS. Therefore, the present study aimed to figure out whether circFUNDC1 could be the potential predictor of SAI that could help to guide preventive treatment. In total, 68 patients were included in the study, 26 of which had infection and 42 without. Copy number of circFUNDC1 in plasma were quantified by quantitative real-time polymerase chain reaction (qPCR). Platelet spike-in experiment and correlation analysis were conducted to explore possible origins of circFUNDC1 in plasma. A significantly elevated level of circFUNDC1 was found in SAI patients compared with not infected AIS patients (P=0.0258). Receiver operating characteristic (ROC) curves demonstrated the prediction significance of circFUNDC1, with the area under the curve (AUC) at 0.6612 and sensitivity, specificity at 69.23%, 61.90% respectively in predicting SAI. Then, when adding circFUNDC1 in the risk model, the AUC increased from 0.7971 in model A to 0.8038 in model B. Additionally, positive correlation was observed between circFUNDC1 level and neutrophils counts. WBC and neutrophil ratios were significantly elevated in SAI patients compared with non-SAI patients. Therefore, circFUNDC1 could be used to construct a risk model for the prediction of SAI that is beneficial for AIS patients’ preventive treatment.

scholarly journals Diagnostic accuracy and value of chromosomal microarray analysis for chromosomal abnormalities in prenatal detection: a prospective clinical study

2020 ◽  
Author(s):  
Hailong Huang ◽  
Yan Wang ◽  
Min Zhang ◽  
Na Lin ◽  
Gang An ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Microarray Analysis ◽  
Operating Characteristic ◽  
Chromosomal Abnormalities ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Chromosomal Microarray ◽  
Prospective Clinical Study ◽  
Chromosomal Microarray Analysis ◽  
Success Rates

Abstract Background Chromosomal microarray analysis (CMA) has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. The aim of this study was to compare the accuracy and diagnostic value of CMA and karyotyping on chromosomal abnormalities in Fujian province of South China. Methods In the study, 410 samples were obtained from pregnant women between March 2015 and December 2016, including 3 villus (0.73%, 3/410), 296 amniotic fluid (72.20%, 296/410), and 111 umbilical cord blood (27.07%, 111/410). Each sample was screening for chromosomal abnormalities by both using CMA and karyotyping. Results The success rates of CMA and karyotyping were 100% (410/410) and 99.27% (407/410), respectively. 61 (14.88%, 61/410) samples were presented with chromosomal abnormalities using CMA, whereas 47 (11.46%, 47/410) samples were shown with chromosomal abnormalities using karyotyping. 31 (7.56%, 31/410) samples with normal karyotypes were found to have chromosomal abnormalities using CMA. Receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of CMA on the diagnosis of chromosomal abnormalities was 0.93, with 90.68% sensitivity and 94.40% specificity. The AUC of karyotyping on the diagnosis of chromosomal abnormalities was 0.90, with 87.56% sensitivity and 91.22% specificity. Conclusions Our data demonstrated that CMA has a better diagnostic value for screening chromosomal abnormalities, especially for pregnant women with normal karyotypes.

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