Diagnostic Value of the EZH2 Immunomarker in Malignant Effusion Cytology

2019 ◽  
Vol 64 (3) ◽  
pp. 248-255
Author(s):  
Piao Piao Ang ◽  
Geok Chin Tan ◽  
Norain Karim ◽  
Yin Ping Wong
Keyword(s):  
Cancer Progression ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Metastatic Carcinoma ◽  
Mesothelial Cells ◽  
Roc Curve Analysis ◽  
Resource Limited ◽  
Reactive N ◽  
Economic Constraints

Background: Differentiating reactive mesothelial cells from metastatic carcinoma in effusion cytology is a challenging task. The application of at least 4 monoclonal antibodies including 2 epithelial markers (Ber-EP4, MOC-31, CEA, or B72.3) and 2 mesothelial markers (calretinin, WT-1, CK5/6, or HBME-1) are often useful in this distinction; however, it is not readily available in many resource-limited developing countries. Aberrant immunoexpression of enhancer of zeste homolog 2 (EZH2), a transcriptional repressor involved in cancer progression, is observed widely in various malignancy. In this study, we evaluate the diagnostic value of EZH2 as a single reliable immunomarker for malignancy in effusion samples. Methods: A total of 108 pleural, peritoneal, and pericardial effusions/washings diagnosed as unequivocally reactive (n = 41) and metastatic carcinoma (n = 67) by cytomorphology over 18 months were reviewed. Among the metastatic carcinoma cases, 54 were adenocarcinoma and others were squamous cell carcinoma (n = 1), carcinosarcoma (n = 1), and carcinoma of undefined histological subtypes (n = 11). Cell block sections were immunostained by EZH2 (Cell Marque, USA). The percentages of EZH2-immunolabeled cells over the total cells of interest were calculated. Receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cut-off score to define EZH2 immunopositivity. Results: A threshold of 8% EZH2-immunolabeled cells allows distinction between malignant and reactive mesothelial cells, with 95.5% sensitivity, 100% specificity, 100% positive predictive value, and 93.2% negative predictive value (p < 0.0001). The area under the curve was 0.988. Conclusion: EZH2 is a promising diagnostic biomarker for malignancy in effusion cytology which is inexpensive yet trustworthy and could potentially be used routinely in countries under considerable economic constraints.

scholarly journals PEMERIKSAAN TINGKAT sdLDL SERUM SEBAGAI PETANDA DIAGNOSTIK STENOSIS KORONER (Serum sdLDL Level as A Diagnostic Marker of Coronary Stenosis)

2018 ◽  
Vol 22 (1) ◽  
pp. 9
Author(s):  
Indranila K Samsuria ◽  
Laily Adninta
Keyword(s):  
Predictive Value ◽  
Coronary Stenosis ◽  
Area Under The Curve ◽  
Clinical Pathology ◽  
Diagnostic Value ◽  
T Test ◽  
Cross Sectional ◽  
Increased Risk ◽  
Test Kit ◽  
Vascular Stenosis

Small dense LDL (sdLDL) is the LDL which particles are small and dense, it is pro-atherogenic. Increased levels of serum sdLDL areassociated with an increased risk of coronary stenosis. The aim of this study was to examine the diagnostic value of sd LDL in coronarystenosis. An analytical observational study with cross sectional approach was conducted at the Department of Clinical Pathology, MedicalFaculty of Diponegoro University/Dr. Kariadi Hospital and the Unit of Cardiac diseases during the period of March-October 2013. Thesubjects were 39 patients suspected of suffering a coronary stenosis. The diagnosis of coronary stenosis, degree of stenosis and numberof vascular stenosis was established at the time of cardiac catheterization. SdLDL assessment used a test kit. The statistical analysis usedwere unpaired t-test, Spearman correlation test, ROC analysis and diagnostic test. LDL levels in stenosis subjects, 35.4±9.01 mg/dL weresignificantly higher compared to levels in subjects that had no stenosis, 20.7±7.10 mg/dL (p<0.001; unpaired t-test). Correlation testresults showed a correlation between levels of serum sdLDL with severe degree of stenosis (correlation coefficient -0.64, p <0.001) and amoderate positive correlation between the number of vascular stenosis (Coefficient correlation 0.46; p=0.003; Spearman Correlation’sTest). The area under the curve of ROC was 0.9 (p <0.001). The cut off levels sdLDL were used to detect stenosis. The results showeda sensitivity of 85.2%, specificity of 75%, positive predictive value of 88.5%, negative predictive value of 69.2% and accuracy of 82%.Levels of serum sdLDL were associated with severe to extensive stenosis degree, and showed a good diagnostic value, thus, it can beused for screening to determine the presence of coronary stenosis.

scholarly journals Immunocytochemistry Test of Protein BRAF Expression for Diagnosis of Well Differentiated Thyroid Carcinoma

2018 ◽  
Vol 11 (3) ◽  
pp. 843-849 ◽  
Author(s):  
I. Wayan Sudarsa ◽  
Elvis Deddy Kurniawan Pualillin ◽  
Putu Anda Tusta Adiputra ◽  
Ida Bagus Tjakra Wibawa Manuaba
Keyword(s):  
Positive Predictive Value ◽  
Thyroid Carcinoma ◽  
Negative Predictive Value ◽  
Diagnostic Test ◽  
Predictive Value ◽  
Preoperative Diagnosis ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Differentiated Thyroid Carcinoma ◽  
Inclusion Criteria

Background: Thyroid carcinoma generally has a good prognosis. The main focus of current research on thyroid carcinoma is to increase the accuracy of preoperative diagnosis of thyroid nodules. When the result of fine needle aspiration biopsy (FNAB) is indeterminate, clinicians often have doubts in determining the surgical management. Objective: Protein BRAF expression analysis can help improve the accuracy of FNAB and optimize the management of differentiated thyroid carcinoma. Methods: This study is a diagnostic test performed from October 2016 at Sanglah General Hospital with 38 patients as subjects who fulfilled the inclusion criteria. Data is being presented in descriptive form before diagnostic test is done to determine sensitivity, specificity, positive predictive value, negative predictive value and the accuracy of immunocytochemistry test for BRAF on indeterminate thyroid nodule. Results: Thirty-eight samples met the inclusion criteria during the study period. Three samples were male (7.9%) and 35 samples (92.1%) were female. The mean age of the sample was 45.21 years (SD ±10.910 years) with ages ranging from 23 to 66 years. Of the 12 samples undergoing isthmolobectomy, 7 samples (58.4%) were determined to be malignant from histopathological results. The sensitivity value of BRAF immunocytochemistry test is 45.45% with a specificity value of 81.25%, a positive predictive value of 76.92%, a negative predictive value of 52% and an accuracy of 60.50%. Analysis of the receiver operator (ROC) curve shows the area under the curve (AUC) of 63.4% with a confidence interval of 45.5–81.2%. Conclusion: Immunocytochemistry BRAF test have a reliable diagnostic value and can be taken into consideration in the preoperative diagnosis of thyroid malignancies.

scholarly journals Using Circ-ANAPC7 as a Novel Type of Biomarker in the Monitoring of Acute Myeloid Leukemia

2021 ◽  
pp. 1-7
Author(s):  
Ying Shen ◽  
Yachun Jia ◽  
Ru Zhang ◽  
Hongli Chen ◽  
Yuandong Feng ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Roc Curve ◽  
Myeloid Leukemia ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Circular Rnas ◽  
Transcriptional Level ◽  
Roc Curve Analysis ◽  
Cell Counts ◽  
Acute Myeloid

<b><i>Introduction:</i></b> Circular RNAs (circRNAs) are a novel class of RNAs which occupy gene expression at the transcriptional or post-transcriptional level, involve in many physiological processes, and participate in many diseases, especially in cancer. Our previous study showed 1 altered circRNA named circ-anaphase promoting complex subunit 7 (ANAPC7) that was upregulated in acute myeloid leukemia (AML). To further clear the expression and clinical significance of circ-ANAPC7, we enlarged the sample size and illuminated the diagnostic and monitoring value of circ-ANAPC7 in AML. <b><i>Methods:</i></b> Real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was supposed to confirm the expression of circ-ANAPC7 of AML patients. We assessed the correlation of circ-ANAPC7 and clinical variables using the Spearman correlation test. The receiver operating characteristic (ROC) curve was carried out to evaluate the diagnostic value. <b><i>Results:</i></b> Circ-ANAPC7 was first found to be upregulated in AML, and its expression was correlated to white blood cell counts in peripheral blood and blast percentage in bone marrow. ROC curve analysis revealed that circ-ANAPC7 has a significant value of auxiliary AML diagnosis (area under the curve = 0.915, <i>p</i> &#x3c; 0.001). Furthermore, the expression level of circ-ANAPC7 was changed accompanied with disease condition transformation. <b><i>Conclusion:</i></b> Circ-ANAPC7 was upregulated in newly diagnosed and relapsed AML. It may serve as potential biomarkers for AML patient’s diagnosis and monitoring.

scholarly journals Predictive value of qSOFA score for death in emergency department resuscitation room among adult trauma patients:a retrospective study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenjuan Huang ◽  
Peng Yang ◽  
Feng Xu ◽  
Du Chen
Keyword(s):  
Emergency Department ◽  
Predictive Value ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Study Endpoint ◽  
Trauma Patients ◽  
Roc Curve Analysis ◽  
Resuscitation Room ◽  
Failure Assessment ◽  
Qsofa Score

Abstract Background To explore the predictive value of the quick Sequential Organ Failure Assessment (qSOFA) score for death in the emergency department (ED) resuscitation room among adult trauma patients. Methods During the period November 1, 2016 to November 30, 2019, data was retrospectively collected of adult trauma patients triaged to the ED resuscitation room in the First Affiliated Hospital of Soochow University. Death occurring in the ED resuscitation room was the study endpoint. Univariate and multivariate analyses were performed to explore the association between qSOFA score and death. Receiver operating characteristic (ROC) curve analysis was also performed for death. Results A total of 1739 trauma victims were admitted, including 1695 survivors and 44 non-survivors. The death proportion raised with qSOFA score: 0.60% for qSOFA = 0, 3.28% for qSOFA = 1, 12.06% for qSOFA = 2, and 15.38% for qSOFA = 3, p < 0.001. Subgroup of qSOFA = 0 was used as a reference. In univariate analysis, crude OR for death with qSOFA = 1 was 5.65 [95% CI 2.25 to 14.24, p < 0.001], qSOFA = 2 was 22.85 [95% CI 8.84 to 59.04, p < 0.001], and qSOFA = 3 was 30.30 [95% CI 5.50 to 167.05, p < 0.001]. In multivariate analysis, with an adjusted OR (aOR) of 2.87 (95% CI 0.84 to 9.87, p = 0.094) for qSOFA = 1, aOR 6.80 (95% CI 1.79 to 25.90, p = 0.005) for qSOFA = 2, and aOR 24.42 (95% CI 3.67 to 162.27, p = 0.001) for qSOFA = 3. The Area Under the Curve (AUC) for predicting death in the ED resuscitation room among trauma patients was 0.78 [95% CI, 0.72–0.85]. Conclusions The qSOFA score can assess the severity of emergency trauma patients and has good predictive value for death in the ED resuscitation room.

scholarly journals Diagnostic Value of the13C Methacetin Breath Test in Various Stages of Chronic Liver Disease

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Hamizah Razlan ◽  
Nurhayaty Muhamad Marzuki ◽  
Mei-Ling Sharon Tai ◽  
Azhar-Shah Shamsul ◽  
Tze-Zen Ong ◽  
...  
Keyword(s):  
Liver Disease ◽  
Liver Fibrosis ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Breath Test ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Cross Sectional Study ◽  
Chronic Liver ◽  
Cross Sectional

The accuracy of the13C-methacetin breath test (13C-MBT) in differentiating between various stages of liver disease is not clear. A cross-sectional study of Asian patients was conducted to examine the predictive value of the13C-MBT in various stages of chronic liver diseases. Diagnostic accuracy of the breath test was determined by sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve analysis. Seventy-seven patients (47 men/30 women, mean age50±16years) were recruited. Forty-seven patients had liver cirrhosis (Child Pugh A = 11, Child Pugh B = 15, and Child Pugh C = 21), 21 had fibrosis, and 9 had chronic inflammation. The sensitivity and positive predictive value for liver fibrosis, cirrhosis (all stages), Child-Pugh A, Child-Pugh B, and Child-Pugh C were 65% and 56%, 89% and 89%, 67% and 42%, 40% and 40%, and 50% and 77%, respectively. Area under curve values for fibrosis was 0.62 (0.39–0.86), whilst that for cirrhosis (all stages) was 0.95 (0.91–0.99). The13C-methacetin breath test has a poor predictive value for liver fibrosis but accurately determines advanced cirrhosis.

Gastric cancer detection using the serum pepsinogen test method

2021 ◽  
pp. 030089162110149
Author(s):  
Dragan Trivanovic ◽  
Stjepko Plestina ◽  
Lorena Honovic ◽  
Renata Dobrila-Dintinjana ◽  
Jelena Vlasic Tanaskovic ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Detection ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Test Method ◽  
Operating Characteristics ◽  
Roc Curve Analysis ◽  
Laboratory Assessment ◽  
Pepsinogen I ◽  
Sensitivity Specificity

Background: Gastric cancer (GC) is the eighth most common cause of cancer deaths in Croatia and one of the most common causes of cancer deaths worldwide. A reliable diagnostic tool for the early detection of GC is essential. Objective: We previously suggested a pepsinogen test method to reduce the mortality from GC by allowing early detection. Here, we report an updated analysis from a prospective single-center clinical study to evaluate the sensitivity and specificity of the pepsinogen test method and to determine whether this test can be used as a part of routine laboratory assessment of high-risk patients. Methods: We present mature data of the pepsinogen test method in the Croatian population after a median follow-up of 36 months. Statistical analyses were performed using a Mann-Whitney U test, multiple logistic regression, and receiver operating characteristics (ROC) to evaluate the predictive power of the assayed biomarkers. Results: Of the 116 patients, 25 patients had GC and 91 demonstrated a nonmalignant pathology based on tissue biopsy. Cutoff values were pepsinogen I ⩽70 and pepsinogen I/II ratio ⩽3.0. Using ROC curve analysis, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were determined to be 87.22%, 78.12%, 90.10%, 71.43%, and 92.86%, respectively, for the diagnosis of GC. The area under the curve was 0.700 (95% confidence interval 0.57–0.83). Conclusion: Pepsinogen tests are valuable for screening a population in need of further diagnosis and could help to avoid unnecessary invasive endoscopic procedures.

scholarly journals Radiomic model for differentiating parotid pleomorphic adenoma from parotid adenolymphoma based on MRI images

2021 ◽  
Author(s):  
Le-le Song ◽  
Shun-jun Chen ◽  
Wang Chen ◽  
Zhan Shi ◽  
Xiao-dong Wang ◽  
...  
Keyword(s):  
Pleomorphic Adenoma ◽  
Predictive Value ◽  
Current Knowledge ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Diagnostic Methods ◽  
Support Vector ◽  
Imaging Data ◽  
Clinical Model

Abstract Background: Distinguishing parotid pleomorphic adenoma (PPA) from parotid adenolymphoma (PA) is important for precision treatment, but there is a lack of readily available diagnostic methods. In this study, we aimed to explore the diagnostic value of radiomic signatures based on magnetic resonance imaging (MRI) for PPA and PA. Methods: The clinical characteristic and imaging data were retrospectively collected from 252 cases (126 cases in the training cohort and 76 patients in the validation cohort) in this study. Radiomic features were extracted from MRI scans, including T1-weighted imaging (T1WI) sequences and T2-weighted imaging (T2WI) sequences. The radiomic features from three sequences (T1WI, T2WI and T1WI combined with T2WI) were selected using univariate analysis, LASSO correlation and Spearman correlation. Then, we built six quantitative radiomic models using the selected features through two machine learning methods (multivariable logistic regression, MLR, and support vector machine, SVM). The performances of the six radiomic models were assessed and the diagnostic efficacies of the ideal T1-2WI radiomic model and the clinical model were compared.Results: The T1-2WI radiomic model using MLR showed optimal discriminatory ability (accuracy = 0.87 and 0.86, F-1 score = 0.88 and 0.86, sensitivity= 0.90 and 0.88, specificity=0.82 and 0.80, positive predictive value=0.86 and 0.84, negative predictive value=0.86 and 0.84 in the training and validation cohorts, respectively) and its calibration was observed to be good (p>0.05). The area under the curve (AUC) of the T1-2WI radiomic model was significantly better than that of the clinical model for both the training (0.95 vs. 0.67, p<0.001) and validation (0.90 vs. 0.68, p=0.001) cohorts.Conclusions: The T1-2WI radiomic model in our study is complementary to the current knowledge of differential diagnosis for PPA and PA.

scholarly journals Radiomic model for differentiating parotid pleomorphic adenoma from parotid adenolymphoma based on MRI images

2020 ◽  
Author(s):  
Le-le Song ◽  
Shun-jun Chen ◽  
Wang Chen ◽  
Zhan Shi ◽  
Xiao-dong Wang ◽  
...  
Keyword(s):  
Pleomorphic Adenoma ◽  
Predictive Value ◽  
Current Knowledge ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Diagnostic Methods ◽  
Support Vector ◽  
Imaging Data ◽  
Clinical Model

Abstract Background: Distinguishing parotid pleomorphic adenoma (PPA) from parotid adenolymphoma (PA) is important for precision treatment, but there is a lack of readily available diagnostic methods. In this study, we aimed to explore the diagnostic value of radiomic signatures based on magnetic resonance imaging (MRI) for PPA and PA. Methods: The clinical characteristic and imaging data were retrospectively collected from 252 cases (126 cases in the training cohort and 76 patients in the validation cohort) in this study. Radiomic features were extracted from MRI scans, including T1-weighted imaging (T1WI) sequences and T2-weighted imaging (T2WI) sequences. The radiomic features from three sequences (T1WI, T2WI and T1WI combined with T2WI) were selected using univariate analysis, LASSO correlation and Spearman correlation. Then, we built six quantitative radiomic models using the selected features through two machine learning methods (multivariable logistic regression, MLR, and support vector machine, SVM). The performances of the six radiomic models were assessed and the diagnostic efficacies of the ideal T1-2WI radiomic model and the clinical model were compared.Results: The T1-2WI radiomic model using MLR showed optimal discriminatory ability (accuracy = 0.87 and 0.86, F-1 score = 0.88 and 0.86, sensitivity= 0.90 and 0.88, specificity=0.82 and 0.80, positive predictive value=0.86 and 0.84, negative predictive value=0.86 and 0.84 in the training and validation cohorts, respectively) and its calibration was observed to be good (p>0.05). The area under the curve (AUC) of the T1-2WI radiomic model was significantly better than that of the clinical model for both the training (0.95 vs. 0.67, p=0.000) and validation (0.90 vs. 0.68, p=0.001) cohorts.Conclusions: The T1-2WI radiomic model in our study is complementary to the current knowledge of differential diagnosis for PPA and PA.

Usefulness of several biomarkers in the management of septic patients: C-reactive protein, procalcitonin, presepsin and mid-regional pro-adrenomedullin

2016 ◽  
Vol 54 (1) ◽  
Author(s):  
Alfredo Enguix-Armada ◽  
Rocío Escobar-Conesa ◽  
Angela García-De La Torre ◽  
María Victoria De La Torre-Prados
Keyword(s):  
Area Under The Curve ◽  
Diagnostic Value ◽  
Apache Ii Score ◽  
C Reactive Protein ◽  
Roc Curve Analysis ◽  
Icu Admission ◽  
Noticeable Increase ◽  
Reactive Protein ◽  
Parametric Statistics ◽  
The Difference

AbstractOur objective is to analyze whether the combination of C-reactive protein (CRP), procalcitonin (PCT), presepsin or SCD14-ST and mid-regional pro-adrenomedullin (MR-proADM) measured in the first 24 h from ICU admission allowing a better management of septic patients (diagnostic and prognostic) both in severe sepsis (SS) and septic shock (SSh).Cohort study of 388 patients admitted in the ICU during 12 months of whom 142 were controls. Biomarkers were measured through immunoluminometric assays in samples of serum or plasma within the first 24 h after admission. Data were evaluated with non-parametric statistics bivariant, ROC curve analysis for diagnostic evaluation and multivariate analyses for survival analysis.In the analyzed cohort, 61.8% of patients were males, mean age: 63 years range (18–90) and 67.8% in controls mean age: 63 years, range (39–91). PCT showed the highest area under the curve (AUC) (0.989) as compared with the rest of biomarkers (p<0.01). PCT also enabled the difference between Gram-positive or Gram-negative bacteria to be determined. The AUCs for CRP (0.922) and presepsin (0.948) showed a similar diagnostic value. In cases of SSh, the AUC of presepsin experienced a noticeable increase (p<0.0001). MR-proADM showed a better prognostic value (p=0.00022) particularly in cases of SSh (p=0.00001) increasing along with the APACHE-II score.PCT, MR-proADM and presepsin are complementary markers that could be of great help in the management of septic patients when they are measured in the first 24 h after ICU admission.

scholarly journals Diagnostic Value of the lncRNA NEAT1 in Peripheral Blood Mononuclear Cells of Patients with Sepsis

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Shuying Huang ◽  
Kejian Qian ◽  
Yuanfang Zhu ◽  
Zikun Huang ◽  
Qing Luo ◽  
...  
Keyword(s):  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Predictive Value ◽  
Mononuclear Cells ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Sepsis Group ◽  
Healthy Controls ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells

Background. This study aims to evaluate the diagnostic value of nuclear-enriched abundant transcript 1 (NEAT1) expression in peripheral blood mononuclear cells (PBMCs) for the early diagnosis of sepsis. Methods. A total of 59 patients with sepsis, 52 noninfectious SIRS patients, and 56 healthy controls were recruited fort this study. The levels of NEAT1 expression in PBMCs were measured using quantitative real-time polymerase chain reaction (qRT-PCR). Results. Compared with healthy controls, NEAT1 expression of PBMCs in sepsis and SIRS groups were significantly increased (3.76 ± 0.71- and 1.64 ± 0.43-fold, resp.) (P<0.01), but NEAT1 levels are significantly lower in the SIRS group than in the sepsis group, and there was no statistical significant relevance between survivors and nonsurvivors in patients with sepsis. NEAT1 with an area under the curve (AUC) of 0.851 (95% CI: 0.812–0.935) indicated sensitivity (67.85%) and specificity (87.27%) for the diagnosis for sepsis, the positive predictive value (PPV) was 83.3%, and the negative predictive value (NPV) was 71.6%. The AUC for NEAT1 in the diagnosis of SIRS versus healthy controls was 0.755 (95% CI: 0.664–0.847), with 69.23% sensitivity and 70.91% specificity, the PPV was 72.3%, and the NPV was 72.49%. Conclusion. Measurement of NEAT1 expression in PBMCs could be considered as a good additive marker for the diagnosis of sepsis.

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