scholarly journals Differentiating T1a–T1b from T2 in gastric cancer lesions with three different measurement approaches based on contrast-enhanced T1W imaging at 3.0 T

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuan Yuan ◽  
Shengnan Ren ◽  
Tiegong Wang ◽  
Fu Shen ◽  
Qiang Hao ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Clinical Benefit ◽  
Predictive Value ◽  
Positive Likelihood Ratio ◽  
Roc Curves ◽  
Maximum Area ◽  
T Stage ◽  
Sensitivity Specificity ◽  
Area And Volume

Abstract Background To explore the diagnostic value of three different measurement approaches in differentiating T1a–T1b from T2 gastric cancer (GC) lesions. Methods A total of 95 consecutive patients with T1a–T2 stage of GC who performed preoperative MRI were retrospectively enrolled between January 2017 and November 2020. The parameters MRI T stage (subjective evaluation), thickness, maximum area and volume of the lesions were evaluated by two radiologists. Specific indicators including AUC, optimal cutoff, sensitivity, specificity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV) and negative predictive value (NPV) of MRI T stage, thickness, maximum area and volume for differentiating T1a–T1b from T2 stage lesions were calculated. The ROC curves were compared by the Delong test. Decision curve analysis (DCA) was used to evaluate the clinical benefit. Results The ROC curves for thickness (AUC = 0.926), maximum area (AUC = 0.902) and volume (AUC = 0.897) were all significantly better than those of the MRI T stage (AUC = 0.807) in differentiating T1a–T1b from T2 lesions, with p values of 0.004, 0.034 and 0.041, respectively. The values corresponding to the thickness (including AUC, sensitivity, specificity, accuracy, PPV, NPV, PLR and NLR) were all higher than those corresponding to the MRI T stage, maximum area and volume. The DCA curves indicated that the parameter thickness could provide the highest clinical benefit if the threshold probability was above 35%. Conclusions Thickness may provide an efficient approach to rapidly distinguish T1a–T1b from T2 stage GC lesions.

scholarly journals Differentiating T1a-T1b from T2 in Gastric Cancer Lesions with Three Different Measurement Approaches Based on Contrast-enhanced T1W Imaging at 3.0 Tesla

2021 ◽  
Author(s):  
Yuan Yuan ◽  
Shengnan Ren ◽  
Tiegong Wang ◽  
Fu Shen ◽  
Qiang Hao ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Clinical Benefit ◽  
Predictive Value ◽  
Positive Likelihood Ratio ◽  
Roc Curves ◽  
Maximum Area ◽  
T Stage ◽  
Sensitivity Specificity ◽  
Area And Volume

Abstract Background To explore the diagnostic value of three different measurement approaches in differentiating T1a-T1b from T2 gastric cancer (GC) lesions. Methods A total of 95 consecutive patients who performed preoperative MRI with T1a-T2 stage were retrospectively enrolled between January 2017 and November 2020. The parameters MRI T stage (subjective evaluation), thickness, maximum area and volume of the lesions were evaluated by two radiologists. Specific indices including AUC, optimal cutoff (if required), sensitivity, specificity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV) and negative predictive value (NPV) of MRI T stage, thickness, maximum area and volume for differentiating T1a-T1b from T2 staged lesions were calculated. The ROC curves were compared by the Delong test. Decision curve analysis (DCA) was used to evaluate the clinical benefit. Results The ROC curves for thickness (AUC = 0.926), maximum area (AUC = 0.902) and volume (AUC = 0.897) were all significantly better than those of the MRI T stage (AUC = 0.807) in differentiating T1a-T1b from T2 lesions, with p values of 0.004, 0.034 and 0.041, respectively. The values corresponding to the thickness (including AUC, sensitivity, specificity, accuracy, PPV, NPV, PLR and NLR) were all higher than those corresponding to the MRI T stage, maximum area and volume. The DCA curves indicated that the parameter thickness could provide the highest clinical benefit if the threshold probability was above 35%. Conclusions Thickness may provide an efficient approach to rapidly distinguish T1a-T1b from T2 staged GC lesions.

scholarly journals Factors Affecting the Accuracy of Endoscopic Ultrasonography in the Diagnosis of Early Gastric Cancer Invasion Depth: A Meta-analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Ding Shi ◽  
Xiao-xia Xi
Keyword(s):  
Gastric Cancer ◽  
Early Gastric Cancer ◽  
Likelihood Ratio ◽  
Endoscopic Ultrasonography ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Value ◽  
Depth Of Invasion ◽  
Invasion Depth ◽  
Sensitivity Specificity

Background. Endoscopic ultrasonography (EUS) is the first imaging modality for investigating the depth of invasion in early gastric cancer (EGC). However, there is presently no consensus on the accuracy of EUS in diagnosing the invasion depth of EGC. Aim. This study is aimed at systematically evaluating the accuracy of EUS in diagnosing the invasion depth of EGC and its affecting factors. Methods. The literatures were identified by searching PubMed, SpringerLink, Cochrane Library, Web of Science, Nature, and Karger knowledge databases. Two researchers extracted the data from the literature and reconstructed these in 2×2 tables. The Meta-DiSc software was used to evaluate the overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic advantage ratio, and 95% confidence interval (CI). The SROC was drawn, and the area under the curve (AUC) was calculated to evaluate the diagnostic value. Results. A total of 17 articles were selected, which included 4525 cases of lesions. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic dominance ratio, and 95% CI of EUS for diagnosing EGC was 0.87 (95% CI: 0.86-0.88), 0.67 (95% CI: 0.65-0.70), 2.90 (95% CI: 2.25-3.75), 0.17 (95% CI: 0.13-0.23), and 18.25 (95% CI: 12.61-26.39), respectively. The overall overstaging rate of mucosa/submucosa 1 (M/SM1) and SM by EUS was 13.31% and 32.8%, respectively, while the overall understaging rate of SM was 29.7%. The total misdiagnosis rates for EUS were as follows: 30.4% for lesions≥2 cm and 20.9% for lesions<2 cm, 27.7% for ulcerative lesions and 21.4% for nonulcerative lesions, and 22% for differentiated lesions and 26.9% for undifferentiated lesions. Conclusion. EUS has a moderate diagnostic value for the depth of invasion of EGC. The shape, size, and differentiation of lesions might be the main factors that affect the accuracy of EUS in diagnosing EGC.

Interpretations of the dial test should be reconsidered. A diagnostic accuracy study reporting sensitivity, specificity, predictive values and likelihood ratios

2018 ◽  
Vol 3 (4) ◽  
pp. 198-204
Author(s):  
Richard Norris ◽  
Christian Kopkow ◽  
Michael James McNicholas
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Knee Ligament ◽  
Predictive Values ◽  
Medial Knee ◽  
Sensitivity Specificity ◽  
Dial Test

ObjectivesTo determine the accuracy of the dial test, used alone and in combination with additional clinical tests, in the diagnosis of an isolated posterolateral corner (PLC) injury, combined PLC-posterior cruciate ligament (PCL) injury or medial knee injury.MethodsA retrospective analysis of consecutive patients who underwent arthroscopic and/or open knee ligament reconstruction surgery was conducted. The dial test was performed in an outpatient’s clinic as part of a routine knee examination. Examination under anaesthetic and intraoperative findings were used as the reference standard test to determine the diagnostic accuracy of the dial test used alone and in combination with other PCL and medial knee tests. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR−) were calculated with corresponding 95% CI.ResultsData from 87 patients were available and included in the data analysis. For an isolated PLC injury, the dial test sensitivity and specificity were 0.20 (95% CI 0.08 to 0.39) and 1.00 (95% CI 0.92 to 1.00). The PPV and NPV were 1.00 (95% CI 0.52 to 1.00) and 0.70 (95% CI 0.59 to 0.80). LR+ and LR− of the dial test detecting isolated PLC injury were infinity (95% CI calculation not possible, infinity) and 0.80 (95% CI 0.41 to 1.57). The diagnostic accuracy of the dial test, when used alone and in combination with other PCL and medial knee tests, was also calculated for combined PLC-PCL and medial knee injuries.ConclusionA negative dial test at 30° of knee flexion can rule out a PLC injury, while a test that is positive at 30° and negative at 90° indicates a PLC injury, without concomitant injury to the PCL or medial knee ligaments. A positive test at both 30° and 90° can indicate isolated PLC, combined PLC-PCL or medial ligament injuries, and other knee examination findings are required to differentially diagnose these injury patterns.Level of evidenceII.

scholarly journals Artificial Intelligence in Gastric Cancer: Identifying Gastric Cancer Using Endoscopic Images with Convolutional Neural Network

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5253
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Bruno Andreas Walther ◽  
Ming-Chin Lin ◽  
Yu-Chuan (Jack) Li
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Work Load ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Gastric cancer (GC) is one of the most newly diagnosed cancers and the fifth leading cause of death globally. Identification of early gastric cancer (EGC) can ensure quick treatment and reduce significant mortality. Therefore, we aimed to conduct a systematic review with a meta-analysis of current literature to evaluate the performance of the CNN model in detecting EGC. We conducted a systematic search in the online databases (e.g., PubMed, Embase, and Web of Science) for all relevant original studies on the subject of CNN in EGC published between January 1, 2010, and March 26, 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 was used to assess the risk of bias. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Moreover, a summary receiver operating characteristic curve (SROC) was plotted. Of the 171 studies retrieved, 15 studies met inclusion criteria. The application of the CNN model in the diagnosis of EGC achieved a SROC of 0.95, with corresponding sensitivity of 0.89 (0.88–0.89), and specificity of 0.89 (0.89–0.90). Pooled sensitivity and specificity for experts endoscopists were 0.77 (0.76–0.78), and 0.92 (0.91–0.93), respectively. However, the overall SROC for the CNN model and expert endoscopists was 0.95 and 0.90. The findings of this comprehensive study show that CNN model exhibited comparable performance to endoscopists in the diagnosis of EGC using digital endoscopy images. Given its scalability, the CNN model could enhance the performance of endoscopists to correctly stratify EGC patients and reduce work load.

scholarly journals Evaluation of the Characteristics of the Enzyme-Linked Immunospot Assay for Diagnosis of Active Tuberculosis in China

2015 ◽  
Vol 22 (5) ◽  
pp. 510-515 ◽  
Author(s):  
Linchuan Wang ◽  
Yan Yu ◽  
Wei Chen ◽  
Jin Feng ◽  
Jinyuan Wang ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Likelihood Ratio ◽  
Roc Curve ◽  
Predictive Value ◽  
Extrapulmonary Tuberculosis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Median Number ◽  
Active Tuberculosis ◽  
Sensitivity Specificity

ABSTRACTThe purpose of this study was to evaluate the characteristics of the T-SPOT.TB test for the diagnosis of active tuberculosis (ATB) and to distinguish ATB from other diseases using a receiver operating characteristic (ROC) curve. A total of 535 patients with suspected active tuberculosis were enrolled in the study and divided into ATB and nonactive tuberculosis (NATB) groups, as well as pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB) subgroups. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio of the T-SPOT.TB test for the diagnosis of ATB were 84.95%, 85.12%, 82.94%, 86.93%, 5.71, and 0.18, respectively. The median number of spot-forming cells (SFCs) in the ATB group was higher than that in the NATB group (71 versus 1;P< 0.0001). The sensitivities in the PTB and EPTB subgroups were 92.31% and 81.77%. The areas under the curve (AUC) for the diagnosis of ATB using the T-SPOT.TB, early secreted antigenic target 6 (ESAT-6), and culture filtrate protein 10 (CFP-10) were 0.906, 0.884, and 0.877, respectively. A cutoff of 42.5 SFCs for ATB yielded a positive predictive value of 100%. Our study shows that the T-SPOT.TB test is useful for the diagnosis of ATB. Utilizing an ROC curve to select an appropriate cutoff made it possible to discriminate ATB from NATB.

scholarly journals The accuracy of modified risk malignancy index (RMI) in predicting malignancy of epithelial type ovarian cancer

2019 ◽  
pp. 228-232
Author(s):  
Esfi Triana ◽  
Defrin Dr. ◽  
Joserizal Serudji ◽  
Adriswan Dr.
Keyword(s):  
Likelihood Ratio ◽  
Predictive Value ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Ovarian Tumour ◽  
Scoring Method ◽  
Chi Square ◽  
Risk Of Malignancy ◽  
Risk Of Malignancy Index ◽  
Sensitivity Specificity

Abstract Objective:To investigate the accuracy of modified Risk of Malignancy Index (RMI) in predicting malignancy of epithelial type ovarian tumour. Method: This research was comparative research using cross-sectional study design, which compared RMI modification and RMI method in predicting malignancy of epithelial type ovarian tumour. The sampling technique was consecutive sampling. This research was conducted on October 2017 until samples were fulfilled in Obstetrics and Gynecology Division of RSUP Dr. M. Djamil and Laboratory of RSUP Dr. M Djamil in Padang. Chi-square test was used to compare specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR, and accuracy of RMI modification and RMI with 95% CI (p≤0,05). Results: A total of 61 subjects were recruited in this study. Sensitivity, specificity, PPV, NPV, PLR, NLR, and accuracy RMI modification scoring was 90.5%, 82.5%, 73.1%, 94.3%, 5.1, 0.1, dan 85.2%. Sensitivity, specificity, PPV, NPV, PLR, NLR, and accuracy RMI scoring was 66.7%, 70%, 53.8%, 80%, 2.2, 0.4, and 70% Conclusions:Modified RMI scoring method was more accurate in predicting the malignancy of ovarian type epithelial tumours than RMI. Keywords: CA125, malignancy, ovarian tumor,pelvic mass, RMI,   Abstrak Tujuan: Mengetahui akurasi Risk of Malignancy Index (RMI) dalam prediksi keganasan tumor ovarium tipe epitel.  Metode: Penelitian ini merupakan penelitian komparatif dengan desain penelitian potong lintang yang membandingkan metode RMI modifikasi dan RMI dalam prediksi keganasan tumor ovarium tipe epitel. Jumlah sampel sebanyak 61 orang. Teknik pengambilan sampel berurutan. Penelitian di mulai pada bulan Oktober 2017 hingga jumlah sampel terpenuhi di Departemen Obstetri dan Ginekologi RSUP Dr. M Djamil dan Laboratorium RSUP Dr. M Djamil Padang. Untuk membandingkan spesifisitas, sensitivitas, nilai duga positif (NDP), nilai duga negatif (NDN), rasio kemungkinan positif (RKP), rasio kemungkinan negatif (RKN), dan akurasi RMI modifikasi dan RMI digunakan uji chi-square dengan 99% CI (p≤0,01). Hasil: Sensitivitas, spesifisitas, NDP, NDN, RKP, RKN, dan akurasi skoring RMI modifikasi adalah 90,5%, 82,5%, 73,1%, 94,3%, 5,1, 0,1, dan 85,2%. Sensitivitas, spesifisitas, NDP, NDN, RKP, RKN, dan akurasi skoring RMI adalah 66,7%, 70%, 53,8%, 80%, 2,2, 0,4, dan 70%. Kesimpulan: Metode skoring RMI modifikasi lebih akurat dalam memprediksi keganasan tumor ovarium tipe epitel dibandingkan RMI. Kata kunci: CA125, keganasan, massapelvik, RMI, tumor ovarium

scholarly journals Exploration of the Efficiency of Radiomics Applied to Left Ventricular Tomograms Obtained From D-SPECT MPI for the Auxiliary Diagnosis of Myocardial Ischemia in CAD

2021 ◽  
Author(s):  
Junpeng Wang ◽  
Xin Fan ◽  
Shanshan Qin ◽  
Han Zhang ◽  
Fei Yu
Keyword(s):  
Myocardial Ischemia ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Roc Curves ◽  
Left Ventricular ◽  
Operating Characteristics ◽  
Evaluation Indexes ◽  
Spect Mpi

Abstract Purpose: To explore the feasibility and efficacy of radiomics with left ventricular tomograms obtained from D-SPECT myocardial perfusion imaging (MPI) for auxiliary diagnosis of myocardial ischemia in coronary artery disease (CAD).Methods: The images of 103 patients with CAD myocardial ischemia between September 2020 and April 2021 were retrospectively selected. After information desensitization processing, format conversion, annotation using the Labelme tool on an open-source platform, lesion classification, and establishment of a database, the images were cropped for analysis. The ResNet18 model was used to automate two steps (classification and segmentation) with five randomization, training and validation steps. Sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive predictive value, negative predictive value, Youden’s index, agreement rate, and kappa value were calculated as evaluation indexes of the classification results for each training-validation step; then, receiver operating characteristics (ROC) curves were drawn, and the areas under the curve (AUCs) were calculated. The Dice coefficient, intersection over union, and Hausdorff distance were calculated as evaluation indexes of the segmentation results for each training-validation step; then, the predicted images were exported.Results: Under the existing conditions, the radiomics model can distinguish myocardial ischemia quite accurately, with AUCs all exceeding 0.95, and predict the areas of myocardial ischemia quite accurately; all evaluated indexes were close to those of the gold standard.Conclusion: Radiomics can be feasibly applied to left ventricular tomograms obtained from D-SPECT MPI for auxiliary diagnosis, with quite good results. Patients may benefit from this approach as technology evolves and associated software is developed.

scholarly journals Highly Accurate and Reproducible Diagnosis of Peanut Allergy Using Epitope Mapping

2020 ◽  
Author(s):  
Paul Kearney ◽  
Robert Getts ◽  
Clive Hayward ◽  
David Luta ◽  
Alex Porter ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Test Performance ◽  
Predictive Value ◽  
Peanut Allergy ◽  
Skin Prick Testing ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Component Testing ◽  
The Subject ◽  
Sensitivity Specificity

AbstractBackgroundMisdiagnosis of peanut allergy is a significant clinical challenge. Here, a novel diagnostic blood-based test using a Bead-Based Epitope Assay (“peanut BBEA”) has been developed on the LEAP cohort and then independently validated on the CoFAR2 and POISED cohorts.MethodsDevelopment of the peanut BBEA followed the National Academy of Medicine’s established guidelines with discovery performed on 133 subjects from the non-interventional arm of the LEAP trial and an independent validation performed on 81 subjects from the CoFAR2 study and 84 subjects from the POISED study. All subject samples were analyzed using the BBEA methodology. The peanut BBEA test measures levels of two Ara h 2 epitopes and compares their combination to a pre=specified threshold. If the combination of the two epitope levels is at or below the threshold, then the subject is ruled “Not Allergic”, otherwise the subject is ruled “Allergic”.All allergic diagnoses were OFC confirmed and subjects’ ages were 7-55 years.ResultsIn validation on the CoFAR2 and POISED cohorts, the peanut BBEA test had a combined sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio and accuracy of 91%, 95%, 95%, 91%, 18.2, 0.09 and 93%, respectively.ConclusionThe peanut BBEA test performance in validation demonstrated overall high accuracy and compared very favorably with existing diagnostic tests for peanut allergy including skin prick testing, peanut sIgE and peanut component testing.

scholarly journals Endtidal carbonmonoxide and carboxyhemoglobin for prediction of significant hyperbilirubinemia in healthy Indian neonates >35 weeks of gestation

2020 ◽  
Vol 7 (6) ◽  
pp. 1225
Author(s):  
Gokul Krishnan R. ◽  
Mangalabharathi S. ◽  
Mohammed Sajjid ◽  
Ramya S.
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Neonatal Period ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Likelihood Ratios ◽  
Early Neonatal Period ◽  
Sensitivity Specificity

Background: Endtidalcarbonmonoxide (ETCOc) and Carboxyhemoglobin (COHB) levels correlate well to bilirubin production and an availability of non-invasive point of care (POC) device in predicting significant hyperbilirubinemia is of great advantage when compared to measurement of serum bilirubin. Objective of the study is to measure a value of ETCOc and COHB in the early neonatal period for the prediction of significant hyperbilirubinemia.Methods: This was the descriptive Cross Sectional Study. ETCOc and COHB were measured 12th hourly for 72 hours followed by TSB in whom the TCB was >14mg/dl. Neonates were classified as jaundiced whose TSB values were in phototherapy range as per AAP Recommendations. Receiver Operative Curves (ROC) were created by appropriate statistical software for ETCOc and COHb to predict significant hyperbilirubinemia. The Sensitivity, Specificity, Positive predictive value, Negative predictive value and likelihood ratios of each was determined and the correlation between ETCOc and COHb levels, ETCOc and TCB, COHB and TCB at different hours of age was evaluated.Results: Among the total 320 infants, 156 of them developed significant hyperbilirubinemia. The ETCOc and COHB level at 60 hours of age was the most predictive of significant hyperbilirubinemia by ROC analysis. ETCOc cut-off of 1.65 ppm at 60 hours of age has a sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of 84.6%, 80.5%, 80.5% and 84.6%, 4.33 and 0.19. COHB cut-off of 1.32 ppm at 60 hours of age has a sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of 84.6%, 81%, 80% and 84.2%, 4.34 and 0.19.ETCOc had a maximum correlation with COHB at 48 hours of age.Conclusions: An increased level of Endtidalcarbonmonoxide and Carboxyhemoglobin in the early neonatal period is useful as a screening test for prediction of significant hyperbilirubinemia.

scholarly journals The Potential Diagnostic Accuracy of Circulating MicroRNAs for Leukemia: A Meta-Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110119
Author(s):  
Wen-Ting Zhang ◽  
Guo-Xun Zhang ◽  
Shuai-Shuai Gao
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Circulating Micrornas ◽  
Sensitivity Specificity

Background: Leukemia is a common malignant disease in the human blood system. Many researchers have proposed circulating microRNAs as biomarkers for the diagnosis of leukemia. We conducted a meta-analysis to evaluate the diagnostic accuracy of circulating miRNAs in the diagnosis of leukemia. Methods: A comprehensive literature search (updated to October 13, 2020) in PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure (CNKI) was performed to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for diagnosing leukemia were pooled for both overall and subgroup analysis. The meta-regression and subgroup analysis were performed to explore heterogeneity and Deeks’ funnel plot was used to assess publication bias. Results: 49 studies from 22 publications with a total of 3,489 leukemia patients and 2,756 healthy controls were included in this meta-analysis. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve were 0.83, 0.92, 10.8, 0.18, 59 and 0.94, respectively. Subgroup analysis shows that the microRNA clusters of plasma type could carry out a better diagnostic accuracy of leukemia patients. In addition, publication bias was not found. Conclusions: Circulating microRNAs can be used as a promising noninvasive biomarker in the early diagnosis of leukemia.

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