Bivariate Random-effects Model Research Articles

Diagnostic and predictive accuracy of the Clinical Frailty Scale among hospitalised older medical patients: a systematic review and meta-analysis protocol

IntroductionFrailty is a common condition affecting older adults and is associated with increased mortality and adverse outcomes. Identification of older adults at risk of adverse outcomes is central to subsequent...

MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Purpose: Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value. Methods: Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features. Results: Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (>5 cm) (DOR = 5.2, 95% CI [3.0–9.0]), rim arterial enhancement (4.2, 95% CI [1.7–10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8–6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4–15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2–4.4]), multifocality (7.1, 95% CI [2.6–19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5–9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4–94.8%] and 93.3% [74.5–98.5%], respectively). Conclusions: Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.

Diagnostic Accuracy of Ultrasonography for the Assessment of Maxillofacial Fractures: A Meta-analysis.

ABSTRACTObjective:To evaluate the pooled sensitivity and specificity of ultrasonography (USG) in maxillofacial fractures.Materials and Methods:A systematic search was performed in five databases (PubMed, Scopus, CINAHL, Web of Science, Dentistry and Oral Sciences Source) from inception to September 12, 2020. Studies that reported or from which sensitivity and specificity can be calculated and studies published in the English language were included. Conference proceedings, letter to editors, and case reports were excluded. Screening of studies, data extraction, and risk of bias assessment (QUADAS -2) were done separately by two review authors. A bivariate random-effects model was used to calculate the pooled estimates.Results:After the removal of duplicates, 1852 studies were included for screening of title and abstracts. Only 22 studies were included in the quantitative synthesis. The sample size ranged from 6 to 87. The majority of the studies assessed orbit and nasal bones fractures. Only two studies included a comprehensive assessment of facial fractures. The overall sensitivity and specificity values were 0.94 and 0.96, respectively.Conclusion:USG has good diagnostic accuracy for the assessment of fractures of orbit and nasal bones. Clinicians need to consider the advantages and limitations of USG before recommending advanced imaging modalities.

Classification of true progression after radiotherapy of brain metastasis on MRI using artificial intelligence: a systematic review and meta-analysis.

BackgroundClassification of true progression from nonprogression (eg, radiation-necrosis) after stereotactic radiotherapy/radiosurgery of brain metastasis is known to be a challenging diagnostic task on conventional magnetic resonance imaging (MRI). The scope and status of research using artificial intelligence (AI) on classifying true progression are yet unknown.MethodsWe performed a systematic literature search of MEDLINE and EMBASE databases to identify studies that investigated the performance of AI-assisted MRI in classifying true progression after stereotactic radiotherapy/radiosurgery of brain metastasis, published before November 11, 2020. Pooled sensitivity and specificity were calculated using bivariate random-effects modeling. Meta-regression was performed for the identification of factors contributing to the heterogeneity among the studies. We assessed the quality of the studies using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria and a modified version of the radiomics quality score (RQS).ResultsSeven studies were included, with a total of 485 patients and 907 tumors. The pooled sensitivity and specificity were 77% (95% CI, 70–83%) and 74% (64–82%), respectively. All 7 studies used radiomics, and none used deep learning. Several covariates including the proportion of lung cancer as the primary site, MR field strength, and radiomics segmentation slice showed a statistically significant association with the heterogeneity. Study quality was overall favorable in terms of the QUADAS-2 criteria, but not in terms of the RQS.ConclusionThe diagnostic performance of AI-assisted MRI seems yet inadequate to be used reliably in clinical practice. Future studies with improved methodologies and a larger training set are needed.

Systematic review of clinical decision rules used for diagnosing pulmonary embolism in the pediatric opulation

Objective: This review aims to evaluate the diagnostic accuracy of existing, adult clinical decision tools for pulmonary embolism, in the pediatric population.
 Methods: A systematic search and screening of the Pubmed, Embase, CINAHL, and Cochrane databases was done in January 2018. Studies evaluating the diagnostic accuracy of clinical decision tools and/or risk factors and clinical features for pulmonary embolism in the pediatric population were included. The measures of diagnostic accuracy of clinical decision tools were calculated. The pooled sensitivity and specificity of risk factors were calculated using a bivariate random effects model. All included studies were assessed for quality using QUADAS-2.
 Results: Six studies were included: three case-control and three retrospective cohort studies. We found that no standard clinical decision tool for pulmonary embolism has been evaluated in the pediatric population. As well, adult clinical decision tools have low diagnostic utility in pediatrics.
 Conclusion: Adult clinical decision tools should not be used for pediatric patients. There was no single risk factor or clinical feature displaying reliable sensitivity; however, a central venous line, a recent surgery, or the finding of hemoptysis, all have a positive likelihood ratio greater than two, demonstrating their potential diagnostic utility. Large, prospective cohort studies are needed.
 

Comparison of 2-D Shear Wave Elastography and Point Shear Wave Elastography for Assessing Liver Fibrosis

Progressive liver fibrosis may result in cirrhosis, portal hypertension and increased risk of hepatocellular carcinoma. We performed a meta-analysis to compare liver fibrosis staging in chronic liver disease patients using 2-D shear wave elastography (2-D SWE) and point shear wave elastography (pSWE). The PubMed, Web of Science and Cochrane Library databases were searched until May 31, 2020 for studies evaluating the diagnostic performance of 2-D SWE and pSWE in assessing liver fibrosis. Pooled sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratios and area under receiver operating characteristic curve were estimated using the bivariate random effects model. As a result, 71 studies with 11,345 patients were included in the analysis. The pooled sensitivities of 2-D SWE and pSWE significantly differed for the detection of significant fibrosis (F ≥ 2; 0.84 vs. 0.76, p < 0.001) and advanced fibrosis (F ≥ 3; 0.90 vs. 0.83, p = 0.003), but not for detection of cirrhosis (F = 4; 0.89 vs. 0.85, p = 0.090). The pooled specificities of 2-D SWE and pSWE did not significantly differ for detection of F ≥ 2 (0.81 vs. 0.79, p = 0.753), F ≥ 3 (0.87 vs. 0.83, p = 0.163) or F = 4 (0.87 vs. 0.84, p = 0.294). Both 2-D SWE and pSWE have high sensitivity and specificity for detecting each stage of liver fibrosis. Two-dimensional SWE has higher sensitivity than pSWE for detection of significant fibrosis and advanced fibrosis.

A new method for synthesizing test accuracy data outperformed the bivariate method

ObjectivesThis study outlines the development of a new method (split component synthesis; SCS) for meta-analysis of diagnostic accuracy studies and assesses its performance against the commonly used bivariate random effects model. MethodsThe SCS method summarizes the study-specific diagnostic odds ratio (on the ln(DOR) scale), which mainly reflects test discrimination rather than threshold effects, and then splits the summary ln(DOR) into its component parts, logit sensitivity (Se) and logit specificity (Sp). Performance of SCS estimator was assessed through simulation and compared against the bivariate random effects model estimator in terms of bias, mean squared error (MSE), and coverage probability across varying degrees of between-studies heterogeneity. ResultsThe SCS estimator for the DOR, Se, and Sp was less biased and had smaller MSE than the bivariate model estimator. Despite the wider width of the 95% confidence intervals under the bivariate model, the latter had a poorer coverage probability than that under the SCS method. ConclusionThe SCS estimator outperforms the bivariate model estimator and thus represents an improvement in the approach to diagnostic meta-analyses. The SCS method is available to researchers through the diagma module in Stata and the SCSmeta function in R.

Diagnostic accuracy of adrenal imaging for subtype diagnosis in primary aldosteronism: systematic review and meta-analysis

ObjectivesAccurate subtype classification in primary aldosteronism (PA) is critical in assessing the optimal treatment options. This study aimed to evaluate the diagnostic accuracy of adrenal imaging for unilateral PA classification.MethodsSystematic...

Diagnostic performance of single-phase CT angiography in detecting large vessel occlusion in ischemic stroke: A systematic review

PurposeTo systematically review the diagnostic performance of single-phase CT angiography (CTA) in detecting intracranial large vessel occlusion (LVO). MethodMEDLINE and Embase were searched for studies investigating the diagnostic performance of single-phase CTA in detecting LVO. Study quality was assessed. Sensitivity and specificity were calculated and meta-analyzed with a bivariate random-effects model. Heterogeneity was assessed with a chi-squared test. ResultsEleven studies were included. High risk of bias with regard to “patient selection”, “reference standard”, and “flow and timing” was present in 4, 1, and 2 studies, respectively. In 7 studies, it was unclear whether reference tests were interpreted blinded to CTA readings. There was variability in types of vessel segments analyzed, resulting in heterogeneous sensitivity and specificity (P < 0.05). Two studies provided data for the proximal anterior circulation (distal intracranial carotid artery, A1-, A2-, M1- and M2-segments), with pooled sensitivity of 88.4 % (95 % CI: 62.2–97.2 %) and pooled specificity of 98.5 % (95 % CI: 33.2–100 %). One study suggested that multiphase CTA improved agreement between nonexperts and an expert in detecting A1-, A2-, M1-, M2-, and M3-segment occlusions compared to single-phase CTA (ĸ = 0.72−0.76 vs. ĸ = 0.32−0.45). No other included study reported added value of advanced CTA (CT perfusion, 4D-CTA, or multiphase CTA) compared to single-phase CTA in detecting proximal anterior circulation LVO. ConclusionThere is lack of high-quality studies on the diagnostic performance of single-phase CTA for LVO detection in the proximal anterior circulation. The added value of advanced CTA techniques in detecting proximal anterior circulation LVO is not completely clear yet.

Vessel Wall Magnetic Resonance Imaging Biomarkers of Symptomatic Intracranial Atherosclerosis: A Meta-Analysis.

Intracranial atherosclerotic disease is a common cause of stroke worldwide. Intracranial vessel wall magnetic resonance imaging may be able to identify imaging biomarkers of symptomatic plaque. We performed a meta-analysis to evaluate the strength of association of imaging features of symptomatic plaque leading to downstream ischemic events. Effects on the strength of association were also assessed accounting for possible sources of bias and variability related to study design and magnetic resonance parameters. PubMed, Scopus, Web of Science, EMBASE, and Cochrane databases were searched up to October 2019. Two independent reviewers extracted data on study design, vessel wall magnetic resonance imaging techniques, and imaging end points. Per-lesion odds ratios (OR) were calculated and pooled using a bivariate random-effects model. Subgroup analyses, sensitivity analysis, and evaluation of publication bias were also performed. Twenty-one articles met inclusion criteria (1750 lesions; 1542 subjects). Plaque enhancement (OR, 7.42 [95% CI, 3.35-16.43]), positive remodeling (OR, 5.60 [95% CI, 2.23-14.03]), T1 hyperintensity (OR, 2.05 [95% CI, 1.27-3.32]), and surface irregularity (OR, 4.50 [95% CI, 1.39-8.57]) were significantly associated with downstream ischemic events. T2 signal intensity was not significant (P=0.59). Plaque enhancement was significantly associated with downstream ischemic events in all subgroup analyses and showed stronger associations when measured in retrospectively designed studies (P=0.02), by a radiologist as a rater (P<0.001), and on lower vessel wall magnetic resonance imaging spatial resolution sequences (P=0.02). Plaque enhancement, positive remodeling, T1 hyperintensity, and surface irregularity emerged as strong imaging biomarkers of symptomatic plaque in patients with ischemic events. Plaque enhancement remained significant accounting for sources of bias and variability in both study design and instrument. Future studies evaluating plaque enhancement as a predictive marker for stroke recurrence with larger sample sizes would be valuable.

The Use of the Central Vein Sign in the Diagnosis of Multiple Sclerosis: A Systematic Review and Meta-analysis.

Background: The central vein sign (CVS) is a radiological feature proposed as a multiple sclerosis (MS) imaging biomarker able to accurately differentiate MS from other white matter diseases of the central nervous system. In this work, we evaluated the pooled proportion of the CVS in brain MS lesions and to estimate the diagnostic performance of CVS to perform a diagnosis of MS and propose an optimal cut-off value. Methods: A systematic search was performed on publicly available databases (PUBMED/MEDLINE and Web of Science) up to 24 August 2020. Analysis of the proportion of white matter MS lesions with a central vein was performed using bivariate random-effect models. A meta-regression analysis was performed and the impact of using particular sequences (such as 3D echo-planar imaging) and post-processing techniques (such as FLAIR*) was investigated. Pooled sensibility and specificity were estimated using bivariate models and meta-regression was performed to address heterogeneity. Inclusion and publication bias were assessed using asymmetry tests and a funnel plot. A hierarchical summary receiver operating curve (HSROC) was used to estimate the summary accuracy in diagnostic performance. The Youden index was employed to estimate the optimal cut-off value using individual patient data. Results: The pooled proportion of lesions showing a CVS in the MS population was 73%. The use of the CVS showed a remarkable diagnostic performance in MS cases, providing a pooled specificity of 92% and a sensitivity of 95%. The optimal cut-off value obtained from the individual patient data pooled together was 40% with excellent accuracy calculated by the area under the ROC (0.946). The 3D-EPI sequences showed both a higher pooled proportion compared to other sequences and explained heterogeneity in the meta-regression analysis of diagnostic performances. The 1.5 Tesla (T) scanners showed a lower (58%) proportion of MS lesions with a CVS compared to both 3T (74%) and 7T (82%). Conclusions: The meta-analysis we have performed shows that the use of the CVS in differentiating MS from other mimicking diseases is encouraged; moreover, the use of dedicated sequences such as 3D-EPI and the high MRI field is beneficial.

Performance of diffusion-weighted imaging for the diagnosis of parotid gland malignancies: A meta-analysis

PurposeThis study aimed to assess the diagnostic performance of diffusion-weighted imaging (DWI) for parotid gland malignancies. MethodsFour databases (PubMed, the Cochrane Library, Embase, and Web of Science) were searched systematically and retrospectively by two researchers until May 18, 2020. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to pool the sensitivity and specificity data for the apparent diffusion coefficient (ADC). Summary receiver operating characteristic curve was constructed, and the area under the curve (AUC) was calculated. The positive (LR+) and negative likelihood ratios (LR-) were also calculated. Subgroup and meta-regression analyses were performed to evaluate heterogeneity within studies. ResultsSixteen studies involving 1004 patients were included. The pooled sensitivity, specificity, and AUC for the ADC to distinguish malignant from begin parotid lesions were 89 %, 76 %, and 0.91, respectively. The LR + was 3.7 and LR- was 0.15, respectively. Subgroup analyses revealed that the applied cut-off b values and study size were sources of heterogeneity for the ADC. There were publication bias concerns. ConclusionsOur meta-analysis suggests that the ADC value provides excellent sensitivity and moderate specificity for the diagnosis of malignant lesions in the parotid gland. However, substantial heterogeneity was found. Therefore, additional larger, prospective studies in combination with standard techniques focusing on parotid tumors should be conducted to determine the true performance of DWI for the differential diagnosis of parotid lesions.

New measures improved the reporting of heterogeneity in diagnostic test accuracy reviews: a metaepidemiological study

ObjectivesTo describe the methods used to quantify heterogeneity and to propose alternative measures to improve reporting of heterogeneity in Cochrane diagnostic test accuracy (DTA) reviews. Study Design and SettingOur metaepidemiological study included all DTA reviews in the Cochrane Library up to October 6th, 2019. We summarized reviews’ characteristics focusing on heterogeneity analysis. We selected reviews with a bivariate model and ≥4 studies for reanalysis. In this group, we fitted bivariate random effects models and we quantified heterogeneity by means of logit variances of sensitivity and specificity, bivariate I2, median odds ratio (OR), and the area of the 95% prediction ellipse. We provided a narrative interpretation of these measures in different scenarios. ResultsThere were 124 Cochrane DTA reviews of which 91 (73%) included meta-analysis. Only in 5 meta-analyses, variances of the logit sensitivity and specificity were reported, and in 21 meta-analyses (23%), the 95% prediction ellipse was reported without any calculation of its area. We selected 60 of these 91 reviews to explore the behavior of all measures of heterogeneity. We found that most reviews described the subjective heterogeneity as moderate or extreme (n = 31/60, 52%), whereas the area of the 95% prediction ellipse and the median OR for sensitivity and specificity showed high variability; the area ranged from 5% to 97%, the median OR of sensitivity ranged from 1.13 to 10.7, and the median OROR of specificity ranged from 1.18 to 19.68. ConclusionCochrane DTA reviews show a poor reporting of between-study heterogeneity. Using median OR and the area of the 95% prediction ellipse will improve reporting and interpretation of this crucial aspect of DTA meta-analysis.

Diagnostic accuracy of the 4AT for delirium detection in older adults: systematic review and meta-analysis.

ObjectiveDetection of delirium in hospitalised older adults is recommended in national and international guidelines. The 4 ‘A’s Test (4AT) is a short (<2 minutes) instrument for delirium detection that is used internationally as a standard tool in clinical practice. We performed a systematic review and meta-analysis of diagnostic test accuracy of the 4AT for delirium detection.MethodsWe searched MEDLINE, EMBASE, PsycINFO, CINAHL, clinicaltrials.gov and the Cochrane Central Register of Controlled Trials, from 2011 (year of 4AT release on the website www.the4AT.com) until 21 December 2019. Inclusion criteria were: older adults (≥65 years); diagnostic accuracy study of the 4AT index test when compared to delirium reference standard (standard diagnostic criteria or validated tool). Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled estimates of sensitivity and specificity were generated from a bivariate random effects model.ResultsSeventeen studies (3,702 observations) were included. Settings were acute medicine, surgery, a care home and the emergency department. Three studies assessed performance of the 4AT in stroke. The overall prevalence of delirium was 24.2% (95% CI 17.8–32.1%; range 10.5–61.9%). The pooled sensitivity was 0.88 (95% CI 0.80–0.93) and the pooled specificity was 0.88 (95% CI 0.82–0.92). Excluding the stroke studies, the pooled sensitivity was 0.86 (95% CI 0.77–0.92) and the pooled specificity was 0.89 (95% CI 0.83–0.93). The methodological quality of studies varied but was moderate to good overall.ConclusionsThe 4AT shows good diagnostic test accuracy for delirium in the 17 available studies. These findings support its use in routine clinical practice in delirium detection.PROSPERO Registration numberCRD42019133702.

Accuracy of contrast-enhanced ultrasound liver imaging reporting and data system: a systematic review and meta-analysis.

After the introduction of the contrast-enhanced ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS), several studies have reported on its performance, but the reported data vary considerably. Therefore, we performed a systematic review and meta-analysis to determine the diagnostic performance of CEUS LI-RADS in patients at risk for hepatocellular carcinoma (HCC) and investigate the causes of study heterogeneity. Original studies published until May 30, 2020, investigating the diagnostic performance of CEUS LI-RADS were identified in the MEDLINE, EMBASE, and Cochrane library databases. Study quality was assessed using the QUADAS-2 tool. Meta-analytic summary sensitivity and specificity for the diagnosis of HCC were calculated using a bivariate random-effects model. Meta-regression analysis was performed to explore the causes of study heterogeneity. Of the 105 articles screened, eight studies were finally analyzed (5428 hepatic observations). The summary sensitivity and specificity of CEUS LI-RADS category 5 (LR-5) for diagnosing HCC were 73% [95% confidence interval (CI) 65-79%; I2 = 93%] and 95% (95% CI 91-97%; I2 = 89%), respectively. Substantial study heterogeneity was noted in both sensitivity and specificity. Study heterogeneity was significantly associated with the proportion of cases of HCC and the type of reference standard (p ≤ 0.05). CEUS LI-RADS had high pooled specificity for diagnosing HCC but suboptimal pooled sensitivity. Substantial study heterogeneity was found, which was significantly associated with the proportion of cases of HCC and the type of reference standard.

Diagnostic Performance of Biomarkers Urinary KIM-1 and YKL-40 for Early Diabetic Nephropathy, in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis.

There is a lack of prediction markers for early diabetic nephropathy (DN) in patients with type 2 diabetes mellitus (T2DM). The aim of this systematic review and meta-analysis was to evaluate the performance of two promising biomarkers, urinary kidney injury molecule 1 (uKIM-1) and Chitinase-3-like protein 1 (YKL-40) in the diagnosis of early diabetic nephropathy in type 2 diabetic patients. A comprehensive search was performed on PubMed by two reviewers until May 2020. For each study, a 2 × 2 contingency table was formulated. Sensitivity, specificity, and other estimates of accuracy were calculated using the bivariate random effects model. The hierarchical summary receiver operating characteristic curve hsROC) was used to pool data and evaluate the area under curve (AUC). The sources of heterogeneity were explored by sensitivity analysis. Publication bias was assessed using Deek’s test. The meta-analysis enrolled 14 studies involving 598 healthy individuals, 765 T2DM patients with normoalbuminuria, 549 T2DM patients with microalbuminuria, and 551 T2DM patients with macroalbuminuria, in total for both biomarkers. The AUC of uKIM-1 and YKL-40 for T2DM patients with normoalbuminuria, was 0.85 (95%CI; 0.82–0.88) and 0.91 (95%CI; 0.88–0.93), respectively. The results of this meta-analysis suggest that both uKIM-1 and YKL-40 can be considered as valuable biomarkers for the early detection of DN in T2DM patients with the latter showing slightly better performance than the former.

Diagnostic performance of MRI for HCC according to contrast agent type: a systematic review and meta-analysis.

Conflicting results have been reported between the use of extracellular contrast agent (ECA) and hepatobiliary contrast agent (HBA) when magnetic resonance imaging (MRI) is used for the diagnosis of hepatocellular carcinoma (HCC). Therefore, we aimed to compare the diagnostic performance of MRI using ECA (ECA-MRI) and HBA (HBA-MRI). Original studies reporting the diagnostic performance of contrast-enhanced MRI for the diagnosis of HCC published between January 2010 and February 2020 were identified in a Pubmed, EMBASE, and Cochrane Library database search. The pooled sensitivity and specificity of ECA-MRI and HBA-MRI were calculated using a bivariate random effects model and compared using a joint-model bivariate meta-regression. Subgroup analyses were performed to compare the diagnostic performance of ECA-MRI and HBA-MRI according to study design, underlying liver disease, lesion size, reference standard, and imaging criteria. Of the 1760 screened articles, 31 studies were included: 15 studies included 2890 lesions imaged using ECA-MRI and 19 studies included 3893 lesions imaged using HBA-MRI. The pooled sensitivity and specificity were not significantly different between ECA-MRI (sensitivity, 72% [95% confidence interval 65-79%]; specificity 92% [89-95%]) and HBA-MRI (76% [68-83%]; 92% [87-95%], p = 0.72). Subgroup analyses did not find differences in diagnostic performance between ECA-MRI and HBA-MRI according to study design (p ≥ 0.11), underlying disease (p ≥ 0.09), lesion size (≤ 2cm, p = 0.97), reference standard (p = 0.70), or imaging criteria (p = 0.33). ECA-MRI showed similar performance to HBA-MRI in the diagnosis of HCC. The contrast agent might be selected with consideration of the advantages of each agent.

Meta-analysis of CT and MRI for differentiation of autoimmune pancreatitis from pancreatic adenocarcinoma

To systematically determine the diagnostic performance of computed tomography (CT) and magnetic resonance imaging (MRI) for differentiating autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC), with a comparison between the two imaging modalities. Literature search was conducted using PubMed and EMBASE databases to identify original articles published between 2009 and 2019 reporting the diagnostic performance of CT and MRI for differentiating AIP from PDAC. The meta-analytic sensitivity and specificity of CT and MRI were calculated, and compared using a bivariate random effects model. Subgroup analysis for differentiating focal AIP from PDAC was performed. Of the 856 articles screened, 11 eligible articles are remained, i.e., five studies for CT, four for MRI, and two for both. The meta-analytic summary sensitivity and specificity of CT were 59% (95% confidence interval [CI], 41-75%) and 99% (95% CI, 88-100%), respectively, while those of MRI were 84% (95% CI, 68-93%) and 97% (95% CI, 87-99%). MRI had a significantly higher meta-analytic summary sensitivity than CT (84% vs. 59%, p = 0.02) but a similar specificity (97% vs. 99%, p = 0.18). In the subgroup analysis for focal AIP, the sensitivity for distinguishing between focal AIP and PDAC was lower than that for the overall analysis. MRI had a higher sensitivity than CT (76% vs. 50%, p = 0.28) but a similar specificity (97% vs. 98%, p = 0.07). MRI might be clinically more useful to evaluate patients with AIP, particularly for differentiating AIP from PDAC. • MRI had an overall good diagnostic performance to differentiate AIP from PDAC with a meta-analytic summary estimate of 83% for sensitivity and of 97% for specificity. • CT had a very high specificity (99%), but a suboptimal sensitivity (59%) for differentiating AIP from PDAC. • Compared with CT, MRI had a higher sensitivity, but a similar specificity.

CT in the prediction of margin-negative resection in pancreatic cancer following neoadjuvant treatment: a systematic review and meta-analysis.

We aimed to systematically evaluate the diagnostic accuracy of CT-determined resectability following neoadjuvant treatment for predicting margin-negative resection (R0 resection) in patients with pancreatic ductal adenocarcinoma (PDAC). Original studies with sufficient details to obtain the sensitivity and specificity of CT-determined resectability following neoadjuvant treatment, with a reference on the pathological margin status, were identified in PubMed, EMBASE, and Cochrane databases until February 24, 2020. The identified studies were divided into two groups based on the criteria of R0 resectable tumor (ordinary criterion: resectable PDAC alone; extended criterion: resectable and borderline resectable PDAC). The meta-analytic summary of the sensitivity and specificity for each criterion was estimated separately using a bivariate random-effect model. Summary results of the two criteria were compared using a joint-model bivariate meta-regression. Of 739 studies initially searched, 6 studies (6 with ordinary criterion and 5 with extended criterion) were included for analysis. The meta-analytic summary of sensitivity and specificity was 45% (95% confidence interval [CI], 19-73%; I2= 88.3%) and 85% (95% CI, 65-94%; I2= 60.5%) for the ordinary criterion, and 81% (95% CI, 71-87%; I2= 0.0%) and 42% (95% CI, 28-57%; I2= 6.2%) for the extended criterion, respectively. The diagnostic accuracy significantly differed between the two criteria (p = 0.02). For determining resectability on CT, the ordinary criterion might be highly specific but insensitive for predicting R0 resection, whereas the extended criterion increased sensitivity but would decrease specificity. Further investigations using quantitative parameters may improve the identification of R0 resection. • CT-determined resectability of PDAC after neoadjuvant treatment using the ordinary criterion shows low sensitivity and high specificity in predicting R0 resection. • With the extended criterion, CT-determined resectability shows higher sensitivity but lower specificity than with the ordinary criterion. • CT-determined resectability with both criteria achieved suboptimal diagnostic performances, suggesting that care should be taken while selecting surgical candidates and when determining the surgical extent after neoadjuvant treatment in patients with PDAC.

Unnecessary thyroid nodule biopsy rates under four ultrasound risk stratification systems: a systematic review and meta-analysis.

To summarize and compare unnecessary biopsy rates and diagnostic performance in the examination of thyroid nodules according to four representative US-based risk stratification systems. MEDLINE/PubMed and EMBASE databases were searched to identify original articles investigating unnecessary biopsy rates according to at least one of the following guidelines: ACR-TIRADS, ATA, EU-TIRADS, and K-TIRADS. The unnecessary biopsy rates for each risk stratification system were pooled using a random-effects model. Meta-regression analyses were performed to explore heterogeneity. Diagnostic odds ratios (DORs) for the appropriate selection of thyroid nodules for fine-needle aspiration were also pooled using a bivariate random-effects model. Eight articles including 13,092 thyroid nodules met the eligibility criteria and were included. The pooled unnecessary biopsy rates of ACR-TIRADS, ATA, EU-TIRADS, and K-TIRADS were 25% (95% CI, 22-29%), 51% (95% CI, 44-58%), 38% (95% CI, 16-66%), and 55% (95% CI, 42-67%), respectively. The pooled unnecessary biopsy rate of ACR-TIRADS was significantly lower than that of ATA (p < .001) and K-TIRADS (p < .001), and also lower than that of EU-TIRADS, but not reaching statistical significance (p = .087). The pooled DORs of ACR-TIRADS, ATA, and K-TIRADS were 5.9 (95% CI, 3.6-9.6), 6.3 (95% CI, 4.5-8.8), and 4.5 (95% CI, 1.7-11.6), respectively, with the differences not being statistically significant. ACR-TIRADS showed a lower unnecessary biopsy rate than the other risk stratification systems albeit DOR was comparable between ACR-TIRADS, ATA, and K-TIRADS. Future revisions of each system should be made by referring to ACR-TIRADS to reduce unnecessary biopsy rates. • The pooled unnecessary biopsy rates of ACR-TIRADS, ATA, EU-TIRADS, and K-TIRADS were 25% (95% CI, 22-29%), 51% (95% CI, 44-58%), 38% (95% CI, 16-66%), and 55% (95% CI, 42-67%), respectively. • The pooled unnecessary biopsy rate of ACR-TIRADS was significantly lower than that of ATA (p < .001) and K-TIRADS (p < .001). • The pooled DORs of ACR-TIRADS, ATA, and K-TIRADS were 5.9 (95% CI, 3.6-9.6), 6.3 (95% CI, 4.5-8.8), and 4.5 (95% CI, 1.7-11.6), respectively, with the differences not being statistically significant.