Quality Assessment Of Diagnostic Accuracy Studies Research Articles

The diagnostic performance of dual-energy CT imaging in cervical lymph node metastasis of papillary thyroid cancer: a meta-analysis

PurposeThis meta-analysis aimed to evaluate the diagnostic efficacy of dual-energy computed tomography (DECT) in detecting cervical lymph node metastasis among papillary thyroid cancer (PTC) patients.MethodsA comprehensive search across PubMed, Embase, and Web of Science databases was conducted to identify pertinent publications up to May 2024. This search focused on studies examining the diagnostic accuracy of DECT in detecting cervical lymph node metastases in PTC patients. We employed a bivariate random-effects model to calculate pooled sensitivity and specificity of DECT. The degree of heterogeneity in the studies was quantified using the I2 statistic. Furthermore, the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was utilized to evaluate the methodological quality of the included studies.ResultsThis meta-analysis encompassed 14 articles, collectively involving 1,615 patients. The pooled sensitivity, specificity, and AUC for DECT in detecting cervical lymph node metastases in PTC patients were 0.81 (95% CI: 0.76–0.85), 0.86 (95% CI: 0.80–0.91), and 0.89 (95% CI: 0.86–0.92), respectively. According to Fagan’s nomogram, for DECT, with a pre-test probability of 50%, the post-test probability was calculated as 85% for a positive result and 18% for a negative result. Deeks’ funnel plot asymmetry test showed no significant publication bias was observed for DECT (p = 0.28).ConclusionOur meta-analysis indicates that DECT demonstrates superior sensitivity and specificity in cervical lymph node metastasis among PTC patients. To corroborate these findings and evaluate their clinical applicability, further prospective studies are necessary.

Phase angle as a marker of muscle quality: A systematic review and meta-analysis

Background & aimsPhase angle (PhA) is a biomarker derived from raw bioelectrical impedance analysis (BIA) values: resistance (R) and reactance (Xc). PhA reflects cellular membrane integrity and, as a result, has been considered a marker of fluid distribution, making it a potential prognostic indicator. A growing body of research demonstrates independent associations between PhA and muscle strength, mass, and composition. In this context, PhA has the extra potential to serve as a marker of muscle quality. However, the evidence supporting its use for this purpose is not well established. This study aimed to investigate the relationship between PhA and markers of muscle quality. MethodsThis systematic review and meta-analysis (Internal Prospective Register of Systematic Reviews – PROSPERO on a registration code: CRD42024507853) focused on observational studies assessing the relationship between PhA and markers of both concepts of muscle quality: the muscle quality index (MQI: strength by a unit of mass) and the muscle composition (i.e., skeletal muscle radiodensity [SMD], muscle echogenicity, muscle fat fraction, inter- and intramuscular adiposity). Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), while the certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Meta-analyses with a random-effects model were conducted. ResultsSeventeen studies were included in this systematic review, encompassing 2,710 participants. Meta-analyses demonstrated that PhA had a moderate positive correlation coefficient with SMD (4 studies, 924 participants; r = 0.54, 95% confidence interval (CI) 0.38 to 0.69, heterogeneity (I2) = 92%) and good accuracy (85%) for classifying low SMD (2 studies, 390 participants; Area Under the Curve – AUC pooled 0.85, 95% CI 0.78 to 0.92, I2 = 0%). PhA was inversely-moderately correlated with muscle echogenicity (8 studies, 1,401 participants; r = - 0.42, 95% CI - 0.57 to - 0.24, I2 = 82%) and positively-weakly correlated with MQI (2 studies, 191 participants; r = 0.36, 95% CI 0.21 to 0.49, I2 = 17%). All studies had a higher risk of bias. The certainty of evidence ranged from low to very low. ConclusionDespite technical challenges, this study demonstrates the potential of PhA as a surrogate marker for muscle quality, particularly expressing muscle composition (SMD). Future studies should utilize BIA with standardized protocols to potentially establish specific cutoff values for PhA, thereby enhancing its diagnostic accuracy and clinical applicability. These studies could additionally explore the mechanisms underlying the associations between PhA and muscle quality aspects. In cases where technical factors are not easily controlled, the use of standardized PhA (SPhA), which converts PhA into Z-scores, could be beneficial. Although this warrants investigation, this approach (SPhA) has the potential to account for variables such as age, sex, device differences, and health status.

Key issues in diagnostic accuracy of sentinel lymph node biopsy in early-stage ovarian cancer: systematic review and meta-analysis

ObjectiveSentinel lymph node (SLN) mapping may reduce the morbidity of lymphadenectomy while maintaining diagnostic accuracy. Nevertheless, SLN mapping in epithelial ovarian cancer is still under investigation. This systematic review and...

Meta-analysis on the Diagnostic Value of SDC2 Methylation in Colorectal Cancer Screening Among Chinese

To systematically evaluate the diagnostic value of syndecan-2 (SDC2) gene methylation status in the detection of Colorectal cancer (CRC) and advanced adenomas (AA) through meta-analysis. Databases including PubMed, Web of Science were searched from 2020 to June 14, 2024. Relevant studies were selected based on predefined inclusion and exclusion criteria. The true positive (TP), false positive (FP), false negative (FN), and true negative (TN) results were calculated for each study. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. A bivariate meta-analysis model was used to pool the sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR), and a summary receiver operating characteristic (SROC) curve was constructed. Spearman’s correlation coefficient, Cochran-Q test, and I² test were used to evaluate heterogeneity. Sensitivity analysis was performed to explore the potential sources of heterogeneity. 24 literatures were included for meta-analysis. The pooled sensitivity was 0.77 for CRC and 0.52 for AA, and the pooled specificity was 0.93 for CRC and 0.91 for AA. The pooled PLR was 10.63 for CRC and 5.57 for AA, and the pooled NLR was 0.25 for CRC and 0.53 for AA. The DOR was 43.21 for CRC and 10.47 for AA. The SROC AUC was 0.91 for CRC and 0.83 for AA. The methylation level of the SDC2 gene in stool samples has significant diagnostic value for colorectal cancer and is considered an ideal biomarker for the early detection of this disease.

An evaluation of the preprints produced at the beginning of the 2022 mpox public health emergency

BackgroundPreprints are scientific articles that have not undergone the peer-review process. They allow the latest evidence to be rapidly shared, however it is unclear whether they can be confidently used for decision-making during a public health emergency. This study aimed to compare the data and quality of preprints released during the first four months of the 2022 mpox outbreak to their published versions.MethodsEligible preprints (n = 76) posted between May to August 2022 were identified through an established mpox literature database and followed to July 2024 for changes in publication status. Quality of preprints and published studies was assessed by two independent reviewers to evaluate changes in quality, using validated tools that were available for the study design (n = 33). Tools included the Newcastle-Ottawa Scale; Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2); and JBI Critical Appraisal Checklists. The questions in each tool led to an overall quality assessment of high quality (no concerns with study design, conduct, and/or analysis), moderate quality (minor concerns) or low quality (several concerns). Changes in data (e.g. methods, outcomes, results) for preprint-published pairs (n = 60) were assessed by one reviewer and verified by a second.ResultsPreprints and published versions that could be evaluated for quality (n = 25 pairs) were mostly assessed as low quality. Minimal to no change in quality from preprint to published was identified: all observational studies (10/10), most case series (6/7) and all surveillance data analyses (3/3) had no change in overall quality, while some diagnostic test accuracy studies (3/5) improved or worsened their quality assessment scores. Among all pairs (n = 60), outcomes were often added in the published version (58%) and less commonly removed (18%). Numerical results changed from preprint to published in 53% of studies, however most of these studies (22/32) had changes that were minor and did not impact main conclusions of the study.ConclusionsThis study suggests the minimal changes in quality, results and main conclusions from preprint to published versions supports the use of preprints, and the use of the same critical evaluation tools on preprints as applied to published studies, in decision-making during a public health emergency.

Using artificial intelligence based imaging to predict lymph node metastasis in non-small cell lung cancer: a systematic review and meta-analysis.

Lung cancer, especially non-small cell lung cancer (NSCLC), is one of the most-deadly malignancies worldwide. Lung cancer has a worse 5-year survival rate than many primary malignancies. Thus, the early detection and prognosis prediction of lung cancer are crucial. The early detection and prognosis prediction of lung cancer have improved with the widespread use of artificial intelligence (AI) technologies. This meta-analysis examined the accuracy and efficacy of AI-based models in predicting lymph node metastasis (LNM) in NSCLC patients using imaging data. Our findings could help clinicians predict patient prognosis and select alternative therapies. We searched the PubMed, Web of Science, Cochrane Library, and Embase databases for relevant articles published up to January 31, 2024. Two reviewers individually evaluated all the retrieved articles to assess their eligibility for inclusion in the meta-analysis. The systematic assessment and meta-analysis comprised articles that satisfied the inclusion criteria (e.g., randomized or non-randomized trials, and observational studies) and exclusion criteria (e.g., articles not published in English), and provided data for the quantitative synthesis. The quality of the included articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled sensitivity, specificity, and area under the curve (AUC) were used to evaluate the ability of AI-based imaging models to predict LNM in NSCLC patients. Sources of heterogeneity were investigated using meta-regression. Covariates, including country, sample size, imaging modality, model validation technique, and model algorithm, were examined in the subgroup analysis. The final meta-analysis comprised 11 retrospective studies of 6,088 NSCLC patients, of whom 1,483 had LNM. The pooled sensitivity, specificity, and AUC of the AI-based imaging model for predicting LNM in NSCLC patients were 0.87 [95% confidence interval (CI): 0.80-0.91], 0.85 (95% CI: 0.78-0.89), and 0.92 (95% CI: 0.90-0.94). Based on the QUADAS-2 results, a risk of bias was detected in the patient selection and diagnostic tests of the included articles. However, the quality of the included articles was generally acceptable. The pooled sensitivity and specificity were heterogeneous (I2>75%). The meta-regression and subgroup analyses showed that imaging modality [computed tomography (CT) or positron emission tomography (PET)/CT], and the neural network method model design significantly affected heterogeneity of this study. Models employing sample size data from a single center and the least absolute shrinkage and selection operator (LASSO) method had greater sensitivity than other techniques. Using the Deek' s funnel plot, no publishing bias was found. The results of the sensitivity analysis showed that deleting each article one by one did not change the findings. Imaging data models based on AI algorithms have good diagnostic accuracy in predicting LNM in patients with NSCLC and could be applied in clinical settings.

Magnetic Resonance Imaging-Based Vertebral Bone Quality Score for Prediction of Cage Subsidence and Screw Loosening in Patients Undergoing Degenerative Lumbar Surgery: A Meta-analysis.

Poor bone quality is a risk factor for postoperative complications after degenerative lumbar fusion surgery. The magnetic resonance imaging-based vertebral bone quality (VBQ) score is a good tool for assessing bone quality, and this is the first meta-analysis performed to summarize the predictive value of the VBQ score for cage subsidence and screw loosening in patients undergoing degenerative lumbar surgery. Studies were comprehensively searched in electronic databases. The quality of the studies was assessed. The pooled sensitivity, specificity and summary receiver operating characteristic curve were calculated. Publication bias was assessed and meta-regression was conducted. We ultimately included 9 studies with a total of 1,404 patients with a mean age of 60.4 years and a percentage of females of 57.0%. According to the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool to assess methodological quality, the quality of the included studies was relatively low and risks of bias might exist. Results showed that a high VBQ was significantly associated with cage subsidence and screw loosening, and risk factor analysis revealed that the merged odds ratio was 5.37 for cage subsidence and 3.87 for screw loosening. With a VBQ cutoff value of 3.34±0.45, the pooled sensitivity and specificity for the diagnosis of postoperative complications were 0.75 and 0.75, respectively, and the area under the curve was 0.82 (95% confidence interval, 0.78-0.85). A high VBQ was associated with a high risk of cage subsidence and screw loosening in patients who underwent degenerative lumbar surgery. The VBQ score could be considered for identifying high-risk patients for further evaluation.

Is concurrent LR-5 associated with a higher rate of hepatocellular carcinoma in LR-3 or LR-4 observations? An individual participant data meta-analysis.

The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations. To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis. Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x . Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis. The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.

Diagnostic value of serum human epididymal secretory protein 4 for endometrial cancer: a systematic review and meta analysis

ObjectiveThe diagnostic value of serum human epididymal secretory protein 4 (HE4) for endometrial cancer (EC) was assessed via evidence-based medicine (EBM) and systematic review (SR) methodologies.MethodsThe Cochrane Library, PubMed, Web of Science, Embase, CBM, CNKI, and Wan Fang databases were searched up to April 1st, 2024, to identify relevant literature. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was utilized to evaluate the quality of the selected studies. The meta-analysis was conducted via RevMan 5.3, STATA 16.1, and Meta-disc software.ResultsA total of 22 studies comprising 9036 cases (3776 cases in the case group and 5260 cases in the control group) were included. The results revealed that HE4 exhibited a pooled sensitivity of 0.59 [95% CI (0.53, 0.64)], specificity of 0.93 [95% CI (0.88, 0.96)], positive likelihood ratio (PLR) of 6.87 [95% CI (4.57, 10.33)], negative likelihood ratio (NLR) of 0.46 [95% CI (0.39, 0.54)], diagnostic odds ratio (DOR) of 14.36 [95% CI (9.37, 21.17)], and area under the receiver operating characteristic curve (AUC) of 0.78 [95% CI (0.75, 0.82)].ConclusionsSerum HE4 demonstrates high specificity and moderate sensitivity for diagnosing EC, thus serving as a valuable biomarker for clinicians either alone or in conjunction with other tumour markers.

Prostate-specific membrane antigen PET versus [99mTc]Tc-MDP bone scan for diagnosing bone metastasis in prostate cancer: a head-to-head comparative meta-analysis.

To evaluate the diagnostic performance of PSMA PET/CT, including [68Ga]Ga-PSMA-11 and [18F]DCFPyL, in comparison with the [99mTc]Tc-MDP bone scan (BS) in identifying bone metastases among prostate cancer patients. A search was performed in the PubMed and Embase databases to locate pertinent publications from inception to February 12, 2024. The studies included were those that examined the diagnostic effectiveness of PSMA PET/CT (covering [68Ga]Ga-PSMA-11 and [18F]DCFPyL) compared to [99mTc]Tc-MDP BS in identifying bone metastases among prostate cancer patients. The quality of the selected studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) checklist. The meta-analysis included nine articles involving 702 patients. The sensitivity of PSMA PET/CT was higher compared to [99mTc]Tc-MDP BS (0.98 vs. 0.85, P < 0.01), while the specificity of PSMA PET/CT was also higher than [99mTc]Tc-MDP BS (0.97 vs. 0.70,P < 0.01). In subgroup analysis, the sensitivity of [68Ga]Ga-PSMA-11 PET/CT was higher compared to [99mTc]Tc-MDP BS (0.98 vs. 0.86), while the specificity of [68Ga]Ga-PSMA-11 PET/CT was also higher than [99mTc]Tc-MDP BS (0.98 vs. 0.65). Our meta-analysis demonstrates that PSMA PET/CT exhibits superior sensitivity and specificity in comparison with [99mTc]Tc-MDP BS for identifying bone metastases in prostate cancer patients. Further research with head-to-head design is necessary to validate these results and evaluate the clinical effectiveness of these imaging methods. https://www.crd.york.ac.uk/prospero/, identifier PROSPERO CRD42024545112.

Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies Using AI (QUADAS-AI): Protocol for a Qualitative Study.

Quality assessment of diagnostic accuracy studies (QUADAS), and more recently QUADAS-2, were developed to aid the evaluation of methodological quality within primary diagnostic accuracy studies. However, its current form, QUADAS-2 does not address the unique considerations raised by artificial intelligence (AI)-centered diagnostic systems. The rapid progression of the AI diagnostics field mandates suitable quality assessment tools to determine the risk of bias and applicability, and subsequently evaluate translational potential for clinical practice. We aim to develop an AI-specific QUADAS (QUADAS-AI) tool that addresses the specific challenges associated with the appraisal of AI diagnostic accuracy studies. This paper describes the processes and methods that will be used to develop QUADAS-AI. The development of QUADAS-AI can be distilled into 3 broad stages. Stage 1-a project organization phase had been undertaken, during which a project team and a steering committee were established. The steering committee consists of a panel of international experts representing diverse stakeholder groups. Following this, the scope of the project was finalized. Stage 2-an item generation process will be completed following (1) a mapping review, (2) a meta-research study, (3) a scoping survey of international experts, and (4) a patient and public involvement and engagement exercise. Candidate items will then be put forward to the international Delphi panel to achieve consensus for inclusion in the revised tool. A modified Delphi consensus methodology involving multiple online rounds and a final consensus meeting will be carried out to refine the tool, following which the initial QUADAS-AI tool will be drafted. A piloting phase will be carried out to identify components that are considered to be either ambiguous or missing. Stage 3-once the steering committee has finalized the QUADAS-AI tool, specific dissemination strategies will be aimed toward academic, policy, regulatory, industry, and public stakeholders, respectively. As of July 2024, the project organization phase, as well as the mapping review and meta-research study, have been completed. We aim to complete the item generation, including the Delphi consensus, and finalize the tool by the end of 2024. Therefore, QUADAS-AI will be able to provide a consensus-derived platform upon which stakeholders may systematically appraise the methodological quality associated with AI diagnostic accuracy studies by the beginning of 2025. AI-driven systems comprise an increasingly significant proportion of research in clinical diagnostics. Through this process, QUADAS-AI will aid the evaluation of studies in this domain in order to identify bias and applicability concerns. As such, QUADAS-AI may form a key part of clinical, governmental, and regulatory evaluation frameworks for AI diagnostic systems globally. DERR1-10.2196/58202.

Assessing the precision of machine learning for diagnosing pulmonary arterial hypertension: a systematic review and meta-analysis of diagnostic accuracy studies.

Pulmonary arterial hypertension (PAH) is a severe cardiovascular condition characterized by pulmonary vascular remodeling, increased resistance to blood flow, and eventual right heart failure. Right heart catheterization (RHC) is the gold standard diagnostic technique, but due to its invasiveness, it poses risks such as vessel and valve injury. In recent years, machine learning (ML) technologies have offered non-invasive alternatives combined with ML for improving the diagnosis of PAH. The study aimed to evaluate the diagnostic performance of various methods, such as electrocardiography (ECG), echocardiography, blood biomarkers, microRNA, chest x-ray, clinical codes, computed tomography (CT) scan, and magnetic resonance imaging (MRI), combined with ML in diagnosing PAH. The outcomes of interest included sensitivity, specificity, area under the curve (AUC), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). This study employed the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool for quality appraisal and STATA V.12.0 for the meta-analysis. A comprehensive search across six databases resulted in 26 articles for examination. Twelve articles were categorized as low-risk, nine as moderate-risk, and five as high-risk. The overall diagnostic performance analysis demonstrated significant findings, with sensitivity at 81% (95% CI = 0.76-0.85, p < 0.001), specificity at 84% (95% CI = 0.77-0.88, p < 0.001), and an AUC of 89% (95% CI = 0.85-0.91). In the subgroup analysis, echocardiography displayed outstanding results, with a sensitivity value of 83% (95% CI = 0.72-0.91), specificity value of 93% (95% CI = 0.89-0.96), PLR value of 12.4 (95% CI = 6.8-22.9), and DOR value of 70 (95% CI = 23-231). ECG demonstrated excellent accuracy performance, with a sensitivity of 82% (95% CI = 0.80-0.84) and a specificity of 82% (95% CI = 0.78-0.84). Moreover, blood biomarkers exhibited the highest NLR value of 0.50 (95% CI = 0.42-0.59). The implementation of echocardiography and ECG with ML for diagnosing PAH presents a promising alternative to RHC. This approach shows potential, as it achieves excellent diagnostic parameters, offering hope for more accessible and less invasive diagnostic methods. PROSPERO (CRD42024496569).

The Role of Radiomics in the Prediction of Clinically Significant Prostate Cancer in the PI-RADS v2 and v2.1 Era: A Systematic Review.

Early detection of clinically significant prostate cancer (csPCa) has substantially improved with the latest PI-RADS versions. However, there is still an overdiagnosis of indolent lesions (iPCa), and radiomics has emerged as a potential solution. The aim of this systematic review is to evaluate the role of handcrafted and deep radiomics in differentiating lesions with csPCa from those with iPCa and benign lesions on prostate MRI assessed with PI-RADS v2 and/or 2.1. The literature search was conducted in PubMed, Cochrane, and Web of Science databases to select relevant studies. Quality assessment was carried out with Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), Radiomic Quality Score (RQS), and Checklist for Artificial Intelligence in Medical Imaging (CLAIM) tools. A total of 14 studies were deemed as relevant from 411 publications. The results highlighted a good performance of handcrafted and deep radiomics methods for csPCa detection, but without significant differences compared to radiologists (PI-RADS) in the few studies in which it was assessed. Moreover, heterogeneity and restrictions were found in the studies and quality analysis, which might induce bias. Future studies should tackle these problems to encourage clinical applicability. Prospective studies and comparison with radiologists (PI-RADS) are needed to better understand its potential.

Comparison of the Performance of [18F]-FDG PET/CT and [18F]-FDG PET/MRI for Lymph Node Metastasis in Breast Cancer: A Systematic Review and Meta- Analysis.

The primary objective of this study was to conduct a comparative analysis of the diagnostic efficacy of [18F]-FDG PET/CT and [18F]-FDG PET/MRI in the detection of breast cancer lymph node metastasis. We conducted a comprehensive search on PubMed, Embase, and Web of Science databases, encompassing eligible articles until March 2023. The pooled sensitivity and specificity for [18F]-FDG PET/CT and [18F]-FDG PET/MRI have been reported as estimates with 95% Confidence Intervals (CIs) using a bivariate random-effect model. Utilizing the I square (I2) statistic, heterogeneity among pooled studies was evaluated. The quality assessment of the included studies was conducted using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) methodology. We included 18 studies (2057 patients). The sensitivity, specificity, and AUC (Area Under the Curve) values of [18F]-FDG PET/CT for overall lymph node metastasis in breast cancer have been found to be 0.58 (0.39 - 0.75), 0.83 (0.69-0.92), and 0.79 (0.75-0.82), respectively. Correspondingly, the values for [18F]-FDG PET/MRI were found to be 0.76 (0.60-0.88), 0.85 (0.77-0.91), and 0.89 (0.86-0.91), respectively. The sensitivity, specificity, and AUC values of [18F]-FDG PET/CT for axillary lymph node metastasis in breast cancer were 0.52 (0.37-0.67), 0.84 (0.68-0.92), and 0.73 (0.69-0.76), respectively. Correspondingly, the values for [18F]-FDG PET/MRI were 0.84 (0.76-0.89), 0.87 (0.75-0.94), and 0.86 (0.83-0.89), respectively. This study has suggested [18F]-FDG PET/MRI to have greater diagnostic power than [18F]-FDG PET/CT in detecting lymph node metastasis in breast cancer. However, the [18F]-FDG PET/MRI results have been obtained from a small sample size study, and more and larger prospective studies are needed for further confirmation on this issue.</p>.

Line-Field Confocal Optical Coherence Tomography: A New Skin Imaging Technique Reproducing a "Virtual Biopsy" with Evolving Clinical Applications in Dermatology.

Line-field confocal optical coherence tomography is a novel technology able to reproduce a "virtual biopsy" of the skin. The aim of this review is to explore the application of line-field confocal optical coherence tomography (LC-OCT) in various skin diseases, covering skin cancers, inflammatory and infectious skin diseases, genetic diseases, cosmetic procedures, and less common disorders. Study selection was conducted based on LC-OCT and using pertinent MeSh terms, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines from inception to March 2024; to evaluate the quality and risk of bias of studies, Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used. the search retrieved 154 papers according to the selection criteria; after removing publications by one or more of the exclusion criteria, a total of 96 studies were found to be suitable for the analysis. Increasing evidence supports the use of LC-OCT as an adjunctive diagnostic tool for the in vivo diagnosis of a variety of skin tumors. As this device can be considered a "bridge" between dermoscopy and histopathology, widening applications in numerous fields of clinical dermatology, including inflammatory skin disease treatment, presurgical mapping, cosmetic procedures, and monitoring of non-invasive therapies, have been explored.

Systematic review and meta-analysis of the diagnostic value of computed tomography angiography for severe internal carotid artery stenosis

BackgroundDue to the increasing incidence of ischaemic cerebrovascular diseases, the accurate assessment of internal carotid artery (ICA) stenosis is crucial for the development of treatment plans. This systematic review and meta-analysis aimed to evaluate the diagnostic value of computed tomography angiography (CTA) for severe ICAstenosis, thereby providing support for clinical decision-making and promoting diagnostic updates.MethodsThe PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database for Chinese Technical Periodicals (VIP), and Chinese Biomedical Literature (CBM) electronic databases were searched from inception to March 21, 2024, to identify publicly available research literature on the use of CTA to diagnose severe ICA stenosis. Literature screening, data extraction, and quality assessment were conducted based on the inclusion and exclusion criteria as well as the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) standards. Data analysis was performed using Stata 17.0 and Meta-Disc 1.4 software. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of the included studies were calculated using Stata 17.0 software, and forest plots and summary receiver operating characteristic (SROC) curves were generated. The area under the curve (AUC) was calculated, and funnel plots were constructed to assess publication bias.ResultsA total of 16 studies with 2368 vascular segments were included. The meta-analysis revealed that the combined sensitivity and specificity of CTA for severe ICA stenosis were 0.93 (95% CI: 0.88 ~ 0.96) and 0.99 (95% CI: 0.96 ~ 1.00), respectively. The combined positive likelihood ratio and negative likelihood ratio were 92.0 (95% CI: 24.2 ~ 349.6) and 0.07 (95% CI: 0.04 ~ 0.13), respectively. The diagnostic odds ratio was 1302 (95% CI: 257 ~ 6606), and the AUC of the SROC curve was 0.98. The Deeks funnel plot suggested no publication bias among the included studies.ConclusionCTA demonstrated high sensitivity and specificity for diagnosing severe ICA stenosis. Therefore, this study provided important evidence for the accurate diagnosis and treatment of severe ICA stenosis. However, there was considerable heterogeneity among the included studies, thus indicating the need for additional high-quality prospective studies to confirm the clinical applicability of CTA.

Diagnostic accuracy of alternative biomarkers for acute aortic syndrome: a systematic review

BackgroundD-dimer is the only biomarker currently recommended in guidelines for the diagnosis of acute aortic syndrome (AAS). We undertook a systematic review to determine whether any alternative biomarkers could be...

Diagnostic Accuracy of Artificial Intelligence Compared to Biopsy in Detecting Early Oral Squamous Cell Carcinoma: A Systematic Review and Meta Analysis.

To summarize and compare the existing evidence on diagnostic accuracy of artificial intelligence (AI) models in detecting early oral squamous cell carcinoma (OSCC). Review was performed in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analysis - Diagnostic Test Accuracy (PRISMA- DTA) checklist and the review protocol is registered under PROSPERO(CRD42023456355). PubMed, Google Scholar, EBSCOhost were searched from January 2000 to November 2023 to identify the diagnostic potential of AI based tools and models. True-positive, false-positive, true-negative, false-negative, sensitivity, specificity values were extracted or calculated if not present for each study. Quality of selected studies was evaluated based on QUADAS (Quality assessment of diagnostic accuracy studies)- 2 tool. Meta-analysis was performed in Meta-Disc 1.4 software and Review Manager 5.3 RevMan using a bivariate model parameter for the sensitivity and specificity and summary points, summary receiver operating curve (SROC), diagnostic odds ratio (DOR) confidence region, and area under curve (AUC) were calculated. Fourteen studies were included for qualitative synthesis and for meta-analysis. Included studies had presence of low to moderate risk of bias. Pooled sensitivity and specificity of 0.43 (CI 0.18- 0.71) and 0.50 (CI 0.20- 0.80) was observed with a pooled positive likelihood ratio of (PLR) 0.86 (0.43 - 1.71) and negative likelihood ratio (NLR) of 1.04 (0.42 - 1.68) was observed with DOR of 0.78 (0.12 - 5.18) and overall accuracy (AUC) being 0.45 respectively. AI based tools has poor to moderate overall diagnostic accuracy. However, to validate our study findings further more standardized diagnostic accuracy studies should be conducted with proper reporting through QUADAS-2 tool. Thus, we can conclude AI based based tool for secondary level of prevention for early OSCC under early diagnosis and prompt treatment.

Comparative efficacy of double plasma molecular adsorption system combined with plasma exchange versus plasma exchange in treating acute-on-chronic liver failure due to hepatitis B: A meta-analysis.

This meta-analysis aims to evaluate the effectiveness of the double plasma molecular adsorption system (DPMAS) in combination with plasma exchange (PE) compared to plasma exchange alone in the treatment of Acute-on-Chronic liver failure (LF) caused by hepatitis B. Until August 31, 2023, a comprehensive search of databases including Embase, Chinese Medical Journal Full-text Database, China Biomedical Literature Database, Wan Fang Medical Network, PubMed, and the Cochrane Library was carried out using keywords like "liver failure," "acute-on-chronic liver failure," "PE," "DPMAS," and related terms. The quality of the included studies was evaluated using QUADS (quality assessment of diagnostic accuracy studies). Software Revman 5.3 was used to examine the data, while Stata 15.1 was used to run Egger's test. Following thorough screening, 452 patients who received PE alone and 429 patients who received DPMAS in addition to PE were included. Every study that was included was of a high caliber. When comparing the DPMAS plus PE group to the PE alone group, the total bilirubin reduction was considerably higher (mean difference [MD] = -49.09, 95% confidence interval [CI]: -54.84 to -43.35, p < .00001). Prothrombin activity (PTA; MD = -1.53, 95% CI: -3.29 to -0.22, p = .09), albumin (ALB; MD = -0.58, 95% CI: -1.57 to 0.41, p = .25), prothrombin time (PT; MD = -0.07, 95% CI: -1.47 to 1.34, p = .92), and platelet count (PLT; MD = -0.08, 95% CI: -1.33 to 1.66, p = .90) did not differ significantly. The improvement in international standardized ratio (INR) was significantly greater in the PE group (MD = 0.07, 95% CI (0.03, 0.10), p = .0001). When combined with DPMAS, PE has been shown to be more effective in lowering total bilirubin levels. PE can also lower INR in individuals who have hepatitis B-related ACLF. This therapeutic strategy also lessens the need for plasma transfusions.

Diagnostic Accuracy of Contrast Enhanced Computed Tomography (CECT) in Cervical Lymph Node Metastasis of Oral Carcinoma: A Systematic Review and Meta-Analysis.

To compare the diagnostic accuracy of Contrast Enhanced Computed Tomography (CECT) compared to conventional imaging modalities and histopathological investigation in cervical lymph node metastasis in adults through a novel meta- analysis. The review protocol is registered under PROSPERO(CRD42021225704) and performed in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analysis - Diagnostic Test Accuracy (PRISMA- DTA) checklist. Databases like PubMed, Google Scholar, EBSCOhost were searched from 2000 to 2023 to identify the diagnostic potential of CECT in cervical lymph node metastasis of oral carcinoma. True-positive, false-positive, true-negative, false-negative, sensitivity, specificity values were extracted or calculated if not present for each study. Quality of selected studies was evaluated based on Quality assessment of diagnostic accuracy studies (QUADAS)- 2 tool. Meta-analysis was performed in Meta-Disc 1.4 software and Review Manager 5.3 using a bivariate model parameter for the pooled sensitivity and pooled specificity. Additional analysis was performed in terms of positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR) and summary receiver operating characteristics (SROC) with Area Under Curve (AUC) and p<0.05 as statistically significant. Six studies were included for qualitative synthesis and as well as for meta-analysis. Two studies had high risk of bias while four studies had low risk of bias. 651 patients underwent CECT and were taken for meta-analysis. The meta-analysis revealed that CECT for diagnosing cervical lymph node metastasis had a pooled sensitivity of 71%, pooled specificity of 14% with 60% Area Under Curve (AUC). +LR of 0.84, -LR of 1.36 and DOR of 0.59. CECT has an overall fair diagnostic ability and is a valid and reliable tool in diagnosing the target condition overcoming high reliance on master specialized capacity for their execution and understanding like other conventional imaging techniques. CECT can be concluded for secondary level of prevention for cervical node metastasis of oral carcinoma under early diagnosis and prompt treatment. However, further standardized accuracy studies are indicated to improve the overall diagnostic accuracy of CECT.