Estimates Of Diagnostic Accuracy Research Articles

Reevaluating the true diagnostic accuracy of dipstick tests to diagnose urinary tract infection using Bayesian latent class analysis.

Previous studies on diagnostic accuracy of dipstick testing for leukocyte esterase (LE) and nitrite to diagnose urinary tract infection (UTI) had used urine culture, which is an imperfect gold standard. Estimates of diagnostic accuracy obtained using the classical gold standard framework might not reflect the true diagnostic accuracy of dipstick tests. We used the dataset from a prospective, observational study conducted in the emergency department of a teaching hospital in southern India. Patients with a clinical suspicion of UTI underwent dipstick testing for LE and nitrite, urine microscopy, and urine culture. Based on the results of urine microscopy and culture, UTI was classified into definite, probable, and possible. Patients with microscopic pyuria and a positive urine culture were adjudicated as definite UTI. Unequivocal imaging evidence of emphysematous pyelonephritis or perinephric collections was also considered definite UTI. We estimated the diagnostic accuracy of LE and nitrite tests using the classical analysis (assuming definite UTI as gold standard) and two different Bayesian latent class models (LCMs; 3-tests in 1-population and 2-tests in 2-populations models). We studied 149 patients. Overall, 64 (43%) patients had definite, 76 (51%) had probable, and 2 (1.3%) had possible UTI; 7 (4.6%) had alternate diagnoses. In classical analysis, LE was more sensitive than nitrite (87.5% versus 70.5%), while nitrite was more specific (24% versus 58%). The 3-tests in 1-population Bayesian LCM indicated a substantially better sensitivity and specificity for LE (98.1% and 47.6%) and nitrite (88.2% and 97.7%). True sensitivity and specificity of urine culture as estimated by the model was 48.7% and 73.0%. Estimates of the 2-tests in 2-populations model were in agreement with the 3-tests in 1-population model. Bayesian LCMs indicate a clinically important improvement in the true diagnostic accuracy of urine dipstick testing for LE and nitrite. Given this, a negative dipstick LE would rule-out UTI, while a positive dipstick nitrite would rule-in UTI in our study setting. True diagnostic accuracy of urine dipstick testing for UTI in various practice settings needs reevaluation using Bayesian LCMs.

Tests to detect and inform the diagnosis of root caries.

Root caries is a well-recognised disease, with increasing prevalence as populations age and retain more of their natural teeth into later life. Like coronal caries, root caries can be associated with pain, discomfort, tooth loss, and contribute significantly to poorer oral health-related quality of life in the elderly. Supplementing the visual-tactile examination could prove beneficial in improving the accuracy of early detection and diagnosis. The detection of root caries lesions at an early stage in the disease continuum can inform diagnosis and lead to targeted preventive therapies and lesion arrest. To assess the diagnostic test accuracy of index tests for the detection and diagnosis of root caries in adults, used alone or in combination with other tests. Cochrane Oral Health's Information Specialist undertook a search of the following databases: MEDLINE Ovid (1946 to 31 December 2018); Embase Ovid (1980 to 31 December 2018); US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov, to 31 December 2018); and the World Health Organization International Clinical Trials Registry Platform (to 31 December 2018). We studied reference lists as well as published systematic review articles. We included diagnostic accuracy study designs that compared one or more index tests (laser fluorescence, radiographs, visual examination, electronic caries monitor (ECM), transillumination), either independently or in combination, with a reference standard. This included prospective studies that evaluated the diagnostic accuracy of single index tests and studies that directly compared two or more index tests. In vitro and in vivo studies were eligible for inclusion but studies that artificially created carious lesions were excluded. Two review authors extracted data independently and in duplicate using a standardised data extraction and quality assessment form based on the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) specific to the review context. Estimates of diagnostic test accuracy were expressed as sensitivity and specificity with 95% confidence intervals (CI) for each dataset. We planned to use hierarchical models for data synthesis and explore potential sources of heterogeneity through meta-regression. Four cross-sectional diagnostic test accuracy studies providing eight datasets with data from 4997 root surfaces were analysed. Two in vitro studies evaluated secondary root caries lesions on extracted teeth and two in vivo studies evaluated primary root caries lesions within the oral cavity. Four studies evaluated laser fluorescence and reported estimates of sensitivity ranging from 0.50 to 0.81 and specificity ranging from 0.40 to 0.80. Two studies evaluated radiographs and reported estimates of sensitivity ranging from 0.40 to 0.63 and specificity ranging from 0.31 to 0.80. One study evaluated visual examination and reported sensitivity of 0.75 (95% CI 0.48 to 0.93) and specificity of 0.38 (95% CI 0.14 to 0.68). One study evaluated the accuracy of radiograph and visual examination in combination and reported sensitivity of 0.81 (95% CI 0.54 to 0.96) and specificity of 0.54 (95% CI 0.25 to 0.81). Given the small number of studies and important differences in the clinical and methodological characteristics of the studies we were unable to pool the results. Consequently, we were unable to formally evaluate the comparative accuracy of the different tests considered in this review. Using QUADAS-2 we judged all four studies to be at overall high risk of bias, but only two to have applicability concerns (patient selection domain). Reasons included bias in the selection process, use of post hoc (data driven) positivity thresholds, use of an imperfect reference standard, and use of extracted teeth. We downgraded the certainty of the evidence due to study limitations and serious imprecision of the results (downgraded two levels), and judged the certainty of the evidence to be very low. Visual-tactile examination is the mainstay of root caries detection and diagnosis; however, due to the paucity of the evidence base and the very low certainty of the evidence we were unable to determine the additional benefit of adjunctive diagnostic tests for the detection and diagnosis of root caries.

Diagnostic Test Accuracy of the Red Reflex Test for Ocular Pathology in Infants

Red reflex testing is a simple and inexpensive method implemented in many countries as an important part of infant screening for ocular pathologies. To review the literature on the diagnostic accuracy of the red reflex test in infant screening for ocular pathologies and to perform meta-analyses to provide summary estimates. The following literature databases were searched for English-language, peer-reviewed literature, published until April 19, 2020: Cochrane Central, PubMed/MEDLINE, Embase, Web of Science Core Collection, BIOSIS Previews, Current Contents Connect, Data Citation Index, Derwent Innovations Index, KCI-Korean Journal Database, Russian Science Citation Index, SciELO Citation Index, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and ClinicalTrials.gov. Eligibility criteria were defined according to population (studies of consecutively screened infants), exposure (red reflex or Brückner test as the index test), comparator (any ophthalmological examination), and study type (any study with diagnostic test accuracy data). The Preferred Reporting Items for Systematic Reviews and Meta-Analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines were followed. Data were extracted independently by 2 authors. For summary estimates of diagnostic test accuracy, the hierarchical summary receiver operating characteristics curve was used. Prevalence of ocular pathologies was introduced for a prevalence meta-analysis, which was then used in calculations of diagnostic accuracy of the red reflex test when applied in infant screening. True-positive, false-positive, true-negative, and false-negative findings; sensitivity; specificity; and positive and negative predictive values. In this meta-analysis, 8713 unique infants from 5 unique studies were eligible for qualitative and quantitative review. All studies used the red reflex test without pupillary dilation and were compared with a reference test performed with pupillary dilation. For any ocular pathology, an estimated sensitivity of 7.5% (95% CI, 7.4%-7.5%) and specificity of 97.5% (95% CI, 97.5%-97.5%) was found. Focusing on ocular pathologies that required a medical or surgical intervention, sensitivity improved to 17.5% (95% CI, 0.8%-84.8%) and specificity remained high at 97.6% (95% CI, 87.7%-99.6%). These findings suggest that an abnormal red reflex finding most likely reflects an underlying ocular pathology. However, a normal red reflex finding during screening does not exclude ocular disease.

Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies Evaluating Point-of-Care Tests of Coagulopathy in Cardiac Surgery.

Treatment guidelines recommend the routine use of point-of-care diagnostic tests for coagulopathy in the management of cardiac surgery patients at risk of severe bleeding despite uncertainty as to their diagnostic accuracy. We performed a systematic review and meta-analysis of studies that evaluated the diagnostic accuracy of viscoelastometry, platelet function tests, and modified thromboelastography (TEG) tests, for coagulopathy in cardiac surgery patients. The reference standard included resternotomy for bleeding, transfusion of non-red cell components, or massive transfusion. We searched MEDLINE, EMBASE, CINAHL, and Clinical Trials.gov, from inception to June 2019. Study quality was assessed using QUADAS-2. Bivariate models were used to estimate summary sensitivity and specificity with (95% confidence intervals). All 29 studies (7440 participants) included in the data synthesis evaluated the tests as predictors of bleeding. No study evaluated their role in the management of bleeding. None was at low risk of bias. Four were judged as low concern regarding applicability. Pooled estimates of diagnostic accuracy were; Viscoelastic tests, 12 studies, sensitivity 0.61 (0.44, 0.76), specificity 0.83 (0.70, 0.91) with significant heterogeneity. Platelet function tests, 12 studies, sensitivity 0.63 (0.53, 0.72), specificity 0.75 (0.64, 0.84) with significant heterogeneity. TEG modification tests, 3 studies, sensitivity 0.80 (0.67, 0.89), specificity 0.76 (0.69, 0.82) with no evidence of heterogeneity. Studies reporting the highest values for sensitivity and specificity had important methodological limitations. In conclusion, we did not demonstrate predictive accuracy for commonly used point-of-care devices for coagulopathic bleeding in cardiac surgery. However, the certainty of the evidence was low.

Effectiveness of tests to detect the presence of SARS-CoV-2 virus, and antibodies to SARS-CoV-2, to inform COVID-19 diagnosis: a rapid systematic review

ObjectivesWe undertook a rapid systematic review with the aim of identifying evidence that could be used to answer the following research questions: (1) What is the clinical effectiveness of tests...

Diagnostic accuracy of the repeatable battery of the assessment of neuropsychological status update, Spanish version, in predicting Alzheimer’s disease among Hispanic older adults in the United States reporting memory problems

Objectives: There are few standardized, Spanish-language diagnostic tools to help identify Hispanic persons at early stages of Alzheimer’s disease (AD). This study evaluated the accuracy of the Spanish version of the Repeatable Battery for the Assessment of Neuropsychological Status-Update (RBANS) in predicting AD in older Hispanic adults in the United States reporting memory problems.Methods: We analyzed data from age, sex, and education level propensity score-matched Hispanic memory clinic patients with (n = 38) and without (n = 38) a clinical diagnosis of AD. Estimates of diagnostic accuracy included sensitivity, specificity, predictive value, and receiver operating characteristic analysis.Results: After controlling for sex and matched pairs, the Total Scale score [area under curve (AUC) = 0.7417] and the Immediate (AUC = 0.7258) and Delayed (AUC = 0.7735) Memory index scores provided better estimates of diagnostic accuracy than Language, Attention, and Visuospatial/Constructional index scores. A minus 2-standard deviation (SD) cut point enhanced the predictive probability of the Delayed Memory index score. A cut point of −1.5 SD optimized the predictive probability of the Total Scale score.Conclusions: These results suggest that optimal cutoff values for the RBANS Delayed Memory index and Total Scale scores that may help identify Hispanic patients with AD as part of a comprehensive diagnostic AD assessment.

Empirical assessment of bias in machine learning diagnostic test accuracy studies.

Machine learning (ML) diagnostic tools have significant potential to improve health care. However, methodological pitfalls may affect diagnostic test accuracy studies used to appraise such tools. We aimed to evaluate the prevalence and reporting of design characteristics within the literature. Further, we sought to empirically assess whether design features may be associated with different estimates of diagnostic accuracy. We systematically retrieved 2 × 2 tables (n = 281) describing the performance of ML diagnostic tools, derived from 114 publications in 38 meta-analyses, from PubMed. Data extracted included test performance, sample sizes, and design features. A mixed-effects metaregression was run to quantify the association between design features and diagnostic accuracy. Participant ethnicity and blinding in test interpretation was unreported in 90% and 60% of studies, respectively. Reporting was occasionally lacking for rudimentary characteristics such as study design (28% unreported). Internal validation without appropriate safeguards was used in 44% of studies. Several design features were associated with larger estimates of accuracy, including having unreported (relative diagnostic odds ratio [RDOR], 2.11; 95% confidence interval [CI], 1.43-3.1) or case-control study designs (RDOR, 1.27; 95% CI, 0.97-1.66), and recruiting participants for the index test (RDOR, 1.67; 95% CI, 1.08-2.59). Significant underreporting of experimental details was present. Study design features may affect estimates of diagnostic performance in the ML diagnostic test accuracy literature. The present study identifies pitfalls that threaten the validity, generalizability, and clinical value of ML diagnostic tools and provides recommendations for improvement.

Estimating prevalence and test accuracy in disease ecology: How Bayesian latent class analysis can boost or bias imperfect test results.

Obtaining accurate estimates of disease prevalence is crucial for the monitoring and management of wildlife populations but can be difficult if different diagnostic tests yield conflicting results and if the accuracy of each diagnostic test is unknown. Bayesian latent class analysis (BLCA) modeling offers a potential solution, providing estimates of prevalence levels and diagnostic test accuracy under the realistic assumption that no diagnostic test is perfect.In typical applications of this approach, the specificity of one test is fixed at or close to 100%, allowing the model to simultaneously estimate the sensitivity and specificity of all other tests, in addition to infection prevalence. In wildlife systems, a test with near‐perfect specificity is not always available, so we simulated data to investigate how decreasing this fixed specificity value affects the accuracy of model estimates.We used simulations to explore how the trade‐off between diagnostic test specificity and sensitivity impacts prevalence estimates and found that directional biases depend on pathogen prevalence. Both the precision and accuracy of results depend on the sample size, the diagnostic tests used, and the true infection prevalence, so these factors should be considered when applying BLCA to estimate disease prevalence and diagnostic test accuracy in wildlife systems. A wildlife disease case study, focusing on leptospirosis in California sea lions, demonstrated the potential for Bayesian latent class methods to provide reliable estimates under real‐world conditions.We delineate conditions under which BLCA improves upon the results from a single diagnostic across a range of prevalence levels and sample sizes, demonstrating when this method is preferable for disease ecologists working in a wide variety of pathogen systems.

Impact of motion artefacts and motion-artefact correction on diagnostic accuracy of apical periodontitis in CBCT images: an ex vivo study in human cadavers.

To assess the impact of motion artefacts and motion-artefact correction on diagnostic accuracy of apical periodontitis (AP) in CBCT images. Based on clinical and radiographic inspection of 40 formalin-fixated human jaw specimens, 77 roots in 45 teeth (molars and premolars), with various disease and treatment state, were selected. The specimens were mounted on a robot simulating 3-mm movement types (nodding, lateral rotation and tremor). CBCT images with and without (controls) movements were acquired in four CBCT units: without motion-artefact correction in Cranex 3Dx, Orthophos SL 3D, and Promax 3D Mid, and with motion-artefact correction in Promax 3D Mid and X1. Three observers blindly assessed (i) whether the images were interpretable and (ii) if AP was present (5-step probability index). Histopathology provided the reference standard for presence of AP. Weighted Kappa statistics described inter-observer agreement. Estimates of diagnostic accuracy were assessed by means of receiver operator characteristic (ROC) curve analysis. Area under the curve (AUC) provided a measure of accuracy, and paired-sample AUC difference tests compared differences amongst the CBCT units and movement types. Observer agreement was substantial for control images, moderate for motion-artefact corrected images and fair for images without motion-artefact correction. When movement was present, motion-artefact correction reduced the percentage of images scored as noninterpretable or with uncertain disease state (score 3 in the 5-step probability index). Control images were not perfectly accurate (both false-positive and false-negative results were present; AUC 0.750-0.799). Images acquired with movement and without motion-artefact correction (AUC 0.541-0.709) were associated with significantly lower accuracy than control images (P<0.05). With motion-artefact correction, accuracy was comparable to that observed in control images (AUC 0.732-0.790). Diagnostic accuracy of apical periodontitis in CBCT images was dependent on the presence of motion artefacts (i.e. lower accuracy associated with the presence of movement). Motion-artefact correction systems positively influenced image interpretability and diagnostic accuracy.

Accuracy of optical coherence tomography for diagnosing glaucoma: an overview of systematic reviews

AimsTo assess the diagnostic accuracy (DTA) of optical coherence tomography (OCT) for detecting glaucoma by systematically searching and appraising systematic reviews (SRs) on this issue.MethodsWe searched a database of SRs...

Establishment of a CALU, AURKA, and MCM2 gene panel for discrimination of metastasis from primary colon and lung cancers.

Metastasis is known as a key step in cancer recurrence and could be stimulated by multiple factors. Calumenin (CALU) is one of these factors which has a direct impact on cancer metastasis and yet, its underlined mechanisms have not been completely elucidated. The current study was aimed to identify CALU co-expressed genes, their signaling pathways, and expression status within the human cancers. To this point, CALU associated genes were visualized using the Cytoscape plugin BisoGenet and annotated with the Enrichr web-based application. The list of CALU related diseases was retrieved using the DisGenNet, and cancer datasets were downloaded from The Cancer Genome Atlas (TCGA) and analyzed with the Cufflink software. ROC curve analysis was used to estimate the diagnostic accuracy of DEGs in each cancer, and the Kaplan–Meier survival analysis was performed to plot the overall survival of patients. The protein level of the signature biomarkers was measured in 40 biopsy specimens and matched adjacent normal tissues collected from CRC and lung cancer patients. Analysis of CALU co-expressed genes network in TCGA datasets indicated that the network is markedly altered in human colon (COAD) and lung (LUAD) cancers. Diagnostic accuracy estimation of differentially expressed genes showed that a gene panel consisted of CALU, AURKA, and MCM2 was able to successfully distinguish cancer tumors from healthy samples. Cancer cases with abnormal expression of the signature genes had a significantly lower survival rate than other patients. Additionally, comparison of CALU, AURKA, and MCM2 proteins between healthy samples, early and advanced tumors showed that the level of these proteins was increased through normal–carcinoma transition in both types of cancers. These data indicate that the interactions between CALU, AURKA, and MCM2 has a pivotal role in cancer development, and thereby needs to be explored in the future.

Estimating the Impact of Verification Bias on Celiac Disease Testing.

The goal of this study was to estimate the impact of verification bias on the diagnostic accuracy of immunoglobulin A tissue transglutaminase (IgA tTG) in detecting celiac disease as reported by an authoritative meta-analysis, the 2016 Comparative Effectiveness Review (CER). Verification bias is introduced to diagnostic accuracy studies when screening test results impact the decision to verify disease status. We adjusted the sensitivity and specificity of IgA tTG reported by the 2016 CER with the proportion of IgA tTG positive and negative individuals who are referred for confirmatory small bowel biopsy. We performed a systematic review from January 1, 2007, to July 19, 2017, to determine these referral rates. The systematic review identified 793 articles of which 9 met inclusion criteria (n=36,477). Overall, 3.6% [95% confidence interval (CI): 1.1%-10.9%] of IgA tTG negative and 79.2.2% (95% CI: 65.0%-88.7%) of IgA tTG positive individuals were referred for biopsy. Adjusting for these referral rates the 2016 CER reported sensitivity of IgA tTG dropped from 92.6% (95% CI: 90.2%-94.5%) to 57.1% (95% CI: 35.4%-76.4%) and the specificity increased from 97.6% (95% CI: 96.3%-98.5%) to 99.6% (95% CI: 98.4%-99.9%). The CER may have largely overestimated the sensitivity of IgA tTG due to a failure to account for verification bias. These findings suggest caution in the interpretation of a negative IgA tTG to rule out celiac disease in clinical practice. More broadly, they highlight the impact of verification bias on diagnostic accuracy estimates and suggest that studies at risk for this bias be excluded from systematic reviews.

The Effect of Scan Length on the Assessment of BOLD Delay in Ischemic Stroke.

Objectives: To evaluate the impact of resting-state functional MRI scan length on the diagnostic accuracy, image quality and lesion volume estimation of BOLD delay maps used for brain perfusion assessment in acute ischemic stroke.Methods: Sixty-three acute ischemic stroke patients received a 340 s resting-state functional MRI within 24 h of stroke symptom onset. BOLD delay maps were calculated from the full scan and four shortened versions (68 s, 136 s, 204 s, 272 s). The BOLD delay lesions on these maps were compared in terms of spatial overlap and volumetric agreement with the lesions derived from the full scans and with time-to-maximum (Tmax) lesions derived from DSC-MRI in a subset of patients (n = 10). In addition, the interpretability and quality of these maps were compared across different scan lengths using mixed models.Results: Shortened BOLD delay scans showed a small volumetric bias (ranging from 0.05 to 5.3 mL; between a 0.13% volumetric underestimation and a 7.7% overestimation relative to the mean of the volumes, depending on scan length) compared to the full scan. Decreased scan length was associated with decreased spatial overlap with both the BOLD delay lesions derived from the full scans and with Tmax lesions. Only the two shortest scan lengths (68 and 136 s) were associated with substantially decreased interpretability, decreased structure clarity, and increased noisiness of BOLD delay maps.Conclusions: BOLD delay maps derived from resting-state fMRI scans lasting 272 and 204 s provide sufficient diagnostic quality and adequate assessment of perfusion lesion volumes. Such shortened scans may be helpful in situations where quick clinical decisions need to be made.

Artificial intelligence abstracts from the European Congress of Radiology: analysis of topics and compliance with the STARD for abstracts checklist

ObjectivesTo analyze all artificial intelligence abstracts presented at the European Congress of Radiology (ECR) 2019 with regard to their topics and their adherence to the Standards for Reporting Diagnostic accuracy studies (STARD) checklist.MethodsA total of 184 abstracts were analyzed with regard to adherence to the STARD criteria for abstracts as well as the reported modality, body region, pathology, and use cases.ResultsMajor topics of artificial intelligence abstracts were classification tasks in the abdomen, chest, and brain with CT being the most commonly used modality. Out of the 10 STARD for abstract criteria analyzed in the present study, on average, 5.32 (SD = 1.38) were reported by the 184 abstracts. Specifically, the highest adherence with STARD for abstracts was found for general interpretation of results of abstracts (100.0%, 184 of 184), clear study objectives (99.5%, 183 of 184), and estimates of diagnostic accuracy (96.2%, 177 of 184). The lowest STARD adherence was found for eligibility criteria for participants (9.2%, 17 of 184), type of study series (13.6%, 25 of 184), and implications for practice (20.7%, 44 of 184). There was no significant difference in the number of reported STARD criteria between abstracts accepted for oral presentation (M = 5.35, SD = 1.31) and abstracts accepted for the electronic poster session (M = 5.39, SD = 1.45) (p = .86).ConclusionsThe adherence with STARD for abstract was low, indicating that providing authors with the related checklist may increase the quality of abstracts.

Early detection treatment response for head and neck carcinomas using intravoxel incoherent motion-magnetic resonance imaging: a meta-analysis.

To evaluate the diagnostic accuracy of intravoxel incoherent motion-MRI (IVIM-MRI) for predicting the treatment response in head and neck squamous cell carcinomas (HNSCC) patients. A comprehensive literature search was performed to identify original articles on diagnostic performance of IVIM in predicting treatment response in HNSCC patients receiving chemoradiotherapy. The IVIM parameters studied were diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient. Summary estimates of diagnostic accuracy were obtained by using a random-effects model. Of 65 studies screened, 8 studies with 347 patients were finally included. The pooled sensitivities and specificities were 76% [95% confidence interval (CI) 69-82%] and 81% (95% CI 70-89%) for pre-treatment D, and 70% (95% CI 58-80%) and 82% (95% CI 66-92%) for △D, respectively. In addition, the sensitivities and specificities ranged from 41.7 to 94% and 67 to 100% for pre-treatment f, and from 55.7 to 76.5% and 72.2 to 93.3% for pre-treatment apparent diffusion coefficient, respectively. The diffusion-related coefficients pre-treatment D and △D demonstrated good accuracy in predicting early treatment response in HNSCC patients. However, because of the variability in reference test and other limitations of included literature, further investigation is needed before implementing any IVIM strategy into clinical practice.

Nonparametric estimation of distributions and diagnostic accuracy based on group-tested results with differential misclassification.

This article concerns the problem of estimating a continuous distribution in a diseased or nondiseased population when only group-based test results on the disease status are available. The problem is challenging in that individual disease statuses are not observed and testing results are often subject to misclassification, with further complication that the misclassification may be differential as the group size and the number of the diseased individuals in the group vary. We propose a method to construct nonparametric estimation of the distribution and obtain its asymptotic properties. The performance of the distribution estimator is evaluated under various design considerations concerning group sizes and classification errors. The method is exemplified with data from the National Health and Nutrition Examination Survey study to estimate the distribution and diagnostic accuracy of C-reactive protein in blood samples in predicting chlamydiaincidence.

Bayesian estimation of diagnostic accuracy of fecal culture and PCR-based tests for the detection of Salmonella enterica in California cull dairy cattle.

Epidemiological studies of low prevalence disease problems are often hindered by the high cost of diagnostic testing. The objective of this study was to evaluate PCR screening of both individual and pooled fecal samples from culled dairy cows for the invA gene of Salmonella followed by culture to determine if the sensitivity and specificity were comparable to the results from traditional culture methods applied to individual samples. Cows from six different dairies were sampled in all four seasons. A total of 240 individual cow fecal samples, 24 fecal pools and 24 pools of 24-hour tetrathionate enrichment broth were tested. Diagnostic sensitivity of PCR screening followed by culture of PCR positive or indeterminate samples (i.e PCR-CUL method) was lower than that of culture (CUL) when applied to individual fecal samples (94.8%, 99.5%), however the specificity was comparable (99.6% and 97.7% respectively). For pools of five fecal samples and pools of five, 24 h tetrathionate broth samples, the specificity of both tests were comparable (∼98%); however, their sensitivity was only comparable in pooled fecal samples (∼93%) but greater for culture compared to PCR-CUL in pooled broth samples (∼99% versus ∼93%). Compared to culture results from testing of individual fecal samples, testing pooled fecal samples by culture had a relative sensitivity of 74% and relative specificity of 96%, testing pooled fecal samples by PCR-CUL resulted in relative sensitivity of 90% and relative specificity of 96%. Testing of pooled 24-hour enrichment broth by PCR-CUL increased the relative sensitivity and specificity to 100%. PCR testing followed by culture of positive or indeterminate samples is a time saving alternative to traditional methods. In addition, pooling of samples may be a useful method for decreasing cost if study aims can accommodate a moderate loss of relative sensitivity.

Diagnostic performance of whole-lesion apparent diffusion coefficient histogram analysis metrics for differentiating benign and malignant breast lesions: a systematic review and diagnostic meta-analysis.

Although whole-lesion apparent diffusion coefficient (ADC) histogram has been increasingly used for breast lesions, it has not been routinely used in clinical practice as an emergent promising imaging tool. To evaluate the performance of whole-lesion ADC histogram analysis metrics for differentiating benign and malignant breast lesions. A systematic PubMed/EMBASE/Cochrane electronic database search was performed for original diagnostic studies from 1 January 1970 to 2 January 2019. Summary estimates of diagnostic accuracy were generated and meta-regression was performed to explore sources of heterogeneity according to study and magnetic resonance imaging characteristics. Five original articles involving 493 patients were included in the meta-analysis. The pooled sensitivity and specificity of whole-lesion ADC histogram analysis were 0.85 (95% confidence interval [CI] = 0.81-0.89) and 0.79 (95% CI = 0.72-0.84) for distinguishing benign and malignant breast lesions, respectively. The area under the curve (AUC) was 0.9178. No publication bias was detected (P = 0.51). In subgroup analysis, the summary sensitivity and specificity of 50th percentile ADC value were 0.81 (95% CI = 0.71-0.88) and 0.86 (95% CI = 0.74-0.94), respectively. Meta-regression analysis indicated no covariates were sources of heterogeneity (P > 0.05). Whole-lesion ADC histogram analysis demonstrated good diagnostic performance for differentiating between benign and malignant breast lesions, with 50th percentile ADC value showing higher diagnostic accuracy than other histogram parameters. Given the limited number of studies included in the analysis, the findings from our meta-analysis will need further confirmation in future research.

The Diagnostic Performance of the Length of Tumor Capsular Contact on MRI for Detecting Prostate Cancer Extraprostatic Extension: A Systematic Review and Meta-Analysis.

The purpose was to review the diagnostic performance of the length of tumor capsular contact (LCC) on magnetic resonance imaging (MRI) for detecting prostate cancer extraprostatic extension (EPE). PubMed and EMBASE databases were searched up to March 24, 2019. We included diagnostic accuracy studies that evaluated LCC on MRI for EPE detection using radical prostatectomy specimen histopathology as the reference standard. Quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled and graphically presented using hierarchical summary receiver operating characteristic (HSROC) plots. Meta-regression and subgroup analyses were conducted to explore heterogeneity. Thirteen articles with 2136 patients were included. Study quality was generally good. Summary sensitivity and specificity were 0.79 (95% confidence interval [CI] 0.73-0.83) and 0.67 (95% CI 0.60-0.74), respectively. Area under the HSROC was 0.81 (95% CI 0.77-0.84). Substantial heterogeneity was present among the included studies according to Cochran's Q-test (p < 0.01) and Higgins I² (62% and 86% for sensitivity and specificity, respectively). In terms of heterogeneity, measurement method (curvilinear vs. linear), prevalence of Gleason score ≥ 7, MRI readers' experience, and endorectal coils were significant factors (p ≤ 0.01), whereas method to determine the LCC threshold, cutoff value, magnet strength, and publication year were not (p = 0.14-0.93). Diagnostic test accuracy estimates were comparable across all assessed MRI sequences. Greater LCC on MRI is associated with a higher probability of prostate cancer EPE. Due to heterogeneity among the studies, further investigation is needed to establish the optimal cutoff value for each clinical setting.

Lead-I ECG for detecting atrial fibrillation in patients attending primary care with an irregular pulse using single-time point testing: A systematic review and economic evaluation.

BackgroundAtrial fibrillation (AF) is the most common type of cardiac arrhythmia and is associated with increased risk of stroke and congestive heart failure. Lead-I electrocardiogram (ECG) devices are handheld instruments that can detect AF at a single-time point.PurposeTo assess the diagnostic test accuracy, clinical impact and cost effectiveness of single-time point lead-I ECG devices compared with manual pulse palpation (MPP) followed by a 12-lead ECG for the detection of AF in symptomatic primary care patients with an irregular pulse.MethodsElectronic databases (MEDLINE, MEDLINE Epub Ahead of Print and MEDLINE In-Process, EMBASE, PubMed and Cochrane Databases of Systematic Reviews, Cochrane Central Database of Controlled Trials, Database of s of Reviews of Effects, Health Technology Assessment Database) were searched to March 2018. Two reviewers screened the search results, extracted data and assessed study quality. Summary estimates of diagnostic accuracy were calculated using bivariate models. Cost-effectiveness was evaluated using an economic model consisting of a decision tree and two cohort Markov models.ResultsDiagnostic accuracyThe diagnostic accuracy (13 publications reporting on nine studies) and clinical impact (24 publications reporting on 19 studies) results are derived from an asymptomatic population (used as a proxy for people with signs or symptoms of AF). The summary sensitivity of lead-I ECG devices was 93.9% (95% confidence interval [CI]: 86.2% to 97.4%) and summary specificity was 96.5% (95% CI: 90.4% to 98.8%).Cost effectivenessThe de novo economic model yielded incremental cost effectiveness ratios (ICERs) per quality adjusted life year (QALY) gained. The results of the pairwise analysis show that all lead-I ECG devices generate ICERs per QALY gained below the £20,000-£30,000 threshold. Kardia Mobile is the most cost effective option in a full incremental analysis. Lead-I ECG tests may identify more AF cases than the standard diagnostic pathway. This comes at a higher cost but with greater patient benefit in terms of mortality and quality of life.LimitationsNo published data evaluating the diagnostic accuracy, clinical impact or cost effectiveness of lead-I ECG devices for the target population are available.ConclusionsThe use of single-time point lead-I ECG devices in primary care for the detection of AF in people with signs or symptoms of AF and an irregular pulse appears to be a cost effective use of NHS resources compared with MPP followed by a 12-lead ECG, given the assumptions used in the base case model.RegistrationThe protocol for this review is registered on PROSPERO as CRD42018090375.