Imperfect Gold Standard Research Articles

Nonparametric receiver operating characteristic curve analysis with an imperfect gold standard.

This article addresses the challenge of estimating receiver operating characteristic (ROC) curves and the areas under these curves (AUC) in the context of an imperfect gold standard, a common issue in diagnostic accuracy studies. We delve into the nonparametric identification and estimation of ROC curves and AUCs when the reference standard for disease status is prone to error. Our approach hinges on the known or estimable accuracy of this imperfect reference standard and the conditional independent assumption, under which we demonstrate the identifiability of ROC curves and propose a nonparametric estimation method. In cases where the accuracy of the imperfect reference standard remains unknown, we establish that while ROC curves are unidentifiable, the sign of the difference between two AUCs is identifiable. This insight leads us to develop a hypothesis-testing method for assessing the relative superiority of AUCs. Compared to the existing methods, the proposed methods are nonparametric so that they do not rely on the parametric model assumptions. In addition, they are applicable to both the ROC/AUC analysis of continuous biomarkers and the AUC analysis of ordinal biomarkers. Our theoretical results and simulation studies validate the proposed methods, which we further illustrate through application in two real-world diagnostic studies.

The Arabic EAT-10 and FEES in dysphagia screening among cancer patients: a comparative prospective study.

Head and neck cancer treatments, such as radiotherapy, chemotherapy, and surgery, have diverse effects on patients, leading to dysphagia as a significant post-treatment issue. This study aims to evaluate the effectiveness of the Arabic version of the EAT-10 screening instrument (A-EAT-10) using Fiber-Optic Endoscopic Evaluation of Swallowing (FEES) as an imperfect gold standard. Additionally, we seek to establish a correlation between A-EAT-10 and PEG tube insertion in head and neck cancer (HNC) patients. Our sample comprised 130 head and neck cancer patients with varying cancer types at King Hussein Cancer Center (KHCC). We followed these patients throughout their distinct treatment plans up to one month after their final treatment session. During follow-up visits, we administered the A-Eat-10 instrument to monitor dysphagia. FEES were conducted at the initial and concluding visits to compare results with A-EAT-10 scores. The results in our tests, assuming independence or dependence, demonstrated excellent agreement. A-EAT-10 exhibited outstanding predictive capabilities with an AUC ranging from 93 to 97%. A-EAT-10 tended to slightly overestimate dysphagia at later treatment stages by approximately 20% compared to FEES, with an RR of 1.2 (95% CI 0.91, 1.56, p-value = 0.21), indicating statistical insignificance. In conclusion, A-EAT-10 is an excellent option for dysphagia evaluation, offering non-invasive, straightforward, and cost-effective advantages compared to FEES. Its utility extends to predicting the need for PEG tube insertion at initial patient visits, making it a valuable tool for informed treatment decisions. Notably, A-EAT-10 demonstrates a diminishing correlation with FEES over time.

Swish and gargle saliva sampling is a patient-friendly and comparable alternative to nasopharyngeal swabs to detect SARS-CoV-2 in outpatient settings for adults and children.

Nasopharyngeal swabs (NPS) are considered the standard specimen for SARS-CoV-2 detection by PCR. We aimed to compare detection performance and patient experience of NPS with swish and gargle saliva (SGS) to determine its potential as an accurate, easy-to-collect, and comfortable alternative. We conducted a prospective study from March to May 2021 and recruited pediatric and adult outpatients seeking COVID-19 testing. Paired NPS and 5-mL SGS were collected from each participant during the same visit and tested in parallel using validated rRT-PCR assays. Variant of concern (VOC) analysis was performed for positive NPS specimens. The participant completed the surveys regarding their experience with the two collection methods. We included 238 participants in the SARS-CoV-2 detection performance analysis. Thirty-two participants tested positive for both NPS and SGS. In comparison to NPS, the sensitivity and specificity of SGS to detect SARS-CoV-2 were 94.1% (95%CI; 80.3%-99.3%) and 97.1% (95%CI; 93.7%-98.9%), respectively. Six participants tested positive only with SGS and only two with NPS. NPS is an imperfect gold standard. Thus, when compared to the COVID-19 case, that is, a patient with positive NPS and/or SGS, the sensitivity for NPS and SGS were 85.0% and 95.0%, respectively. VOC results (n = 26) revealed that 92% of the cases were alpha. From the 238 surveys, 89.9% of the participants described SGS collection as comfortable or very comfortable compared to 15.1% for NPS; 90.2% of the participants were likely or very likely to return for SGS collection compared to 59.3% for NPS. SGS is an alternative to NPS for SARS-CoV-2 detection in adult and pediatric outpatients as it is more patient-friendly while still maintaining comparable performance.IMPORTANCEWidespread and frequent testing for COVID-19 was an important strategy to identify infected patients to isolate and control the spread of the disease during the pandemic. The nasopharyngeal swab (NPS) global supply chain and access to trained healthcare professionals for standard NPS collection were often compromised. Patient discomfort and limited access challenged health systems to reach large numbers for testing in adult and pediatric populations. Our study revealed that swish and gargle saliva (SGS) was comparable to NPS in detecting SARS-CoV-2 and more patient-friendly than NPS. Patients were more likely to repeat the test with SGS. SGS was amenable to self-collection instead of relying on skilled professionals. This comprehensive evaluation highlights the challenges of comparing the accuracy of new methods to imperfect gold standards and identifies additional patient-centric factors that should be considered when defining such standards. Thus, SGS is an advantageous alternative specimen collection for outpatient en masse testing.

The Challenges of Spirometric Diagnosis of COPD.

Chronic obstructive pulmonary disease (COPD) is one of the top causes of morbidity and mortality worldwide. Although for many years its accurate diagnosis has been a focus of intense research, it is still challenging. Due to its simplicity, portability, and low cost, spirometry has been established as the main tool to detect this condition, but its flawed performance makes it an imperfect COPD diagnosis gold standard. This review aims to provide an up-to-date literature overview of recent studies regarding COPD diagnosis; we seek to identify their limitations and establish perspectives for spirometric diagnosis of COPD in the XXI century by combining deep clinical knowledge of the disease with advanced computer analysis techniques.

Evaluation of Nested broad-range PCR for Pathogen Detection in Negative Blood Cultures

Background: Bloodstream infections are a major cause of morbidity and mortality among all age groups. In the laboratory, it is routinely diagnosed by performing a blood culture which is considered an imperfect gold standard. The diagnostic limitations and uncertainties of blood cultures are related to low sensitivity, particularly in antibiotic-exposed cases, and extended time for pathogen detection that increases turn-around-time of the results. An alternative and recently introduced nucleic acid amplification method for 16S rDNA, a conserved DNA sequence common to all bacteria, has gained significant. It has high sensitivity and an ability to detect organisms that are non-cultivable or nonviable owing to prior antibiotic treatment and where the organism fails to grow on a culture medium. Objectives: To determine the utility of broad-range PCR in the detection of pathogens from negative blood culture was the aim of our study. Materials and Methods: A total of 50 negative blood cultures after 5 days of incubation on BacT/Alert continuously monitored blood culture system were included in this study. From each blood broth sample, DNA was isolated which was subjected to a broad range 16S rDNA nested PCR. The PCR products obtained were visualized on agarose gel electrophoresis and the results were interpreted. Results: Broad range bacterial 16S rDNA nested PCR detected the desired amplicon in 4/50 (8%) of the blood culture-negative samples. Conclusion: The broad range bacterial nested PCR method if used in combination with routine culture techniques in clinical microbiology laboratories will increase the detection of Bloodstream pathogens.

Meta-analysis of dichotomous and ordinal tests with an imperfect gold standard.

Standard methods for the meta‐analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of dichotomous and ordinal test data from a single study, and for the meta‐analysis of dichotomous tests. However, they have not previously been used for the meta‐analysis of ordinal tests. In this article, we developed a Bayesian multivariate probit latent class model for the simultaneous meta‐analysis of ordinal and dichotomous tests without assuming a gold standard, which also allows one to obtain summary estimates of joint test accuracy. We fitted the models using the software Stan, which uses a state‐of‐the‐art Hamiltonian Monte Carlo algorithm, and we applied the models to a dataset in which studies evaluated the accuracy of tests, and test combinations, for deep vein thrombosis. We demonstrate the issues with dichotomising ordinal test accuracy data in the presence of an imperfect gold standard, before applying and comparing several variations of our proposed model which do not require the data to be dichotomised. The models proposed will allow researchers to more appropriately meta‐analyse ordinal and dichotomous tests without a gold standard, potentially leading to less biased estimates of test accuracy. This may lead to a better understanding of which tests, and test combinations, should be used for any given medical condition.

Rationale and Design of a Randomized Controlled Trial of Donor-Derived Cell-Free DNA to Detect Rejection in Cardiac Transplantation (DETECT)

<h3>Purpose</h3> Endomyocardial biopsy (EMB) for rejection surveillance in cardiac transplantation is invasive, costly, associated with complications, variable in interpretation and thus an imperfect gold standard. Donor-derived cell-free DNA (dd-cfDNA) is an emerging biomarker for detection and surveillance of cardiac allograft rejection. Elevated circulating levels of dd-cfDNA are associated with acute cellular and antibody-mediated rejection in observational studies, but a clinical strategy trial to establish its usefulness in decreasing or eliminating EMB has not been conducted. We describe the rationale and design of the randomized clinical trial, Donor-Derived Cell-free <b>D</b>NA to D<b>ET</b>ect R<b>E</b>jection in <b>C</b>ardiac <b>T</b>ransplantation (DETECT) to test the hypothesis that dd-cfDNA monitoring is non-inferior to standard of care (SOC) surveillance EMB during year 1 post-transplant. <h3>Methods</h3> DETECT is a prospective, multicenter, open-label, randomized controlled trial in 600 adult heart transplant recipients at 40 transplant centers, randomized 1:1 30 days post-transplant to surveillance with dd-cfDNA (Prospera, Natera, San Carlos, CA) (Intervention) versus EMB surveillance (SOC) and followed for 1 year. Rejection surveillance in both arms will be performed per the institution's SOC EMB surveillance schedule. <h3>Results</h3> The primary endpoint is the composite of treated rejection +/- graft dysfunction, any graft dysfunction, listing for or undergoing re-transplantation or death. Secondary endpoints include number of heart biopsies performed, development of de novo donor specific antibodies and cost of care. The study has 80% power to demonstrate non-inferiority if the primary endpoint rate in the experimental arm is no greater than 0.27 (non-inferiority margin of 0.15, assuming a control rate of 0.22). Sample size re-estimation will occur once 80% of subjects are enrolled or 50% reach 1 year follow-up, whichever occurs first in order to maintain 80% power. If the non-inferiority hypothesis is met, analysis for superiority of surveillance with dd-cfDNA will be performed. <h3>Conclusion</h3> The DETECT trial will establish the efficacy and safety of dd-cfDNA as a primary clinical monitoring strategy for cardiac allograft rejection in an effort to decrease or eliminate invasive surveillance biopsies in adult heart transplant recipients.

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.

Testing for Severe Acute Respiratory Syndrome-Coronavirus 2: Challenges in Getting Good Specimens, Choosing the Right Test, and Interpreting the Results.

We explore ways to reduce errors in laboratory diagnosis of severe acute respiratory syndrome-coronavirus 2 infection by considering preanalytic, analytic, and postanalytic sources. To address preanalytic challenges, we first consider alternative anatomic sites for specimen collection, then discuss self-collection, alternative sampling devices, and transport media. Strengths and limitations of various analytic test systems are considered in the context of postanalytic challenges associated with making test results meaningful, specifically considering the complex relationship between "positive" test results and reproduction and shedding of intact virus. Finally, we provide recommendations regarding healthcare worker surveillance and release of patients with coronavirus disease 2019 from isolation. Material was derived from a Webinar available to the public, manufacturer's websites, U.S. Food and Drug Administration, and Centers for Disease Control and Prevention websites and from both peer-reviewed papers identified by PubMed search and nonpeer-reviewed papers posted on Biorxiv and Medrxiv. Unpublished data came from the Washington State Department of Health. We included studies that compared diagnostic performance strategies without introducing bias due to use of an imperfect gold standard. Case series and case reports were included as necessary to illuminate the significance of results. Data were extracted manually. Sensitivity, specificity, and CIs were computed from article data using a composite reference standard. Nucleic acid-based tests were assumed to perform at 100% specificity. Although sputum and bronchoalveolar lavage samples provide the highest diagnostic sensitivity for severe acute respiratory syndrome-coronavirus 2, nasopharyngeal, mid turbinate, and nasal specimens are suitable in most cases and require less use of personal protective equipment. When desired sampling materials are unavailable, alternatives may be substituted with no loss of performance. Both reverse transcriptase polymerase chain reaction tests and rapid nucleic acid-based tests offer good performance in most circumstances. Testing is not required to release most patients from isolation.

Acute Kidney Injury Biomarkers: What Do They Tell Us?

The definition of acute kidney injury (AKI) is now well established and encompasses changes in both the urine output and the serum creatinine (SCr) over time. Many studies to date have concentrated solely on the SCr criteria, as this is relatively easy to monitor, given that accurate urine output is rarely measured outside critical care areas. However, many studies have emphasised the inadequacies of SCr in highlighting potential renal injury in a timely fashion. These limitations reflect not only acute changes in creatinine metabolism in the critically ill but also the kinetics of creatinine generation that may hinder early recognition of AKI. In turn, this may prevent judicious intervention promoting the misconception that little can be done for patients with this devastating condition except treating the consequences. Such observations have led to much research focused on identifying early indicators of AKI that may enable early treatment and hopefully lead to improved outcomes. This explains in part the reasoning behind the interest in biomarkers of AKI and which may see them develop a role as part of established clinical tool(s) in both the assessment of severity of AKI and the potential to assess recovery. However, much of the effort behind biomarker research has focused on the ability of such candidate molecules to predict AKI as defined by the imperfect gold standards used currently. It may be that the presence of renal biomarkers associated with renal stress or injury in isolation dictates poor outcomes and as such may provide diagnostic certainty in their own right.

Evidence of Misclassification of Drug-Event Associations Classified as Gold Standard 'Negative Controls' by the Observational Medical Outcomes Partnership (OMOP).

Pharmacovigilance includes analysis of large databases of information on drugs and events using algorithms that detect disproportional frequencies of associations. In order to test such algorithms, attempts have been made to provide canonical reference lists of so-called 'positive controls' and 'negative controls'. Reference sets with even modest levels of misclassification may result in under- or overstatement of the performance of algorithms. We sought to determine the extent to which 'negative control' drug-event pairs in the Observational Medical Outcomes Partnership (OMOP) database are misclassified We searched the medical literature for evidence of associations between drugs and events listed by OMOP as negative controls. The criteria used in OMOP to classify positive and negative controls are asymmetric; drug-event associations published only as case series or case reports are classified as positive controls if they are cited in Drug-Induced Diseases by Tisdale and Miller, but as negative controls if case series or case reports exist but are not cited in Tisdale and Miller. Of 233 drug-event pairs classified in the 2013 version of OMOP as negative controls, 21 failed to meet pre-specified OMOP adjudication criteria; in another 19 cases we found case reports, case series, or observational evidence that the drug and event are associated. Overall, OMOP misclassified, or may have misclassified, 40 (17%) of all 'negative controls.' Results from studies of the performance of signal-detection algorithms based on the OMOP gold standard should be viewed with circumspection, because imperfect gold standards may lead to under/overstatement of absolute and relative signal detection algorithm performance. Improvements to OMOP would include omitting misclassified drug-event pairs, assigning more specific event labels, and using more extensive sources of information.

A Meta-Analysis of Typhoid Diagnostic Accuracy Studies: A Recommendation to Adopt a Standardized Composite Reference.

Novel typhoid diagnostics currently under development have the potential to improve clinical care, surveillance, and the disease burden estimates that support vaccine introduction. Blood culture is most often used as the reference method to evaluate the accuracy of new typhoid tests; however, it is recognized to be an imperfect gold standard. If no single gold standard test exists, use of a composite reference standard (CRS) can improve estimation of diagnostic accuracy. Numerous studies have used a CRS to evaluate new typhoid diagnostics; however, there is no consensus on an appropriate CRS. In order to evaluate existing tests for use as a reference test or inclusion in a CRS, we performed a systematic review of the typhoid literature to include all index/reference test combinations observed. We described the landscape of comparisons performed, showed results of a meta-analysis on the accuracy of the more common combinations, and evaluated sources of variability based on study quality. This wide-ranging meta-analysis suggests that no single test has sufficiently good performance but some existing diagnostics may be useful as part of a CRS. Additionally, based on findings from the meta-analysis and a constructed numerical example demonstrating the use of CRS, we proposed necessary criteria and potential components of a typhoid CRS to guide future recommendations. Agreement and adoption by all investigators of a standardized CRS is requisite, and would improve comparison of new diagnostics across independent studies, leading to the identification of a better reference test and improved confidence in prevalence estimates.

Proceedings of the University of Pennsylvania 5th annual conference on statistical issues in clinical trials: emerging statistical issues in biomarker validation for clinical trials.

This issue of Clinical Trials contains the proceedings of the fifth in a series of symposia held at the University of Pennsylvania on current statistical issues in clinical trials. This symposium, held in spring 2012, focused on emerging statistical issues in biomarker validation for clinical trials, a topic highly relevant to the ever-increasing concerns about clinical trial efficiency While the titles of the papers in the Table are self explanatory, the presentations and panel discussions offer a very broad spectrum of viewpoints and emphases from both long-time and more recent researchers. Simple questions which create difficult statistical issues such as how to calibrate new biomarkers against imperfect gold standards; regulatory perspective on when biomarkers are ‘good’ enough to be used in clinical trials; how to quantify treatment effect explained by biomarkers subject to measurement error are addressed (see Table). Other topics include fraud in Omics biomarker validation, and the approach to assessing clinical utility along with statistical validation. Expert panels provided thoughtful commentary on the presentations, and there were provocative and insightful questions and comments from the floor; these discussions are included along with the papers. Table 2012 Conference on Emerging Statistical Issues in Biomarker Validation for Clinical Trials The Penn conference series is aimed at facilitating advances in approaches to the statistical design, implementation and analysis of clinical trials. Earlier conferences in this series focused on proof-of-concept studies and ‘go–no go’ decision making [3], development of targeted therapies [4], comparative effectiveness studies [5] and emerging statistical issues in the conduct and monitoring of clinical trials [6]

Imperfect gold standards for biomarker evaluation

Serum creatinine has been used as the diagnostic test for acute kidney injury (AKI) for decades despite having imperfect sensitivity and specificity. Novel tubular injury biomarkers may revolutionize the diagnosis of AKI; however, even if a novel tubular injury biomarker is 100% sensitive and 100% specific, it may appear inaccurate when using serum creatinine as the gold standard. In general, the apparent diagnostic performance of a biomarker depends not only on its ability to detect injury but also on disease prevalence and the sensitivity and specificity of the imperfect gold standard. Apparent errors in diagnosis using a new biomarker may be a reflection of errors in the imperfect gold standard itself rather than poor performance of the biomarker.

High-field MR-Spectroscopy (MRS) allows novel insights in alterd hepatic lipid and energy metabolism in NAFLD with potential distinction of NASH and advanced fibrosis

Background/Aims: The rising prevalence of NAFLD and the imperfect gold standard of liver biopsy calls for better diagnostic methods. We aimed to evaluate MRS as non-invasive tool also permitting novel mechanistic and pathogenetic insights into alterations of hepatocellular metabolism in NAFLD. We therefore quantified hepatocellular lipid content (HCL) by 3.0-T 1 H-MRS and 31P-metabolites by 7.0-T 31P-MRS to assess whether MRS permits a non-invasive distinction between NAFL, NASH and different fibrosis stages.

Estimating the True Accuracy of Diagnostic Tests for Dengue Infection Using Bayesian Latent Class Models

BackgroundAccuracy of rapid diagnostic tests for dengue infection has been repeatedly estimated by comparing those tests with reference assays. We hypothesized that those estimates might be inaccurate if the accuracy of the reference assays is not perfect. Here, we investigated this using statistical modeling.Methods/Principal FindingsData from a cohort study of 549 patients suspected of dengue infection presenting at Colombo North Teaching Hospital, Ragama, Sri Lanka, that described the application of our reference assay (a combination of Dengue IgM antibody capture ELISA and IgG antibody capture ELISA) and of three rapid diagnostic tests (Panbio NS1 antigen, IgM antibody and IgG antibody rapid immunochromatographic cassette tests) were re-evaluated using Bayesian latent class models (LCMs). The estimated sensitivity and specificity of the reference assay were 62.0% and 99.6%, respectively. Prevalence of dengue infection (24.3%), and sensitivities and specificities of the Panbio NS1 (45.9% and 97.9%), IgM (54.5% and 95.5%) and IgG (62.1% and 84.5%) estimated by Bayesian LCMs were significantly different from those estimated by assuming that the reference assay was perfect. Sensitivity, specificity, PPV and NPV for a combination of NS1, IgM and IgG cassette tests on admission samples were 87.0%, 82.8%, 62.0% and 95.2%, respectively.ConclusionsOur reference assay is an imperfect gold standard. In our setting, the combination of NS1, IgM and IgG rapid diagnostic tests could be used on admission to rule out dengue infection with a high level of accuracy (NPV 95.2%). Further evaluation of rapid diagnostic tests for dengue infection should include the use of appropriate statistical models.

Rapid Antigen Detection Tests for Malaria Diagnosis in Severely Ill Papua New Guinean Children: A Comparative Study Using Bayesian Latent Class Models

BackgroundAlthough rapid diagnostic tests (RDTs) have practical advantages over light microscopy (LM) and good sensitivity in severe falciparum malaria in Africa, their utility where severe non-falciparum malaria occurs is unknown. LM, RDTs and polymerase chain reaction (PCR)-based methods have limitations, and thus conventional comparative malaria diagnostic studies employ imperfect gold standards. We assessed whether, using Bayesian latent class models (LCMs) which do not require a reference method, RDTs could safely direct initial anti-infective therapy in severe ill children from an area of hyperendemic transmission of both Plasmodium falciparum and P. vivax. Methods and FindingsWe studied 797 Papua New Guinean children hospitalized with well-characterized severe illness for whom LM, RDT and nested PCR (nPCR) results were available. For any severe malaria, the estimated prevalence was 47.5% with RDTs exhibiting similar sensitivity and negative predictive value (NPV) to nPCR (≥96.0%). LM was the least sensitive test (87.4%) and had the lowest NPV (89.7%), but had the highest specificity (99.1%) and positive predictive value (98.9%). For severe falciparum malaria (prevalence 42.9%), the findings were similar. For non-falciparum severe malaria (prevalence 6.9%), no test had the WHO-recommended sensitivity and specificity of >95% and >90%, respectively. RDTs were the least sensitive (69.6%) and had the lowest NPV (96.7%).ConclusionsRDTs appear a valuable point-of-care test that is at least equivalent to LM in diagnosing severe falciparum malaria in this epidemiologic situation. None of the tests had the required sensitivity/specificity for severe non-falciparum malaria but the number of false-negative RDTs in this group was small.

Measuring urinary tubular biomarkers in type 2 diabetes does not add prognostic value beyond established risk factors

Tubulointerstitial disease plays an important role in the pathophysiology of diabetic kidney disease. To determine whether biomarkers of tubular injury could predict renal outcome and mortality in patients with type 2 diabetes, we measured urinary levels of kidney injury molecule-1 (KIM-1) and glycoprotein non-metastatic melanoma B (Gpnmb), both normalized to the urinary creatinine, in 978 individuals from the Edinburgh Type 2 Diabetes Study. At baseline, 238 patients had an estimated glomerular filtration rate (eGFR) below 60 ml/min/1.73 m2 while 147 and 15 patients had microalbuminuria or overt proteinuria, respectively. Both the urine KIM-1 and Gpnmb to creatinine ratios correlated with the urinary albumin to creatinine ratio, the duration of diabetes, and the stringency of glycemic control but not with blood pressure or baseline eGFR. Higher ratios of each marker were associated with a faster decline in kidney function during 4 years of follow-up; however, this was not independent of the urinary albumin to creatinine ratio. Higher KIM-1, but not Gpnmb ratios were associated with an increased risk of mortality, but this association was no longer significant after adjustment for other risk factors, in particular albuminuria. Thus, tubular injury in persons with type 2 diabetes may contribute to the decline in kidney function; however, measuring the urinary concentration of these two tubular biomarkers does not confer additional prognostic information beyond established risk factors.

Evaluation of a Typhoid IgM flow assay for the diagnosis of typhoid fever in Cambodian children using a Bayesian modelling approach assuming an imperfect gold standard

Evaluation of a Typhoid IgM flow assay for the diagnosis of typhoid fever in Cambodian children using a Bayesian modelling approach assuming an imperfect gold standard

Evaluation of Screening Tests for Detecting Chlamydia trachomatis

In recent years, the evaluation of nucleic acid amplification tests (NAATs) for detecting Chlamydia trachomatis and Neisseria gonorrhea is based on a methodology called the patient-infected-status algorithm (PISA). In the simplest version of PISA, 4 test-specimen combinations (comparator tests) are used to define the gold standard. If a person shows a positive result by any 2 or more of these 4 comparator tests, the person is classified as infected; otherwise, the person is considered to be uninfected. A new test is then compared with this diagnostic algorithm. PISA-based sensitivity and specificity estimates of nucleic acid amplification tests have been published in the medical and microbiologic literature and have been included in FDA-approved package inserts of NAATs for detecting C. trachomatis. Using simulations, we compare 2 versions of the patient-infected-status algorithm with latent-class models and an imperfect gold standard. We show that the PISA can produce highly biased test-performance parameter estimates. In a series of simulated scenarios, none of the 95% confidence intervals for PISA-based estimates of sensitivity and prevalence contained the true values. In addition, the PISA-based estimates of sensitivity and specificity change markedly as the true prevalence changes. We recommend that PISA should not be used for estimating the sensitivity and specificity of tests.