Advances in the Diagnosis of Endemic Treponematoses: Yaws,Bejel, and Pinta

Improved understanding of the differential diagnosis of endemic treponematoses is needed to inform clinical practice and to ensure the best outcome for a new global initiative for the eradication of yaws, bejel, and pinta. Traditionally, the human treponematoses have been differentiated based upon their clinical manifestations and epidemiologic characteristics because the etiologic agents are indistinguishable in the laboratory. Serological tests are still considered standard laboratory methods for the diagnosis of endemic treponematoses and new rapid point-of-care treponemal tests have become available which are extremely useful in low-resource settings. In the past ten years, there has been an increasing effort to apply polymerase chain reaction to treponematoses and whole genome fingerprinting techniques have identified genetic signatures that can differentiate the existing treponemal strains; however, definitive diagnosis is also hampered by widespread unavailability of molecular diagnostics. We review the dilemmas in the diagnosis of endemic treponematoses, and advances in the discovery of new diagnostic tools.     

Bayesian latent class models for identifying canine visceral leishmaniosis using diagnostic tests in the absence of a gold standard

BackgroundLike many infectious diseases, there is no practical gold standard for diagnosing clinical visceral leishmaniasis (VL). Latent class modeling has been proposed to estimate a latent gold standard for identifying disease. These proposed models for VL have leveraged information from diagnostic tests with dichotomous serological and PCR assays, but have not employed continuous diagnostic test information.Methods/Principal findingsIn this paper, we employ Bayesian latent class models to improve the identification of canine visceral leishmaniasis using the dichotomous PCR assay and the Dual Path Platform (DPP) serology test. The DPP test has historically been used as a dichotomous assay, but can also yield numerical information via the DPP reader. Using data collected from a cohort of hunting dogs across the United States, which were identified as having either negative or symptomatic disease, we evaluate the impact of including numerical DPP reader information as a proxy for immune response. We find that inclusion of DPP reader information allows us to illustrate changes in immune response as a function of age.Conclusions/SignificanceUtilization of continuous DPP reader information can improve the correct discrimination between individuals that are negative for disease and those with clinical VL. These models provide a promising avenue for diagnostic testing in contexts with multiple, imperfect diagnostic tests. Specifically, they can easily be applied to human visceral leishmaniasis when diagnostic test results are available. Also, appropriate diagnosis of canine visceral leishmaniasis has important consequences for curtailing spread of disease to humans.     

Validation and Quality Control of Protein Microarray-based Analytical Methods

Protein microarray technology is used mainly in the research laboratory and it is being used to uncover important diagnostic and prognostic markers that may one day emerge as routine clinical laboratory tests. It is important that these methods are subject to control procedures, in order to ensure that data of the highest quality are obtained. If quality is not controlled, the assay may yield erroneous results that would mask or confound meaningful diagnostic or prognostic associations. This chapter surveys the range of strategies designed to assure the analytical quality of protein microarray methods and it also highlights some of the potential pitfalls when moving these arrays into routine clinical practice. With the development of appropriate quality control and assurance measures, we anticipate protein microarray-based assays will be of substantial benefit in the future practice of laboratory medicine.     

Insights into latent class analysis of diagnostic test performance

Latent class analysis is used to assess diagnostic test accuracy when a gold standard assessment of disease is not available but results of multiple imperfect tests are. We consider the simplest setting, where 3 tests are observed and conditional independence (CI) is assumed. Closed-form expressions for maximum likelihood parameter estimates are derived. They show explicitly how observed 2- and 3-way associations between test results are used to infer disease prevalence and test true- and false-positive rates. Although interesting and reasonable under CI, the estimators clearly have no basis when it fails. Intuition for bias induced by conditional dependence follows from the analytic expressions. Further intuition derives from an Expectation Maximization (EM) approach to calculating the estimates. We discuss implications of our results and related work for settings where more than 3 tests are available. We conclude that careful justification of assumptions about the dependence between tests in diseased and nondiseased subjects is necessary in order to ensure unbiased estimates of prevalence and test operating characteristics and to provide these estimates clinical interpretations. Such justification must be based in part on a clear clinical definition of disease and biological knowledge about mechanisms giving rise to test results.     

Pathology: coming in from the cold

Following the UK’s organ retention scandals that occurred a decade ago, politicians unleashed a deluge of well-intentioned but naïve and unnecessarily burdensome regulations that have progressively stymied human tissue-based research, stifling development of improved diagnostic and prognostic tests as well as discovery of new treatments based on sound knowledge of human-specific biology. For the UK to maintain a leading role in medical research, more sensible levels of regulation need to be introduced that recognise differences between tissue from donors who have passed-away and surgical tissue that is surplus to diagnostic requirements and that otherwise will be incinerated. While it is important to reassure the public that research using their tissues will be conducted within an approved ethical framework, it is equally important to ensure that, as hospital staff and academic researchers, we are able to fulfil our unwritten covenant with patients to do our utmost to seek better diagnostic assays and more predictive prognostic indicators, while collaborating with our colleagues in academia and industry and hence bring hope to patients with illnesses for which no effective treatments are yet available. There is a clear case for introducing an opt-out system as the default to allow all surplus surgical tissues to be immediately available for research, concomitant with an education campaign. This is the optimal and most ethical approach to ensure the wishes of the vast majority of patients are respected by allowing their residual surgical tissues and relevant clinical information to be made available for research without the current levels of obstruction and hindrance.     

A Systematic Review of the Screening Accuracy of the HIV Dementia Scale and International HIV Dementia Scale

Background

The HIV Dementia Scale (HDS) and International HIV Dementia Scale (IHDS) are brief tools that have been developed to screen for and aid diagnosis of HIV-associated dementia (HAD). They are increasingly being used in clinical practice for minor neurocognitive disorder (MND) as well as HAD, despite uncertainty about their accuracy.

Methods and Findings

A systematic review of the accuracy of the HDS and IHDS was conducted. Studies were assessed on Standards for Reporting Diagnostic Accuracy criteria. Pooled sensitivity, specificity, likelihood ratios (LR) and diagnostic odds ratios (DOR) were calculated for each scale as a test for HAD or MND. We retrieved 15 studies of the HDS, 10 of the IHDS, and 1 of both scales. Thirteen studies of the HDS were conducted in North America, and 7 of the IHDS studies were conducted in sub-Saharan Africa. Estimates of accuracy were highly heterogeneous between studies for the HDS but less so for the IHDS. Pooled DOR for the HDS was 7.52 (95% confidence interval 3.75–15.11), sensitivity and specificity for HAD were estimated at 68.1% and 77.9%, and sensitivity and specificity for MND were estimated at 42.0% and 91.2%. Pooled DOR for the IHDS was 3.49 (2.12–5.73), sensitivity and specificity for HAD were 74.3% and 54.7%, and sensitivity and specificity for MND were 64.3% and 66.0%.

Conclusion

Both scales were low in accuracy. The literature is limited by the lack of a gold standard, and variation in estimates of accuracy is likely to be due to differences in reference standard. There is a lack of studies comparing both scales, and they have been studied in different populations, but the IHDS may be less specific than the HDS. These rapid tests are not recommended for diagnostic use, and further research is required to inform their use in asymptomatic screening.     

Landscape analysis of NTD diagnostics and considerations on the development of a strategy for regulatory pathways

Access to quality-assured, accurate diagnostics is critical to ensure that the 2021–2030 neglected tropical disease (NTD) road map targets can be achieved. Currently, however, there is limited regulatory oversight and few quality assurance mechanisms for NTD diagnostic tools. In attempting to address such challenges and the changing environment in regulatory requirements for diagnostics, a landscape analysis was conducted, to better understand the availability of NTD diagnostics and inform future regulatory frameworks. The list of commercially available diagnostics was compiled from various sources, including WHO guidance, national guidelines for case detection and management, diagnostic target product profiles and the published literature. The inventory was analyzed according to diagnostic type, intended use, regulatory status, and risk classification. To estimate the global need and size of the market for each type of diagnostic, annual procurement data were collected from WHO, procurement agencies, NGOs and international organizations, where available and global disease prevalence. Expert interviews were also conducted to ensure a better understanding of how diagnostics are procured and used. Of 125 diagnostic tools included in this analysis, rapid diagnostic tools accounted for 33% of diagnostics used for NTDs and very few diagnostics had been subjected to regulatory assessment. The number of tests needed for each disease was less than 1 million units per annum, except in the case of two diseases, suggesting limited commercial value. Despite the nature of the market, and presumed insufficient return on commercial investment, acceptable levels of assurance on performance, quality and safety of diagnostics are still required. Priority actions include setting up an agile, interim, stepwise risk assessment mechanism, in particular for diagnostics of lower risk, in order to support national NTD programmes and their partners with the selection and procurement of the diagnostics needed to control, eliminate and eradicate NTDs.     

Bayesian sample size determination for prevalence and diagnostic test studies in the absence of a gold standard test

Planning studies involving diagnostic tests is complicated by the fact that virtually no test provides perfectly accurate results. The misclassification induced by imperfect sensitivities and specificities of diagnostic tests must be taken into account, whether the primary goal of the study is to estimate the prevalence of a disease in a population or to investigate the properties of a new diagnostic test. Previous work on sample size requirements for estimating the prevalence of disease in the case of a single imperfect test showed very large discrepancies in size when compared to methods that assume a perfect test. In this article we extend these methods to include two conditionally independent imperfect tests, and apply several different criteria for Bayesian sample size determination to the design of such studies. We consider both disease prevalence studies and studies designed to estimate the sensitivity and specificity of diagnostic tests. As the problem is typically nonidentifiable, we investigate the limits on the accuracy of parameter estimation as the sample size approaches infinity. Through two examples from infectious diseases, we illustrate the changes in sample sizes that arise when two tests are applied to individuals in a study rather than a single test. Although smaller sample sizes are often found in the two-test situation, they can still be prohibitively large unless accurate information is available about the sensitivities and specificities of the tests being used.     

Transfer of manualized CBT for social phobia into clinical practice (SOPHO-PRAX): a study protocol for a cluster-randomized controlled trial

ABSTRACT: BACKGROUND: Cognitive-behavioral therapy (CBT) is generally known to be efficacious in the treatment of social phobia when applied in RCT's, namely when the treatment manual is based on the Clark-Wells approach. However, little is known about the efficacy of manualized treatments in routine clinical practice (Phase IV of psychotherapy research). The present study (SOPHO-PRAX) is a continuation of a large multi-centre randomized clinical trial (SOPHO-NET) and analyses the extent to which additional training practitioners in manualized procedures enhances treatment effect. METHODS: N = 36 private practitioners will be included in three treatment centres and randomly designated to either training in manualized CBT or no specific training. The treatment effects of the therapies conducted by both groups of therapists will be compared. A total of 162 patients (N = 116 completers; N = 58 per condition) will be enrolled. Liebowitz Social Anxiety Scale (LSAS) will serve as primary outcome measure. Remission from social phobia is defined as LSAS total [less than or equal to] 30 points. Data will be collected at treatment begin, after 8, 15, and 25 sessions (50 mins. each), at treatment completion, as well at 6 and 12 months post-treatment. DISCUSSION: The present CBT trial combines elements of randomized-controlled trials and naturalistic studies in an innovative way. It will directly inform about the incremental effects of procedures established in a controlled trial into clinical practice. Study results are relevant to health care decisions and policy. They may serve to improve quality of treatment, and shorten the timeframe between the development and widespread dissemination of effective methods, thereby reducing health cost expenditures. The results of this study will not only inform about the degree to which the new methods lead to an improvement of treatment course and outcome, but also about whether the effects of routine psychotherapeutic treatment are comparable to those of the controlled, strictly manualized treatments of the SOPHO-NET study. Trial Registration: ClinicalTrials.gov identifier: NCT01388231. This study was funded by the German Federal Ministry of Education and Research (SOPHO-NET: BMBF 01GV0607; SOPHO-PRAX: BMBF 01GV1001).     

Diagnostic Accuracy and Optimal Use of Three Tests for Tuberculosis in Live Badgers

Background

Accurate diagnosis of tuberculosis (TB) due to infection with Mycobacterium bovis is notoriously difficult in live animals, yet important if we are to understand the epidemiology of TB and devise effective strategies to limit its spread. Currently available tests for diagnosing TB in live Eurasian badgers (Meles meles) remain unvalidated against a reliable gold standard. The aim of the present study was to evaluate the diagnostic accuracy and optimal use of three tests for TB in badgers in the absence of a gold standard.

Methodology/Principal Findings

A Bayesian approach was used to evaluate the diagnostic accuracy and optimal use of mycobacterial culture, gamma-interferon assay and a commercially available serological test using multiple samples collected from 305 live wild badgers. Although no single test was judged to be sufficiently sensitive and specific to be used as a sole diagnostic method, selective combined use of the three tests allowed guidelines to be formulated that allow a diagnosis to be made for individual animals with an estimated overall accuracy of 93% (range: 75% to 97%). Employing this approach in the study population of badgers resulted in approximately 13 out of 14 animals having their true infection status correctly classified from samples collected on a single capture.

Conclusions/Significance

This method of interpretation represents a marked improvement on the current procedure for diagnosing M. bovis infection in live badgers. The results should be of use to inform future test and intervention strategies with the aim of reducing the incidence of TB in free-living wild badger populations.     

Interpretation of diagnostic data: 5. How to do it with simple maths.

The use of simple maths with the likelihood ratio strategy fits in nicely with our clinical views. By making the most out of the entire range of diagnostic test results (i.e., several levels, each with its own likelihood ratio, rather than a single cut-off point and a single ratio) and by permitting us to keep track of the likelihood that a patient has the target disorder at each point along the diagnostic sequence, this strategy allows us to place patients at an extremely high or an extremely low likelihood of disease. Thus, the numbers of patients with ultimately false-positive results (who suffer the slings of labelling and the arrows of needless therapy) and of those with ultimately false-negative results (who therefore miss their chance for diagnosis and, possibly, efficacious therapy) will be dramatically reduced. The following guidelines will be useful in interpreting signs, symptoms and laboratory tests with the likelihood ratio strategy: Seek out, and demand from the clinical or laboratory experts who ought to know, the likelihood ratios for key symptoms and signs, and several levels (rather than just the positive and negative results) of diagnostic test results. Identify, when feasible, the logical sequence of diagnostic tests. Estimate the pretest probability of disease for the patient, and, using either the nomogram or the conversion formulas, apply the likelihood ratio that corresponds to the first diagnostic test result. While remembering that the resulting post-test probability or odds from the first test becomes the pretest probability or odds for the next diagnostic test, repeat the process for all the pertinent symptoms, signs and laboratory studies that pertain to the target disorder. However, these combinations may not be independent, and convergent diagnostic tests, if treated as independent, will combine to overestimate the final post-test probability of disease. You are now far more sophisticated in interpreting diagnostic tests than most of your teachers. In the last part of our series we will show you some rather complex strategies that combine diagnosis and therapy, quantify our as yet nonquantified ideas about use, and require the use of at least a hand calculator.     

Outcome of coronary plaque burden: a 10-year follow-up of aggressive medical management

Estimation of left ventricular (LV) mass has both prognostic and therapeutic value independent of traditional risk factors. Unfortunately, LV mass evaluation has been underestimated in clinical practice. Assessment of LV mass can be performed by a number of imaging modalities. Despite inherent limitations, conventional echocardiography has fundamentally been established as most widely used diagnostic tool. 3-dimensional echocardiography (3DE) is now feasible, fast and accurate for LV mass evaluation. 3DE is also superior to conventional echocardiography in terms of LV mass assessment, especially in patients with abnormal LV geometry. Cardiovascular magnetic resonance (CMR) and cardiovascular computed tomography (CCT) are currently performed for LV mass assessment and also do not depend on cardiac geometry and display 3-dimensional data, as well. Therefore, CMR is being increasingly employed and is at the present standard of reference in the clinical setting. Although each method demonstrates advantages over another, there are also disadvantages to receive attention. Diagnostic accuracy of methods will also be increased with the introduction of more advanced systems. It is also likely that in the coming years new and more accurate diagnostic tests will become available. In particular, CMR and CCT have been intersecting hot topic between cardiology and radiology clinics. Thus, good communication and collaboration between two specialties is required for selection of an appropriate test.     

Nonparametric estimation of ROC curves in the absence of a gold standard

In the evaluation of diagnostic accuracy of tests, a gold standard on the disease status is required. However, in many complex diseases, it is impossible or unethical to obtain such a gold standard. If an imperfect standard is used, the estimated accuracy of the tests would be biased. This type of bias is called imperfect gold standard bias. In this article we develop a nonparametric maximum likelihood method for estimating ROC curves and their areas of ordinal-scale tests in the absence of a gold standard. Our simulation study shows that the proposed estimators for the ROC curve areas have good finite-sample properties in terms of bias and mean squared error. Further simulation studies show that our nonparametric approach is comparable to the binormal parametric method, and is easier to implement. Finally, we illustrate the application of the proposed method in a real clinical study on assessing the accuracy of seven specific pathologists in detecting carcinoma in situ of the uterine cervix.     

Proteomics: from basic research to diagnostic application. A review of requirements & needs

For several years proteomics research has been expected to lead to the finding of new markers that will translate into clinical tests applicable to samples such as serum, plasma and urine: so-called in vitro diagnostics (IVDs). Attempts to implement technologies applied in proteomics, in particular protein arrays and surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS), as IVD instruments have initiated constructive discussions on opportunities and challenges inherent in such a translation process also with respect to the use of multi-marker profiling approaches and pattern signatures in IVD. Taking into account the role that IVD plays in health care, we describe IVD requirements and needs. Subject to stringent costs versus benefit analyses, IVD has to provide reliable information about a person's condition, prognosis or risk to suffer a disease, thus supporting decisions on treatment or prevention. It is mandatory to fulfill requirements in routine IVD, including disease prevention, diagnosis, prognosis, and treatment monitoring or follow up among others. To fulfill IVD requirements, it is essential to (1) provide diagnostic tests that allow for definite and reliable diagnosis tied to a decision on interventions (prevention, treatment, or nontreatment), (2) meet stringent performance characteristics for each analyte (in particular test accuracy, including both precision of the measurement and trueness of the measurement), and (3) provide adequate diagnostic accuracy, i.e., diagnostic sensitivity and diagnostic specificity, determined by the desired positive and negative predictive values which depend on disease frequency. The fulfillment of essential IVD requirements is mandatory in the regulated environment of modern diagnostics. Addressing IVD needs at an early stage can support a timely and effective transition of findings and developments into routine diagnosis. IVD needs reflect features that are useful in clinical practice. This helps to generate acceptance and assists the implementation process. On the basis of IVD requirements and needs, we outline potential implications for clinical proteomics focused on applied research activities.     

Clinical examination,xeromammography, and fine-needle aspiration cytology in diagnosis of breast tumours.

The diagnostic accuracy of clinical examination, xeromammography, and fine-needle aspiration cytology was compared with definitive histological findings in 255 breast lumps excised during one year. When suitable aspirates were obtained for cytological examination the diagnostic accuracy of aspiration cytology was higher than clinical examination or xeromammography. A diagnostic accuracy of 99% was achieved when all three screening tests were in agreement. As well as confirming a clinical diagnosis of malignancy, cytology is useful in identifying malignancy when clinical findings suggest that the tumour is benign. The availability of accurate cytology has affected patient management in many ways. Xeromammography did not enhance the diagnostic accuracy of clinical examination and aspiration cytology in patients presenting with a breast lump and, as a procedure with potential hazard, the benefit of routine xeromammography is questionable when an efficient cytological service is available.     

A framework for clinical evaluation of diagnostic technologies.

Most new diagnostic technologies have not been adequately assessed to determine whether their application improves health. Comprehensive evaluation of diagnostic technologies includes establishing technologic capability and determining the range of possible uses, diagnostic accuracy, impact on the health care provider, therapeutic impact and impact on patient outcome. Guidelines to determine whether each of these criteria have been met adequately are presented. Diagnostic technologies should be disseminated only if they are less expensive, produce fewer untoward effects and are at least as accurate as existing methods, if they eliminate the need for other investigations without loss of accuracy, or if they lead to institution of effective therapy. Establishing patient benefit often requires a randomized controlled trial in which patients receive the new test or an alternative diagnostic strategy. Other study designs are logistically less difficult but may not provide accurate assessment of benefit. Rigorous assessment of diagnostic technologies is needed for efficient use of health care resources.     

Defining the True Sensitivity of Culture for the Diagnosis of Melioidosis Using Bayesian Latent Class Models

Background

Culture remains the diagnostic gold standard for many bacterial infections, and the method against which other tests are often evaluated. Specificity of culture is 100% if the pathogenic organism is not found in healthy subjects, but the sensitivity of culture is more difficult to determine and may be low. Here, we apply Bayesian latent class models (LCMs) to data from patients with a single Gram-negative bacterial infection and define the true sensitivity of culture together with the impact of misclassification by culture on the reported accuracy of alternative diagnostic tests.

Methods/Principal Findings

Data from published studies describing the application of five diagnostic tests (culture and four serological tests) to a patient cohort with suspected melioidosis were re-analysed using several Bayesian LCMs. Sensitivities, specificities, and positive and negative predictive values (PPVs and NPVs) were calculated. Of 320 patients with suspected melioidosis, 119 (37%) had culture confirmed melioidosis. Using the final model (Bayesian LCM with conditional dependence between serological tests), the sensitivity of culture was estimated to be 60.2%. Prediction accuracy of the final model was assessed using a classification tool to grade patients according to the likelihood of melioidosis, which indicated that an estimated disease prevalence of 61.6% was credible. Estimates of sensitivities, specificities, PPVs and NPVs of four serological tests were significantly different from previously published values in which culture was used as the gold standard.

Conclusions/Significance

Culture has low sensitivity and low NPV for the diagnosis of melioidosis and is an imperfect gold standard against which to evaluate alternative tests. Models should be used to support the evaluation of diagnostic tests with an imperfect gold standard. It is likely that the poor sensitivity/specificity of culture is not specific for melioidosis, but rather a generic problem for many bacterial and fungal infections.     

Estimating Diagnostic Accuracy of Raters Without a Gold Standard by Exploiting a Group of Experts

Summary In diagnostic medicine, estimating the diagnostic accuracy of a group of raters or medical tests relative to the gold standard is often the primary goal. When a gold standard is absent, latent class models where the unknown gold standard test is treated as a latent variable are often used. However, these models have been criticized in the literature from both a conceptual and a robustness perspective. As an alternative, we propose an approach where we exploit an imperfect reference standard with unknown diagnostic accuracy and conduct sensitivity analysis by varying this accuracy over scientifically reasonable ranges. In this article, a latent class model with crossed random effects is proposed for estimating the diagnostic accuracy of regional obstetrics and gynaecological (OB/GYN) physicians in diagnosing endometriosis. To avoid the pitfalls of models without a gold standard, we exploit the diagnostic results of a group of OB/GYN physicians with an international reputation for the diagnosis of endometriosis. We construct an ordinal reference standard based on the discordance among these international experts and propose a mechanism for conducting sensitivity analysis relative to the unknown diagnostic accuracy among them. A Monte Carlo EM algorithm is proposed for parameter estimation and a BIC‐type model selection procedure is presented. Through simulations and data analysis we show that this new approach provides a useful alternative to traditional latent class modeling approaches used in this setting.     

New approaches for reconstructing phylogenies from gene order data

We report on new techniques we have developed for reconstructing phylogenies on whole genomes. Our mathematical techniques include new polynomial-time methods for bounding the inversion length of a candidate tree and new polynomial-time methods for estimating genomic distances which greatly improve the accuracy of neighbor-joining analyses. We demonstrate the power of these techniques through an extensive performance study based on simulating genome evolution under a wide range of model conditions. Combining these new tools with standard approaches (fast reconstruction with neighbor-joining, exploration of all possible refinements of strict consensus trees, etc.) has allowed us to analyze datasets that were previously considered computationally impractical. In particular, we have conducted a complete phylogenetic analysis of a subset of the Campanulaceae family, confirming various conjectures about the relationships among members of the subset and about the principal mechanism of evolution for their chloroplast genome. We give representative results of the extensive experimentation we conducted on both real and simulated datasets in order to validate and characterize our approaches. We find that our techniques provide very accurate reconstructions of the true tree topology even when the data are generated by processes that include a significant fraction of transpositions and when the data are close to saturation.     

Assessing strength of evidence in diagnostic tests

Clinical encounters between clinicians and patients begin with an attempt at diagnosis, a foundational element in determining a patient's ultimate outcome. Diagnosis that is expedient and accurate will result in a treatment that is expedient, appropriate, and cost-effective. In essence, evidence-based diagnosis is as vital as evidence-based intervention and treatment. If surgeons are committed to making expedient and accurate diagnoses, they must strive to apply diagnostic tests not just on the basis of ease, novelty, or availability but for the soundness of evidence behind them. In the scopes of both aesthetic and reconstructive surgery, advocating evidence-driven diagnostic test use is relevant. A pertinent example of how this relates to plastic surgery is the U.S. Food and Drug Administration recommendation to screen asymptomatic women with silicone breast implants with magnetic resonance imaging. For an important recommendation such as this that has tremendous cost implications to patients, sound study design and rigorous evaluation of the accuracy of magnetic resonance imaging as a screening tool has important health policy implications. The authors demonstrate how to determine the accuracy of diagnostic tests and, more importantly, illustrate the essential qualities of any study to establish the accuracy of a diagnostic test.