David E. Bruns

The STARD Statement for Reporting Studies of Diagnostic Accuracy: Explanation and Elaboration

The quality of reporting of studies of diagnostic accuracy is less than optimal. Complete and accurate reporting is necessary to enable readers to assess the potential for bias in the study and to evaluate the generalizability of the results. A group of scientists and editors has developed the STARD (Standards for Reporting of Diagnostic Accuracy) statement to improve the reporting the quality of reporting of studies of diagnostic accuracy. The statement consists of a checklist of 25 items and flow diagram that authors can use to ensure that all relevant information is present. This explanatory document aims to facilitate the use, understanding, and dissemination of the checklist. The document contains a clarification of the meaning, rationale, and optimal use of each item on the checklist, as well as a short summary of the available evidence on bias and applicability. The STARD statement, checklist, flowchart, and this explanation and elaboration document should be useful resources to improve reporting of diagnostic accuracy studies. Complete and informative reporting can only lead to better decisions in health care.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. APPROACH An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence Based Laboratory Medicine Committee of the AACC jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. CONTENT In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (Hb A(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of Hb A(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. SUMMARY The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.

The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration.

Introduction In studies of diagnostic accuracy, results from one or more tests are compared with the results obtained with the reference standard on the same subjects. Such accuracy studies are a vital step in the evaluation of new and existing diagnostic technologies (1, 2). Several factors threaten the internal and external validity of a study of diagnostic accuracy (3-8). Some of these factors have to do with the design of such studies, others with the selection of patients, the execution of the tests, or the analysis of the data. In a study involving several meta-analyses a number of design deficiencies were shown to be related to overly optimistic estimates of diagnostic accuracy (9). Exaggerated results from poorly designed studies can trigger premature adoption of diagnostic tests and can mislead physicians to incorrect decisions about the care for individual patients. Reviewers and other readers of diagnostic studies must therefore be aware of the potential for bias and a possible lack of applicability. A survey of studies of diagnostic accuracy published in four major medical journals between 1978 and 1993 revealed that the methodological quality was mediocre at best (8). Furthermore, this review showed that information on key elements of design, conduct, and analysis of diagnostic studies was often not reported (8). To improve the quality of reporting of studies of diagnostic accuracy the Standards for Reporting of Diagnostic Accuracy (STARD) initiative was started. The objective of the STARD initiative is to improve the quality of reporting of studies of diagnostic accuracy. Complete and accurate reporting allows the reader to detect the potential for bias in the study and to judge the generalizability and applicability of the results. For this purpose, the STARD project group has developed a single-page checklist. Where possible, the decision to include items in the checklist was based on evidence linking these items to bias, variability in results, or limitations of the applicability of results to other settings. The checklist can be used to verify that all essential elements are included in the report of a study. This explanatory document aims to facilitate the use, understanding, and dissemination of the checklist. The document contains a clarification of the meaning, rationale, and optimal use of each item on the checklist, as well as a short summary of the available evidence on bias and applicability. The first part of this document contains a summary of the design and terminology of diagnostic accuracy studies. The second part contains an item-by-item discussion with examples. Studies of Diagnostic Accuracy Studies of diagnostic accuracy have a common basic structure (10). One or more tests are evaluated, with the purpose of detecting or predicting a target condition. The target condition can refer to a particular disease, a disease stage, a health status, or any other identifiable condition within a patient, such as staging a disease already known to be present, or a health condition that should prompt clinical action, such as the initiation, modification, or termination of treatment. Here test refers to any method for obtaining additional information on a patients health status. This includes laboratory tests, imaging tests, function tests, pathology, history, and physical examination. In a diagnostic accuracy study, the test under evaluationreferred to here as the index testis applied to a series of subjects. The results obtained with the index test are compared with the results of the reference standard, obtained in the same subjects. In this framework, the reference standard is the best available method for establishing the presence or absence of the target condition. The reference standard can be a single test, or a combination of methods and techniques, including clinical follow-up of tested subjects. The term accuracy refers to the amount of agreement between the results from the index test and those from the reference standard. Diagnostic accuracy can be expressed in a number of ways, including sensitivityspecificity pairs, likelihood ratios, diagnostic odds ratios, and areas under ROC [receiver-operating characteristic] curves (11, 12). Study Question, Design, and Potential for Bias Early in the evaluation of a test, the author may simply want to know if the test is able to discriminate. The appropriate early question may be Do the test results in patients with the target condition differ from the results in healthy people? If preliminary studies answer this question affirmatively, the next study question is, Are patients with specific test results more likely to have the target disorder than similar patients with other test results? The usual study design to answer this is to apply the index test and the reference standard to a number of patients who are suspected of the target condition. Some study designs are more prone to bias and have a more limited applicability than others. In this article, the term bias refers to difference between the observed measures of test performance and the true measures. No single design is guaranteed to be both feasible and able to provide valid, informative, and relevant answers with optimal precision to all study questions. For each study, the reader must judge the relevance, the potential for bias, and the limitations to applicability, making full and transparent reporting critical. For this reason, checklist items refer to the research question that prompted the study of diagnostic accuracy and ask for an explicit and complete description of the study design and results. Variability Measures of test accuracy may vary from study to study. Variability may reflect differences in patient groups, differences in setting, differences in definition of the target condition, and differences in test protocols or in criteria for test positivity (13). For example, bias may occur if a test is evaluated under circumstances that do not correspond to those of the research question. Examples are evaluating a screening test for early disease in patients with advanced stages of the disease and evaluating a physicians office test device in the specialty department of a university hospital. The checklist contains a number of items to make sure that a study report contains a clear description of the inclusion criteria for patients, the testing protocols and the criteria for positivity, as well as an adequate account of subjects included in the study and their results. These items will enable readers to judge if the study results apply to their circumstances. Items in the Checklist The next section contains a point-by-point discussion of the items on the checklist. The order of the items corresponds to the sequence used in many publications of diagnostic accuracy studies. Specific requirements made by journals could lead to a different order. Item 1. Identify the Article as a Study of Diagnostic Accuracy (Recommend MeSH Heading Sensitivity and Specificity) Example (an Excerpt from a Structured Abstract) Purpose: To determine the sensitivity and specificity of computed tomographic colonography for colorectal polyp and cancer detection by using colonoscopy as the reference standard (14). Electronic databases have become indispensable tools to identify studies. To facilitate retrieval of their study, authors should explicitly identify it as a report of a study of diagnostic accuracy. We recommend the use of the term diagnostic accuracy in the title or abstract of a report that compares the results of one or more index tests with the results of a reference standard. In 1991 the National Library of Medicines MEDLINE database introduced a specific keyword (MeSH heading) for diagnostic studies: Sensitivity and Specificity. Using this keyword to search for studies of diagnostic accuracy remains problematic (15-19). In a selected set of MEDLINE journals covering publications between 1992 through 1995, the use of the MeSH heading Sensitivity and Specificity identified only 51% of all studies of diagnostic accuracy and incorrectly identified many articles that were not reports of studies on diagnostic accuracy (18). In the example, the authors used the more general term Performance Characteristics of CT Colonography in the title. The purpose section of the structured abstract explicitly mentions sensitivity and specificity. The MEDLINE record for this paper contains the MeSH Sensitivity and Specificity. Item 2. State the Research Questions or Study Aims, Such as Estimating Diagnostic Accuracy or Comparing Accuracy between Tests or across Participant Groups Example Invasive x-ray coronary angiography remains the gold standard for the identification of clinically significant coronary artery disease . A noninvasive test would be desirable. Coronary magnetic resonance angiography performed while the patient is breathing freely has reached sufficient technical maturity to allow more widespread application with a standardized protocol. Therefore, we conducted a study to determine the [accuracy] of coronary magnetic resonance angiography in the diagnosis of native-vessel coronary artery disease (20). The Helsinki Declaration states that biomedical research involving people should be based on a thorough knowledge of the scientific literature (21). In the introduction of scientific reports authors describe the scientific background, previous work on the subject, the remaining uncertainty, and, hence, the rationale for their study. Clearly specified research questions help the readers to judge the appropriateness of the study design and data analysis. A single general description, such as diagnostic value or clinical usefulness, is usually not very helpful to the readers. In the example, the authors use the introduction section of their paper to describe the potential of coronary magnetic resonance angiography as a non-invasive alternative to conventional x-ray angiography in the diagn

STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting Diagnostic Accuracy (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

Oxidation of polyethylene glycols by alcohol dehydrogenase

The present studies were undertaken to investigate the enzymology of a fatal toxic syndrome that resulted from the absorption and subsequent oxidation of polyethylene glycol (PEG). The presence of organic acids of PEG in the blood of poisoned patients and in an animal model suggested that the metabolism of PEG involved sequential oxidations by alcohol dehydrogenase (ADH) and aldehyde dehydrogenase. A key question concerned the ability of ADH to initiate this pathway for oxidation of PEG. In the present studies the oxidation of PEG homologues by ADH was characterized. The polymer homologues of ethylene glycol from n = 1 to n = 8 were used as substrates. ADH catalyzed the oxidation of each of these PEGs. The oxidation of PEG was inhibited by the ADH inhibitor 4-methylpyrazole. With the exception of diethylene glycol, the Km decreased as the homologue number increased, and the Vmax decreased progressively through the series. The concentrations of PEG in the blood of poisoned humans and animals were 0.06 to 0.8 Km of ADH for all the PEG homologues above the triethylene glycol. These investigations establish ADH as a candidate enzyme for mammalian metabolism of PEG and thus suggest that specific inhibitors of ADH may prove to be useful as tools to treat PEG poisoning.

Current Issues in Measurement and Reporting of Urinary Albumin Excretion

BACKGROUND Urinary excretion of albumin indicates kidney damage and is recognized as a risk factor for progression of kidney disease and cardiovascular disease. The role of urinary albumin measurements has focused attention on the clinical need for accurate and clearly reported results. The National Kidney Disease Education Program and the IFCC convened a conference to assess the current state of preanalytical, analytical, and postanalytical issues affecting urine albumin measurements and to identify areas needing improvement. CONTENT The chemistry of albumin in urine is incompletely understood. Current guidelines recommend the use of the albumin/creatinine ratio (ACR) as a surrogate for the error-prone collection of timed urine samples. Although ACR results are affected by patient preparation and time of day of sample collection, neither is standardized. Considerable intermethod differences have been reported for both albumin and creatinine measurement, but trueness is unknown because there are no reference measurement procedures for albumin and no reference materials for either analyte in urine. The recommended reference intervals for the ACR do not take into account the large intergroup differences in creatinine excretion (e.g., related to differences in age, sex, and ethnicity) nor the continuous increase in risk related to albumin excretion. DISCUSSION Clinical needs have been identified for standardization of (a) urine collection methods, (b) urine albumin and creatinine measurements based on a complete reference system, (c) reporting of test results, and (d) reference intervals for the ACR.

Dopamine-1 Receptor Coupling Defect in Renal Proximal Tubule Cells in Hypertension

The ability of the dopamine-1 (D1)-like receptor to stimulate adenylyl cyclase (AC) and phospholipase C (PLC), inhibit sodium transport in the renal proximal tubule (RPT), and produce natriuresis is attenuated in several rat models of hypertension. Since the inhibitory effect of D1-like receptors on RPT sodium transport is also reduced in some patients with essential hypertension, we measured D1-like receptor coupling to AC and PLC in cultures of human RPT cells from normotensive (NT) and hypertensive (HT) subjects. Basal cAMP concentrations were the same in NT (n=6) and HT (n=4). However, the D1-like receptor agonist fenoldopam increased cAMP production to a greater extent in NT (maximum response=67+/-1%) than in HT (maximum response=17+/-5%), with a potency ratio of 105. Dopamine also increased cAMP production to a greater extent in NT (32+/-3%) than in HT (14+/-3%). The fenoldopam-mediated increase in cAMP production was blocked by SCH23390 (a D1-like receptor antagonist) and by antisense D1 oligonucleotides in both HT and NT, indicating action at the D1 receptor. The stimulatory effects of forskolin and parathyroid hormone-related protein of cAMP accumulation were not statistically different in NT and HT, indicating receptor specificity and an intact G-protein/AC pathway. The fenoldopam-stimulated PLC activity was not impaired in HT, and the primary sequence and expression of the D1 receptor were the same in NT and HT. However, D1 receptor serine phosphorylation in the basal state was greater in HT than in NT and was not responsive to fenoldopam stimulation in HT. These studies demonstrate the expression of D1 receptors in human RPT cells in culture. The uncoupling of the D1 receptor in both rats (previously described) and humans (described here) suggests that this mechanism may be involved in the pathogenesis of hypertension; the uncoupling may be due to ligand-independent phosphorylation of the D1 receptor in hypertension.

Tight Glucose Control in the Intensive Care Unit: Are Glucose Meters up to the Task?

Many institutions use tight glycemic control (TGC)1 protocols in their intensive care units (ICUs). TGC protocols became standard of care after the initial, very promising, studies demonstrating that it improved patient outcomes (1). For instance, Van den Berghe et al. (1) demonstrated that TGC reduced mortality by one-third in surgical intensive care patients. Other early studies of TGC also demonstrated marked and significant benefits in infection rates and mortality. Typical TGC protocols consist of placing postoperative and critically ill patients on a continuous intravenous insulin infusion, checking their blood glucose concentrations on an hourly basis (or other schedule), and giving a bolus of insulin and/or changing the infusion rate of insulin based on the glucose concentration, with a goal of maintaining glucose between 4.4 and 6.7 mmol/L (80 and 120 mg/dL). Of the numerous variations in protocols regarding timing and frequency of glucose measurements, insulin infusion rates, and target glucose values, all have a goal of maintaining tight glycemic control in critically ill patients. A new metaanalysis has suggested that TGC protocols offer limited if any benefits in critically ill adults and revealed that these protocols resulted in a 3- to 5-fold increased risk of hypoglycemia (2). The metaanalysis examined 29 randomized controlled trials that met predefined inclusion criteria. Of the 27 trials that examined mortality as an endpoint, 16 favored TGC and 11 favored usual care, but the reductions in relative risk were statistically significant (95% confidence) in only 2 of the 16 favoring TGC and in none of the 11 favoring usual care. The only outcome for which TGC demonstrated a significantly reduced risk was the development of septicemia; this was seen in surgical intensive care patients but not in medical ICU patients. The metaanalysis concluded that TGC may not be as beneficial as predicted from some …

STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

Position Statement Executive Summary: Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND Multiple laboratory tests are used in the diagnosis and management of patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. APPROACH An expert committee compiled evidence-based recommendations for the use of laboratory analysis in patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. A draft of the guidelines was posted on the Internet, and the document was modified in response to comments. The guidelines were reviewed by the joint Evidence-Based Laboratory Medicine Committee of the AACC and the National Academy of Clinical Biochemistry and were accepted after revisions by the Professional Practice Committee and subsequent approval by the Executive Committee of the American Diabetes Association. CONTENT In addition to the long-standing criteria based on measurement of venous plasma glucose, diabetes can be diagnosed by demonstrating increased hemoglobin A1c (HbA1c) concentrations in the blood. Monitoring of glycemic control is performed by the patients measuring their own plasma or blood glucose with meters and by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. SUMMARY The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.