STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies
Patrick M Bossuyt1, Johannes B Reitsma2, David E Bruns3
1Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands; p.m.bossuyt@amc.uva.nl.
Clinical Chemistry
|October 30, 2015
Summary
Incomplete reporting wastes resources in biomedical research. STARD 2015 provides updated guidelines for reporting diagnostic accuracy studies, enhancing transparency and reproducibility.
Area of Science:
- Biomedical Research
- Medical Diagnostics
- Research Methodology
Background:
- Incomplete reporting in biomedical research leads to significant avoidable waste.
- Lack of essential information hinders study identification, critical appraisal, and replication.
- The Standards for Reporting of Diagnostic Accuracy Studies (STARD) was previously developed to address these issues.
Purpose of the Study:
- To present STARD 2015, an updated checklist for reporting diagnostic accuracy studies.
- To incorporate recent evidence on bias and variability in diagnostic accuracy.
- To improve the completeness and transparency of diagnostic accuracy study reports.
Main Methods:
- Development of STARD 2015 involved updating the original STARD statement.
- The updated list comprises 30 essential reporting items.
- Incorporation of recent evidence on sources of bias and variability in diagnostic accuracy.
Main Results:
- STARD 2015 provides a comprehensive list of 30 essential items for reporting diagnostic accuracy studies.
- The updated guidelines reflect current understanding of bias and variability.
- Facilitates consistent and complete reporting.
Conclusions:
- STARD 2015 offers an updated framework to enhance the quality of reporting for diagnostic accuracy studies.
- Adherence to STARD 2015 can improve transparency and reduce research waste.
- Promotes better critical appraisal and replication of diagnostic accuracy research.
More Related Videos
Related Concept Videos
01:13Sensitivity, Specificity, and Predicted Value
1.8K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Sensitivity is the...
1.8K
01:15Receiver Operating Characteristic Plot
575
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
575
01:13Accuracy and Errors in Hypothesis Testing
680
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
680
01:24Automated Microbial Diagnostics
40
Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
40
01:29Bias in Epidemiological Studies
1.6K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.6K
01:30Serum Laboratory Studies, Stool Test, Breath Test
1.1K
Gastrointestinal (GI) diagnostic studies are pivotal in confirming, ruling out, diagnosing, or staging various diseases, including cancers. Following diagnosis, allocating time for discussions with the patient and providing informational resources is crucial. Diagnostic assessments of the GI tract often occur in outpatient settings like endoscopy suites or GI labs. Preparation for these tests may include dietary restrictions, fasting, liquid bowel preparations, laxatives, enemas, and the...
1.1K