Dr. Antonio Steardo, a pharmacologist with experience in evaluating diagnostic devices and their clinical accuracy, supports companies, laboratories, and professionals in methodological validation and performance analysis of diagnostic tests. Thanks to his skills in sensitivity, specificity, accuracy measures, study bias, and reporting standards, he offers specialist consultancy to ensure that medical devices are reliable, reproducible, and truly useful in clinical practice.
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Diagnostic accuracy and sensitivity
Qualitative and quantitative evaluation of medical devices to determine their ability to correctly identify pathological conditions. Includes analysis of sensitivity, specificity, and overall test performance across different clinical settings.
Purposes of diagnostic tests
Understanding the aims of tests—screening, diagnosis, monitoring, or confirmation—and selecting the most appropriate methods to evaluate their effectiveness based on the clinical objective.
Formulating diagnostic questions
Knowing how to define targeted questions to address specific diagnostic problems. Proper formulation guides the choice of study design and metrics to be used.
Optimal design of diagnostic studies
Description of the most suitable study models for evaluating diagnostic tests, considering the population, gold standard, inclusion criteria, and data collection methods.
Searching for diagnostic evidence
Ability to quickly identify relevant publications for different types of diagnostic questions, utilizing advanced search strategies and reliable sources.
Evaluation of accuracy studies
Critical analysis of studies measuring diagnostic test performance, with attention to bias, methodology, population, and the quality of the gold standard.
Diagnostic reporting standards
Understanding international guidelines (such as STARD) to ensure transparency, reproducibility, and quality in the presentation of diagnostic study results.
Evaluation of systematic reviews
Ability to analyze systematic reviews of diagnostic studies, assessing their methodology, selection criteria, data synthesis, and robustness of conclusions.
Bias in diagnostic studies
Description of the main forms of design-related bias—selection, verification, spectrum, incorporation—and strategies to reduce or avoid them.
Measures of diagnostic accuracy
Understanding and calculating sensitivity, specificity, positive and negative likelihood ratios, predictive values, and other fundamental metrics to correctly interpret test performance.
Combined evaluation of multiple tests
Analysis of how multiple diagnostic tests can be integrated to improve precision, reduce false positives/negatives, and support more accurate clinical decisions.
Sample size calculation
Determination of the sample size required for simple diagnostic studies, ensuring statistical power and reliability of results.
Visual presentation of results
Understanding the most effective ways to graphically represent results: ROC curves, flowcharts, contingency tables, and intuitive visualizations.
Impact of results on clinical decisions
Analysis of how diagnostic test results influence patient management, therapeutic choices, and the definition of clinical pathways.
Communicating results to physicians
Guidelines for communicating test results clearly and usefully to clinicians, facilitating interpretation and decision-making.
Adoption of diagnostic services
Understanding factors that influence the implementation of diagnostic tests in clinical practice, including costs, training, workflow, and organizational impact.
Issues in screening programs
Analysis of critical issues in screening programs: overdiagnosis, false positives, patient anxiety, and evaluation of the risk-benefit ratio.
Interaction between diagnosis and monitoring
Understanding how initial diagnosis and subsequent monitoring integrate into clinical management, ensuring continuity and precision in the therapeutic pathway.