Intention-to-diagnose and distinct research foci in diagnostic accuracy studies

Authors

• Scott R. Evans, The Biostatistics Center, George Washington University, Rockville, MD, USA; Department of Biostatistics, Milken Institute School of Public Health, George Washington University, Rockville, MD, USA. Electronic address: sevans@bsc.gwu.edu.
• Gene Pennello, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA.
• Shanshan Zhang, The Biostatistics Center, George Washington University, Rockville, MD, USA; Department of Biostatistics, Milken Institute School of Public Health, George Washington University, Rockville, MD, USA.
• Yixuan Li, The Biostatistics Center, George Washington University, Rockville, MD, USA.
• Yike Wang, The Biostatistics Center, George Washington University, Rockville, MD, USA; Department of Biostatistics, Milken Institute School of Public Health, George Washington University, Rockville, MD, USA.
• Qian Cao, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA.
• Lauren Komarow, The Biostatistics Center, George Washington University, Rockville, MD, USA.
• Toshimitsu Hamasaki, The Biostatistics Center, George Washington University, Rockville, MD, USA; Department of Biostatistics, Milken Institute School of Public Health, George Washington University, Rockville, MD, USA.
• Victoria Petrides, Abbott, Abbott Park, IL, USA.
• Kristen Meier, Silver Spring, MD, USA.
• Norberto Pantoja Galicia, Foundation Medicine, Boston, MA, USA.
• Vance G. Fowler, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA; Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
• Helen W. Boucher, Tufts University School of Medicine, Boston, MA, USA; Tufts Medicine, Boston, MA, USA.
• Sarah B. Doernberg, Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
• Ritu Banerjee, Division of Pediatric Infectious Diseases, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA.
• Maria Helena Rigatto, Medical Sciences Post-Graduation Program, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Department of Internal Medicine, Medical School, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Infectious Diseases Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
• Barry N. Kreiswirth, Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, NJ, USA.
• Robert A. Bonomo, Department of Medicine, Case Western Reserve University School of Medicine, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, USA; Case Western Reserve University VA Center for Antimicrobial Resistance and Epidemiology (Case VA CARES), Research Service, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, USA; Department of Pharmacology, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Department of Molecular Biology and Microbiology, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Department of Biochemistry, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
• Henry F. Chambers, Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
• Robin Patel, Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; Division of Public Health, Infectious Diseases, and Occupational Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA.

Document Type

Journal Article

Publication Date

3-27-2025

Journal

The Lancet. Infectious diseases

DOI

10.1016/S1473-3099(25)00070-2

Abstract

The intention-to-diagnose principle, an analogue to the intention-to-treat principle in clinical trials, protects the foundation for inference in diagnostic test accuracy studies. This foundation provides for robust control of error rates during hypothesis testing and correct coverage probability during confidence interval estimation of accuracy parameters, in well defined populations for transparent generalisability. The intention-to-diagnose principle requires distinguishing between various non-positive non-negative (NPNN) test results, such as equivocal and invalid results, and appropriate handling of these distinct results during statistical analyses. Pragmatic application accuracy, pragmatic scientific accuracy, and explanatory scientific accuracy are three major research foci in studies of diagnostic test accuracy. Selection of appropriate analysis sets and appropriate handling of NPNN results depend on the specific focus. Selection has important implications regarding preservation of the foundation for statistical inference, generalisability, and comparability with results from other studies. We recommended analyses for diagnostic accuracy studies that include the estimation of accuracy parameters associated with each research foci. A free online tool is available to estimate these accuracy parameters. As with dedicated commitment to the intention-to-treat principle in clinical trials, commitment to application of the intention-to-diagnose principle will lead to studies with high integrity, a comprehensive understanding of the scientific and administration characteristics of the diagnostic test, clarity of interpretation and generalisability, and better clinical decision making.

APA Citation

Evans, Scott R.; Pennello, Gene; Zhang, Shanshan; Li, Yixuan; Wang, Yike; Cao, Qian; Komarow, Lauren; Hamasaki, Toshimitsu; Petrides, Victoria; Meier, Kristen; Galicia, Norberto Pantoja; Fowler, Vance G.; Boucher, Helen W.; Doernberg, Sarah B.; Banerjee, Ritu; Rigatto, Maria Helena; Kreiswirth, Barry N.; Bonomo, Robert A.; Chambers, Henry F.; and Patel, Robin, "Intention-to-diagnose and distinct research foci in diagnostic accuracy studies" (2025). GW Authored Works. Paper 6750.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/6750

Department

Biostatistics and Bioinformatics