In screening large populations a diagnostic test is frequently used repeatedly. An example is screening for bowel cancer using the fecal occult blood test (FOBT) on several occasions such as at 3 or 6 days. The question that is addressed here is how often should we repeat a diagnostic test when screening for a specific medical condition. Sensitivity is often used as a performance measure of a diagnostic test and is considered here for the individual application of the diagnostic test as well as for the overall screening procedure. The latter can involve an increasingly large number of repeated applications, but how many are sufficient? We demonstrate the issues involved in answering this question using real data on bowel cancer at St Vincents Hospital in Sydney. As data are only available for those testing positive at least once, an appropriate modeling technique is developed on the basis of the zero-truncated binomial distribution which allows for population heterogeneity. The latter is modeled using discrete nonparametric maximum likelihood. If we wish to achieve an overall sensitivity of 90%, the FOBT should be repeated for 2 weeks instead of the 1 week that was used at the time of the survey. A simulation study also shows consistency in the sense that bias and standard deviation for the estimated sensitivity decrease with an increasing number of repeated occasions as well as with increasing sample size.
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http://dx.doi.org/10.1002/bimj.202300175 | DOI Listing |
Objectives: To determine and compare the diagnostic accuracy of imaging tests for the prediction of RA progression in people with inflammatory joint pain or CSA.
Methods: We searched MEDLINE, Embase and Web of Science from 1987 to March 2024. Studies evaluating any imaging tests in participants with inflammatory joint pain or CSA, without clinical synovitis were eligible.
Clin Rheumatol
January 2025
Department of Rheumatology and Immunology, The First Medical Center, People Liberation Army General Hospital, Beijing, 100853, China.
To study the clinical, imaging, and computed tomography (CT)-guided biopsy pathology of patients with infectious sacroiliitis (ISI). We retrospectively analysed 135 patients diagnosed with ISI between 2008 and 2020, comprehensively evaluating clinical characteristics, laboratory test outcomes, pathological examination results, and magnetic resonance images (MRI). Among the 135 patients with ISI, 90 (66.
View Article and Find Full Text PDFAbdom Radiol (NY)
January 2025
Departmet of Urology, Medical Academy, Lithuanian University of Health Sciences, Mickeviciaus str. 9, Kaunas, 44307, Lithuania.
Objectives: This study aimed to investigate the accuracy of multiparametric magnetic resonance imaging (mpMRI), genetic urinary test (GUT), and prostate cancer prevention trial risk calculator version 2.0 (PCPTRC2) for the clinically significant prostate cancer (csPCa) diagnostic in biopsy-naïve patients.
Materials And Methods: In a single center study between 2021 and 2024 participants underwent prostate mpMRI, GUT, and ultrasound (US) guided biopsy.
Age Ageing
January 2025
Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Background: A mobile cognition scale for community screening in cognitive impairment with rigorous validation is in paucity. We aimed to develop a digital scale that overcame low education for community screening for mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and AD.
Methods: A mobile cognitive self-assessment scale (CogSAS) was designed through the Delphi process, which is feasible for the older population with low education.
J Clin Exp Neuropsychol
January 2025
Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Introduction: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becoming increasingly complicated by the number of adults who fabricate or exaggerate symptoms. Novel methods are needed to improve the assessment process required to detect these noncredible symptoms. The present study investigated whether unsupervised machine learning (ML) could serve as one such method, and detect noncredible symptom reporting in adults undergoing ADHD evaluations.
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