111 research outputs found
The likelihood ratio and its graphical representation
No full textDiagnostic tests are important clinical tools. Bayes’ theorem and Bayesian approach are important methods for interpreting test results. The Bayesian
factor, the so-called likelihood ratio, has not always been well-understood. In this article, we try to discuss the likelihood ratio and its value for a
specific test result, a positive or negative test result, and a range of test results, along with their graphical representations
Re: Eric A. Klein, Arnon Chait, Jason M. Hafron, et al. The Single-parameter, Structure-based IsoPSA Assay Demonstrates Improved Diagnostic Accuracy for Detection of Any Prostate Cancer and High-grade Prostate Cancer Compared to a Concentration-based Assay of Total Prostate-specific Antigen: A Preliminary Report. Eur Urol 2017;72:942–9
No full textOn determining the most appropriate test cut-off value: the case of tests with continuous results
No full textThere are several criteria for determination of the most appropriate cut-off value in a diagnostic test with continuous results. Mostly based on receiver operating characteristic (ROC) analysis, there are various methods to determine the test cut-off value. The most common criteria are the point on ROC curve where the sensitivity and specificity of the test are equal; the point on the curve with minimum distance from the left-upper corner of the unit square; and the point where the Youden’s index is maximum. There are also methods mainly based on Bayesian decision analysis. Herein, we show that a proposed method that maximizes the weighted number needed to misdiagnose, an index of diagnostic test effectiveness we previously proposed, is the most appropriate technique compared to the aforementioned ones. For determination of the cut-off value, we need to know the pretest probability of the disease of interest as well as the costs incurred by misdiagnosis. This means that even for a certain diagnostic test, the cut-off value is not universal and should be determined for each region and for each disease condition
Advancing ICOS agonism in solid tumors: lessons from INDUCE-1
No full textThe inducible T-cell co-stimulator (ICOS, CD278) represents an appealing yet complex target within the CD28 immunoglobulin receptor superfamily. Unlike constitutively expressed co-stimulatory molecules, ICOS is minimally present on naïve T cells and is upregulated following T-cell receptor engagement. This inducible expression pattern, and its crosstalk with other co-stimulatory pathways such as OX40, 4-1BB, CD40, and CD28, position ICOS as a promising candidate for immune agonism. The phase I INDUCE-1 study of the ICOS agonist feladilimab (GSK3359609) employed a pharmacodynamically guided design that prioritized biological activity over toxicity thresholds. Although feladilimab demonstrated favorable safety and robust receptor occupancy, clinical responses were limited—echoing similar experiences with vopratelimab (JTX-2011) and other ICOS agonists. These outcomes highlight that effective ICOS modulation depends not only on receptor engagement but also on spatial and temporal regulation of effector versus regulatory T-cell responses. Future ICOS-directed strategies, whether agonistic or antagonistic, monoclonal or bispecific, will require rational combination approaches and biomarker-driven patient selection to fully harness this pathway’s therapeutic potential
The apparent prevalence, the true prevalence
No full textSerologic tests are important for conducting seroepidemiologic and prevalence studies. However, the tests used are typically imperfect and produce false-positive and false-negative results. This is why the seropositive rate (apparent prevalence) does not typically reflect the true prevalence of the disease or condition of interest. Herein, we discuss the way the true prevalence could be derived from the apparent prevalence and test sensitivity and specificity. A computer simulation based on the Monte-Carlo algorithm was also used to further examine a situation where the measured test sensitivity and specificity are also uncertain. We then complete our review with a real example. The apparent prevalence observed in many prevalence studies published in medical literature is a biased estimation and cannot be interpreted correctly unless we correct the value
Association Between Race and Comorbid Conditions Among Older Adults with Dementia
No full textBackground/Objective: Dementia is estimated to affect over 150 million individuals by 2050. Individuals with dementia commonly suffer from other comorbid conditions which can affect quality of life and result in increased health care expenditures. We conducted this study to determine the frequency of comorbid conditions between representative samples of non-Hispanic Black and White US adults aged ≥65 with dementia. Methods: This cross-sectional study was conducted on non-Hispanic Black and White adults aged 65 and older with dementia whose data were retrieved from the National Hospital Ambulatory Medical Care Survey, 2016–2021, and the National Ambulatory Medical Care Survey, 2016, 2018, and 2019. Dementia was defined based on medical record abstraction. The exposure was Black vs. White race. The outcome was a sum of 13 comorbid conditions, including obesity, hypertension, cancer, cerebrovascular disease, congestive heart failure, and coronary artery disease, assessed in older adults with dementia. Results: A total of 1354 non-Hispanic (1175 White and 179 Black) participants were studied. The mean number of comorbid conditions, as well as the prevalence of obesity, cerebrovascular disease, congestive heart failure, and coronary artery disease, was significantly (p < 0.01) higher in the Black vs. White study participants. The Black participants were more likely to have more than two comorbid conditions relative to those who were White (odds ratio 2.5; 95% confidence interval 1.6 to 3.7). Conclusions: A higher burden of comorbid conditions was observed among non-Hispanic Blacks compared to non-Hispanic White older adults with dementia. Future studies should examine the quality of life and health care utilization implications of this finding
450 Developing Methods for High-Resolution Characterization of Plasma Cells
No full textOBJECTIVES/GOALS: Antibodies play an important role in the pathogenesis of a wide range of diseases, including cancer, autoimmune diseases, and infections. There are currently no reliable methods to isolate and study specific plasma cell subpopulations as antibody production sources. We aim to develop methods to study plasma cells in high resolution. METHODS/STUDY POPULATION: We will use molecular cloning to engineer fusion proteins that would bind plasma cell proteins to study these cells based on their surface features. The first phase of our study consists of assessing the efficacy of this plasma cell isolation method in established cell lines (e.g., RPMI 8226) and also antibody-secreting cell lines that we are establishing as a part of this study. In the second phase of the study, we will assess the efficacy of this method by studying antigen-specific plasma cell populations in the bone marrow aspiration samples of 20 healthy volunteers using various assays, including ELISPOT, flow cytometry, and fluorescent microscopy. RESULTS/ANTICIPATED RESULTS: We have designed the constructs and have completed the cloning. The final plasmids have been verified using various restriction enzymes and Sanger sequencing. Following the transfection of Freestyle HEK 293F cells and isolation of respective proteins, we expect to be able to utilize these engineered proteins to differentiate various antibody-secreting plasma cells. We will use cell lines for proof-of-concept experiments and will subsequently move this method to human bone marrow samples. We expect to be able to visualize multiple specific antibody-secreting plasma cell populations using fluorescent microscopy and utilize this method to isolate them by cell sorting via flow cytometry. DISCUSSION/SIGNIFICANCE: We expect to be able to use this method to target specific plasma cell clones in the advancement of precision medicine regarding the treatment of plasma cell disorders (e.g., multiple myeloma) and also expand its use in other areas, such as antibody discovery and the assessment of the humoral immune responses in infectious diseases
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