An original approach was used to better evaluate the capacity of a prognostic marker using published survival curves.

J Clin Epidemiol

Department of Biostatistics, Pharmacoepidemiology and Subjective Measures in Health Sciences, EA 4275, Nantes University, 1 rue Gaston Veil, 44035 Nantes, France.

Published: April 2014

Objectives: Predicting chronic disease evolution from a prognostic marker is a key field of research in clinical epidemiology. However, the prognostic capacity of a marker is not systematically evaluated using the appropriate methodology. We proposed the use of simple equations to calculate time-dependent sensitivity and specificity based on published survival curves and other time-dependent indicators as predictive values, likelihood ratios, and posttest probability ratios to reappraise prognostic marker accuracy.

Study Design And Setting: The methodology is illustrated by back calculating time-dependent indicators from published articles presenting a marker as highly correlated with the time to event, concluding on the high prognostic capacity of the marker, and presenting the Kaplan-Meier survival curves. The tools necessary to run these direct and simple computations are available online at http://www.divat.fr/en/online-calculators/evalbiom.

Results: Our examples illustrate that published conclusions about prognostic marker accuracy may be overoptimistic, thus giving potential for major mistakes in therapeutic decisions.

Conclusion: Our approach should help readers better evaluate clinical articles reporting on prognostic markers. Time-dependent sensitivity and specificity inform on the inherent prognostic capacity of a marker for a defined prognostic time. Time-dependent predictive values, likelihood ratios, and posttest probability ratios may additionally contribute to interpret the marker's prognostic capacity.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jclinepi.2013.10.022DOI Listing

Publication Analysis

Top Keywords

prognostic marker
16
prognostic capacity
16
survival curves
12
capacity marker
12
prognostic
10
better evaluate
8
marker
8
published survival
8
time-dependent sensitivity
8
sensitivity specificity
8

Similar Publications

T-helper 17 (Th17) cells significantly influence the onset and advancement of malignancies. This study endeavor focused on delineating molecular classifications and developing a prognostic signature grounded in Th17 cell differentiation-related genes (TCDRGs) using machine learning algorithms in head and neck squamous cell carcinoma (HNSCC). A consensus clustering approach was applied to The Cancer Genome Atlas-HNSCC cohort based on TCDRGs, followed by an examination of differential gene expression using the limma package.

View Article and Find Full Text PDF

Ultrasensitive Detection of Circulating Plasma Cells Using Surface-Enhanced Raman Spectroscopy and Machine Learning for Multiple Myeloma Monitoring.

Anal Chem

January 2025

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, Fujian 350117, China.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma cells in the bone marrow. Despite therapeutic advancements, there remains a critical need for reliable, noninvasive methods to monitor multiple myeloma. Circulating plasma cells (CPCs) in peripheral blood are robust and independent prognostic markers, but their detection is challenging due to their low abundance.

View Article and Find Full Text PDF

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease, and inflammation plays a key role in the pathogenesis of COPD. The aim of this study is to investigate the association between systemic immune inflammation index (SII), systemic inflammatory response index (SIRI),pan-immune inflammation value (PIV), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) and all-cause mortality in patients with chronic obstructive pulmonary disease (COPD), and to evaluate the effect of composite inflammatory markers on the prognosis of COPD patients. We obtained data on COPD patients from the Medical Information Mart for Intensive Care (MIMIC) -IV database and divided patients into four groups based on quartiles of baseline levels of inflammatory markers, The primary outcomes were in-hospital and ICU mortality.

View Article and Find Full Text PDF

Predictive strength of inflammatory scores for in-hospital mortality in infective endocarditis.

Herz

January 2025

Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University, 737 N. Michigan Avenue Suite 1600, 60611, Chicago, IL, USA.

Background: Inflammatory markers have been proposed as prognostic tools for predicting in-hospital mortality in infective endocarditis (IE). Nonetheless, it is unclear whether these markers provide additional prognostic value over established indicators. This study compared nine different inflammation scores to assess their effectiveness in enhancing the prediction of in-hospital mortality.

View Article and Find Full Text PDF

Prognostic value of coronary plaque composition in symptomatic patients with obstructive coronary artery disease.

Eur Radiol

January 2025

Hôpital Privé Jacques Cartier, Institut Cardiovasculaire Paris Sud (ICPS), Ramsay-Santé, 91300, Massy, France.

Objectives: To determine whether plaque composition analysis defined by cardiac CT can provide incremental prognostic value above coronary artery disease (CAD) burden markers in symptomatic patients with obstructive CAD.

Materials And Methods: Between 2009 and 2019, a multicentric registry included all consecutive symptomatic patients with obstructive CAD (at least one ≥ 50% stenosis on CCTA) and was followed for major adverse cardiovascular (MACE) defined by cardiovascular death or nonfatal myocardial infarction. Each coronary segment was scored visually for both the degree of stenosis and composition of plaque, which were classified as non-calcified, mixed, or calcified.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!