Dataset Information

A score test for comparing cross-sectional survival data with a fraction of non-susceptible patients and its application in clinical immunology.

ABSTRACT:

Objectives

In cross-sectional studies of time-to-event data collected by patient examinations at a single random point in time, a fraction of them will not experience the event regardless of the length of the follow-up time. This is the case in clinical immunology studies that include a mixed population, with both immune-reactive and immune-tolerant (or non-susceptible) patients. In these cases, classical tests of current status data may perform poorly. New methods for testing these data are needed.

Methods

In the two-sample comparison setting, we propose a score test for testing the null hypothesis that survival does not differ in either the non-susceptible fraction or the time-to-event distribution among the susceptible fraction.

Results

In a wide range of scenarios, simulation results show interesting improvements in power for the proposed score test compared to the logrank-type test in most of the configurations we investigated. In a cross-sectional study of drug immunogenicity among treated multiple sclerosis patients, the proposed score test reveals that gender is associated with the immunogenicity of interferon.

SUBMITTER: Jonas SF

PROVIDER: S-EPMC5493340 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

A score test for comparing cross-sectional survival data with a fraction of non-susceptible patients and its application in clinical immunology.

Jonas Sarah Flora SF Mbogning Cyprien C Hässler Signe S Broët Philippe P

PloS one 20170630 6

<h4>Objectives</h4>In cross-sectional studies of time-to-event data collected by patient examinations at a single random point in time, a fraction of them will not experience the event regardless of the length of the follow-up time. This is the case in clinical immunology studies that include a mixed population, with both immune-reactive and immune-tolerant (or non-susceptible) patients. In these cases, classical tests of current status data may perform poorly. New methods for testing these data ...[more]

PMID: 28665947

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Project description:BackgroundPatients with acute toxic hemoperfusion are prone to deep vein thrombosis. However, there is no risk assessment model for thrombosis in patients with acute toxic hemoperfusion. Therefore, we compared three commonly used risk assessment models for deep vein thrombosis to determine the model most suitable for assessment of deep vein thrombosis in patients with acute toxic hemoperfusion.MethodsCaprini, Autar, and Padua thrombosis risk assessment models were used to assess the risk of deep vein thrombosis in patients with acute poisoning and hemoperfusion admitted to a grade A hospital in Shandong province from October 2017 to February 2019. The predictive values of the three models were compared using receiver operating characteristic (ROC) curve analysis.ResultsThe risk assessment model scores of Caprini, Autar, and Padua were 7.55 ± 1.76, 8.63 ± 2.36, and 3.92 ± 0.55, respectively. The Caprini risk assessment model was significantly different (p < 0.05) in high-risk patients in the thrombus and non-thrombotic groups; the difference between the other two models was not significant (p > 0.05). The areas under the ROC curve of the Caprini, Autar, and Padua risk assessment models were 0.673, 0.585, and 0.535, respectively. The difference in areas under the ROC curve between the Caprini risk assessment model and the Autar risk assessment model as well as the Padua risk assessment model was significant (p < 0.05), but the areas under the ROC curve of the Autar risk assessment model and the Padua risk assessment model were not statistically significant (p > 0.05). The Caprini risk assessment model had a sensitivity of 91.9%, specificity of 33.1%, and a Youden index of 0.249. The sensitivity and specificity of Autar's risk assessment model were 37.0 and 77.2%, respectively, and the Youden index was 0.141. The Padua risk assessment model had a sensitivity of 91.3%, specificity of 15.0%, and a Youden index of 0.063.ConclusionThe three thrombosis risk assessment models were not suitable for patients with acute poisoning and hemoperfusion.

Dataset Information

A score test for comparing cross-sectional survival data with a fraction of non-susceptible patients and its application in clinical immunology.

Objectives

Methods

Results

Publications

A score test for comparing cross-sectional survival data with a fraction of non-susceptible patients and its application in clinical immunology.

Similar Datasets

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