Stabilizing cumulative incidence estimation of pregnancy outcome with delayed entries

2018 ◽  
Vol 61 (5) ◽  
pp. 1290-1302 ◽  
Author(s):  
Valentin Rousson ◽  
Arthur Allignol ◽  
Alexandre Aurousseau ◽  
Ursula Winterfeld ◽  
Jan Beyersmann
Keyword(s):  
Pregnancy Outcome ◽  
Cumulative Incidence ◽  
Incidence Estimation

Excess cumulative incidence estimation for matched cohort survival studies

2020 ◽  
Vol 39 (20) ◽  
pp. 2606-2620
Author(s):  
Cristina Boschini ◽  
Klaus K. Andersen ◽  
Hélène Jacqmin‐Gadda ◽  
Pierre Joly ◽  
Thomas H. Scheike
Keyword(s):  
Cumulative Incidence ◽  
Matched Cohort ◽  
Incidence Estimation ◽  
Survival Studies

scholarly journals Improving SARS-CoV-2 cumulative incidence estimation through mixture modelling of antibody levels

2021 ◽  
Author(s):  
C. Bottomley ◽  
M. Otiende ◽  
S. Uyoga ◽  
K. Gallagher ◽  
E.W. Kagucia ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Antibody Level ◽  
Cumulative Incidence ◽  
Model Estimate ◽  
Mixture Modelling ◽  
Seroprevalence Data ◽  
Incidence Estimation ◽  
Using Data ◽  
Serological Data ◽  
Antibody Levels

AbstractAs countries decide on vaccination strategies and how to ease movement restrictions, estimates of cumulative incidence of SARS-CoV-2 infection are essential in quantifying the extent to which populations remain susceptible to COVID-19. Cumulative incidence is usually estimated from seroprevalence data, where seropositives are defined by an arbitrary threshold antibody level, and adjusted for sensitivity and specificity at that threshold. This does not account for antibody waning nor for lower antibody levels in asymptomatic or mildly symptomatic cases. Mixture modelling can estimate cumulative incidence from antibody-level distributions without requiring adjustment for sensitivity and specificity. To illustrate the bias in standard threshold-based seroprevalence estimates, we compared both approaches using data from several Kenyan serosurveys. Compared to the mixture model estimate, threshold analysis underestimated cumulative incidence by 31% (IQR: 11 to 41) on average. Until more discriminating assays are available, mixture modelling offers an approach to reduce bias in estimates of cumulative incidence.One-Sentence SummaryMixture models reduce biases inherent in the standard threshold-based analysis of SARS-CoV-2 serological data.

scholarly journals Impact of and Correction for Outcome Misclassification in Cumulative Incidence Estimation

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137454 ◽  
Author(s):  
Giorgos Bakoyannis ◽  
Constantin T. Yiannoutsos
Keyword(s):  
Cumulative Incidence ◽  
Incidence Estimation

Dimensions of prenatal anxiety and their influence on pregnancy outcome

1979 ◽  
Vol 135 (1) ◽  
pp. 22-26 ◽  
Author(s):  
Kay Standley ◽  
Bradley Soule ◽  
Stuart A. Copans
Keyword(s):  
Pregnancy Outcome ◽  
Prenatal Anxiety
Sign in / Sign up

Export Citation Format

Share Document