Cure models: Methods, applications and implementationYingweiPeng, BinbingYu, 2021, Hardback, first edition, Chapman & Hall/CRC Biostatistics Series, 268 pages, £74.99, ISBN‐9780367145576

2021 ◽  
Author(s):  
Ash Bullement
Keyword(s):  
Cure Models

scholarly journals PCN447 NEW METHODOLOGY IN PARAMETRIC NETWORK META-ANALYSIS: NON-MIXTURE CURE MODELS

2019 ◽  
Vol 22 ◽  
pp. S523
Author(s):  
S. van Beekhuizen ◽  
M.J. Ouwens ◽  
H.A. Pham ◽  
M. Postma ◽  
B. Heeg
Keyword(s):  
Meta Analysis ◽  
Cure Models ◽  
Parametric Network

scholarly journals Identifiability of cure models revisited

2014 ◽  
Vol 130 ◽  
pp. 261-274 ◽  
Author(s):  
Leonid Hanin ◽  
Li-Shan Huang
Keyword(s):  
Cure Models

Cure Models

2021 ◽  
pp. 153-212
Author(s):  
Catherine Legrand
Keyword(s):  
Cure Models

scholarly journals MO4 - COMPARING MIXTURE CURE MODELS WITH STANDARD PARAMETRIC MODELS WITHIN THREE- AND FIVE-STATE PARTITION SURVIVAL FRAMEWORKS

2018 ◽  
Vol 21 ◽  
pp. S11
Author(s):  
I. van Oostrum ◽  
E. Buskens ◽  
M.J. Ouwens ◽  
M.J. Postma ◽  
B. Heeg
Keyword(s):  
Parametric Models ◽  
Cure Models

Cure Models

2017 ◽  
pp. 1-5
Author(s):  
Vern T. Farewell
Keyword(s):  
Cure Models

scholarly journals Bias in Mean Survival From Fitting Cure Models With Limited Follow-Up

2020 ◽  
Vol 23 (8) ◽  
pp. 1034-1039
Author(s):  
Megan Othus ◽  
Aasthaa Bansal ◽  
Harry Erba ◽  
Scott Ramsey
Keyword(s):  
Cure Models

scholarly journals Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up

2020 ◽  
Vol 189 (11) ◽  
pp. 1421-1426
Author(s):  
Yicheng Ma ◽  
Helen E Jenkins ◽  
Paola Sebastiani ◽  
Jerrold J Ellner ◽  
Edward C Jones-López ◽  
...  
Keyword(s):  
Likelihood Function ◽  
The United States ◽  
Simulation Studies ◽  
Serial Interval ◽  
Slow Progression ◽  
Cure Models ◽  
Study Population ◽  
Credible Information ◽  
Active Disease

Abstract Serial interval (SI), defined as the time between symptom onset in an infector and infectee pair, is commonly used to understand infectious diseases transmission. Slow progression to active disease, as well as the small percentage of individuals who will eventually develop active disease, complicate the estimation of the SI for tuberculosis (TB). In this paper, we showed via simulation studies that when there is credible information on the percentage of those who will develop TB disease following infection, a cure model, first introduced by Boag in 1949, should be used to estimate the SI for TB. This model includes a parameter in the likelihood function to account for the study population being composed of those who will have the event of interest and those who will never have the event. We estimated the SI for TB to be approximately 0.5 years for the United States and Canada (January 2002 to December 2006) and approximately 2.0 years for Brazil (March 2008 to June 2012), which might imply a higher occurrence of reinfection TB in a developing country like Brazil.

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