Literature DB >> 23017250

smcure: an R-package for estimating semiparametric mixture cure models.

Chao Cai1, Yubo Zou, Yingwei Peng, Jiajia Zhang.   

Abstract

The mixture cure model is a special type of survival models and it assumes that the studied population is a mixture of susceptible individuals who may experience the event of interest, and cure/non-susceptible individuals who will never experience the event. For such data, standard survival models are usually not appropriate because they do not account for the possibility of cure. This paper presents an R package smcure to fit the semiparametric proportional hazards mixture cure model and the accelerated failure time mixture cure model.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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Year:  2012        PMID: 23017250      PMCID: PMC3494798          DOI: 10.1016/j.cmpb.2012.08.013

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  10 in total

1.  A nonparametric mixture model for cure rate estimation.

Authors:  Y Peng; K B Dear
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

2.  Estimation in a Cox proportional hazards cure model.

Authors:  J P Sy; J M Taylor
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

3.  A semi-parametric accelerated failure time cure model.

Authors:  Chin-Shang Li; Jeremy M G Taylor
Journal:  Stat Med       Date:  2002-11-15       Impact factor: 2.373

4.  A SAS macro for parametric and semiparametric mixture cure models.

Authors:  Fabien Corbière; Pierre Joly
Journal:  Comput Methods Programs Biomed       Date:  2006-12-08       Impact factor: 5.428

5.  A new estimation method for the semiparametric accelerated failure time mixture cure model.

Authors:  Jiajia Zhang; Yingwei Peng
Journal:  Stat Med       Date:  2007-07-20       Impact factor: 2.373

6.  Semi-parametric estimation in failure time mixture models.

Authors:  J M Taylor
Journal:  Biometrics       Date:  1995-09       Impact factor: 2.571

7.  A generalized F mixture model for cure rate estimation.

Authors:  Y Peng; K B Dear; J W Denham
Journal:  Stat Med       Date:  1998-04-30       Impact factor: 2.373

8.  The use of mixture models for the analysis of survival data with long-term survivors.

Authors:  V T Farewell
Journal:  Biometrics       Date:  1982-12       Impact factor: 2.571

9.  Comparison of autologous and allogeneic bone marrow transplantation for treatment of high-risk refractory acute lymphoblastic leukemia.

Authors:  J H Kersey; D Weisdorf; M E Nesbit; T W LeBien; W G Woods; P B McGlave; T Kim; D A Vallera; A I Goldman; B Bostrom
Journal:  N Engl J Med       Date:  1987-08-20       Impact factor: 91.245

10.  Interferon alfa-2b adjuvant therapy of high-risk resected cutaneous melanoma: the Eastern Cooperative Oncology Group Trial EST 1684.

Authors:  J M Kirkwood; M H Strawderman; M S Ernstoff; T J Smith; E C Borden; R H Blum
Journal:  J Clin Oncol       Date:  1996-01       Impact factor: 44.544

  10 in total
  9 in total

1.  NPHMC: an R-package for estimating sample size of proportional hazards mixture cure model.

Authors:  Chao Cai; Songfeng Wang; Wenbin Lu; Jiajia Zhang
Journal:  Comput Methods Programs Biomed       Date:  2013-10-11       Impact factor: 5.428

2.  Utilization of a Mixture Cure Rate Model based on the Generalized Modified Weibull Distribution for the Analysis of Leukemia Patients.

Authors:  Mohamed Elamin Omer; Mohd Abu Bakar; Mohd Adam; Mohd Mustafa
Journal:  Asian Pac J Cancer Prev       Date:  2021-04-01

3.  Cure models to estimate time until hospitalization due to COVID-19: A case study in Galicia (NW Spain).

Authors:  Maria Pedrosa-Laza; Ana López-Cheda; Ricardo Cao
Journal:  Appl Intell (Dordr)       Date:  2021-05-12       Impact factor: 5.086

4.  Short-term and long-term prognostic value of histological response and intensified chemotherapy in osteosarcoma: a retrospective reanalysis of the BO06 trial.

Authors:  Eni Musta; Nan van Geloven; Jakob Anninga; Hans Gelderblom; Marta Fiocco
Journal:  BMJ Open       Date:  2022-05-10       Impact factor: 3.006

5.  Defining the Chance of Statistical Cure Among Patients with Extrahepatic Biliary Tract Cancer.

Authors:  Gaya Spolverato; Fabio Bagante; Cecilia G Ethun; George Poultsides; Thuy Tran; Kamran Idrees; Chelsea A Isom; Ryan C Fields; Bradley Krasnick; Emily Winslow; Clifford Cho; Robert C G Martin; Charles R Scoggins; Perry Shen; Harveshp D Mogal; Carl Schmidt; Eliza Beal; Ioannis Hatzaras; Rivfka Shenoy; Shishir K Maithel; Timothy M Pawlik
Journal:  World J Surg       Date:  2017-01       Impact factor: 3.352

6.  EM algorithms for fitting multistate cure models.

Authors:  Lauren J Beesley; Jeremy M G Taylor
Journal:  Biostatistics       Date:  2019-07-01       Impact factor: 5.899

7.  Laplacian-P-splines for Bayesian inference in the mixture cure model.

Authors:  Oswaldo Gressani; Christel Faes; Niel Hens
Journal:  Stat Med       Date:  2022-03-14       Impact factor: 2.497

8.  What Cure Models Can Teach us About Genome-Wide Survival Analysis.

Authors:  Sven Stringer; Damiaan Denys; René S Kahn; Eske M Derks
Journal:  Behav Genet       Date:  2015-11-09       Impact factor: 2.805

9.  The cure model in perinatal epidemiology.

Authors:  Emil A Stoltenberg; Hedvig Me Nordeng; Eivind Ystrom; Sven O Samuelsen
Journal:  Stat Methods Med Res       Date:  2020-02-11       Impact factor: 3.021

  9 in total

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