Literature DB >> 18992379

Comparison of detailed and succinct cohort modelling approaches in a multi-regional evaluation of cervical cancer vaccination.

Donna Debicki1, Nicole Ferko, Nadia Demarteau, Steve Gallivan, Chris Bauch, Andrea Anonychuk, Lorenzo Mantovani, Stefano Capri, Cheng-Yang Chou, Baudouin Standaert, Lieven Annemans.   

Abstract

Mathematical models have been used extensively in the evaluation of chronic diseases and in exploring the health economics of vaccination. In this study, we examine the value of having two different cohort models based on similar assumptions, one comprehensive and one simplified, which can be used to evaluate the impact of cervical cancer vaccination. To compare models, we ran cost-effectiveness analyses in four geographical regions (Italy, the UK, Taiwan and Canada). We show that the models produce comparable results and therefore can be used independently. However, as they require different complexities of data inputs, they are more suited to different circumstances depending on the level of data inputs available or the complexity of the research question asked.

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Year:  2008        PMID: 18992379     DOI: 10.1016/j.vaccine.2008.02.040

Source DB:  PubMed          Journal:  Vaccine        ISSN: 0264-410X            Impact factor:   3.641


  22 in total

1.  Selecting a mix of prevention strategies against cervical cancer for maximum efficiency with an optimization program.

Authors:  Nadia Demarteau; Thomas Breuer; Baudouin Standaert
Journal:  Pharmacoeconomics       Date:  2012-04       Impact factor: 4.981

2.  Public health impact of human papillomavirus vaccination on prevention of cervical cancer in France.

Authors:  Abdelkader El Hasnaoui; Nadia Demarteau; Denis Granados; Baudouin Standaert; Bruno Detournay
Journal:  Int J Public Health       Date:  2011-06-28       Impact factor: 3.380

Review 3.  Modeling preventative strategies against human papillomavirus-related disease in developed countries.

Authors:  Karen Canfell; Harrell Chesson; Shalini L Kulasingam; Johannes Berkhof; Mireia Diaz; Jane J Kim
Journal:  Vaccine       Date:  2012-11-20       Impact factor: 3.641

Review 4.  The cost effectiveness of human papillomavirus vaccines: a systematic review.

Authors:  Katherine Seto; Fawziah Marra; Adam Raymakers; Carlo A Marra
Journal:  Drugs       Date:  2012-03-26       Impact factor: 11.431

5.  A generally applicable cost-effectiveness model for the evaluation of vaccines against cervical cancer.

Authors:  Nadia Demarteau; Bruno Detournay; Bertrand Tehard; Abdelkader El Hasnaoui; Baudouin Standaert
Journal:  Int J Public Health       Date:  2010-11-26       Impact factor: 3.380

6.  Cost-effectiveness of different human papillomavirus vaccines in Singapore.

Authors:  Vernon J Lee; Sun Kuie Tay; Yee Leong Teoh; Mei Yin Tok
Journal:  BMC Public Health       Date:  2011-03-31       Impact factor: 3.295

7.  Cost-effectiveness analysis of human papillomavirus DNA testing and Pap smear for cervical cancer screening in a publicly financed health-care system.

Authors:  I H-I Chow; C-H Tang; S-L You; C-H Liao; T-Y Chu; C-J Chen; C-A Chen; R-F Pwu
Journal:  Br J Cancer       Date:  2010-11-23       Impact factor: 7.640

8.  A cost-utility analysis of cervical cancer vaccination in preadolescent Canadian females.

Authors:  Andrea M Anonychuk; Chris T Bauch; Maraki Fikre Merid; Georges Van Kriekinge; Nadia Demarteau
Journal:  BMC Public Health       Date:  2009-10-31       Impact factor: 3.295

9.  Cost-effectiveness of human papillomavirus vaccination for prevention of cervical cancer in Taiwan.

Authors:  Pang-Hsiang Liu; Fu-Chang Hu; Ping-Ing Lee; Song-Nan Chow; Chao-Wan Huang; Jung-Der Wang
Journal:  BMC Health Serv Res       Date:  2010-01-11       Impact factor: 2.655

10.  Modeling the impact of the difference in cross-protection data between a human papillomavirus (HPV)-16/18 AS04-adjuvanted vaccine and a human papillomavirus (HPV)-6/11/16/18 vaccine in Canada.

Authors:  Michele Kohli; Donna Lawrence; Jennifer Haig; Andrea Anonychuk; Nadia Demarteau
Journal:  BMC Public Health       Date:  2012-10-13       Impact factor: 3.295

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