Literature DB >> 9351166

A simple non-linear model in incidence prediction.

T Dyba1, T Hakulinen, L Päivärinta.   

Abstract

A simple model is proposed for incidence prediction. The model is non-linear in parameters but linear in time, following models in environmental cancer epidemiology. Assuming a Poisson distribution for the age and period specific numbers of incident cases approximate confidence and prediction intervals are calculated. The major advantage of this model over current models is that age-specific predictions can be made with greater accuracy. The model also preserves in the period of prediction the age pattern of incidence rates existing in the data. It may be fitted with any package which includes an iteratively reweighted least squares algorithm, for example GLIM. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are presented as an example.

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Year:  1997        PMID: 9351166     DOI: 10.1002/(sici)1097-0258(19971030)16:20<2297::aid-sim668>3.0.co;2-f

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  13 in total

1.  Prediction of cancer incidence in Tyrol/Austria for year of diagnosis 2020.

Authors:  Willi Oberaigner; Sabine Geiger-Gritsch
Journal:  Wien Klin Wochenschr       Date:  2014-09-06       Impact factor: 1.704

Review 2.  Planning for tomorrow: global cancer incidence and the role of prevention 2020-2070.

Authors:  Isabelle Soerjomataram; Freddie Bray
Journal:  Nat Rev Clin Oncol       Date:  2021-06-02       Impact factor: 66.675

3.  Incidence of Multiple vs First Cutaneous Squamous Cell Carcinoma on a Nationwide Scale and Estimation of Future Incidences of Cutaneous Squamous Cell Carcinoma.

Authors:  Selin Tokez; Loes Hollestein; Marieke Louwman; Tamar Nijsten; Marlies Wakkee
Journal:  JAMA Dermatol       Date:  2020-12-01       Impact factor: 10.282

4.  A statistical model of the international spread of wild poliovirus in Africa used to predict and prevent outbreaks.

Authors:  Kathleen M O'Reilly; Claire Chauvin; R Bruce Aylward; Chris Maher; Sam Okiror; Chris Wolff; Deo Nshmirimana; Christl A Donnelly; Nicholas C Grassly
Journal:  PLoS Med       Date:  2011-10-18       Impact factor: 11.069

5.  Modelling predictions of cancer deaths in Northern Ireland.

Authors:  D French; D Catney; A T Gavin
Journal:  Ulster Med J       Date:  2006-05

6.  Unemployment and prostate cancer mortality in the OECD, 1990-2009.

Authors:  Mahiben Maruthappu; Johnathan Watkins; Abigail Taylor; Callum Williams; Raghib Ali; Thomas Zeltner; Rifat Atun
Journal:  Ecancermedicalscience       Date:  2015-05-14

7.  Cancer burden in slovenia with the time trends analysis.

Authors:  Vesna Zadnik; Maja Primic Zakelj; Katarina Lokar; Katja Jarm; Urska Ivanus; Tina Zagar
Journal:  Radiol Oncol       Date:  2017-02-22       Impact factor: 2.991

8.  Predictions of cancer incidence in Wielkopolska in 2018.

Authors:  Dariusz Godlewski; Piotr Wojtyś; Andrzej Antczak
Journal:  Contemp Oncol (Pozn)       Date:  2012-02-29

9.  Estimation and projection of the national profile of cancer mortality in China: 1991-2005.

Authors:  L Yang; D M Parkin; L D Li; Y D Chen; F Bray
Journal:  Br J Cancer       Date:  2004-06-01       Impact factor: 7.640

Review 10.  Vismodegib: the proof of concept in Basal cell carcinoma.

Authors:  Narjiss Berrada; Siham Lkhoyali; Hind Mrabti; Hassan Errihani
Journal:  Clin Med Insights Oncol       Date:  2014-06-02
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