On predicting cancer mortality using ANOVA-type P-spline models

Extrapolating cancer mortality trends can be very valuable as a tool to predict cancer burden. National Health Agencies use different models to figure out future evolution of cancer, but they mainly work at national level. However, developed countries are divided into different regions with their ow...

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Published inRevstat Vol. 13; no. 1; p. 21
Main Authors Etxeberria, Jaione, Ugarte, Maria Dolores, Goicoa, Tomas, Militino, Ana F
Format Journal Article
LanguageEnglish
Published Instituto Nacional de Estatistica 01.03.2015
Instituto Nacional de Estatística | Statistics Portugal
Subjects
Online AccessGet full text
ISSN1645-6726
2183-0371
DOI10.57805/revstat.v13i1.162

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Abstract Extrapolating cancer mortality trends can be very valuable as a tool to predict cancer burden. National Health Agencies use different models to figure out future evolution of cancer, but they mainly work at national level. However, developed countries are divided into different regions with their own governments and health care systems, and this should be taken into account. In this paper, an ANOVA-type P-spline model is considered to predict the number of mortality cases in forthcoming years in regions within a country. The model is very interesting as it allows to split the predictions into components representing region-specific features and characteristics common to the whole country. Prediction variability is also calculated to provide prediction intervals. Real data on cancer mortality are used for illustration. Key-Words: region-specific predictions; smoothing and predicting counts; space-time interactions; prostate cancer. AMS Subject Classification: * 62M20, 62G08, 62H11.
AbstractList Extrapolating cancer mortality trends can be very valuable as a tool to predict cancer burden. National Health Agencies use different models to figure out future evolution of cancer, but they mainly work at national level. However, developed countries are divided into different regions with their own governments and health care systems, and this should be taken into account. In this paper, an ANOVA-type P-spline model is considered to predict the number of mortality cases in forthcoming years in regions within a country. The model is very interesting as it allows to split the predictions into components representing region-specific features and characteristics common to the whole country. Prediction variability is also calculated to provide prediction intervals. Real data on cancer mortality are used for illustration.
Extrapolating cancer mortality trends can be very valuable as a tool to predict cancer burden. National Health Agencies use different models to figure out future evolution of cancer, but they mainly work at national level. However, developed countries are divided into different regions with their own governments and health care systems, and this should be taken into account. In this paper, an ANOVA-type P-spline model is considered to predict the number of mortality cases in forthcoming years in regions within a country. The model is very interesting as it allows to split the predictions into components representing region-specific features and characteristics common to the whole country. Prediction variability is also calculated to provide prediction intervals. Real data on cancer mortality are used for illustration. Key-Words: region-specific predictions; smoothing and predicting counts; space-time interactions; prostate cancer. AMS Subject Classification: * 62M20, 62G08, 62H11.
Audience Academic
Author Etxeberria, Jaione
Ugarte, Maria Dolores
Goicoa, Tomas
Militino, Ana F
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SubjectTerms Analysis of variance
Cancer
Forecasts and trends
Mortality
Patient outcomes
Prognosis
prostate cancer
region-specific predictions
smoothing and predicting counts
space-time interactions
Spline theory
United States
Title On predicting cancer mortality using ANOVA-type P-spline models
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