Modeling and trend analysis of leukemia in children using time series methods

Background & Aim: Time series analysis is used to detect a model and predict the future amounts of the series, which is based on previous data. One of the commonly used models in time series is autoregressive integrated moving average (ARIMA) model. 30% of diseases in children are acute leukemi...

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Main Authors: Marzieh Mahmudimanesh, Abbas Bahrampour, Nooshin Akbari Sharak, Zahra Farahmandinia
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2017-08-01
Series:Journal of Biostatistics and Epidemiology
Subjects:
Online Access:https://jbe.tums.ac.ir/index.php/jbe/article/view/113
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spelling doaj-5b827c8d260c4955a1184c73daa330b02020-12-06T04:15:23ZengTehran University of Medical SciencesJournal of Biostatistics and Epidemiology2383-41962383-420X2017-08-0123Modeling and trend analysis of leukemia in children using time series methodsMarzieh Mahmudimanesh0Abbas Bahrampour1Nooshin Akbari Sharak2Zahra Farahmandinia3Department of Epidemiology and Biostatistics, School of Public Health, Kerman University of Medical Sciences, Kerman, IranDepartment of Epidemiology and Biostatistics, School of Public Health, Research Center for Modeling and Health, InstituteDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, IranDepartment of Pediatrics, Afzalipour School of Medicine, Kerman University of Medical Sciences, Kerman, Iran Background & Aim: Time series analysis is used to detect a model and predict the future amounts of the series, which is based on previous data. One of the commonly used models in time series is autoregressive integrated moving average (ARIMA) model. 30% of diseases in children are acute leukemia, out of which acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) consist 97% of acute leukemia types. In this study which is a modeling study, the ARIMA time series model is fitted on the acute leukemia cancer in children and the best model is selected. Methods & Materials: This study which is related to the children with cancer ALL and AML, and includes age groups from 1 year old to 15 years old, the ARIMA time series model is fitted on these data, and the best model is selected based on the Akaike information criteria. Trend analysis was also conducted based on the criteria R2 and mean squared error, mean absolute deviation, and mean absolute percentage error were considered as the best equations for the series. Results: ARIMA models are investigated, and the best model is selected and also it was shown that the procedure of catching blood cancer has been increasingly from 82 to 88 and then decreasingly but it may get an increasing procedure in the future. Furthermore, the procedure was shown in two sexual groups and it was observed that catching blood cancer had a decreasing procedure in men and had an increasing procedure in women and appropriate ARIMA model was also determined for each group. Conclusion: According to the forecasts for the next 10 years, the incidence of this cancer will be increasing in the future. There was an increasing trend for female group and a downward trend for male group. https://jbe.tums.ac.ir/index.php/jbe/article/view/113Time seriesAuto regressive integratedmoving averageTrend analysisleukemiaAcute lymphoblasticleukemiaAcute myeloid leukemia
collection DOAJ
language English
format Article
sources DOAJ
author Marzieh Mahmudimanesh
Abbas Bahrampour
Nooshin Akbari Sharak
Zahra Farahmandinia
spellingShingle Marzieh Mahmudimanesh
Abbas Bahrampour
Nooshin Akbari Sharak
Zahra Farahmandinia
Modeling and trend analysis of leukemia in children using time series methods
Journal of Biostatistics and Epidemiology
Time series
Auto regressive integratedmoving average
Trend analysis
leukemia
Acute lymphoblasticleukemia
Acute myeloid leukemia
author_facet Marzieh Mahmudimanesh
Abbas Bahrampour
Nooshin Akbari Sharak
Zahra Farahmandinia
author_sort Marzieh Mahmudimanesh
title Modeling and trend analysis of leukemia in children using time series methods
title_short Modeling and trend analysis of leukemia in children using time series methods
title_full Modeling and trend analysis of leukemia in children using time series methods
title_fullStr Modeling and trend analysis of leukemia in children using time series methods
title_full_unstemmed Modeling and trend analysis of leukemia in children using time series methods
title_sort modeling and trend analysis of leukemia in children using time series methods
publisher Tehran University of Medical Sciences
series Journal of Biostatistics and Epidemiology
issn 2383-4196
2383-420X
publishDate 2017-08-01
description Background & Aim: Time series analysis is used to detect a model and predict the future amounts of the series, which is based on previous data. One of the commonly used models in time series is autoregressive integrated moving average (ARIMA) model. 30% of diseases in children are acute leukemia, out of which acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) consist 97% of acute leukemia types. In this study which is a modeling study, the ARIMA time series model is fitted on the acute leukemia cancer in children and the best model is selected. Methods & Materials: This study which is related to the children with cancer ALL and AML, and includes age groups from 1 year old to 15 years old, the ARIMA time series model is fitted on these data, and the best model is selected based on the Akaike information criteria. Trend analysis was also conducted based on the criteria R2 and mean squared error, mean absolute deviation, and mean absolute percentage error were considered as the best equations for the series. Results: ARIMA models are investigated, and the best model is selected and also it was shown that the procedure of catching blood cancer has been increasingly from 82 to 88 and then decreasingly but it may get an increasing procedure in the future. Furthermore, the procedure was shown in two sexual groups and it was observed that catching blood cancer had a decreasing procedure in men and had an increasing procedure in women and appropriate ARIMA model was also determined for each group. Conclusion: According to the forecasts for the next 10 years, the incidence of this cancer will be increasing in the future. There was an increasing trend for female group and a downward trend for male group.
topic Time series
Auto regressive integratedmoving average
Trend analysis
leukemia
Acute lymphoblasticleukemia
Acute myeloid leukemia
url https://jbe.tums.ac.ir/index.php/jbe/article/view/113
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