Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools

Background: Cancer is one of the most devastating diseases that influence humanity in the modern era. The effect is not confined to morbidity and mortality, but it is also extended to social and economic consequences despite the advancements made in the medical and healthcare fields. The present cas...

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Autores principales:	Engy Refaat Rashed, Mostafa Essam Eissa
Formato:	article
Lenguaje:	EN
Publicado:	Emergency Department of Hospital San Pedro (Logroño, Spain) 2020
Materias:	cancer mortality ratio spc usa who Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/8666317b5ff343ef89d01695d6ee508f
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spelling	oai:doaj.org-article:8666317b5ff343ef89d01695d6ee508f2021-12-02T18:12:17ZLong-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools10.5281/zenodo.37406102695-5075https://doaj.org/article/8666317b5ff343ef89d01695d6ee508f2020-04-01T00:00:00Zhttps://doi.org/10.5281/zenodo.3740610https://doaj.org/toc/2695-5075Background: Cancer is one of the most devastating diseases that influence humanity in the modern era. The effect is not confined to morbidity and mortality, but it is also extended to social and economic consequences despite the advancements made in the medical and healthcare fields. The present case overview will focus on the overall long-term assessment of death rates from malignancy from 1960 to 2017 as part of a global study of the mortality trend of this disease. Methods: Statistical analysis and process control methodologies were used to study the death rate trend over this recorded period using statistical programs platform. A combination of techniques that could be used sequentially after database processing and stratification were used including distribution fitting, descriptive statistics, data fitting mathematical pattern, Gaussian Mixture Model (GMM) box plot and Individual-Moving Range (I-MR) trending chart. Results: Two-parameter Weibull distribution (or Weibull 2) was the most appropriate that has fitted the distribution pattern of data and used for the construction of the process-behavior chart. The last two decades of the dataset showed a progressive decline in the mortality rates, which were almost linear with a higher magnitude of a negative slope than that of the initial rising pattern from 1960 until the 1990s. The hump-shaped trend showed underlying two distribution clusters: An initial distribution (I) of 81% of data of higher average mortality rates and minor one (II) that covers the last decade of monitoring record. Discussion: A significant improvement in cancer healthcare was witnessed with a noticeable breakthrough in the last decade in the USA.Engy Refaat RashedMostafa Essam EissaEmergency Department of Hospital San Pedro (Logroño, Spain)articlecancermortality ratiospcusawhoMedicine (General)R5-920ENIberoamerican Journal of Medicine, Vol 2, Iss 2, Pp 55-60 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	cancer mortality ratio spc usa who Medicine (General) R5-920
spellingShingle	cancer mortality ratio spc usa who Medicine (General) R5-920 Engy Refaat Rashed Mostafa Essam Eissa Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools
description	Background: Cancer is one of the most devastating diseases that influence humanity in the modern era. The effect is not confined to morbidity and mortality, but it is also extended to social and economic consequences despite the advancements made in the medical and healthcare fields. The present case overview will focus on the overall long-term assessment of death rates from malignancy from 1960 to 2017 as part of a global study of the mortality trend of this disease. Methods: Statistical analysis and process control methodologies were used to study the death rate trend over this recorded period using statistical programs platform. A combination of techniques that could be used sequentially after database processing and stratification were used including distribution fitting, descriptive statistics, data fitting mathematical pattern, Gaussian Mixture Model (GMM) box plot and Individual-Moving Range (I-MR) trending chart. Results: Two-parameter Weibull distribution (or Weibull 2) was the most appropriate that has fitted the distribution pattern of data and used for the construction of the process-behavior chart. The last two decades of the dataset showed a progressive decline in the mortality rates, which were almost linear with a higher magnitude of a negative slope than that of the initial rising pattern from 1960 until the 1990s. The hump-shaped trend showed underlying two distribution clusters: An initial distribution (I) of 81% of data of higher average mortality rates and minor one (II) that covers the last decade of monitoring record. Discussion: A significant improvement in cancer healthcare was witnessed with a noticeable breakthrough in the last decade in the USA.
format	article
author	Engy Refaat Rashed Mostafa Essam Eissa
author_facet	Engy Refaat Rashed Mostafa Essam Eissa
author_sort	Engy Refaat Rashed
title	Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools
title_short	Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools
title_full	Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools
title_fullStr	Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools
title_full_unstemmed	Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools
title_sort	long-term monitoring of cancer mortality rates in usa: a descriptive analysis using statistical process control tools
publisher	Emergency Department of Hospital San Pedro (Logroño, Spain)
publishDate	2020
url	https://doaj.org/article/8666317b5ff343ef89d01695d6ee508f
work_keys_str_mv	AT engyrefaatrashed longtermmonitoringofcancermortalityratesinusaadescriptiveanalysisusingstatisticalprocesscontroltools AT mostafaessameissa longtermmonitoringofcancermortalityratesinusaadescriptiveanalysisusingstatisticalprocesscontroltools
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Long-term monitoring of Cancer Mortality Rates in USA: A descriptive analysis using statistical process control tools

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