Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer

<p>In this paper, the data was analyzed by data mining techniques of association rules. The data for 506 patients consist of an identification number, stage of tumour, a code for the treatment to which the patient was assigned, the date of randomization, the total months of follow-up since ran...

Full description

Bibliographic Details
Main Authors: Iing Lukman, Emy Khikmawati
Format: Article
Language:English
Published: Politeknik Harapan Bersama Tegal 2019-01-01
Series:Jurnal Informatika: Jurnal Pengembangan IT
Online Access:http://ejournal.poltektegal.ac.id/index.php/informatika/article/view/1252
id doaj-0067a82d9e8d4f68844ca5f04ac42ca2
record_format Article
spelling doaj-0067a82d9e8d4f68844ca5f04ac42ca22020-11-25T00:12:51ZengPoliteknik Harapan Bersama TegalJurnal Informatika: Jurnal Pengembangan IT2477-51262548-93562019-01-0141161910.30591/jpit.v4i1.1252851Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic CancerIing Lukman0Emy Khikmawati1Universitas Malahayati BandarlampungUniversitas Malahayati Bandarlampung<p>In this paper, the data was analyzed by data mining techniques of association rules. The data for 506 patients consist of an identification number, stage of tumour, a code for the treatment to which the patient was assigned, the date of randomization, the total months of follow-up since randomization, an indicator for the survival status or cause of death, and the values of twelve pretreatment covariates. The goal of an analysis should be to compare the treatments with respect to survival of the patients. Since this was a randomized study it would ordinarily not be necessary to adjust for the values of the pretreatment covariates. However, in such studies it is advisable to examine the prognostic significance of the covariates and to confirm that they are balanced across treatment groups.  In addition, the analyst should look for important treatment-covariates interactions which might lead to the definition of subsets of patients in which treatment differences were significantly more marked or even reversed.</p>http://ejournal.poltektegal.ac.id/index.php/informatika/article/view/1252
collection DOAJ
language English
format Article
sources DOAJ
author Iing Lukman
Emy Khikmawati
spellingShingle Iing Lukman
Emy Khikmawati
Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer
Jurnal Informatika: Jurnal Pengembangan IT
author_facet Iing Lukman
Emy Khikmawati
author_sort Iing Lukman
title Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer
title_short Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer
title_full Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer
title_fullStr Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer
title_full_unstemmed Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer
title_sort association rules of prognostic variables for survival in a randomized comparison of treatments for prostatic cancer
publisher Politeknik Harapan Bersama Tegal
series Jurnal Informatika: Jurnal Pengembangan IT
issn 2477-5126
2548-9356
publishDate 2019-01-01
description <p>In this paper, the data was analyzed by data mining techniques of association rules. The data for 506 patients consist of an identification number, stage of tumour, a code for the treatment to which the patient was assigned, the date of randomization, the total months of follow-up since randomization, an indicator for the survival status or cause of death, and the values of twelve pretreatment covariates. The goal of an analysis should be to compare the treatments with respect to survival of the patients. Since this was a randomized study it would ordinarily not be necessary to adjust for the values of the pretreatment covariates. However, in such studies it is advisable to examine the prognostic significance of the covariates and to confirm that they are balanced across treatment groups.  In addition, the analyst should look for important treatment-covariates interactions which might lead to the definition of subsets of patients in which treatment differences were significantly more marked or even reversed.</p>
url http://ejournal.poltektegal.ac.id/index.php/informatika/article/view/1252
work_keys_str_mv AT iinglukman associationrulesofprognosticvariablesforsurvivalinarandomizedcomparisonoftreatmentsforprostaticcancer
AT emykhikmawati associationrulesofprognosticvariablesforsurvivalinarandomizedcomparisonoftreatmentsforprostaticcancer
_version_ 1725397129407496192