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...
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Politeknik Harapan Bersama Tegal
2019-01-01
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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 |
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1725397129407496192 |