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COX PROPORTIONAL HAZARD REGRESSION SURVIVAL ANALYSIS FOR TYPE 2 DIABETES MELITUS

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 1 (2022) · hlm. 253–262

DOI
10.30598/barekengvol16iss1pp251-260
ISSN
2615-3017, 1978-7227
Terbit
2022-03-21
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng

Abstrak

One of the most widely used methods of survival analysis is Cox proportional hazard regression. It is a semiparametric regression used to investigate the effects of a number of variables on the dependent variable based on survival time. Using the Cox proportional hazard regression method, this study aims to estimate the factors that influence the survival of patients with type 2 diabetes mellitus. The estimated parameter values, as well as the Cox Regression equation model, were also investigated. A total of 1293 diabetic patients with type 2 diabetes were studied, with data taken from medical records at PKU Muhammadiyah Hospital in Yogyakarta, Indonesia. These variables have regression coefficients of 1.36, 1.59, -0.63, 0.11, and 0.51, respectively. Furthermore, the results showed the hazard ratio for female patients was 1.16 times male patients. Patients on insulin treatment had a 4.92-fold higher risk of death than those on other therapy profiles. Patients with normal blood sugar levels (GDS 140 mg/dl) had a 1.12 times higher risk of death than those with other blood glucose levels. Type 2 diabetes mellitus is a challenge for many Indonesians, in addition to being a deadly condition that was initially difficult to diagnose. As a result, patient survival analysis is needed to reduce the patient's risk of death.

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  • Universiti Malaysia Terengganu
  • Universitas Ahmad Dahlan
  • Sebelas Maret University
  • Binus University
  • Jakarta State Polytechnic
  • Universitas Nahdlatul Ulama Indonesia
  • Institut Teknologi Sepuluh Nopember
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Abdul Aziz K. Abdul HamidUniversiti Malaysia Terengganu2
Muhamad ChamdaniSebelas Maret University2
Samsul ArifinBinus University2
I Gusti Agung Anom YudistiraBinus University2
Rinda NariswariBinus University2
Abdul Azis AbdillahJakarta State Polytechnic2
Salsalia Nor FatimahUniversitas Nahdlatul Ulama Indonesia2
Kartika Chrysti SuryandariSebelas Maret University2
Suhartono SuhartonoInstitut Teknologi Sepuluh Nopember1
Ade Dedi RohayanaUniversitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan1
Goh Kang WenAfiliasi tidak diketahui1
Rahmania Ayu WardaniUniversitas Ahmad Dahlan1
Nursyiva IrsalindaUniversitas Ahmad Dahlan1
Dera Kurnia LaelyUniversitas Ahmad Dahlan1
Muhammad ArdiyansyahUniversity of Jyväskylä1
Sharifah Sakinah Syed Abd MutalibAfiliasi tidak diketahui1
Raden Fenny SyafarianiUniversitas Komputer Indonesia1
Wan Nuraini Fahana Wan NasirUniversiti Malaysia Terengganu1
Nurul Hila ZainuddinSultan Idris Education University1
Indriyani IndriyaniUniversitas Jambi1
Urfia RizqiAfiliasi tidak diketahui1
Siti Mumun MunirohAfiliasi tidak diketahui1
Maghfur AhmadAfiliasi tidak diketahui1
Siti Sahatul FatimahSebelas Maret University1
Zaenal MustakimAfiliasi tidak diketahui1
Tarmidzi TarmidziAfiliasi tidak diketahui1
Siti FatimahSebelas Maret University1
Muhammad Amien IbrahimBinus University1
Nerru Pranuta MurnakaAfiliasi tidak diketahui1
Nanang SusyantoUniversitas Gadjah Mada1
Wan Saliha Wan AlwiUniversiti Malaysia Terengganu1
Nur Edayu ZainiUniversiti Malaysia Terengganu1
Mohd Noor Afiq RamleeUniversiti Malaysia Terengganu1

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Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">COX PROPORTIONAL HAZARD REGRESSION SURVIVAL ANALYSIS FOR TYPE 2 DIABETES MELITUS</dc:title>
	<dc:creator>Mahmudah, Umi</dc:creator>
	<dc:creator>Surono, Sugiyarto</dc:creator>
	<dc:creator>Prasetyo, Puguh Wahyu</dc:creator>
	<dc:creator>Lola, Muhamad Safiih</dc:creator>
	<dc:creator>Haryati, Annisa Eka</dc:creator>
	<dc:description xml:lang="en-US">One of the most widely used methods of survival analysis is Cox proportional hazard regression. It is a semiparametric regression used to investigate the effects of a number of variables on the dependent variable based on survival time. Using the Cox proportional hazard regression method, this study aims to estimate the factors that influence the survival of patients with type 2 diabetes mellitus. The estimated parameter values, as well as the Cox Regression equation model, were also investigated. A total of 1293 diabetic patients with type 2 diabetes were studied, with data taken from medical records at PKU Muhammadiyah Hospital in Yogyakarta, Indonesia. These variables have regression coefficients of 1.36, 1.59, -0.63, 0.11, and 0.51, respectively. Furthermore, the results showed the hazard ratio for female patients was 1.16 times male patients. Patients on insulin treatment had a 4.92-fold higher risk of death than those on other therapy profiles. Patients with normal blood sugar levels (GDS 140 mg/dl) had a 1.12 times higher risk of death than those with other blood glucose levels. Type 2 diabetes mellitus is a challenge for many Indonesians, in addition to being a deadly condition that was initially difficult to diagnose. As a result, patient survival analysis is needed to reduce the patient's risk of death. </dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-03-21</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4956</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss1pp251-260</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan; 253-262</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss1year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4956/4028</dc:relation>
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