ANALISIS SURVIVAL PADA DATA REKURENSI DENGAN MENGGUNAKAN COUNTING PROCESS APPROACH DAN MODEL PWP-GT STUDY KASUS: DATA KANKER SERVIK DI RUMAH SAKIT DR.SOETOMO SURABAYA

NOVITASARI, DIAH AYU (2014) ANALISIS SURVIVAL PADA DATA REKURENSI DENGAN MENGGUNAKAN COUNTING PROCESS APPROACH DAN MODEL PWP-GT STUDY KASUS: DATA KANKER SERVIK DI RUMAH SAKIT DR.SOETOMO SURABAYA. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kanker Serviks merupakan jenis kanker dengan jumlah pasien wanita paling banyak nomer dua di dunia. Penyebab utama kanker Serviks adalah infeksi Human Papilloma Virus (HPV). Pada stadium akhir atau kasus yang parah maka terpaksa dilakukan histerektomi, yaitu bedah pengangkatan rahim (uterus) secara total agar sel-sel kanker yang sudah berkembang dalam kandungan tidak menyebar ke bagian lain dalam tubuh. Namun pengobatan pada stadium awal tidak serta merta menyembuhkan kanker Serviks. Analisis yang sering digunakan untuk menganalisis kanker serviks adalah analisis survival overall. Namun, analisis yang dilakukan dengan survival overall menggunakan data 1-5 tahun setelah pasien terdiagnosa kanker Serviks. Padahal kenyataannya angka rekurensi kanker Serviks sangat tinggi meskipun pasien sudah menjalani operasi, sehingga diperlukan juga analisis survival untuk data rekurensi. Banyak model cox proporsional hazard yang telah dikembangkan untuk menganalisis data yang berulang atau rekurensi data. Namun, model yang direkomendasikan untuk menganalisis data rekurensi adalah model Prentice William Peterson-Gap Time (PWP-GT)). Tujuan dari penelitian ini adalah mengkaji estimator model Prentice William Peterson-Gap Time (PWP-GT) dan hasil model akan dibandingkan dengan hasil dari metode pendekatan cox proporsional hazard yaitu Counting Process Approach serta mengaplikasikannya pada data kanker Serviks di Rumah Sakit DR.Soetomo Surabaya. Pada model Counting Process Approach, Stadium merupakan variabel prediktor yang berpengaruh signifikan terhadap variabel respon dengan nilai estimasi parameter sebesar -0.54517. Pada Model PWP-GT, variabel prediktor yang berpengaruh signifikan terhadap variabel respon yaitu variabel jenis kanker dengan nilai estimasi parameter sebesar -1.46399. ===================================================================================================== Cervical cancer is a type of cancer with the number of female patients most number two in the world. In Indonesia, Cervical cancer is the number one cause of death in women. Primary cause of cervical cancer is infection Human Papilloma Virus (HPV) or human papilloma virus. In the later stages or severe cases it is forced to do a hysterectomy, the surgical removal of the uterus (womb) in total so that cancer cells that have developed in the womb does not spread to other parts of the body. However, treatment at an early stage and m erta not cure cervical cancer. Cases of recurrence often occurs after initial treatment has been carried out. Analysis is often used to analyze cervical cancer is overall survival analysis. However, the analysis performed by using the data overall survival of 1-5 years after patient diagnosed with cervical cancer. Although in the fact, recurrent rate of cervical cancer is very high even though the patient had undergone surgery, so it is also necessary for the survival analysis of data recurrent. Many cox proportional hazard models that have been developed to analyze the data are repeated or recurrent data. However, the recommended models for analyzing the data is modeled recurrence William Prentice Peterson- Gap Time (PWP-GT)). The purpose of this study is to examine the model estimator William Prentice Peterson- Gap Time (PWP-GT) and the model results will be compared with the results of Cox proportional hazard approach is Counting Process Approach and applying it to the data of cervical cancer in Dr.Soetomo Hospital Surabaya. On Counting Process Approach, Stadium is a predictor variables that significantly influence the response variable with the value of parameter estimation is -0. 54517. the PWP-GT model, predictor variables that significantly influence the response variable is the variable type of cancer with the estimated value of the parameter is -1.46399.

Item Type: Thesis (Masters)
Additional Information: RTSt 519.546 Nov a
Uncontrolled Keywords: Analisis Survival, Rekurensi, Counting Process Approach, Kanker Servik, PWP-GT.
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA278.2 Regression Analysis
Divisions: Faculty of Mathematics and Science > Statistics > (S2) Master Theses
Depositing User: Mr. Tondo Indra Nyata
Date Deposited: 05 Jan 2017 07:49
Last Modified: 05 Jan 2017 07:49
URI: http://repository.its.ac.id/id/eprint/1338

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