Analisis Survival pada Faktor Prognostik Pasien Kanker Prostat Menggunakan Regresi Cox

Antares, M. Aldevaran Jaylani (2026) Analisis Survival pada Faktor Prognostik Pasien Kanker Prostat Menggunakan Regresi Cox. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kanker prostat merupakan salah satu kanker yang paling banyak diderita pria di dunia maupun di Indonesia, dengan kelangsungan hidup pasien yang bervariasi sehingga diperlukan identifikasi faktor prognostik yang memengaruhi laju kematian pasien. Penelitian ini bertujuan untuk mendeskripsikan karakteristik pasien kanker prostat berdasarkan faktor-faktor prognostik serta memperoleh faktor-faktor yang berpengaruh signifikan terhadap laju kematian pasien menggunakan analisis survival dengan model regresi Cox proportional hazard (Cox PH). Data yang digunakan merupakan data sekunder rekam medis 84 pasien kanker prostat di RSUD Dr. Soetomo Surabaya periode Januari-Juni 2025, dengan tujuh variabel prediktor yaitu usia, kadar PSA, skor Gleason, kemoterapi, operasi, riwayat diabetes, dan riwayat hipertensi. Dari 84 pasien, sebanyak 9 pasien (11%) mengalami event kematian sedangkan 75 pasien (89%) tersensor. Hasil uji log-rank pada taraf signifikansi 5% menunjukkan bahwa status kemoterapi dan riwayat hipertensi memiliki perbedaan kurva survival yang signifikan antar kelompok. Pengujian asumsi proportional hazard dengan pendekatan goodness-of-fit residual Schoenfeld menunjukkan bahwa seluruh variabel telah memenuhi asumsi PH, sehingga model Cox PH dapat digunakan. Seleksi model dengan eliminasi backward berdasarkan nilai AIC mengeliminasi variabel riwayat diabetes dan usia, sehingga diperoleh model terbaik dengan lima variabel prediktor, yaitu kadar PSA, skor Gleason, status kemoterapi, status operasi, dan riwayat hipertensi, yang secara serentak berpengaruh signifikan terhadap laju kematian pasien. Secara parsial, variabel yang berpengaruh signifikan adalah skor Gleason, status kemoterapi, status operasi, dan riwayat hipertensi, sedangkan kadar PSA belum signifikan secara parsial namun tetap dipertahankan dalam model karena kontribusinya terhadap penurunan nilai AIC. Status kemoterapi teridentifikasi memberikan efek protektif terhadap kelangsungan hidup pasien, sedangkan status operasi dan riwayat hipertensi berhubungan dengan peningkatan risiko kematian, namun demikian, arah hubungan pada variabel operasi dan skor Gleason berlawanan dengan teori klinis, yang diduga disebabkan oleh ketimpangan jumlah sampel dan kejadian event pada masing-masing kategori. Hasil penelitian ini diharapkan dapat menjadi dasar pertimbangan bagi pihak rumah sakit dalam meningkatkan kualitas pelayanan dan strategi penanganan pasien kanker prostat.
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Prostate cancer is one of the most commonly diagnosed cancers among men worldwide and in Indonesia, with patient survival varying considerably, making it necessary to identify prognostic factors that influence the patient mortality rate. This study aims to describe the characteristics of prostate cancer patients based on prognostic factors and to determine the factors that significantly influence the patient mortality rate using survival analysis with the Cox proportional hazards (Cox PH) regression model. The data used are secondary data obtained from the medical records of 84 prostate cancer patients at Dr. Soetomo General Hospital, Surabaya, during the period January–June 2025, comprising seven predictor variables: age, PSA level, Gleason score, chemotherapy status, surgery status, history of diabetes, and history of hypertension. Of the 84 patients, 9 patients (11%) experienced the death event, while 75 patients (89%) were censored. The log-rank test results at a 5% significance level showed that chemotherapy status and history of hypertension had significantly different survival curves between groups. Testing of the proportional hazards assumption using the Schoenfeld residual goodness-of-fit approach showed that all variables satisfied the PH assumption, allowing the Cox PH model to be used. Model selection using backward elimination based on the AIC value eliminated the variables history of diabetes and age, resulting in the best model comprising five predictor variables PSA level, Gleason score, chemotherapy status, surgery status, and history of hypertension which simultaneously had a significant effect on the patient mortality rate. Partially, the variables found to have a significant effect were Gleason score, chemotherapy status, surgery status, and history of hypertension, while PSA level was not statistically significant on its own but was retained in the model due to its contribution to reducing the AIC value. Chemotherapy status was identified as having a protective effect on patient survival, whereas surgery status and history of hypertension were associated with an increased risk of death. However, the direction of the relationship for the surgery and Gleason score variables was contrary to clinical theory, which is presumed to be due to an imbalance in the number of samples and event occurrences within each category. The results of this study are expected to serve as a basis of consideration for the hospital in improving the quality of care and treatment strategies for prostate cancer patients

Item Type:	Thesis (Other)
Uncontrolled Keywords:	analisis survival, faktor prognostik, hazard ratio, kanker prostat, regresi Cox PH Cox PH regression, hazard ratio, prostate cancer, prognostic factors, survival analysis
Subjects:	H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	M. Aldevaran Jaylani Antares
Date Deposited:	04 Aug 2026 09:29
Last Modified:	04 Aug 2026 09:29
URI:	http://repository.its.ac.id/id/eprint/143645

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