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"This handbook focuses on the analysis of lifetime data arising from the biological and medical sciences. It deals with semiparametric and nonparametric methods. For investigators new to this field, the book provides an overview of the topic along with examples of the methods discussed. It presents both classical methods and modern Bayesian approaches to the analysis of data"--"Preface This volume examines modern techniques and research problems in the analysis of life time data analysis. This area of statistics deals with time to event data which is complicated not only by the dynamic nature of events occurring in time but by censoring where some events are not observed directly but rather they are known to fall in some interval or range. Historically survival analysis is one of the oldest areas of statistics dating its origin to classic life table construction begun in the 1600's. Much of the early work in this area involved constructing better life tables and long tedious extensions of non-censored nonparametric estimators. Modern survival analysis began in the late 1980's with pioneering work by Odd Aalen on adapting classical Martingale theory to these more applied problems. Theory based on these counting process martingales made the development of techniques for censored and truncated data in most cases easier and opened the door to both Bayesian and classical statistics for a wide range of problems and applications. In this volume we present a series of papers which provide an introduction to the advances in survival analysis techniques in the past thirty years. These papers can serve four complimentary purposes. First, they provide an introduction to various areas in survival analysis for graduates students and other new researchers to this eld. Second, they provide a reference to more established investigators in this area of modern investigations into survival analysis. Third, with a bit of supplementation on counting process theory this volume is useful as a text for a second or advanced course in survival analysis. We have found that the instructor of such a course can pick and chose papers in areas he/​she deem most useful to the"

"Pada tahun 2022, jumlah kematian kanker payudara di Indonesia merupakan yang keempat tertinggi secara global. Banyaknya kematian kanker payudara salah satunya disebabkan oleh komorbiditas. Studi ini bertujuan untuk mengetahui hubungan komorbiditas dengan survival tiga tahun kanker payudara di Indonesia.  Studi ini menggunakan desain studi kohort retrospektif dan mencakup 896 sampel dari Data Sampel General BPJS Kesehatan tahun 2018-2023. Kurva dan probabilitas survival dibuat dengan metode Kaplan-Meier. Sedangkan hubungan dilihat dengan uji log-rank dan Hazard Ratio (HR) dianalisis dengan uji cox regression. Hasil studi menunjukkan cumulative survival probability (CSP) pada total sampel di bulan ke-36 adalah 49,9%, median waktu survival adalah 35,34 bulan. Pasien kanker payudara yang memiliki komorbid dan komorbid lainnya memiliki risiko kematian yang lebih tinggi dalam tiga tahun (Komorbid CSP = 43,7%; HR = 1,38; 95% CI = 1,01-1,89, komorbid lainnya CSP = 42,4%; HR = 1,43; 95% CI = 1,01-2,04). Studi ini tidak menemukan perbedaan survival yang signifikan antara kedua kelompok di variabel gangguan metabolik termasuk diabetes, hipertensi, penyakit kardiovaskular, usia saat diagnosis, status pernikahan, kondisi sosial ekonomi, dan tempat tinggal. Survival pasien kanker payudara di Indonesia termasuk rendah, khususnya pasien dengan komorbid.

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In 2022, Indonesia ranked fourth globally in the number of breast cancer deaths. One of the contributing factors to the high mortality rate is comorbidity. This study aims to examine the association between comorbidities and three-year survival of breast cancer patients in Indonesia. A retrospective cohort design was used, involving 896 samples from the 2018–2023 BPJS Kesehatan General Sample Data. Survival curves and probabilities were estimated using the Kaplan-Meier method, while associations were analyzed using the log-rank test and Hazard Ratios (HR) via Cox regression. The study found that the cumulative survival probability (CSP) at 36 months for the overall sample was 49.9%, with a median survival time of 35,34 months. Breast cancer patients with comorbidities and other comorbid conditions had a higher risk of death within three years (comorbidity CSP = 43.7%; HR = 1.38; 95% CI = 1.01–1.89, other comorbidities CSP = 42.4%; HR = 1.43; 95% CI = 1.01–2.04). No significant differences in survival were found based on metabolic disorders including diabetes, hypertension, cardiovascular disease, age at diagnosis, marital status, socioeconomic status, or place of residence. Breast cancer survival in Indonesia remains low, particularly among patients with comorbidities."

"Penelitian survival secara historical cohort pada enam puluh dua penderita tumor ovarium borderline. Terdapat 9 penderita stadium FIGO IA, 9 stadium IC, 3 stadium IIIA, 2 stadium IIIB, 4 stadium IIIC, 1 stadium IV dan 34 stadium inadekuat. Dua puluh satu penderita dilakukan pembedahan radikal, 10 penderita hanya dilakukan histerektomi total dan salfingo-ooforektomi bilateral, 6 penderita dilakukan pembedahan konservatif, 24 penderita hanya dilakukan unilateral salfingo-ooforektomi atau kistektomi dan 1 penderita hanya biopsi saja. Enam belas penderita mendapat kemoterapi adjuvan kombinasi dengan platinum base, yaitu 8 penderita stadium inadekuat, 7 stadium III dan 1 stadium IV. Lama pengamatan lanjut antara 0,002 sampai 10,48 tahun dengan median 3,5 tahun. Lima puluh sembilan penderita tetap hidup. Tiga penderita meninggal karena penyakitnya. Residif terjadi pada 4 penderita. Ketahanan hidup penderita 2 tahun 96% dan 10 tahun 94%. Pada test ?log rank? didapatkan residu dan tipe histologi merupakan faktor prognostik yang bermakna mempengaruhi survival. (Med J Indones 2002; 11: 222-9)

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Sixty-two patients with borderline tumors of ovary were historical cohort analyzed for survival characteristics. There were 9 patients with FIGO stage IA, 9 with stage IC, 3 with stage IIIA, 2 with stage IIIB, 4 with stage IIIC, 1 with stage IV and 34 with inadequate stage tumors. Twenty one patients had surgical staging with radical surgery, 10 patient had at least a total abdominal hysterectomy and bilateral salpingo-oophorectomy, 6 patient had surgical staging with conservative surgery, 24 patient had at least a unilateral salphingo-oophorectomy or ovarian cystectomy and 1 patient had biopsy. Sixteen patients received cisplatin-based combination chemotherapy, that were 8 with inadequate stage tumors, 7 with stage III tumors and 1 with stage IV tumor. Follow-up range from 0.02 to 10.48 years, with a median of 3.5 years. Fifty nine patient were alive. Three patients died, all of disease. Recurrence were found in 4 patients. The overall 2-years survival rate was 96% and 10-years survival rate was 94%. In log rank test, residual disease and histology type were significant predictor of survival. (Med J Indones 2002; 11:222-9)"