Survival analysis of cervical cancer using stratified Cox regression

Purnami, Santi Wulan; Inayati, Kurnia Dwi; Sari, Nariza Wanti Wulan; Chosuvivatwong, Virasakdi; Sriplung, Hutcha

doi:10.1063/1.4945076

Cited by 6 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…What is clear is that all these facts show the special position of this health problem in the world and Iran. Despite the fact that in recent decades, many studies have been conducted in the field of cervical cancer survival analyses ( 7 – 10 ), but in recent years, no study has been conducted in this regard in Kerman province, which is the largest province of Iran located in the southeast of Iran. Therefore, the analysis of data related to the new information of patients with cervical cancer in order to investigate the relationship between various factors with the survival rate of patients, especially in the less developed regions of the country, can be the innovation of this study.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Survival of Patients with Cervical Cancer

Hasankhani,

Jahani,

Bazrafshan

et al. 2023

ijph

View full text Add to dashboard Cite

Background: Cervical cancer is the fourth leading cause of cancer-related death among women worldwide. We aimed to identify the factors affecting the survival rate of cervical cancer patients, as these factors are vital for preventing the progression and effective treatment of cancer. Methods: In this retrospective cohort study, 254 patients with cervical cancer who were registered in The Kerman Population-Based Cancer Registry (KPBCR) between 2012 and 2022 and whose status was known to be alive or dead were enrolled. Since the proportional hazard assumption was not established for the type of treatment, the extended Cox model was used to determine the variables influencing the survival of the patients. Results: The mean survival time of the patients was 91.28 ± 3.02 months. The results of fitting the extended Cox model showed that the risk of death increases by 1.02 per year of age at diagnosis (HR=1.02; 95% CI: 1.00, 1.04). Moreover, for a one-unit increase in body mass index (BMI), the risk of death increased by 0.93 (HR=0.93; 95% CI: 0.88, 0.98). The risk of death in patients with disease stages III&IV was 3.08 times that of patients with disease stages I&II (HR=3.08; 95% CI: 1.05, 9.03). The risk of death in patients receiving at least one of the radiotherapy and chemotherapy treatments after 18 months was 7.11 times that of patients undergoing surgery (HR=7.11; 95% CI: 1.69, 29.91). Conclusion: The age of diagnosis, BMI, disease stage, and type of treatment significantly affect the survival of patients. Thus, raising women's awareness of periodical examinations and early diagnosis can reduce the risk of death and prevent cervical cancer progression.

show abstract

Section: Introductionmentioning

confidence: 99%

Factors Affecting Survival of Patients with Cervical Cancer

Hasankhani,

Jahani,

Bazrafshan

et al. 2023

ijph

View full text Add to dashboard Cite

show abstract

A simulation study and application of feature selection on survival least square support vector machines

Khoiri¹,

Prastyo²,

Purnami³

2019

The 4TH INNOVATION AND ANALYTICS CONFERENCE &Amp; EXHIBITION (IACE 2019)

View full text Add to dashboard Cite

Cox Model Survival Analysis to Evaluate Treatment of Electro-Capacitive Cancer Therapy (ECCT) For Cancer Patients

Purnami

Putra

Edina

et al. 2021

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Cancer is a disease caused by uncontrolled growth of abnormal cells in the body. Lung cancer, brain cancer and breast cancer are a deadly threat to sufferers. Cancer treatment using a therapy called Electro-Capacitive Cancer Therapy (ECCT) has received a lot of medical attention. Since 2012, the C-Tech Labs Edwar Technology Cancer Research Tangerang has applied ECCT to the therapeutic treatment more than 11,000 cancer patients. In this study, the Cox Proportional Hazard model was used to asses factors that affects survival of cancer patients. Some prognostic factors are evaluated included age of patient and type treatments such as herbs therapy, chemotherapy, radiotherapy and monitoring frequency of ECCT. The all three survival models (breast cancer, brain cancer, and lung cancer) identified the same prognostic factors. The study showed that monitoring frequency of ECCT is significant factor that influenced in cancer survival for all three survival models. Based on the Cox survival model, the hazard ratio (HR) value ranges from are 0.8 – 0.9. It means that each additional one time the frequency of monitoring, the risk of experiencing death decreased by 0.8 – 0.9 times.

show abstract

Survival analysis of cervical cancer using stratified Cox regression

Cited by 6 publications

References 3 publications

Factors Affecting Survival of Patients with Cervical Cancer

Factors Affecting Survival of Patients with Cervical Cancer

A simulation study and application of feature selection on survival least square support vector machines

Cox Model Survival Analysis to Evaluate Treatment of Electro-Capacitive Cancer Therapy (ECCT) For Cancer Patients

Contact Info

Product

Resources

About