title: Report: Study is about the prevalence of the HCV disease and survival of HCV patients with associated factors in the population of district Multan.
abstract: To find out the significant factors associated with HCV disease and evaluate the impact of these factors on the survival pattern of HCV patients in district Multan. The study was conducted in Nishter Hospital of Multan district from 1st January 2011 to 1st October 2012. To see a significant difference between the survival rates of patients with associated factors, non-parametric Cox- proportional hazard model with their graphical results were used. All the patients above 11 years old of both sexes were included in the study. All those who were surviving with HCV disease were studied with their associated factors such as age, family history (FH) barber/parlor services, blood group (BG) types weight loss (WL), Gender and drug use were collected from Nishter Hospital Multan. Results indicated that age, blood group types and gender are the most significant factors in the patients who are surviving with HCV disease. It was also observed that survival rate of female patients is high as compare to male patients.
authors.affiliation: Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
authors.forename: Hina
authors.initials: H
authors.lastname: Tabassum
authors.affiliation: Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
authors.forename: Muhammad
authors.initials: M
authors.lastname: Amin
authors.affiliation: Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
authors.forename: Muhammad
authors.initials: M
authors.lastname: Amanullah
authors.affiliation: Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
authors.forename: Sana
authors.initials: S
authors.lastname: Tabassum
mesh_terms: D005260:Female; D006526:Hepatitis C / Q000453:epidemiology* / Q000401:mortality; D006801:Humans; D008297:Male; D010154:Pakistan / Q000453:epidemiology; D015995:Prevalence; D016016:Proportional Hazards Models