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The comparison of censored quantile regression methods in prognosis factors of breast cancer survival
- Source :
- Scientific Reports, Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- The Cox proportional hazards model is a widely used statistical method for the censored data that model the hazard rate rather than survival time. To overcome complexity of interpreting hazard ratio, quantile regression was introduced for censored data with more straightforward interpretation. Different methods for analyzing censored data using quantile regression model, have been introduced. The quantile regression approach models the quantile function of failure time and investigates the covariate effects in different quantiles. In this model, the covariate effects can be changed for patients with different risk and is a flexible model for controlling the heterogeneity of covariate effects. We illustrated and compared five methods in quantile regression for right censored data included Portnoy, Wang and Wang, Bottai and Zhang, Yang and De Backer methods. The comparison was made through the use of these methods in modeling the survival time of breast cancer. According to the results of quantile regression models, tumor grade and stage of the disease were identified as significant factors affecting 20th percentile of survival time. In Bottai and Zhang method, 20th percentile of survival time for a case with higher unit of stage decreased about 14 months and 20th percentile of survival time for a case with higher grade decreased about 13 months. The quantile regression models acted the same to determine prognostic factors of breast cancer survival in most of the time. The estimated coefficients of five methods were close to each other for quantiles lower than 0.1 and they were different from quantiles upper than 0.1.
- Subjects :
- Percentile
Science
Breast Neoplasms
Kaplan-Meier Estimate
Article
Medical research
Breast cancer
Risk Factors
Statistics
Covariate
medicine
Humans
Neoplasm Staging
Proportional Hazards Models
Cancer
Mathematics
Models, Statistical
Multidisciplinary
Proportional hazards model
Hazard ratio
Age Factors
Middle Aged
Quantile function
Prognosis
medicine.disease
Survival Analysis
Quantile regression
Multivariate Analysis
Medicine
Regression Analysis
Female
Quantile
Subjects
Details
- ISSN :
- 20452322
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....153b53f4d430faefefcee6167d00a4e4