ArticleJournal of research in health sciences2017
Comparison of Weibull and Lognormal Cure Models with Cox in the Survival Analysis Of Breast Cancer Patients in Rafsanjan.
Article in Journal of research in health sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Learning Survival Distributions with the Asymmetric Laplace Distribution.Proceedings of machine learning research · 2025Article
- Exposures to pesticides and risk of cancer: Evaluation of recent epidemiological evidence in humans and paths forward.International journal of cancer · 2023Article
- Determining the Factors Affecting Long-Term and Short-Term Survival of Breast Cancer Patients in Rafsanjan Using a Mixture Cure Model.Journal of research in health sciences · 2021Article
- Short-term and long-term survival of patients with gastric cancer.Gastroenterology and hepatology from bed to bench · 2021Article
- Factors Affecting Long-Survival of Patients with Breast Cancer by Non-Mixture and Mixture Cure Models Using the Weibull, Log-logistic and Dagum Distributions: A Bayesian Approach.Asian Pacific journal of cancer prevention : APJCP · 2020Article
- Comparison of Penalized Cox Regression Methods in Low-Dimensional Data with Few-Events: An Application to Dialysis Patients' Data.Journal of research in health sciences · 2019Article
- Long-Term Disease-Free Survival of Non-Metastatic Breast Cancer Patients in Iran: A Survival Model with Competing Risks Taking Cure Fraction and Frailty into AccountAsian Pacific journal of cancer prevention : APJCP · 2017Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBreast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer. STUDY
designA cohort study.
methodsThe current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14.
resultsAccording to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study.
conclusionsBased on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.
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Identifiers
28413171PMC7191012W2591227038What OpenQuestion holds
Registered trials
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