English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Objective: In this study, we aimed to compare the results of the survival analysis of the patients with breast cancer using Weibull, Gamma, Gompertz, Log-Logistic and Log-Normal parametric models. Material and Methods: The data obtained from 5457 patients with breast cancer from Ege University Cancer Research Centre between 1992 and 2007 was used in this study. The patients were divided into two groups with respect to their ages, they were divided into two groups as 49 and below and 50 and above. The Log rank test was applied to compare the survival curves of the two age groups obtained by Kaplan Meier method. A survival analysis was conducted by using Weibull, Gamma, Gompertz, Loglogistic and Lognormal distribution of parametric models. Results: Survival curves of two groups were compared by using a log-rank test and no statistical significant difference was found between the two groups. In the analysis of the survival periods using parametric models, the age variable is taken as the covariate. To determine the best model among parametric models, Akaike Information Criteria (AIC) was exploited. The results of the study revealed that the survival model found by the Gompertz distribution was the most appropriate one. Conclusion: By using AIC, the models obtained via Weibull, Loglogistic, Lognormal, Gamma and Gompertz were compared and the most suitable model for the obtained data distribution was determined. Although the AIC values for the five distributions in question were very close to each other, the Gompertz distribution, which had the lowest AIC value, was determined as the most suitable model.Ama?: Bu ?al??mada meme kanserli hastalara ait sa?kal?m analizlerinin sonu?lar?n? Weibull, Gamma, Gompertz, Log-Logistic ve Log-Normal parametrik modelleri kullanarak kar??la?t?rmay? ama?lad?k. Gere? ve Y?ntemler: ?al??mada Ege ?niversitesi Kanser Ara?t?rma Merkezi nde kay?tl? 1992 ile 2007 y?llar? aras?ndaki 5457 meme kanserli hastadan elde edilen veriler kullan?lm??t?r. Hastalar 50 ya? ve ?st?ndekiler ile 50 ya? alt?ndakiler olmak ?zere iki gruba ayr?ld?lar. Kaplan Meier metodu ile elde edilen iki gruba ait sa?kal?m e?rileri kar??la?t?r?l?rken Log rank testi uygulanm??t?r. Meme kanserli hasta verileri ile birlikte Weibull, Gamma, Gompertz, Loglogistic and Lognormal  parametrik modelleri kullan?larak bir sa?kal?m analizi yap?lm??t?r. Bulgular: ?ki grubun sa?kal?m e?rileri long-rank testi kullan?larak kar??la?t?r?lm??, istatistiksel olarak anlaml? fark bulunmam??t?r. Parametrik testler kullan?larak yap?lan sa?kal?m s?relerinin analizinde, ya? ortak de?i?ken olarak ele al?nm??t?r. Parametrik modeller i?erisinde en iyi olan? belirlemek ?zere Akaike Bilgi Kriteri (ABK)nden faydalan?lm??t?r. ?al??ma sonu?lar? Gompertz da??l?m? ile bulunan sa?kal?m modelinin en uygunu oldu?unu ortaya koymu?tur. Sonu?: ABK kullan?larak Weibull, Loglogistic, Lognormal, Gamma ve Gompertz ile elde edilen modeller kar??la?t?r?lm?? ve elde edilen veri da??l?m? i?in en uygun model ele al?nm??t?r. S?z konusu be? da??l?m hakk?ndaki ABK de?erleri birbirine ?ok yak?n bulunmu? ve ABK de?eri en d???k olan Gompertz da??l?m?, en uygun model olarak de?erlendirilmi?tir

Comparison of Five Survival Models: Breast Cancer Registry Data from Ege University Cancer Research Center