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. 2010 Nov 13:2010:847-51.

Parametric survival models for predicting the benefit of adjuvant chemoradiotherapy in gallbladder cancer

Samuel J Wang  1 , Jayashree Kalpathy-Cramer, Jong Sung Kim, C David Fuller, Charles R Thomas
Affiliations

Parametric survival models for predicting the benefit of adjuvant chemoradiotherapy in gallbladder cancer

Samuel J Wang et al. AMIA Annu Symp Proc. .

Abstract

The Cox proportional hazards model is the most commonly used survival model in oncology; however, this semi-parametric model may not be the most appropriate survival model when the proportionality assumption does not hold. In this study, we consider the use of several types of accelerated failure time parametric survival techniques for modeling the benefit of adjuvant chemoradiotherapy for gallbladder cancer. In comparing the Weibull, exponential, log-logistic, and log-normal models, we found that the log-normal had the most favorable Akaike Information Criterion, and additional analyses of this model indicated that our gallbladder cancer dataset exhibited a good fit with the log-normal cumulative hazard function. This log-normal survival model can be used to help predict which patients will benefit from adjuvant chemoradiotherapy.

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Figures

Figure 1.
Figure 1.
Kaplan-Meier Overall Survival by T stage.
Figure 2.
Figure 2.
Kaplan-Meier Overall Survival by receipt of adjuvant chemoradiotherapy.
Figure 3.
Figure 3.
Plot of the log-normal transformed cumulative hazard function vs log time.
See this image and copyright information in PMC

References

    1. Bartlett DL, Ramanathan RK, Deutsch M, et al. Cancer of the Biliary Tree. In: DeVita VT Jr, editor. Cancer: Principles and Practice of Oncology. Philadelphia: Lippincott-Raven; 2004.
    1. Cox DR. Regression models and life tables (with discussion) J R Stat Soc B. 1972;24:187–200.
    1. Boag JW. Maximum likelihood estimates of the proportion of patients cured by cancer therapy. J R Stat Soc B. 1949;11:15–44.
    1. Rutqvist LE, Wallgren A, Nilsson B. Is breast cancer a curable disease? A study of 14,731 women with breast cancer from the Cancer Registry of Norway. Cancer. 1984;53:1793–800. - PubMed
    1. Gamel JW, Vogel RL, Valagussa P, et al. Parametric survival analysis of adjuvant therapy for stage II breast cancer. Cancer. 1994;74:2483–90. - PubMed

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