Prognostic Groups in Colorectal Carcinoma Patients Based on Tumor Cell Proliferation and Classification and Regression Tree (CART) Survival Analysis

2006 ◽  
Vol 14 (1) ◽  
pp. 34-40 ◽  
Author(s):  
Vladimir A. Valera ◽  
Beatriz A. Walter ◽  
Naoyuki Yokoyama ◽  
Yu Koyama ◽  
Tsuneo Iiai ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Survival Analysis ◽  
Colorectal Carcinoma ◽  
Tumor Cell ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Tumor Cell Proliferation ◽  
Prognostic Groups ◽  
Classification And Regression

Thresholding of prominent biomarkers of breast cancer on overall survival using classification and regression tree

2021 ◽  
pp. 1-10
Author(s):  
Pragya Kumari ◽  
Gajendra K. Vishwakarma ◽  
Atanu Bhattacharjee
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Survival Analysis ◽  
Regression Tree ◽  
Vital Role ◽  
Classification And Regression Tree ◽  
Brier Score ◽  
Risk Of Death ◽  
Cart Analysis ◽  
Classification And Regression

BACKGROUND: HER2, ER, PR, and ERBB2 play a vital role in treating breast cancer. These are significant predictive and prognosis biomarkers of breast cancer. OBJECTIVE: We aim to obtain a unique biomarker-specific prediction on overall survival to know their survival and death risk. METHODS: Survival analysis is performed on classified data using Classification and Regression Tree (CART) analysis. Hazard ratio and Confidence Interval are computed using MLE and the Bayesian approach with the CPH model for univariate and multivariable illustrations. Validation of CART is executed with the Brier score, and accuracy and sensitivity are obtained using the k-nn classifier. RESULTS: Utilizing CART analysis, the cut-off value of continuous-valued biomarkers HER2, ER, PR, and ERBB2 are obtained as 14.707, 8.128, 13.153, and 6.884, respectively. Brier score of CART is 0.16 towards validation of methodology. Survival analysis gives a demonstration of the survival estimates with significant statistical strategies. CONCLUSIONS: Patients with breast cancer are at low risk of death, whose HER2 value is below its cut-off value, and ER, PR, and ERBB2 values are greater than their cut-off values. This comparison is with the patient having the opposite side of these cut-off values for the same biomarkers.

Low molecular weight hyaluronan inhibits colorectal carcinoma growth by decreasing tumor cell proliferation and stimulating immune response

2009 ◽  
Vol 278 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Laura Alaniz ◽  
Miguel Rizzo ◽  
Mariana Malvicini ◽  
Jorge Jaunarena ◽  
Diego Avella ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Immune Response ◽  
Cell Proliferation ◽  
Colorectal Carcinoma ◽  
Tumor Cell ◽  
Low Molecular Weight ◽  
Tumor Cell Proliferation

Classification and regression tree based survival analysis in oak-dominated forests of Missouri's Ozark highlands

2006 ◽  
Vol 36 (7) ◽  
pp. 1740-1748 ◽  
Author(s):  
Zhaofei Fan ◽  
John M Kabrick ◽  
Stephen R Shifley
Keyword(s):  
Survival Analysis ◽  
Regression Tree ◽  
Species Group ◽  
Classification And Regression Tree ◽  
Tree Age ◽  
Oak Forests ◽  
Shortleaf Pine ◽  
White Oak ◽  
Tree Survival ◽  
Classification And Regression

Tree survival or mortality is a stochastic process and highly variable over time and space. Many factors contribute to this process, including tree age, tree size, competition, drought, insects, and diseases. Traditional parametric approaches to modeling tree survival or mortality are often unable to capture this variation, especially in natural, mixed-species forests. We analyzed tree survival in Missouri Ozark oak forests using a combination of classification and regression tree (CART) and survival analysis of more than 35 000 trees with DBH >11 cm measured four times between 1992 and 2002. We employed a log-rank test with CART to classify trees into seven disjoint survival groups and used a nonparametric Kaplan–Meier (product limit) method to estimate tree survival rate and construct confidence intervals for each survival group. We found that tree species, crown class, DBH, and basal area of larger trees were the variables most closely associated with differences in tree survival rates. In these mature oak forests, mortality for the red oak species group was three to six times greater than for the white oak, hickory, or shortleaf pine species group. The results provide practical information to guide development of silvicultural prescriptions to reduce losses to mortality.

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