International Journal of Statistics and Reliability Engineering

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Vol 9, No 2:

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Modelling Of Lymph Node Count In Endometrial Cancer Patients Using Zero Inflated Generalized Poisson Model

Abstract

Prediction of the number of involved lymph nodes in an endometrial cancer patient is crucial for medical practitioners to identify the progression of the disease. Sometimes the distribution of involved nodes shows over dispersion. This over dispersion may be due to unobserved heterogeneity viz. larger proportion of zero nodal counts. For this study, data concerning a total of 170 patients were taken from a local cancer hospital. We have fitted several count regression models and compared them to identify the model with the best performance for predicting the number of involved lymph nodes. Based on the lowest AIC and BIC values, the Zero Inflated Generalized Poisson model is found to be the best-fitted model for explaining nodal involvement in endometrial cancer patients. The predictors viz., obstetric history, higher grade, and tumor size are significantly associated with a greater number of involved lymph nodes (P-value <0.05). In conclusion, an obstetric history significantly increased the chance of negative nodes while the tumor size and grade status significantly increased the chance of positive nodes among EC patients

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ISSN(P) 2350-0174

ISSN(O) 2456-2378

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