Overall Survival Prediction for Colon Cancer Patients of 0–IV Stages With and Without Surgical Operation Through a Revised Taylor Series Expansion Algorithm: A Population-Based Study in Taiwan

Abstract

This study was aimed to predict the overall survival of colon cancer patients at various (0–IV) stages and provided a robust assessment of the expediency of a surgical operation for such patients. The proposed prediction algorithm was based on the well-known hit and target model adopted for analyzing the cell death from the microscopic viewpoint and implied the application of the Taylor series expansion to the population-based survey dataset (in particular, to the population-based study of colon cancer patients in Taiwan covering the period from 2007 to 2016). In the proposed algorithm, the fundamental degradation of patient's health was represented by a specific function comprising a single exponential term exp(–αt), which was multiplied by an additional term P(αt) that specified the recovery effect of a particular therapy. The revised algorithm successfully predicted the colon cancer patients' overall survival at stages 0–IV and evaluated the expediency necessity of surgical operation for patients at various stages as well. For the above population-based survey dataset, the calculated lethal frequency and average residual life of colon cancer patients who undergone surgical operation amounted to {0.029, 0.036, 0.058, 0.077, 0.236} yr–1 and {34.5, 27.8, 17.2, 13.0, 4.2} yr for stages 0–IV, respectively, while those for the respective groups of patients with no surgical operation was assessed as {0.116, 0.181, 0.256, 0.203, 0.504} yr–1 and {8.6, 5.5, 3.9, 4.9, 2.0} yr, respectively. The proposed algorithm was also applied to interpret the overall survival of lung cancer patients at stages III and IV and exhibited a partial agreement with the actual collected data.