Refined Taylor Series Expansion-Based Prediction of the Overall Survival for Nonsmall Cell Lung Cancer Patients of Clinical Stage Iiia-N2 After Various Treatments: Taiwan Population-Based Study of 2655 Cases From 2010 to 2017

Abstract

The overall survival (OS) prediction for nonsmall cell lung carcinoma (NSCLC) patients of clinical IIIA-N2 stage undergone various treatments was investigated through a refined Taylor series expansion algorithm. The model was created according to a population-based study in Taiwan. The proposed prediction algorithm is based on the well-known hit and target model adopted for analyzing the cell death from the microscopic viewpoint. It also implies the application of the Taylor series expansion to the population-based survey dataset. In the proposed algorithm, the basic degradation of a patient’s health is represented via a specific function comprising a single exponential term exp([Formula: see text]). The refined algorithm successfully predicted NSCLC IIIA-N2 patients’ OS rate. A total of 127,301 patients were collected from 2010 to 2017. Then, 2655 patients were recognized as effective events and classified into eight classes according to various medical treatments, namely surgical operation, radiotherapy, and chemotherapy. For each class of patients, the average life was evaluated, according to Taylor’s expansion algorithm, and the average derived life range spread from 3.51 to 7.81 years. An index of life gain with specific treatment was defined according to the Taguchi optimization analysis. The life gains provided by the surgical operation, chemotherapy, and radiotherapy were 2.74, 1.18, and 0.48 years. The surgical operation was the most beneficial treatment, which is in concert with recommendations of European experts. A similar finding was also reflected in four out of eight classes, which included the surgical operation in the treatment plans of most Taiwanese hospitals.