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Ansari, Daniel, et al. "Early-onset pancreatic cancer: a population-based study using the SEER registry." Langenbeck’s Archives of Surgery 404.5 (2019): 565-571.

has been cited by the following article:

Article

A Modern Analytical Approach for Assessing the Treatment Effectiveness of Pancreatic Adenocarcinoma Patients Belonging to Different Demographics and Cancer Stages

1Assistant Professor Eastern Virginia Medical School

2Distinguished University Professor University of South Florida


Journal of Cancer Research and Treatment. 2023, Vol. 11 No. 1, 13-18
DOI: 10.12691/jcrt-11-1-3
Copyright © 2023 Science and Education Publishing

Cite this paper:
Aditya Chakraborty, Chris P. Tsokos. A Modern Analytical Approach for Assessing the Treatment Effectiveness of Pancreatic Adenocarcinoma Patients Belonging to Different Demographics and Cancer Stages. Journal of Cancer Research and Treatment. 2023; 11(1):13-18. doi: 10.12691/jcrt-11-1-3.

Correspondence to: Aditya  Chakraborty, Assistant Professor Eastern Virginia Medical School. Email: chakraa@evms.edu

Abstract

Purpose: The purpose of the study is to detect the treatment effectiveness for different patient groups (belonging to different demographics and cancer stages, taking different treatments) at early stages. Method: In this study, we introduced an analytical method to monitor the behavior of survival times of pancreatic adenocarcinoma patients by introducing two new concepts: Survival Index (SI), and Stochastic Growth Intensity Function (SGIF), ζ(t). A total of 108 patient groups receiving three different treatments; only chemotherapy (C), only radiation (R), and a combination of chemotherapy and radiation (C + R) were constructed using the SEER Cancer Database. Results: Our analytical method is helpful to predict the survival pattern based on the (SI) as a function of time t; which necessarily provides information if the specific treatment has been useful for the particular patient group. That is if (SI) > 1 implies the treatment has an adverse effect on the patient’s survival. (SI) ≈ 1 implies the survival rate is approximately constant by the implementation of the treatment, and (SI) < 1 implies the treatment has been effective on the patient’s survival. Conclusion: The adaptability of our technique stems from the fact that our algorithm may be used for any number of patient groups of any age, of any race, at any specific cancer stage, and receiving any unique treatment or combination.

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