On the Modeling of Causative and Dependence Relationship of Cancers based on Gender and Cumulative Incidence

Abstract

Objectives: The goal of our study was to model the causative relationship and dependence of morbidity, mortality, and cumulative incidence with respect to GLOBOCAN 2020 age standardized world estimates for female and male malignancies using two adjustable parameters having physical significance.
 Methods: The GLOBOCAN age standardized world estimates for patients for the year 2020 were used in this investigation. For the purposes of analyzing descriptive and analytical data, Kaleidagraph and Origin Software were employed. Bivariate empirical cross- correlation and dependency analyses were used to model how the variables were related to one another. The ratio of new cases to fatalities was calculated using equations comparing the stages of various malignancies.
 Results: In this work, the use of a two-state parameter resulted in the estimation of the optimal solution. The results demonstrated a non-linear correlation with a progressive increase when the cumulative risk of cancer death for each sex was examined separately versus the global cumulative risk of cancer mortality for both sexes. Males experienced the increase more dramatically than females. This finding suggests that the global male-to-female population ratio is not the only factor contributing to cumulative risk.
 Conclusion: South-Eastern Asia, out of all the regions of the world examined in this study, reached its inflection point at (16.23, 14.87). This generates the baseline and standard against which the overall risk of other countries can be measured. The global cumulative risk, which was estimated at 21.50 for females and 17.94 for males, respectively, dropped at this inflection point.