Analysis of Cancer Incidence Using Count Regression Models

• Author(s): Manu Ibrahim Babaja ; Umar Farouk Abbas ; Kaseem E. Lasisi
• Paper ID: 1704587
• Page: 61-70
• Published Date: 03-06-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 12 June-2023

Abstract

Cancer has become a major cause of morbidity and mortality in Adamawa, Nigeria and the world at large. Despite the threat cancer poses to the world, less attentions is giving to the menace compared to the other public health issues such as corona Virus that the world stood up and fought it. Research was conducted on 1,168 registered cancer patients in Adamawa state, Nigeria. Systematic random sampling was used to extract demographic information such as age, sex, marital status, level of education, occupation, date of first diagnoses. Data were analyzed using percentages, mean and modified negative binomial regression Model that was used which was later compared to the based model Poisson and the classical negative binomial model. It was discovered that the modified negative binomial regression model significantly outperformed both the based and classical model. It was further discovered that 92% of the confirmed cases survived the treatment with only 8% of the mortality recorded from the confirmed cases. 35% mortality were recorded from the 112 (65%) of the pending cases that were yet to be confirmed. This mortality which seems to be high in patients with pending cases were due to the lost in follow up from the patients. Surgery was discovered to be the best method for the treatment of cancer followed by the combinations of treatments. Lastly, it was discovered that Age influence the expected log count of the topography of cancer outcome of treatment by -0.1173, Sex influence the expected log count of the topographer of cancer treatment outcome by -0.2598, Educational status influence expected log count of the outcome of the treatment by 0.0369, Treatment type influence the expected log count of the topography of the outcome of the treatment of cancer by -0.0416. In conclusion, the risk factors to successful treatment of cancer in Adamawa includes the in ability to dictate cancer on time, lack of follow up with the treatment from the patients, treatment type and age of the patients as well the sex.

Citations

IRE Journals:
Manu Ibrahim Babaja , Umar Farouk Abbas , Kaseem E. Lasisi "Analysis of Cancer Incidence Using Count Regression Models" Iconic Research And Engineering Journals Volume 6 Issue 12 2023 Page 61-70

IEEE:
Manu Ibrahim Babaja , Umar Farouk Abbas , Kaseem E. Lasisi "Analysis of Cancer Incidence Using Count Regression Models" Iconic Research And Engineering Journals, 6(12)