Title

Logistic Regression Model: The Effect of Chemotherapy on 10 Year Survival for Women with Colon Cancer

Submitter and Co-author information

Mohamad EA Musa, University of WindsorFollow

Standing

Graduate (PhD)

Type of Proposal

Poster Presentation

Type of Proposal

Visual Presentation (Poster, Installation, Demonstration)

Challenges Theme

Building Viable, Healthy and Safe Communities

Your Location

Windsor

Faculty

Faculty of Arts, Humanities and Social Sciences

Faculty Sponsor

Dr. Jill Grant

Abstract/Description of Original Work

Colon cancer is a widespread form of treatable cancer common among many populations in the United States and Canada. In this particular logistic regression model, the database took place in California, United States and is part of a cancer registry-based colon cancer cohort which included 6300 people who resided in California between the years 1995 and 2000.

This data base was approved to be used for our quantitative data analysis course at the University of Windsor, School of Social Work, to students at the level of doctorate studies. This original logistic regression model will look at the effects of chemotherapy on ten year survival for women with colon cancer. This model will look at women in particular and if they are associated with shorter survival rates. The model also looks at age groups of women along with their stage of colon cancer. The model will finally test an interaction effect between being a black woman and poverty groups and also between the refusals of chemotherapy among black women with colon cancer. This secondary data analysis sample is restricted to 3012 participants which accounts for almost 92% of the women included in this sample. Results showed a strong relationship between chemotherapy treatment and 10 years survival of colon cancer. Women who received chemotherapy are almost ten times as likely to have a high survival rate for 10 years as those who did not receive chemotherapy treatment.

Benefits of early diagnoses, and the importance of chemotherapy care among different groups of poverty can negatively influence the survival time of women. Generalized findings towards bigger populations as the impact can apply to other minority groups in the United States and Canada.

Location

Windsor

Grand Challenges

Viable, Healthy and Safe Communities

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Logistic Regression Model: The Effect of Chemotherapy on 10 Year Survival for Women with Colon Cancer

Windsor

Colon cancer is a widespread form of treatable cancer common among many populations in the United States and Canada. In this particular logistic regression model, the database took place in California, United States and is part of a cancer registry-based colon cancer cohort which included 6300 people who resided in California between the years 1995 and 2000.

This data base was approved to be used for our quantitative data analysis course at the University of Windsor, School of Social Work, to students at the level of doctorate studies. This original logistic regression model will look at the effects of chemotherapy on ten year survival for women with colon cancer. This model will look at women in particular and if they are associated with shorter survival rates. The model also looks at age groups of women along with their stage of colon cancer. The model will finally test an interaction effect between being a black woman and poverty groups and also between the refusals of chemotherapy among black women with colon cancer. This secondary data analysis sample is restricted to 3012 participants which accounts for almost 92% of the women included in this sample. Results showed a strong relationship between chemotherapy treatment and 10 years survival of colon cancer. Women who received chemotherapy are almost ten times as likely to have a high survival rate for 10 years as those who did not receive chemotherapy treatment.

Benefits of early diagnoses, and the importance of chemotherapy care among different groups of poverty can negatively influence the survival time of women. Generalized findings towards bigger populations as the impact can apply to other minority groups in the United States and Canada.