Related Experiment Video
Updated: Jul 23, 2025
06:46
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
306
Evaluating Disparities in Colon Cancer Survival in American Indian/Alaskan Native Patients Using the National Cancer
Harika Nalluri1, Schelomo Marmor1, Saranya Prathibha1
1Department of Surgery, University of Minnesota, Minneapolis, MN, USA.
Journal of Racial and Ethnic Health Disparities
|July 11, 2023
Summary
American Indian/Alaskan Native (AI/AN) patients face higher colon cancer mortality than non-Hispanic White (nHW) individuals. Factors like younger age, more comorbidities, and treatment delays contribute to these survival disparities.
Area of Science:
- Oncology
- Health Disparities Research
- Epidemiology
Background:
- Colon cancer exhibits higher mortality rates in American Indian/Alaskan Native (AI/AN) populations compared to non-Hispanic White (nHW) individuals.
- Understanding the factors contributing to these survival disparities is crucial for targeted interventions.
Purpose of the Study:
- To identify patient, tumor, and treatment-related factors associated with survival disparities in AI/AN versus nHW colon cancer patients.
- To analyze survival outcomes across different stages of colon cancer in these demographic groups.
Main Methods:
- Utilized the National Cancer Database (2004-2016) to identify AI/AN (n=2127) and nHW (n=527,045) patients with stage I-IV colon cancer.
- Employed Kaplan-Meier analysis for overall survival estimation and Cox proportional hazard ratios to determine independent predictors of survival.
Main Results:
- AI/AN patients with stage I-III colon cancer had significantly shorter median survival (73 months) than nHW patients (77 months; p<0.001).
- AI/AN race was an independent predictor of higher overall mortality (HR 1.19, 95% CI 1.01-1.33; p=0.002).
- AI/AN patients presented with younger age, more comorbidities, greater rurality, higher stage tumors, and received chemotherapy with delays or less frequently for stage III disease compared to nHW patients.
Conclusions:
- Identified patient, tumor, and treatment factors potentially explaining worse survival rates in AI/AN colon cancer patients.
- Acknowledged limitations including AI/AN population heterogeneity and the use of overall survival as an endpoint.
- Emphasized the need for further research to develop strategies for eliminating colon cancer survival disparities.
More Related Videos
Related Concept Videos
01:21Cancer Survival Analysis
394
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
394
01:20Comparing the Survival Analysis of Two or More Groups
226
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
226
01:24Kaplan-Meier Approach
188
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
188
01:05Cancer-Critical Genes II: Tumor Suppressor Genes
7.5K
Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
7.5K