Related Experiment Video
Updated: Apr 19, 2026
06:14
In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data
Published on: April 18, 2019
7.0K
Racial differences in three major NHL subtypes: descriptive epidemiology
Yang Li1, Yu Wang1, Zhuoyue Wang1
1School of Statistics and The Center for Applied Statistics, Renmin University of China, 59 Zhongguancun Ave. Beijing, 100872, China.
Cancer Epidemiology
|January 7, 2015
Summary
Racial disparities in non-Hodgkin lymphoma (NHL) subtypes like diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) show varied patient characteristics, incidence, and survival rates across different racial groups in the U.S.
Area of Science:
- Hematology
- Oncology
- Epidemiology
- Health Disparities
Background:
- Non-Hodgkin lymphoma (NHL) encompasses over 60 subtypes with varying aggressiveness.
- Key NHL subtypes include diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL).
- NHL presentation, etiology, and prognosis differ across racial groups for each subtype.
Purpose of the Study:
- To analyze racial differences in patient characteristics, incidence rates, and survival for DLBCL, FL, and CLL/SLL.
- To compare these patterns across different racial groups within the U.S. population.
Main Methods:
- Analysis of Surveillance, Epidemiology, and End Results (SEER) data from 1992-2010.
- Inclusion of patients diagnosed with DLBCL, FL, and CLL/SLL.
- Comparison of patient characteristics, incidence, and survival across racial groups (Non-Hispanic Whites, Hispanic Whites, Blacks, Asians/Pacific Islanders) using stratification and multivariate analysis.
Main Results:
- Significant racial variations observed in patient characteristics (gender, age, stage, lymph site) across NHL subtypes.
- Non-Hispanic Whites exhibited the highest incidence rates for all three subtypes.
- Non-Hispanic Whites also showed the highest five-year relative survival rates, followed by Hispanic Whites.
Conclusions:
- Substantiated racial differences in characteristics, incidence, and survival exist for DLBCL, FL, and CLL/SLL patients in the U.S.
- Observed patterns of these differences vary significantly depending on the specific NHL subtype.
- Further data collection and analysis are recommended to fully understand and interpret these across-race and subtype variations.
Related Concept Videos
02:55Stereotypes, Prejudice, and Discrimination
96.0K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
96.0K
01:15One-Way ANOVA: Equal Sample Sizes
4.5K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
4.5K
01:29Bias in Epidemiological Studies
1.7K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.7K
00:55Relative Frequency Distribution
14.5K
A relative frequency distribution is the proportion or fraction of times a value occurs in a data set. To find the relative frequencies, one can divide each frequency by the total number of data points in the sample. It is very similar to a regular frequency distribution, except that instead of reporting how many data values fall in a class, a relative frequency distribution reports the fraction of data values that fall in a class. These fractions or proportions are called relative frequencies...
14.5K
01:15One-Way ANOVA: Unequal Sample Sizes
7.1K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
7.1K
01:25Statistical Methods for Analyzing Epidemiological Data
1.3K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.3K