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Risk Assessment Macros, Software Programs, and Tools

The following risk assessment tools were developed by DCEG investigators. They are freely available for use by other researchers.

Breast Cancer

BCRA R Package

BCRA is an R package that projects absolute risk of invasive breast cancer according to NCI’s Breast Cancer Risk Assessment Tool (BCRAT) algorithm for specified race/ethnic groups and age intervals.

Breast Cancer Risk Assessment SAS Macro (Version 4, Gail Model)

A SAS macro (commonly referred to as the Gail Model) that projects absolute risk of invasive breast cancer according to NCI’s Breast Cancer Risk Assessment Tool (BCRAT) algorithm for specified race/ethnic groups and age intervals. 

Asian Pacific Islander American Women - Breast Cancer Risk Assessment SAS Macro

Software that projects absolute breast cancer risk over defined age intervals for Asian and Pacific Islander American women with specific risk factors.

CARE Model SAS Macro: Breast Cancer Risk Assessment for African American Women

The CARE Model is a SAS macro that allows researchers to estimate an African American woman's risk of developing invasive breast cancer over specified age intervals.

Breast Cancer with Mammographic Density Risk Assessment SAS Macro

A SAS macro that projects absolute invasive breast cancer risk for white women based on measurements of mammographic density and other risk factors.

Breast, Endometrial, and Ovarian Risk Assessment SAS Macros

Software that projects absolute risk for breast, endometrial, and ovarian cancer in Caucasian and African American women.

(Hisp)anic-American (BrCa) (R)isk (A)ssessment (M)acro

Breast Cancer Risk Prediction macro for projecting risk for Hispanic Americans.

Colon Cancer

Colon Cancer Risk Assessment - SAS Macro

A SAS macro that projects absolute risk of colon cancer according to NCI’s Colorectal Cancer Risk Assessment Tool (CCRAT) algorithm.

Colon Cancer Risk Assessment - Gauss Program

An executable file (in GAUSS) that projects absolute colon cancer risk (with confidence intervals) according to NCI’s Colorectal Cancer Risk Assessment Tool (CCRAT) algorithm. GAUSS is not needed to run the program.

Lung Cancer

Lung Cancer Risk Models for Screening (R package: lcrisks)

In both the absence and presence of screening, the R package calculates individual risks of lung cancer and lung cancer death based on covariates: age, education, sex, race, smoking intensity/duration/quit-years, Body Mass Index, family history of lung-cancer, and self-reported emphysema. In the presence of CT screening akin to the NLST (3 yearly screens, 5 years of follow-up), it uses the covariates to estimate risk of false-positive CT screen as well as the reduction in risk of lung cancer death and increase in risk of lung cancer screening. This package also estimates the Life Years Gained From Screening-CT (LYFS-CT) as per Cheung et al., 2019. It requires the same variables as LCDRAT plus 12 additional comorbidities and the year of patient assessment.

lcmodels

The R package provides individual risks of lung cancer and lung cancer death based on various published papers: Bach et al., 2003; Spitz et al., 2007; Cassidy et al., 2008 (LLP); Hoggart et al., 2012; Tammemagi et al., 2013; Marcus et al., 2015 (LLPi); Wilson and Weissfeld, 2015 (Pittsburgh); Katki et al., 2016 (LCRAT, LCDRAT, and versions constrained to a few variables); Katki et al., 2018. This package also estimates the Life Years Gained From Screening-CT (LYFS-CT) as per Cheung et al., 2019. It requires the same variables as LCDRAT plus 12 additional comorbidities and the year of patient assessment.

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