Risk Module

Progeny Clinical includes validated risk assessment models to calculate 5-year and lifetime cancer risk, as well as gene mutation probabilities for any member of a pedigree.  Any missing or invalid data required to run these models are automatically identified for you. Risk calculation results can be easily saved and timestamped within the database or saved as a pdf file at any time.

Current Risk Models

The following models are currently available in the latest release of Progeny:


A breast cancer risk assessment tool incorporating family history, endogenous hormonal factors, benign disease, risk factors such as age and body mass index, and genetic factors (including BRCA) into a single statistical model.(Cancer Research Technology, 2016)

  • Developed in 2005.
  • Proportional hazard model; the relative risk based on personal factors is used to adjust the calculated genetic absolute risk.
  • Incorporates features of Gail and Claus models, as well as height/BMI, use of HRT, cousins with breast cancer, and unaffected females. Only includes biopsies with atypia, hyperplasia or LCIS.
  • Also provides an estimate of BRCA1/2 mutation probability

A statistical model, with associated software, for assessing the probability that an individual carries a germline deleterious mutation of the BRCA1 and BRCA2 genes, based on family history of breast and ovarian cancer. (Giovanni Parmigiani, 2016)

  • Bayesian model based on an age-specific breast or ovarian cancer probabilities.
  • Bayesian = specify a prior probability and update in light of new relevant data.
  • Takes into account both affected and unaffected individuals up to second-degree relatives, breast and ovarian cancer history, male brcx, bilateral brcx, breast pathology, and oophorectomy status as well as ethnicity.
  • Does not take into account many non-hereditary risk factors or noninvasive brcx.
  • Does not incorporate non-BRCA risk elements, so will underestimate risk in breast-cancer only families

A statistical model with associated software for assessing the probability that an individual carries a germline deleterious mutation of the MLH1, MSH2, and genes based on family history of colorectal and endometrial cancer. (Giovanni Parmigiani, 2016)


A statistical model, with associated software, for assessing
the probability that an individual carries a germline deleterious mutation of the putative susceptibility gene(s) and the risk of developing pancreatic cancer in future, based on family history of pancreatic cancer. (Giovanni Parmigiani, 2016)


A statistical model, with associated software, for assessing the probability than an individual carries a germline deleterious mutation of CDKN2A (p16), based on family history of single primary and multiple primary melanomas.(Giovanni Parmigiani, 2016)

PREMM 1,2,6

A clinical prediction algorithm designed to estimate the cumulative and individual probabilities that an individual is an MLH1, MSH2, or MSH6 mutation carrier.”(Lynch Syndrome (Hereditary Nonpolyposis Colorectal Cancer), 2016)

  • Designed specifically to help determine risk for MLH1, MSH2, and MSH6.
  • Takes into account First and Second-degree relatives, ages of diagnosis for either colon or endometrial, and takes into account other Lynch-associated cancers (ovary, stomach, small intestine, urinary tract, renal, brain, pancreas and sebaceous gland tumors).

A computerized tool that estimates a woman’s 5 year and lifetime risk of developing breast cancer; also called the National Cancer Institute (NCI) Breast Cancer Risk Assessment Tool. (NIH…Turning Discovery Into Health, 2016)

  • Developed by Mitchell Gail in 1989.
  • A logistic regression model based on data from Breast Cancer Detection & Demonstration project (2,852 cases and 3,146 controls).
  • Modified in 1999 (sometimes called NCI-Gail): incidence rates are for invasive cancers only; age-specific incidence rates from SEER data; included data for African Americans.
  • Incorporates mostly nongenetic risk factors; age, race, ages at menarche and first live birth, first degree relatives with breast cancer and previous breast biopsy.
  • Only valid for women 35yo and older.
  • Takes into account atypical hyperplasia but not LCIS.

A risk model for familial risk of breast cancer in a large population-based, case-control study conducted by the Centers for Disease Control.”(Evans, 2016)

  • Provides age-specific risk estimates of breast cancer in women with a family history.
  • Based on data from the Cancer and Steroid Hormone Study (4,730 cases and 4,688 controls).
  • Incorporates maternal and/or paternal 1st and 2nd degree relatives and adjusts risk based on age at diagnosis.

Bayes Mendel includes these 4 risk models: BRCAPRO, MMRPRO, PancPRO, and MelaPRO.

Risk server IP addresses and domain names

The Progeny software requires that the domain/IP address progenygenetics.com/ be white-listed in the firewall in order for the Risk Module to be utilized in Progeny. For a more granular configuration, the domains/IP addresses listed below can be white-listed per individual risk model.


Risk Model Domain IP Address
Tyrer-Cuzick http://tyrer-cuzick.riskcalculation.progenygenetics.com/ProgenyRiskService
Bayes Mendel http://bayes.riskcalculation.progenygenetics.com:8080/RiskServiceWeb
Premm http://premm.riskcalculation.progenygenetics.com:8080/RiskServiceWeb
Gail http://gail.riskcalculation.progenygenetics.com:8080/RiskServiceWeb
Claus http://claus.riskcalculation.progenygenetics.com:8080/RiskServiceWeb
Risk Warehouse http://datawarehouse.progenygenetics.com:8080/ProgenyWarehouse


Is this secure?

Absolutely, the handshake between your web client and the risk server does not pass any PHI data from your database. All data used for calculating risk are de-identified. This data includes all the necessary fields that are required for the risk mapping such as different cancers, the age when diagnosed, genes tested such as BRCA1, BRCA2, CK14, CK 5.6, MLH1, MSH2, and others.

Risk Assessment

Progeny Clinical includes validated risk assessment models to calculate 5-year and lifetime cancer risk, as well as gene mutation probabilities for any member of the pedigree. Located on the web, users now have the ability to run the Bayes Mendel, Tyrer-Cuzick, Gail, Claus, and Premm Risk Assessment Models.

View Video: Run Risk Models

To run the Risk Models, start by clicking the Show Risk button on the Pedigree Toolbar to open the risk models pane:



  • The Cogwheel is used to choose which risk models the user would like to run, set the risk threshold, and display data inputs.
  • Calculate – calculates the chosen risk model(s).
  • Save Report/Delete Report – Save/Delete the risk report which can be downloaded and/or printed as a PDF. If saved, gives a date and time stamp of when the report was saved.
  • Risk Models – The available risk models include BRCAPro, MMRPro, PancPro, MelaPro, Tyrer-Cuzick, Premm, Gail, and Claus.
  • Use Competing Mortality for Tyrer-Cuzick – For Tyrer-Cuzick only. Takes into consideration external factors into this Risk model, e.g. injuries, sicknesses, accidents, and other non-cancer risks.
    View Video: Set Competing Mortality for Tyrer-Cuzick
  • Risk Threshold – specifies what risk calculation percent will be highlighted in red once that threshold is reached.
  • Reporting – Display data inputs – After the Risk Models are run, displays the data inputs that were taken into account when running the specified models in the PDF viewer.
  • Do not show this dialog again – specifies that the only way to reach the risk settings is by clicking the cog wheel.
Risk assessment results


Validation Errors – shows if you have missing data or if the criteria for the model to run were not met. Displayed in red on the Cancer Risk and/or Mutation Probabilities (Ex: missing age at breast cancer).

Cancer Risk – 5 years and Lifetime Risk.

Mutation Probabilities – All mutation probabilities are displayed here.


Blackford, A. (2016, December). BayesMendel v2.1: An R package for cancer risk prediction. Retrieved from Biostatistics & Computational Biology AT THE DANA-FARBER CANCER INSTITUTE: http://bcb.dfci.harvard.edu/bayesmendel/BayesMendel.pdf

Cancer Research Technology. (2016, December). IBIS SOFTWARE (TYRER-CUZICK MODEL). Retrieved from Cancer Research Technology: http://www.cancertechnology.co.uk/ibis-software-tyrer-cuzick-model

Cuzick, J. (2016, December). IBIS Breast Cancer Risk Evaluation Tool. Retrieved from IBIS Breast Cancer Risk Evaluation Tool: http://www.ems-trials.org/riskevaluator

Evans, D. G. (2016, December). Breast cancer risk-assessment models. Retrieved from Breast Cancer Research: http://breast-cancer-research.biomedcentral.com/articles/10.1186/bcr1750

Giovanni Parmigiani, W. W. (2016, December). Why BayesMendel. Retrieved from Bio: http://bcb.dfci.harvard.edu/BayesMendel

Lynch Syndrome (Hereditary Nonpolyposis Colorectal Cancer). (2016, December). Retrieved from Dana Farber Cancer Institute: http://premm.dfci.harvard.edu

NIH…Turning Discovery Into Health. (2016, December). Breast Cancer Risk Assessment Tool. Retrieved from National Cancer Institute: https://www.cancer.gov/bcrisktool/about-tool.aspx#references

Updated on April 11, 2018

Was this article helpful?