Cancer Risk Prediction Models:
A Workshop on Development, Evaluation, and Application

Introduction and Perspectives: Cancer Control and Population Sciences
Robert Croyle
Director, Division of Cancer Control and Population Sciences, National Cancer Institute

Introduction and Perspectives: Cancer Epidemiology and Genetics
Robert Hoover
Director, Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute

Workshop Overview and Objectives
Andrew Freedman

Session I: Applications of Cancer Risk Prediction Models
Moderator: Andrew Freedman

Clinical Use of Risk Prediction Models
Laura Esserman

Estimating Population Burden of Disease
Karen Kuntz

Application of Cancer Risk Prediction Models: Intervention Trials
Joe Costantino

Session II: Cancer Risk and Susceptibility Gene Prediction Models in Use and Development
Oral Presentation followed by Poster Session

A Breast Cancer Prediction Model Incorporating Familial and Personal Risk Factors
Jack Cuzick

Poster Session
Rooms: Thomas Room and Salon C

Session III: Goals and Issues in the Development of Cancer Risk Prediction Models for Various Purposes
Moderator: Graham Colditz
Panelists: Mitchell Gail, Bernard Rosner, Beverly Rockhill, Colin Begg

Topics to be discussed:
Developing Risk Models

• to incorporate clinical, epidemiologic, and/or biological/genetic markers (e.g., melanoma vs. Gail Model)
• for rare vs. common cancers (e.g., ovary vs. breast)
• using different design methodologies and data sources (e.g., cohorts vs. case-control vs. expert opinion)
• using specialized vs. generalized populations
• for clinical decision making
• for individual vs. population-wide prevention strategies

Working Lunch
Lessons Learned From Cardiovascular Risk Models: Experience from the Framingham Study
Lisa Sullivan

Session IV: Risk Assessment Models for Predicting Cancer Susceptibility Genes and Cancer Risk
Moderator: Daniela Seminara

The BOADICEA model of genetic susceptibility to breast and ovarian cancer: updating, validation and predictions
Antonis Antoniou

Modifiers of Cancer Risk in BRCA1/2 Mutation Carriers: Study Design and Analysis Issues
Tim Rebbeck

Susceptibility Prediction in Familial Colon Cancer
Giovanni Parmigiani

Risk Assessment for HNPCC
Chris Amos

Genetic Susceptibility Risk Models in Clinical Decision Making
Susan Domchek

Session V: Preliminary Discussion of Key Objectives and Research Gaps
Moderator: Patricia Hartge

Identify research issues, gaps, priorities, and resources needed to advance the field of cancer risk prediction. Make specific recommendations for implementation.

Breakout Discussion Sessions:

• Session 1: Salons A&B
  Risk prediction models for clinical decision making, intervention studies, and population-based prevention strategies (focus on breast)
  Breakout leaders: Joe Costantino, Jack Cuzick, Laura Esserman, and Victor Vogel
• Session 2: Room 3017
  Risk prediction models for clinical decision making, intervention studies, and population-based prevention strategies (focus on lung, colorectal, melanoma, and cancers other than breast)
  Breakout leaders: Peter Bach, Graham Colditz, Ernie Hawk, and Tom Imperiale
• Session 3: Logan Room
  Risk prediction models for genetic susceptibility
  Breakout leaders: David Euhus, Judy Garber, and Tim Rebbeck
• Session 4: Room 3016
  Risk prediction model evaluation and validation
  Breakout leaders: Michael Kattan, Dan McGee, Martin Schumacher, and Ewout Steyerberg

Session VI: Validation and Evaluation Methodology
Moderator: Susan Hilsenbeck

General Talk on Criteria for Model Assessment
Ruth Pfeiffer

Variability Explained: Calibration, Goodness of Fit, and Unbiased Estimation
Dan McGee

Comparing the Accuracy of Prediction Models
Michael Kattan

Assessment of Prediction Error of Risk Prediction Models
Martin Schumacher

Presentation on Current Population Resources for the Development and Validation of Cancer Risk and Susceptibility Prediction Models
Daniela Seminara

Session VII: Discussion, Summary and Future Research Directions and Wrap-Up
Moderator: Rachel Ballard-Barbash

• Report from Breakout Session 1: Risk prediction models for clinical decision making, intervention studies, and population-based prevention strategies (focus on breast)
• Report from Breakout Session 2: Risk prediction models for clinical decision making, intervention studies, and population-based prevention strategies (focus on lung, colorectal, melanoma, and cancers other than breast)
• Report from Breakout Session 3: Risk prediction models for genetic susceptibility
• Report from Breakout Session 4: Risk prediction model evaluation and validation