Support

Support Options

Submit a Support Ticket

Category Series
Abstract

Population balance models capture the behavior of a heterogeneous population by describing variation among individuals. These models represent the continuum between purely empirical models and mechanistic model where details are often lumped into measurable parameters without explicitly accounting for detailed mechanisms. In the models of colorectal cancer (CRC), a patients CRC risk varies based on his age, demographics, and clinical history. The tools available on the cceHUB, which were built in the cceHUB shared development environment - allow a user to run the population balance models and explore the dynamics of CRC development for a target population or individual patient.

A presentation describing this research was given at the HSRD Work-in-Progress seminar series at the Veterans Administration Hospital on August 30, 2010 by Eric Sherer and Michael Catlin. See The effects of inadequate preparation quality for colonoscopy.

Three population-based tools have been developed for cceHUB:



Predicting the Incidence of Colorectal Cancer

image The colorectal cancer incidence prediction model is a stochastic simulation of CRC incidence with age. This model describes the accumulation of somatic mutations within a single cell for genes commonly altered in colorectal adenomas and carcinomas. The model predictions are compared to the Indiana population and scenarios based on race and gender parameters/data are available.

Browse the collection of tool runs for the parameters such as male/female and black/white for the population of the state of Indiana. NOTE: Click on the Browse link, scroll down, then click on the tool Colorectal Cancer Incidence Prediction Model

.
image



Monte Carlo Simulations of Colorectal Cancer Development

image The tool Monte Carlo simulation of colorectal cancer development performs Monte Carlo simulations on four CRC incidence models that describe the likelihood that an individual will develop CRC at a certain age.

  • The sequential mutation model of Nordling (1953) demonstrates that a series of roughly six somatic mutations captures the observed linear log (CRC incidence) versus log(age) relationship.
  • The model of Luebeck and Moogavkar (2002) includes the abnormal proliferation of an adenoma (which develops after a series of somatic mutations) as an intermediate step to carcinoma.
  • The MISCAN-COLON model of Loeve et al. (1999) describes the natural history of the adenoma-carcinoma sequence. Small adenomas develop at an age-dependent rate and then make discrete transitions to larger sized adenomas or to and among CRC stages.

Since each Monte Carlo trial is a random re-creation of an individual patient lifetime, the behavior of a population can be approximated by observing the results of multiple Monte Carlo trials.

Browse the collection of tool runs for predictions of patients with colorectal cancer or advanced adenoma at each CRC screen. NOTE: Click on the Browse link, scroll down, then click on the tool Monte Carlo Simulations of Colorectal Cancer Development

.
image



Patient-Specific Colonic Neoplasia Incidence

image

The tool patient-specific colonic neoplasia incidence predicts the likelihood of CRC and other colonic neoplasia for an individual patient based on his demographic risk factors and endoscopic history. Risk factors for CRC differ between patients and can include characteristics such as gender, age, and family history of CRC. In addition, clinical risk factors such as finding multiple or advanced adenomas at a baseline colonoscopy have shown even stronger ties to CRC risk than the demographic characteristics.

Browse the collection of tool runs for predicting the likelihood of CRC and other colonic neoplasia based on risk factors and health history. NOTE: Click on the Browse link, scroll down, then click on the tool Patient-Specific Colonic Neoplasia Incidence

.
image



Contributor Ann Christine Catlin
  • super-administrator
credits Eric Sherer, e-Enterprise Center, Purdue University; Veteran's Administration CoE on Implementing Evidence-based Practice; Indiana University Center for Health Services and Outcomes Research; Regenstrief Institute, Inc.
references CO Nordling, A new theory on cancer-inducing mechanism. British Journal of Cancer, 7: 68-72, 1953.

EG Luebeck and SH Moolgavkar, Multistage carcinogenesis and the incidence of colorectal cancer. PNAS, 99: 15095-15100, 2002.

F Loeve, R Boer, GJ vn Oortmarssen, M van Ballegooijen, and JDF Habbema, The MISCAN-COLON simulation model for the evaluation of colorectal cancer screening. Computers and Biomedical Research, 32: 13-33, 1999.

Cite this work

Researchers should cite this work as follows:

  • Eric Sherer (2010), "Population-Based Models," http://ccehub.org/resources/289.

    BibTex | EndNote

Tags
  1. colorectal cancer
  2. population-based models

In This Series

  1. The effects of inadequate preparation quality for colonoscopy

    02 Oct 2010 | Teaching Materials | Contributor(s): Eric Sherer, Michael Catlin

    We describe research carried out during June-August 2010 for the Veterans Administration Health Services Research and Development Center (HSRD) in Indianapolis. This work was presented to the HSRD Work-in-Progress seminar series at the Veteran's Administration Hospital on August 30, 2010.

  2. Patient-specific colorectal cancer prediction model

    17 Mar 2010 | Tools | Contributor(s): Eric Sherer

    This model predicts the likely findings of colonoscopy exams based on a patient's demographic characteristics and endoscopic history.

  3. An Adaptive-Predictive Model for Colonic Neoplasia Incidence

    15 Mar 2009 | Downloads | Contributor(s): Eric Sherer

    Discovery Brown Bag Seminar Series sponsored by Regenstrief Center for Healthcare Engineering. RCHE presents Dr. Eric Sherer, Medical Informatics Fellow Candidate, VA CIEBP. Dr. Sherer has contributed several population-based models to cceHUB, and interested users can explore the colorectal …

  4. Monte Carlo Simulation for four CRC Incidence Models

    12 Dec 2008 | Tools | Contributor(s): Eric Sherer

    A Monte Carlo Simulator determines the risk of colorectal cancer (CRC) development in a population by calculating multiple, individual patient trajectories.

  5. Introduction to Population Balance Modeling

    02 Oct 2008 | Teaching Materials | Contributor(s): Eric Sherer

    This presentation gives an overview of the role and applications of population balance (or structured) models in describing biological phenomenon. These models represent the continuum between purely empirical models and mechanistic models where details are often lumped into the structured …

  6. Predicting Patient-specific CRC Incidence from Polyp Prevalence

    17 Jun 2008 | Teaching Materials | Contributor(s): Eric Sherer

    Seminal work on CRC incidence modeling argued that the slope of the linear log-log CRC incidence with age implies that 6 or 7 somatic mutations are required for transformation to CRC. Subsequent modeling efforts have built on this theme by using models of linear, sequential transformations for …

  7. Colorectal Cancer Incidence Prediction Model

    16 Jun 2008 | Tools | Contributor(s): Eric Sherer, Mohd Haziq Rahmad

    Stochastic simulation of polyp and colorectal cancer (CRC) incidence with patient age.