Chapter 5: Actual and counterfactual smoking prevalence rates in the U.S. population via microsimulation.

The smoking history generator (SHG) developed by the National Cancer Institute simulates individual life/smoking histories that serve as inputs for the Cancer Intervention and Surveillance Modeling Network (CISNET) lung cancer models. In this chapter, we review the SHG inputs, describe its outputs, and outline the methodology behind it. As an example, we use the SHG to simulate individual life histories for individuals born between 1890 and 1984 for each of the CISNET smoking scenarios and use those simulated histories to compute the corresponding smoking prevalence over the period 1975-2000.

Chapter 13: CISNET lung models: comparison of model assumptions and model structures.

Sophisticated modeling techniques can be powerful tools to help us understand the effects of cancer control interventions on population trends in cancer incidence and mortality. Readers of journal articles are, however, rarely supplied with modeling details. Six modeling groups collaborated as part of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) to investigate the contribution of U.

An economic evaluation of atorvastatin for primary prevention of cardiovascular events in type 2 diabetes.

Objective: The CARDS trial, a multicentre, randomized, controlled trial, found that atorvastatin 10 mg/day for patients with type 2 diabetes mellitus and normal low-density lipoprotein (LDL)-cholesterol significantly reduced cardiovascular (CV) events, including stroke. We estimated the cost effectiveness of atorvastatin as primary prevention against CV disease from the short-term and lifetime US payer perspectives.

Research Design And Methods: We constructed a decision analytic (Markov) model to evaluate long-term costs and outcomes for atorvastatin 10 mg/day versus no HMG-CoA reductase inhibitor (statin) therapy for patients with type 2 diabetes and no history of a CV event.

Impact of adjuvant therapy and mammography on U.S. mortality from 1975 to 2000: comparison of mortality results from the cisnet breast cancer base case analysis.

The CISNET breast cancer program is a consortium of seven research groups modeling the impact of various cancer interventions on the national trends of breast cancer incidence and mortality. Each of the modeling groups participated in a CISNET breast cancer base case analysis with the objective of assessing the impact of mammography and adjuvant therapy on breast cancer mortality between 1975 and 2000. The comparative modeling approach used to address this question allowed for a unique view into the process of modeling.

A comparative review of CISNET breast models used to analyze U.S. breast cancer incidence and mortality trends.

The CISNET Breast Cancer program is a National Cancer Institute-sponsored collaboration composed of seven research groups that have modeled the impact of screening and adjuvant treatment on trends in breast cancer incidence and mortality over the period 1975-2000 (base case). This collaboration created a unique opportunity to make direct comparison of results from different models of population-based cancer screening produced in response to the same question. Comparing results in all but the most cursory way necessitates comparison of the models themselves.

Additional common inputs for analyzing impact of adjuvant therapy and mammography on U.S. mortality.

In estimating the impact of mammography and adjuvant treatment on U.S. breast cancer mortality rates, several parameters were common to all the Cancer Intervention and Surveillance Modeling Network (CISNET) models participating in the breast cancer base case.