Modeling human papillomavirus and cervical cancer in the United States for analyses of screening and vaccination

Background: To provide quantitative insight into current U.S. policy choices for cervical cancer prevention, we developed a model of human papillomavirus (HPV) and cervical cancer, explicitly incorporating uncertainty about the natural history of disease. Methods: We developed a stochastic microsimulation of cervical cancer that distinguishes different HPV types by their incidence, clearance, persistence, and progression. Input parameter sets were sampled randomly from uniform distributions, and simulations undertaken with each set. Through systematic reviews and formal data synthesis, we established multiple epidemiologic targets for model calibration, including age-specific prevalence of HPV by type, age-specific prevalence of cervical intraepithelial neoplasia (CIN), HPV type distribution within CIN and cancer, and age-specific cancer incidence. For each set of sampled input parameters, likelihood-based goodness-of-fit (GOF) scores were computed based on comparisons between model-predicted outcomes and calibration targets. Using 50 randomly resampled, good-fitting parameter sets, we assessed the external consistency and face validity of the model, comparing predicted screening outcomes to independent data. To illustrate the advantage of this approach in reflecting parameter uncertainty, we used the 50 sets to project the distribution of health outcomes in U.S. women under different cervical cancer prevention strategies. Results: Approximately 200 good-fitting parameter sets were identified from 1,000,000 simulated sets. Modeled screening outcomes were externally consistent with results from multiple independent data sources. Based on 50 good-fitting parameter sets, the expected reductions in lifetime risk of cancer with annual or biennial screening were 76% (range across 50 sets: 69–82%) and 69% (60–77%), respectively. The reduction from vaccination alone was 75%, although it ranged from 60% to 88%, reflecting considerable parameter uncertainty about the natural history of type-specific HPV infection. The uncertainty surrounding the model-predicted reduction in cervical cancer incidence narrowed substantially when vaccination was combined with every-5-year screening, with a mean reduction of 89% and range of 83% to 95%. Conclusion: We demonstrate an approach to parameterization, calibration and performance evaluation for a U.S. cervical cancer microsimulation model intended to provide qualitative and quantitative inputs into decisions that must be taken before long-term data on vaccination outcomes become available. This approach allows for a rigorous and comprehensive description of policy-relevant uncertainty about health outcomes under alternative cancer prevention strategies. The model provides a tool that can accommodate new information, and can be modified as needed, to iteratively assess the expected benefits, costs, and cost-effectiveness of different policies in the U.S

ELECTROPHORETIC DISPLAYS WITH TUNABLE, ANGLE-INDEPENDENT COLOR

Electrophoretic displays (EPDs), which exploit the surface charge of microparticles to control their deposition, have become widely available in consumer electronics, such as e-readers and smartwatches. However, a full-color EPD has yet to be demonstrated and commercialized. Here, we demonstrate colloidal assemblies of engineered quasi-amorphous photonic materials, using pigmentary α-Fe2O3/SiO2 core/shell nanoparticles, exhibiting non- iridescent tunable colors which can be tuned electrophoretically. The observed colors result from combination of colloidal particle arrangements, giving rise to structural color, along with the inherent pigmentary color of the α-Fe2O3/SiO2 nanoparticles. Colloidal particle assemblies of α-Fe2O3/SiO2 core/shell nanoparticles, and therefore the resulting colors, can be manipulated by shell thickness, particle concentration and external electrical stimuli. Dynamic tunability of α-Fe2O3/SiO2 nanomaterials in the visible wavelengths is demonstrated using reversible electrophoretic deposition with a noticeable difference between transmitted and reflected colors. The distinct contrast generated can be exploited for tunable display applications. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-704082

Ultralight, ultrastiff mechanical metamaterials

The mechanical properties of ordinary materials degrade substantially with reduced density because their structural elements bend under applied load. We report a class of microarchitected materials that maintain a nearly constant stiffness per unit mass density, even at ultralow density. This performance derives from a network of nearly isotropic microscale unit cells with high structural connectivity and nanoscale features, whose structural members are designed to carry loads in tension or compression. Production of these microlattices, with polymers, metals, or ceramics as constituent materials, is made possible by projection microstereolithography (an additive micromanufacturing technique) combined with nanoscale coating and postprocessing. We found that these materials exhibit ultrastiff properties across more than three orders of magnitude in density, regardless of the constituent material

Morphology of Electrophoretically Deposited Films on Electrode Strips

Studies of the kinetics of electrophoretic deposition (EPD) processes have generally focused on electrode geometries that yield analytical solutions, such as infinite parallel planes and concentric cylinders. In this article, we construct a finite element model for EPD of material onto a planar strip electrode, which shows excellent qualitative agreement to experimental results in a similar system. Notably, we demonstrate that the presence of the edges of the electrode lead to a singularity in the electric field that significantly affects the morphology of the deposit at short times or for thin deposits

Modeling human papillomavirus and cervical cancer in the United States for analyses of screening and vaccination

Abstract Background To provide quantitative insight into current U.S. policy choices for cervical cancer prevention, we developed a model of human papillomavirus (HPV) and cervical cancer, explicitly incorporating uncertainty about the natural history of disease. Methods We developed a stochastic microsimulation of cervical cancer that distinguishes different HPV types by their incidence, clearance, persistence, and progression. Input parameter sets were sampled randomly from uniform distributions, and simulations undertaken with each set. Through systematic reviews and formal data synthesis, we established multiple epidemiologic targets for model calibration, including age-specific prevalence of HPV by type, age-specific prevalence of cervical intraepithelial neoplasia (CIN), HPV type distribution within CIN and cancer, and age-specific cancer incidence. For each set of sampled input parameters, likelihood-based goodness-of-fit (GOF) scores were computed based on comparisons between model-predicted outcomes and calibration targets. Using 50 randomly resampled, good-fitting parameter sets, we assessed the external consistency and face validity of the model, comparing predicted screening outcomes to independent data. To illustrate the advantage of this approach in reflecting parameter uncertainty, we used the 50 sets to project the distribution of health outcomes in U.S. women under different cervical cancer prevention strategies. Results Approximately 200 good-fitting parameter sets were identified from 1,000,000 simulated sets. Modeled screening outcomes were externally consistent with results from multiple independent data sources. Based on 50 good-fitting parameter sets, the expected reductions in lifetime risk of cancer with annual or biennial screening were 76% (range across 50 sets: 69–82%) and 69% (60–77%), respectively. The reduction from vaccination alone was 75%, although it ranged from 60% to 88%, reflecting considerable parameter uncertainty about the natural history of type-specific HPV infection. The uncertainty surrounding the model-predicted reduction in cervical cancer incidence narrowed substantially when vaccination was combined with every-5-year screening, with a mean reduction of 89% and range of 83% to 95%. Conclusion We demonstrate an approach to parameterization, calibration and performance evaluation for a U.S. cervical cancer microsimulation model intended to provide qualitative and quantitative inputs into decisions that must be taken before long-term data on vaccination outcomes become available. This approach allows for a rigorous and comprehensive description of policy-relevant uncertainty about health outcomes under alternative cancer prevention strategies. The model provides a tool that can accommodate new information, and can be modified as needed, to iteratively assess the expected benefits, costs, and cost-effectiveness of different policies in the U.S.</p

Modeling human papillomavirus and cervical cancer in the United States for analyses of screening and vaccination-3

<p><b>Copyright information:</b></p><p>Taken from "Modeling human papillomavirus and cervical cancer in the United States for analyses of screening and vaccination"</p><p>http://www.pophealthmetrics.com/content/5/1/11</p><p>Population Health Metrics 2007;5():11-11.</p><p>Published online 29 Oct 2007</p><p>PMCID:PMC2213637.</p><p></p>nge lines represent the results from matched model outputs in the presence of screening. Vertical axes represent prevalence, proportion, or incidence reduction as appropriate, and horizontal axes represent age or other categories as appropriate