Leg muscle volume during 30-day 6-degree head-down bed rest with isotonic and isokinetic exercise training

Magnetic resonance imaging (MRI) was used to compare the effect of two modes of lower-extremity exercise training on the mass (volume) of posterior leg group (PLG) muscles (soleus, flexor hallucis longus, tibialis posterior, lateral and medial gastrocnemius, and flexor digitorum longus) on 19 men (ages 32-42 years) subjected to intense dynamic-isotonic (ITE, cycle ergometer, number of subjects (N) = 7), isokinetic (IKE, torque egrometer, N = 7), and no exercise (NOE, N = 5) training for 60 min/day during head-down bed rest (HDBR). Total volume of the PLG muscles decreased (p less than 0.05) similarly: ITE = 4.3 +/- SE 1.6%, IKE = 7.7 +/- 1.6%, and NOE = 6.3 +/- 0.8%; combined volume (N = 19) loss was 6.1 +/- 0.9%. Ranges of volume changes were 2.6% to -9.0% (ITE), -2.1% to -14.9% (IKE), and -3.4% to -8/1% (NOE). Correlation coefficients (r) of muscle volume versus thickness measured with ultrasonography were: ITE r + 0.79 (p less than 0.05), IKE r = 0.27 (not significant (NS)), and NOE r = 0.63 (NS). Leg-muscle volume and thickness were highly correlated (r = 0.79) when plasma volume was maintained during HDBR with ITE. Thus, neither intensive lower extremity ITE nor IKE training influence the normal non-exercised posterior leg muscle atrophy during HDBR. The relationship of muscle volume and thickness may depend on the mode of exercise training associated with the maintenance of plasma volume

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

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

Cost Effectiveness of Metal Stents in Relieving Obstructive Jaundice in Patients with Pancreatic Cancer

ASGE and ESGE guidelines recommend endoscopic metal stent placement for pancreatic carcinoma patients with biliary obstruction, and whose estimated life expectancy is greater than 6 months. Because median overall survival (OS) of metastatic pancreatic adenocarcinoma until recently has been less than 6 months, plastic biliary stents were preferentially placed rather than metal due to the greater upfront cost of the latter. Recent advances in the treatment of metastatic pancreatic cancer have extended median OS beyond the 6-month range. Given this improvement in OS, we performed a cost-effectiveness analysis of initial metal biliary versus plastic stent placement in metastatic pancreatic cancer patients with biliary obstruction. A Markov model was developed to predict lifetime costs, quality-adjusted life years (QALYs), and cost effectiveness of metal compared with plastic stents. Adult patients entered the model with locally advanced cancer and underwent endoscopic retrograde cholangiopancreatography (ERCP) with placement of metal or plastic stents. A targeted literature search was conducted to identify published sources, which were used to estimate clinical, cost, utility, and event rate inputs to the model. Results were estimated from the third-party payer perspective in 2012 US dollars per QALY. One-way and probabilistic sensitivity analyses were conducted to assess the impact on model outcomes resulting from uncertainty among inputs. Our analysis found that initial placement of metal stents was more cost effective than plastic biliary stents with lower overall costs due to lower restenting rates while at the same time associated with a better quality of life. Based on model projections, placement of metal stents could save approximately $1450 per patient over a lifetime, while simultaneously improving quality of life. These findings were robust in sensitivity analyses. Placement of metal biliary stents at initial onset of obstructive jaundice in adult patients with metastatic pancreatic carcinoma with an expected OS greater than 6 months was found to be a more cost-effective strategy than plastic stents. These results reinforce guidelines' suggestions for metal stent placement

Modeling human papillomavirus and cervical cancer in the United States for analyses of screening and vaccination-1

<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>f each calibration target. Dashed gray lines represent model outputs prior to calibration and selection. Green lines represent model outputs after calibration and selection. Vertical axes represent duration, prevalence, proportion, or incidence rate as appropriate, and horizontal axes represent age or other categories as appropriate

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