Projected life-expectancy gains with statin therapy for individuals with elevated c-reactive protein levels

AbstractObjectivesWe sought to estimate the potential gains in life expectancy achieved with statin therapy for individuals without overt hyperlipidemia but with elevated C-reactive protein (CRP) levels.BackgroundPersons with low-density lipoprotein (LDL) cholesterol levels below current treatment guidelines and elevated CRP levels are at increased risk of cardiovascular disease and may benefit from statin therapy.MethodsWe constructed a decision-analytic model to estimate the gains in life expectancy with statin therapy for individuals without overt hyperlipidemia but with elevated CRP levels. The annual risks of myocardial infarction (MI) and stroke, as well as the efficacy of statin therapy, were based on evidence from randomized trials. Estimates of prognosis after MI or stroke were derived from population-based studies.ResultsWe estimated that 58-year-old men and women with CRP levels ≥0.16 mg/dl but LDL cholesterol <149 mg/dl would gain 6.6 months and 6.4 months of life expectancy, respectively, with statin therapy. These gains were similar to those for patients with LDL cholesterol ≥149 mg/dl (6.7 months for men and 6.6 months for women). In sensitivity analyses, we identified the baseline risk of MI and the efficacy of statin therapy for preventing MI as the most important factors in determining the magnitude of benefit with statin therapy.ConclusionsOur results suggest that individuals with elevated CRP levels, many of whom do not meet current National Cholesterol Education Program guidelines for drug treatment, may receive a substantial benefit from statin therapy. This analysis supports a crucial need for direct intervention trials aimed at subjects with elevated CRP levels

Cost-Effectiveness of Interferon Beta-1a, Interferon Beta-1b, and Glatiramer Acetate in Newly Diagnosed Non-primary Progressive Multiple Sclerosis

AbstractObjectiveTo perform a cost-effectiveness analysis of three immunomodulatory treatments for newly diagnosed nonprimary progressive MS: interferon beta-1a, interferon beta-1b, and glatiramer acetate.MethodsWe developed a state-transition model to estimate the health effects and costs associated with interferon beta-1a, interferon beta-1b, glatiramer acetate, and no treatment for hypothetical cohorts of men and women with non-primary progressive MS. We used the Expanded Disability Status Scale as the measure of disability and included both relapses and disease progression in the model. We evaluated treatment strategies assuming a 10-year treatment duration using the societal perspective. We elicited preferences for disability and treatment states using standard-gamble questions and modeled the disutility associated with treatment administration and side effects explicitly. Main outcome measures were net gains in quality-adjusted life expectancy and incremental cost-effectiveness ratios in dollars per quality-adjusted life year (QALY) gained.ResultsFor treatment duration of 10 years for newly diagnosed non-primary progressive MS, interferon beta-1a yielded the largest gain in quality-adjusted life expectancy with an incremental cost-effectiveness ratio of $2,200,000/QALY for women and$1,800,000/QALY for men, compared with no treatment. For a 5-year treatment duration, a “no treatment” strategy yielded more quality-adjusted life years than any of the treatment strategies. Cost-effectiveness ratios were similar for all three immunomodulatory treatments evaluated.ConclusionsCost-effectiveness results for all three immunomodulatory treatments for MS were unfavorable in the simulated study population under a wide range of assumptions. For treatment duration less than or equal to 5 years, expected benefits of treatment may not outweigh disutility associated with side effects and treatment discomfort

Characterization and valuation of uncertainty of calibrated parameters in stochastic decision models

We evaluated the implications of different approaches to characterize uncertainty of calibrated parameters of stochastic decision models (DMs) in the quantified value of such uncertainty in decision making. We used a microsimulation DM of colorectal cancer (CRC) screening to conduct a cost-effectiveness analysis (CEA) of a 10-year colonoscopy screening. We calibrated the natural history model of CRC to epidemiological data with different degrees of uncertainty and obtained the joint posterior distribution of the parameters using a Bayesian approach. We conducted a probabilistic sensitivity analysis (PSA) on all the model parameters with different characterizations of uncertainty of the calibrated parameters and estimated the value of uncertainty of the different characterizations with a value of information analysis. All analyses were conducted using high performance computing resources running the Extreme-scale Model Exploration with Swift (EMEWS) framework. The posterior distribution had high correlation among some parameters. The parameters of the Weibull hazard function for the age of onset of adenomas had the highest posterior correlation of -0.958. Considering full posterior distributions and the maximum-a-posteriori estimate of the calibrated parameters, there is little difference on the spread of the distribution of the CEA outcomes with a similar expected value of perfect information (EVPI) of \$653 and \$685, respectively, at a WTP of \$66,000/QALY. Ignoring correlation on the posterior distribution of the calibrated parameters, produced the widest distribution of CEA outcomes and the highest EVPI of \$809 at the same WTP. Different characterizations of uncertainty of calibrated parameters have implications on the expect value of reducing uncertainty on the CEA. Ignoring inherent correlation among calibrated parameters on a PSA overestimates the value of uncertainty.Comment: 17 pages, 6 figures, 3 table

Contribution of H. pylori and Smoking Trends to US Incidence of Intestinal-Type Noncardia Gastric Adenocarcinoma: A Microsimulation Model

Background: Although gastric cancer has declined dramatically in the US, the disease remains the second leading cause of cancer mortality worldwide. A better understanding of reasons for the decline can provide important insights into effective preventive strategies. We sought to estimate the contribution of risk factor trends on past and future intestinal-type noncardia gastric adenocarcinoma (NCGA) incidence. Methods and Findings: We developed a population-based microsimulation model of intestinal-type NCGA and calibrated it to US epidemiologic data on precancerous lesions and cancer. The model explicitly incorporated the impact of Helicobacter pylori and smoking on disease natural history, for which birth cohort-specific trends were derived from the National Health and Nutrition Examination Survey (NHANES) and National Health Interview Survey (NHIS). Between 1978 and 2008, the model estimated that intestinal-type NCGA incidence declined 60% from 11.0 to 4.4 per 100,000 men, <3% discrepancy from national statistics. H. pylori and smoking trends combined accounted for 47% (range = 30%–58%) of the observed decline. With no tobacco control, incidence would have declined only 56%, suggesting that lower smoking initiation and higher cessation rates observed after the 1960s accelerated the relative decline in cancer incidence by 7% (range = 0%–21%). With continued risk factor trends, incidence is projected to decline an additional 47% between 2008 and 2040, the majority of which will be attributable to H. pylori and smoking (81%; range = 61%–100%). Limitations include assuming all other risk factors influenced gastric carcinogenesis as one factor and restricting the analysis to men. Conclusions: Trends in modifiable risk factors explain a significant proportion of the decline of intestinal-type NCGA incidence in the US, and are projected to continue. Although past tobacco control efforts have hastened the decline, full benefits will take decades to be realized, and further discouragement of smoking and reduction of H. pylori should be priorities for gastric cancer control efforts. Please see later in the article for the Editors' Summar

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

Using Cerebrospinal Fluid Biomarker Testing to Target Treatment to Patients with Mild Cognitive Impairment: A Cost-Effectiveness Analysis

Objective Cerebrospinal fluid (CSF) biomarkers are shown to facilitate a risk identification of patients with mild cognitive impairment (MCI) into different risk levels of progression to Alzheimer’s disease (AD). Knowing a patient’s risk level provides an opportunity for earlier interventions, which could result in potential greater benefits. We assessed the cost effectiveness of the use of CSF biomarkers in MCI patients where the treatment decision was based on patients’ risk level. Methods We developed a state-transition model to project lifetime quality-adjusted life-years (QALYs) and costs for a cohort of 65-year-old MCI patients from a US societal perspective. We compared four test-and-treat strategies where the decision to treat was based on a patient’s risk level (low, intermediate, high) of progressing to AD with two strategies without testing, one where no patients were treated during the MCI phase and in the other all patients were treated. We performed deterministic and probabilistic sensitivity analyses to evaluate parameter uncertainty. Results Testing and treating low-risk MCI patients was the most cost-effective strategy with an incremental cost-effectiveness ratio (ICER) of US$37,700 per QALY. Our results were most sensitive to the level of treatment effectiveness for patients with mild AD and for MCI patients. Moreover, the ICERs for this strategy at the 2.5th and 97.5th percentiles were US$18,900 and US$50,100 per QALY, respectively. Conclusion Based on the best available evidence regarding the treatment effectiveness for MCI, this study suggests the potential value of performing CSF biomarker testing for early targeted treatments among MCI patients with a narrow range for the ICER

Targeting mitochondrial oxidative phosphorylation eradicates therapy-resistant chronic myeloid leukemia stem cells

Treatment of chronic myeloid leukemia (CML) with imatinib mesylate and other second-and/or third-generation c-Abl-specific tyrosine kinase inhibitors (TKIs) has substantially extended patient survival(1). However, TKIs primarily target differentiated cells and do not eliminate leukemic stem cells (LSCs)(2-4). Therefore, targeting minimal residual disease to prevent acquired resistance and/or disease relapse requires identification of new LSC-selective target(s) that can be exploited therapeutically(5,6). Considering that malignant transformation involves cellular metabolic changes, which may in turn render the transformed cells susceptible to specific assaults in a selective manner(7), we searched for such vulnerabilities in CML LSCs. We performed metabolic analyses on both stem cell-enriched (CD34(+) and CD34(+)CD38(-)) and differentiated (CD34(-)) cells derived from individuals with CML, and we compared the signature of these cells with that of their normal counterparts. Through combination of stable isotope-assisted metabolomics with functional assays, we demonstrate that primitive CML cells rely on upregulated oxidative metabolism for their survival. We also show that combination treatment with imatinib and tigecycline, an antibiotic that inhibits mitochondrial protein translation, selectively eradicates CML LSCs both in vitro and in a xenotransplantation model of human CML. Our findings provide a strong rationale for investigation of the use of TKIs in combination with tigecycline to treat patients with CML with minimal residual disease

Modeling good research practices - overview: a report of the ISPOR-SMDM modeling good research practices task force - 1.

Models—mathematical frameworks that facilitate estimation of the consequences of health care decisions—have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR modeling task force reported in 2003 has led to a new task force, jointly convened with the Society for Medical Decision Making, and this series of seven papers presents the updated recommendations for best practices in conceptualizing models; implementing state–transition approaches, discrete event simulations, or dynamic transmission models; dealing with uncertainty; and validating and reporting models transparently. This overview introduces the work of the task force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these papers includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making

Emulator-based Bayesian calibration of the CISNET colorectal cancer models

PURPOSE: To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET) 's SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.METHODS: We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANN) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.RESULTS: The optimal ANN for SimCRC had four hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had one hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 hours for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.CONCLUSIONS: Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, like the CISNET CRC models.</p

Novel mutations in TARDBP (TDP-43) in patients with familial amyotrophic lateral sclerosis.

The TAR DNA-binding protein 43 (TDP-43) has been identified as the major disease protein in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with ubiquitin inclusions (FTLD-U), defining a novel class of neurodegenerative conditions: the TDP-43 proteinopathies. The first pathogenic mutations in the gene encoding TDP-43 (TARDBP) were recently reported in familial and sporadic ALS patients, supporting a direct role for TDP-43 in neurodegeneration. In this study, we report the identification and functional analyses of two novel and one known mutation in TARDBP that we identified as a result of extensive mutation analyses in a cohort of 296 patients with variable neurodegenerative diseases associated with TDP-43 histopathology. Three different heterozygous missense mutations in exon 6 of TARDBP (p.M337V, p.N345K, and p.I383V) were identified in the analysis of 92 familial ALS patients (3.3%), while no mutations were detected in 24 patients with sporadic ALS or 180 patients with other TDP-43-positive neurodegenerative diseases. The presence of p.M337V, p.N345K, and p.I383V was excluded in 825 controls and 652 additional sporadic ALS patients. All three mutations affect highly conserved amino acid residues in the C-terminal part of TDP-43 known to be involved in protein-protein interactions. Biochemical analysis of TDP-43 in ALS patient cell lines revealed a substantial increase in caspase cleaved fragments, including the approximately 25 kDa fragment, compared to control cell lines. Our findings support TARDBP mutations as a cause of ALS. Based on the specific C-terminal location of the mutations and the accumulation of a smaller C-terminal fragment, we speculate that TARDBP mutations may cause a toxic gain of function through novel protein interactions or intracellular accumulation of TDP-43 fragments leading to apoptosis