Economics of the clinical management of lung cancer in France: an analysis using a Markov model.
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ABSTRACT:
SUBMITTER: Chouaid C
PROVIDER: S-EPMC2409571 | biostudies-other | 2004 Jan
REPOSITORIES: biostudies-other
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Project description:BackgroundProstate cancer (PCa) is the most common non-skin cancer among men in developed countries. Several novel treatments have been adopted by healthcare systems to manage PCa. Most of the observational studies and randomized trials on PCa have concurrently evaluated fewer treatments over short follow-up. Further, preceding decision analytic models on PCa management have not evaluated various contemporary management options. Therefore, a contemporary decision analytic model was necessary to address limitations to the literature by synthesizing the evidence on novel treatments thereby forecasting short and long-term clinical outcomes.ObjectivesTo develop and validate a Markov Monte Carlo model for the contemporary clinical management of PCa, and to assess the clinical burden of the disease from diagnosis to end-of-life.MethodsA Markov Monte Carlo model was developed to simulate the management of PCa in men 65 years and older from diagnosis to end-of-life. Health states modeled were: risk at diagnosis, active surveillance, active treatment, PCa recurrence, PCa recurrence free, metastatic castrate resistant prostate cancer, overall and PCa death. Treatment trajectories were based on state transition probabilities derived from the literature. Validation and sensitivity analyses assessed the accuracy and robustness of model predicted outcomes.ResultsValidation indicated model predicted rates were comparable to observed rates in the published literature. The simulated distribution of clinical outcomes for the base case was consistent with sensitivity analyses. Predicted rate of clinical outcomes and mortality varied across risk groups. Life expectancy and health adjusted life expectancy predicted for the simulated cohort was 20.9 years (95%CI 20.5-21.3) and 18.2 years (95% CI 17.9-18.5), respectively.ConclusionStudy findings indicated contemporary management strategies improved survival and quality of life in patients with PCa. This model could be used to compare long-term outcomes and life expectancy conferred of PCa management paradigms.
| S-EPMC4256380 | biostudies-literature
Project description:Adverse events (AEs) related to medical treatments in non-small cell lung cancer (NSCLC) are frequent and need an appropriate costing in health economic models. Nevertheless, data on costs associated with AEs in NSCLC are scarce, particularly since the development of immunotherapy with specific immune-related AEs.To estimate the costs of grades 3 and 4 AEs related to NSCLC treatments including immunotherapy in France.Grades 3 and 4 AEs related to treatment and reported in at least 1% of patients in Phase III clinical trials for erlotinib, ramucirumab plus docetaxel, docetaxel, pemetrexed plus carboplatin plus bevacizumab, platinum-based chemotherapies, nivolumab and pembrolizumab were identified. When no cost evaluation was reported in literature, estimates on standard treatments and medical resource use for each AE were obtained thanks to an expert panel. Total cost per AE was calculated from a French national health insurance perspective and updated in 2017 Euros. Hospital stay costs were estimated based on public and private weighted tariffs and data from the French Medical Information System (Programme de Médicalisation des Systèmes d'Information). Costs of tests, consultations and treatments were calculated based on national reimbursement tariffs.Overall, costs of grades 3 and 4 AEs related to treatment ranged from €46 per event to €7,742 per year. Fourteen out of 24 AEs identified had a mean estimated cost over €2,000. The highest mean costs were related to type 1 diabetes (€7,742 per year) followed by pneumonitis (€5,786 per event), anemia (€5,752 per event), dehydration (€5,207 per event) and anorexia (€4,349 per event). Costs were mostly driven by hospitalization costs.Among the AEs identified, a majority appeared to have an important economic impact, with a management cost of at least €2,000 per event mainly driven by hospitalization costs. This study may be of interest for economic evaluations of new interventions in NSCLC.
| S-EPMC5538537 | biostudies-other
Project description:The availability of reliable genetic linkage maps is crucial for functional and evolutionary genomic analyses. Established theory and methods of genetic linkage analysis have made map construction a routine exercise in diploids. However, many evolutionarily, ecologically, and/or agronomically important species are autopolyploids, with autotetraploidy being a typical example. These species undergo much more complicated chromosomal segregation and recombination at meiosis than diploids. In addition, there is evidence of polyploidy-induced and highly dynamic changes in the structure of the genome. These polysomic characteristics indicate the inappropriateness of the theory and methods of linkage analysis in diploids for use in these species and a gap in the theory and methodology of tetraploid map construction. This paper presents a theoretical model and statistical framework for multilocus linkage analysis in autotetraploids for use with dominant and/or codominant DNA molecular markers. The theory and methods incorporate the essential features of allele segregation and recombination under tetrasomic inheritance and the major challenges in statistical modeling and marker data analysis. We validated the method and explored its statistical properties by intensive simulation study and demonstrated its utility by analysis of AFLP and SSR marker data from an outbred autotetraploid potato population.
| S-EPMC2840161 | biostudies-literature
Project description:ObjectivesThis study analyses the cost-effectiveness of annual low-dose CT (LDCT) screening of high-risk cancer populations in Chinese urban areas.DesignWe used a Markov model to evaluate LDCT screening from a sociological perspective.SettingThe data from two large lung cancer screening programmes in China were used.ParticipantsThe sample consisted of 100 000 smokers who underwent annual LDCT screening until age 76.InterventionThe study comprises five screening strategies, with the initial screening ages in both the screening strategies and their corresponding non-screening strategies being 40, 45, 50, 55 and 60 years, respectively.Primary and secondary outcome measuresThe incremental cost-effectiveness ratio (ICER) between screening and non-screening strategies at the same initial age was evaluated.ResultsIn the baseline scenario, compared with those who were not screened, the specific mortality from lung cancer decreased by 18.52%-23.13% among those who underwent screening. The ICER of LDCT screening ranges from US$13 056.82 to US$15 736.06 per quality-adjusted life year, which is greater than one but less than three times the gross domestic product per capita in China. An initial screening age of 55 years is the most cost-effective strategy.ConclusionsBaseline analysis shows that annual LDCT screening of heavy smokers in Chinese urban areas is likely to be cost-effective. The sensitivity analysis reveals that sensitivity, specificity and the overdiagnosis rate influence the cost-effectiveness of LDCT screening. All scenarios tested demonstrate cost-effectiveness, except for the combination of worst values of sensitivity, specificity and overdiagnosis. Therefore, the cost-effectiveness of a screening strategy depends on the performance of LDCT screenings.
| S-EPMC8252866 | biostudies-literature
Project description:BackgroundRoutine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.MethodsA Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.ResultsAlgorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.ConclusionOur findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.
| S-EPMC2735038 | biostudies-literature
Project description:The classic view of metastatic cancer progression is that it is a unidirectional process initiated at the primary tumor site, progressing to variably distant metastatic sites in a fairly predictable, although not perfectly understood, fashion. A Markov chain Monte Carlo mathematical approach can determine a pathway diagram that classifies metastatic tumors as "spreaders" or "sponges" and orders the timescales of progression from site to site. In light of recent experimental evidence highlighting the potential significance of self-seeding of primary tumors, we use a Markov chain Monte Carlo (MCMC) approach, based on large autopsy data sets, to quantify the stochastic, systemic, and often multidirectional aspects of cancer progression. We quantify three types of multidirectional mechanisms of progression: (i) self-seeding of the primary tumor, (ii) reseeding of the primary tumor from a metastatic site (primary reseeding), and (iii) reseeding of metastatic tumors (metastasis reseeding). The model shows that the combined characteristics of the primary and the first metastatic site to which it spreads largely determine the future pathways and timescales of systemic disease.
| S-EPMC3644026 | biostudies-literature
Project description:To estimate the expected incremental lifetime cost of treatment of keratoconus compared to the expected cost of the treatment of myopia.Cost estimate from the patient's perspective using a Markov decision model.We modeled a hypothetical cohort of people with clinically significant incident keratoconus as defined by the Collaborative Longitudinal Evaluation of Keratoconus (CLEK) Study. We included costs of clinic visits, fitting fees, contact lenses, surgical procedures, and complications. Survival curves of corneal transplants and associated complications were modeled using data from the 2007 Australian Graft Registry. Medical treatment regimens after surgery were defined by expert opinion.The expected value of the lifetime cost of the treatment of keratoconus over myopia was $25 168 with a standard deviation of $16 247 and a median of $17 596. The factors that most influenced the lifetime cost were the probability of initial corneal transplant and a subsequent regraft. The cost of routine care had relatively little influence on the lifetime cost of care.The expected lifetime cost of treatment of keratoconus represents a significant cost to patients and payors. While the cost of routine care for keratoconus is not trivial, the primary factor influencing changes in the cost of care for keratoconus is the probability of corneal transplant. Combined with the significantly impaired vision-related quality of life and the relatively young onset of disease, the economic burden of the treatment of keratoconus represents a significant public health concern.
| S-EPMC4714341 | biostudies-literature
Project description:In the genomic era, group association tests are of great interest. Due to the overwhelming number of individual genomic features, the power of testing for association of a single genomic feature at a time is often very small, as are the effect sizes for most features. Many methods have been proposed to test association of a trait with a group of features within a functional unit as a whole, e.g. all SNPs in a gene, yet few of these methods account for the fact that generally a substantial proportion of the features are not associated with the trait. In this paper, we propose to model the association for each feature in the group as a mixture of features with no association and features with non-zero associations to explicitly account for the possibility that a fraction of features may not be associated with the trait while other features in the group are. The feature-level associations are first estimated by generalized linear models; the sequence of these estimated associations is then modeled by a hidden Markov chain. To test for global association, we develop a modified likelihood ratio test based on a log-likelihood function that ignores higher order dependency plus a penalty term. We derive the asymptotic distribution of the likelihood ratio test under the null hypothesis. Furthermore, we obtain the posterior probability of association for each feature, which provides evidence of feature-level association and is useful for potential follow-up studies. In simulations and data application, we show that our proposed method performs well when compared with existing group association tests especially when there are only few features associated with the outcome.
| S-EPMC4834946 | biostudies-literature
Project description:The non-homogeneous model of nucleotide substitution proposed by Barry and Hartigan (Stat Sci, 2: 191-210) is the most general model of DNA evolution assuming an independent and identical process at each site. We present a computational solution for this model, and use it to analyse two data sets, each violating one or more of the assumptions of stationarity, homogeneity, and reversibility. The log likelihood values returned by programs based on the F84 model (J Mol Evol, 29: 170-179), the general time reversible model (J Mol Evol, 20: 86-93), and Barry and Hartigan's model are compared to determine the validity of the assumptions made by the first two models. In addition, we present a method for assessing whether sequences have evolved under reversible conditions and discover that this is not so for the two data sets. Finally, we determine the most likely tree under the three models of DNA evolution and compare these with the one favoured by the tests for symmetry.
| S-EPMC2658871 | biostudies-literature
Project description:Particle deposition in the lung during inhalation is of interest to a wide range of biomedical sciences due to the noninvasive therapeutic route to deliver drugs to the lung and other organs via the blood stream. Before reaching the alveoli, particles must transverse the bifurcating network of airways. Computational fluid mechanical studies are often used to estimate high-fidelity flow patterns through the large conducting airways, but there is a need for reduced-dimensional modeling that enables rapid parameter optimization while accommodating the complete airway network. Here, we introduce a Markov chain model with each state corresponding to an airway segment in which a particle may be located. The local flows and transition probabilities of the Markov chain, verified against computational fluid dynamics simulations, indicate that the independent effects of three fundamental forces (gravity, fluid drag, diffusion) provide a sufficient approximation of overall particle behavior. The model enables fast computation of how different inhalation strategies, called flow policies, determine total particle escape rates and local particle deposition. In a 3-dimensional airway tree model, the optimal flow policy minimizing the risk of deposition at each generation, compared to other inlet flow waveforms, predicted significantly higher probability of escape defined as the fraction of particles exiting the tree. The model also predicts a small influence of body orientation with respect to a gravitational field on total escape probability, but a significant effect of airway narrowing on regional deposition. In summary, this model provides insight into inhalation strategies for targeted drug delivery.
| S-EPMC7419522 | biostudies-literature