Browsing by Subject "Cost-effectiveness analysis"

Now showing 1 - 3 of 3
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    Long-term Comparative Effectiveness of Rheumatoid Arthritis Treatment Strategies
    (2013-08) Jalal, Hawre
    Rheumatoid arthritis (RA) is a chronic debilitating disease characterized by progressive joint damage, reduced quality of life, loss of productivity and premature death. It affects 1% of the adult US population, and is one of the most demanding diseases on our healthcare resources. Biologic disease modifiers are new drugs that provide hope to improve the course of RA; however, biologics are among the most expensive specialty drugs. Although the treatment costs of RA have recently increased with the introduction of biologics, most of the economic and societal impacts are due to consequences of RA rather than direct treatment costs. Thus, the cost-effectiveness of biologics in RA is of high priority as recognized by many agencies including the National Institute of Health. This thesis focuses on three limitations of the current cost-effectiveness analyses (CEA) of biologics in RA. First, Most CEAs are based on randomized clinical trials (RCT) that are rarely applicable to real-life clinical practice. This thesis examines the long-term comparative clinical- and cost-effectiveness of biologics using clinical practice data from a large registry of RA patients (The National Data-Bank of Rheumatic Diseases). Second, we lack a meta-analytical approach specific to CEAs, and previous tools are deemed inappropriate. This thesis presents a novel approach of meta-analysis specific to CEAs. Using this tool we examine if prior CEAs of biologics in RA are consistent. Third, due to the biologics' high costs, RA treatment guidelines often recommend biologics as second line agents after nonbiologics. However, early aggressive treatment is crucial to avoid permanent joint damage. In this thesis we use Markov decision processes (MDP) as an innovative approach to identify the optimal timing of biologics in RA. The results from this analysis have significant policy, clinical and methodological implications. This work provides important insights into the comparative effectiveness of biologics in RA from a US societal perspective, which can influence health policy and medical insurance coverage decisions. Methodologically, the proposed meta-analytical approach can be applied to other conditions, and have the potential to reconcile the inconsistencies in published CEAs and improve the quality of future studies.
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    Statistical and mathematical modeling to evaluate the cost-effectiveness of Helicobacter pylori screening and treating strategies in Mexico in the setting of antibiotic resistance
    (2017-08) Alarid Escudero, Fernando
    Helicobacter pylori (H. pylori), a bacterium that is present in the stomach of half of the world’s population with disproportionate burden in developing countries, is the strongest known biological risk factor for gastric cancer. Gastric cancer is the fourth most common type of cancer and the second cause of cancer death in the world. In particular, in Mexico gastric cancer is the third highest cause of cancer death in adults, with some regions having cancer mortality rates that are twice the national average (8.0 vs. 3.9 per 100,000, respectively). H. pylori can be treated with antibiotics, but widespread treatment may lead to significant levels of antibiotic resistance (ABR). ABR is one of the main causes of H. pylori treatment failure and represents one of the greatest emerging global health threats. In this thesis, we use statistical and mathematical modeling to investigate the health benefits, harms, costs and cost-effectiveness of screen-and-treat strategies for identifying and treating persons with H. pylori to inform public health practice in three steps. First, we estimated the age-specific force of infection of H. pylori --defined as the instantaneous per capita rate at which susceptibles acquire infection-- using a novel hierarchical nonlinear Bayesian catalytic epidemic model with data from a national H. pylori seroepidemiology survey in Mexico. Second, we developed an age-structured, susceptible-infected-susceptible (SIS) transmission model of H. pylori infection in Mexico that included both treatment-sensitive and treatment-resistant strains. Model parameters were derived from the published literature and estimated from primary data. Using the model, we projected H. pylori infection and resistance levels over 20 years without treatment and for three hypothetical population-wide treatment policies assumed to be implemented in 2018. In sensitivity analyses, we considered different mixing patterns and trends of background antibiotic use. We validated the model against historical values of prevalence of infection and ABR of H. pylori. Third, we expanded the SIS model to incorporate the natural history of gastric carcinogenesis including gastritis, intestinal metaplasia, dysplasia and ultimately non-cardia gastric cancer. We then estimated the cost-effectiveness of various screen-and-treat strategies for H. pylori infection and ABR in the Mexican population from the health sector perspective.
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    Treat your partners right: Implication of sexual contact networks in partner management for sexually transmitted infections
    (2020-06) Kao, Szu-Yu
    Sexually transmitted infections (STIs) have continued to increase among the heterosexual population and men who have sex with men (MSM) in the last five years. To better inform STI control strategies, the factors that influence the disease dynamics of STIs can be important to incorporate in developing infectious disease modeling for cost-effectiveness analysis. The spread of STIs depends on the macrostructure (e.g., random, clustered, scale-free networks) and microstructure (e.g., relationship dynamics) of the contact networks, and the sexual behaviors (e.g., condom use) commonly adopted in the population. In this thesis, we investigated different aspects that could influence STI transmission and the cost and effectiveness of STI control strategies in the population of interest. First, we evaluated how the structure of sexual contact network influences the cost and effectiveness of partner management strategies controlling for bacterial STIs in MSM. We found that the network structure, the compliance to intervention, and the resource constraint matter in determining the optimal partner management strategy. Second, we evaluated how relationship dynamics affects the cost-effectiveness of partner management strategies and quantified the value of key measures (concurrency and the average relationship duration) that inform relationship dynamics. We found that modeling sexual contact networks without measures informing relationship dynamics might lead to recommendation of a less cost-effective partner management strategy to control bacterial STIs, resulting societal loss. The value of collecting concurrency information is higher than the value of relationship duration. Third, we explored how HIV status disclosure, partner selection and condom use behavior changed with HIV prevalence in MSM using evolutionary game theory. We found that these behaviors varied with HIV prevalence. In particular, HIV-positive individuals were more likely to disclose their status and less likely to use condom at a high HIV prevalence than at a low HIV prevalence. These behavior changes should be considered in cost-effectiveness analysis to better inform interventions of HIV/STIs.