Cost-effectiveness of pharmacogenomic-guided treatment for major depression.

BACKGROUND: Pharmacogenomic testing to identify variations in genes that influence metabolism of antidepressant medications can enhance efficacy and reduce adverse effects of pharmacotherapy for major depressive disorder. We sought to establish the cost-effectiveness of implementing pharmacogenomic testing to guide prescription of antidepressants. METHODS: We developed a discrete-time microsimulation model of care pathways for major depressive disorder in British Columbia, Canada, to evaluate the effectiveness and cost-effectiveness of pharmacogenomic testing from the public payer's perspective over 20 years. The model included unique patient characteristics (e.g., metabolizer phenotypes) and used estimates derived from systematic reviews, analyses of administrative data (2015-2020) and expert judgment. We estimated incremental costs, life-years and quality-adjusted life-years (QALYs) for a representative cohort of patients with major depressive disorder in BC. RESULTS: Pharmacogenomic testing, if implemented in BC for adult patients with moderate-severe major depressive disorder, was predicted to save the health system $956 million ($4926 per patient) and bring health gains of 0.064 life-years and 0.381 QALYs per patient (12 436 life-years and 74 023 QALYs overall over 20 yr). These savings were mainly driven by slowing or avoiding the transition to refractory (treatment-resistant) depression. Pharmacogenomic-guided care was associated with 37% fewer patients with refractory depression over 20 years. Sensitivity analyses estimated that costs of pharmacogenomic testing would be offset within about 2 years of implementation. INTERPRETATION: Pharmacogenomic testing to guide antidepressant use was estimated to yield population health gains while substantially reducing health system costs. These findings suggest that pharmacogenomic testing offers health systems an opportunity for a major value-promoting investment.

Costs of major depression covered / not covered in British Columbia, Canada.

BACKGROUND: Major depressive disorder (MDD) is one of the world's leading causes of disability. Our purpose was to characterize the total costs of MDD and evaluate the degree to which the British Columbia provincial health system meets its objective to protect people from the financial impact of illness. METHODS: We performed a population-based cohort study of adults newly diagnosed with MDD between 2015 and 2020 and followed their health system costs over two years. The expenditure proportion of MDD-related, patient paid costs relative to non-subsistence income was estimated, incidences of financial hardship were identified and the slope index of inequality (SII) between the highest and lowest income groups compared across regions. RESULTS: There were 250,855 individuals diagnosed with MDD in British Columbia over the observation period. Costs to the health system totalled >$1.5 billion (2020 CDN), averaging $138/week for the first 12 weeks following a new diagnosis and $65/week to week 52 and $55/week for weeks 53-104 unless MDD was refractory to treatment ($125/week between week 12-52 and $101/week over weeks 53-104). The proportion of MDD-attributable costs not covered by the health system was 2-15x greater than costs covered by the health system, exceeding $700/week for patients with severe MDD or MDD that was refractory to treatment. Population members in lower-income groups and urban homeowners had disadvantages in the distribution of financial protection received by the health system (SII reached - 8.47 and 15.25, respectively); however, financial hardship and inequities were mitigated province-wide if MDD went into remission (SII - 0.07 to 0.6). CONCLUSIONS: MDD-attributable costs to health systems and patients are highest in the first 12 weeks after a new diagnosis. During this time, lower income groups and homeowners in urban areas run the risk of financial hardship.

Characterizing undiagnosed chronic obstructive pulmonary disease: a systematic review and meta-analysis.

BACKGROUND: A significant proportion of patients with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Characterizing these patients can increase our understanding of the 'hidden' burden of COPD and the effectiveness of case detection interventions. METHODS: We conducted a systematic review and meta-analysis to compare patient and disease factors between patients with undiagnosed persistent airflow limitation and those with diagnosed COPD. We searched MEDLINE and EMBASE for observational studies of adult patients meeting accepted spirometric definitions of COPD. We extracted and pooled summary data on the proportion or mean of each risk factor among diagnosed and undiagnosed patients (unadjusted analysis), and coefficients for the adjusted association between risk factors and diagnosis status (adjusted analysis). RESULTS: Two thousand eighty-three records were identified through database searching and 16 articles were used in the meta-analyses. Diagnosed patients were less likely to have mild (v. moderate to very severe) COPD (odds ratio [OR] 0.30, 95%CI 0.24-0.37, 6 studies) in unadjusted analysis. This association remained significant but its strength was attenuated in the adjusted analysis (OR 0.72, 95%CI 0.58-0.89, 2 studies). Diagnosed patients were more likely to report respiratory symptoms such as wheezing (OR 3.51, 95%CI 2.19-5.63, 3 studies) and phlegm (OR 2.16, 95% CI 1.38-3.38, 3 studies), had more severe dyspnea (mean difference in modified Medical Research Council scale 0.52, 95%CI 0.40-0.64, 3 studies), and slightly greater smoking history than undiagnosed patients. Patient age, sex, current smoking status, and the presence of coughing were not associated with a previous diagnosis. CONCLUSIONS: Undiagnosed patients had less severe airflow obstruction and fewer respiratory symptoms than diagnosed patients. The lower disease burden in undiagnosed patients may significantly delay the diagnosis of COPD.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol.

BACKGROUND: Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD. METHODS AND ANALYSIS: Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep. CONCLUSION: SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

Solvation effects on like-charge attraction.

We present results of molecular dynamics simulations of the electrostatic interaction between two parallel charged rods in the presence of divalent counterions. Such polyelectrolytes have been considered as a simple model for understanding electrostatic interactions in highly charged biomolecules such as DNA. Since there are correlations between the free charge carriers, the phenomenon of like charge attraction appears for specific parameters. We explore the role of solvation effects and the resulting deviations from Coulomb's law on the nanoscale on this peculiar phenomenon. The behavior of the force between the charged rods in a simulation with atomistic representation of water molecules is completely different from a model in which water is modeled as a continuum dielectric. By calculating counterion-rodion pair correlation functions, we find that the presence of water molecules changes the structure of the counterion cloud and results in both qualitative and quantitative changes of the force between highly charged polyelectrolytes.

Collaborating with Patient Partners to Model Clinical Care Pathways in Major Depressive Disorder: The Benefits of Mixing Evidence and Lived Experience.

BACKGROUND: Partnering with patients can enrich the design and development of models of clinical care pathways, yet the practice is not commonplace. Guidelines or "best practices" for patient involvement in modeling are scarce. OBJECTIVES: In this paper, we outline the steps we took to form an effective partnership with patients to design a robust microsimulation Markov model of major depressive disorder care pathways in British Columbia, Canada, with the aim of encouraging other teams to partner with patients in healthcare modeling endeavors. METHODS: We describe three unique phases of our collaborative process: uncertainty, mapping, and structured collaboration. We then explore the unique contributions the patient partners made, not only to the model itself, but to our process. Key perspectives are shared from both the modeler and the patient partners in their own words. RESULTS: The patient partners made distinct contributions by challenging and verifying modeling assumptions, noting limitations of the model, and suggesting areas for future research. Both the patient partners and the modelers saw great value in the partnership and agreed that the model was strengthened by the diversity of the team. CONCLUSIONS: We present our learning and key recommendations for future modeling teams in the absence of tested frameworks. We encourage more widespread adoption of patient involvement in modeling and the development of guidelines for such work to increase the democracy of scientific decision making.

A comparison of three strategies to reduce the burden of osteoarthritis: A population-based microsimulation study.

OBJECTIVES: The purpose of this study was to compare three strategies for reducing population health burden of osteoarthritis (OA): improved pharmacological treatment of OA-related pain, improved access to joint replacement surgery, and prevention of OA by reducing obesity and overweight. METHODS: We applied a validated computer microsimulation model of OA in Canada. The model simulated a Canadian-representative open population aged 20 years and older. Variables in the model included demographics, body mass index, OA diagnosis, OA treatment, mortality, and health-related quality of life. Model parameters were derived from analyses of national surveys, population-based administrative data, a hospital-based cohort study, and the literature. We compared 8 what-if intervention scenarios in terms of disability-adjusted life years (DALYs) relative to base-case, over a wide range of time horizons. RESULTS: Reductions in DALYs depended on the type of intervention, magnitude of the intervention, and the time horizon. Medical interventions (a targeted increase in the use of painkillers) tended to produce effects quickly and were, therefore, most effective over a short time horizon (a decade). Surgical interventions (increased access to joint replacement) were most effective over a medium time horizon (two decades or longer). Preventive interventions required a substantial change in BMI to generate a significant impact, but produced more reduction in DALYs than treatment strategies over a very long time horizon (several decades). CONCLUSIONS: In this population-based modeling study we assessed the potential impact of three different burden reduction strategies in OA. Data generated by our model may help inform the implementation of strategies to reduce the burden of OA in Canada and elsewhere.

Development and Validation of the Evaluation Platform in COPD (EPIC): A Population-Based Outcomes Model of COPD for Canada.

BACKGROUND: We report the development, validation, and implementation of an open-source population-based outcomes model of chronic obstructive pulmonary disease (COPD) for Canada. METHODS: Evaluation Platform in COPD (EPIC) is a discrete-event simulation model of Canadians 40 years of age or older. Three core features of EPIC are its open-population design (incorporating projections of future population growth, aging, and smoking trends), its incorporation of heterogeneity in lung function decline and burden of exacerbations, and its modeling of the natural history of COPD from inception. Multiple original data analyses, as well as values reported in the literature, were used to populate the model. Extensive face validity and internal and external validity evaluations were performed. RESULTS: The model was internally validated on demographic projections, mortality rates, lung function trajectories, COPD exacerbations, costs and health state utility values, and stability of COPD prevalence over time within strata of risk factors. In external validation, it moderately overestimated the rate of overall exacerbations in 2 independent trials but generated consistent estimates of rate of severe exacerbations and mortality. LIMITATIONS: In its current version, EPIC does not consider uncertainty in the evidence. Several components such as additional (e.g., environmental and occupational) risk factors, treatment, symptoms, and comorbidity will have to be added in future iterations. Predictive validity of EPIC needs to be examined prospectively against future empirical studies. CONCLUSIONS: EPIC is the first multipurpose, open-source, outcome- and policy-focused model of COPD for Canada. Platforms of this type have the capacity to be iteratively updated to incorporate the latest evidence and to project the outcomes of many different scenarios within a consistent framework.

Stability of synchronized states in networks of phase oscillators.

The stability of synchronized states (frequency locked states) in networks of phase oscillators is investigated for several network topologies. It is shown that for some topologies there is more than one stable synchronized state according to the sign of coupling strength between oscillators. It is also shown that in some cases the synchronized state corresponds to zero order parameter.