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Objectives: Estimates on the distribution of patients with multiple myeloma (MM) by line of therapy (LOT) are scarce and get outdated quickly as new treatments become available. The objective of this study was to estimate the number of patients with MM by LOT and the number of patients who have received at least 4 previous LOTs including proteasome inhibitors, immunomodulatory agents, and anti-CD38 monoclonal antibodies (mAbs).Methods: A compartmental model was developed to calculate the number of patients by LOT. Two pathways were considered based on stem cell transplant eligibility, and at each pathway, treatments were stratified in 2 types: anti-CD38 mAbs or other. The model population was stratified into 4 subgroups based on age and cytogenetic risk. Model inputs were informed from real-world evidence.Results: The model estimated that, in 2020, 126 869 patients were living with MM in the United States. Of these, 105 701 received treatment in any LOT, with 56 959, 27 252, 11 258, and 5217 in lines 1 to 4, respectively, and 5015 in line 5 or beyond. The model estimated that 3497 patients received at least 4 previous LOTs including proteasome inhibitors, immunomodulatory agents, and anti-CD38 mAbs. The model overall prevalence predictions aligned well with publicly available estimates.Conclusions: This study proposes a novel framework to estimate MM prevalence. It can assist clinicians to understand future trends in MM epidemiology, healthcare systems to plan for future resource use allocation, and payers to quantify the budget impact of new treatments. [ABSTRACT FROM AUTHOR]

Simple Summary: Ovarian cancer (OC) is a leading cause of cancer-related death and 85% of women with advanced OC relapse after chemotherapy. First-line (1L) maintenance therapy is given to prolong the benefit of chemotherapy. However, selection of a 1L maintenance therapy is challenging given the number of therapies available and the lack of clinical trials that directly compare these therapies. Indirect treatment comparisons (ITCs) allow the comparison of therapies across trials and may inform selection of the most appropriate treatment option. ITCs must follow statistical principles to ensure similarity among trials and allow for a fair comparison. This study assessed whether two types of ITC could be performed to compare the poly(ADP-ribose) polymerase inhibitor niraparib with other 1L maintenance therapies. The 12 clinical trials assessed differed too significantly to meet recommended criteria for comparison. This study highlights the need for caution when comparing trial data to inform treatment decisions. Selecting a first-line (1L) maintenance option for ovarian cancer is challenging given the variety of therapies, differing trials, and the lack of head-to-head data for angiogenesis and poly(ADP-ribose) polymerase (PARP) inhibitors. Thus, indirect treatment comparisons (ITCs) can aid treatment decision making. This study assessed the feasibility of two ITCs, a network meta-analysis (NMA) and a population-adjusted ITC (PAIC), comparing the efficacy of the PARP inhibitor niraparib in the PRIMA trial (NCT02655016) with other 1L maintenance treatments. A systematic literature review was conducted to identify trials using the Cochrane Handbook for Systematic Reviews of Interventions to assess differences in trial design, population characteristics, treatment arms, and outcome measures. All 12 trials identified were excluded from the NMA due to the absence of a common comparator and differences in survival measures and/or inclusion criteria. The PAIC comparing PRIMA and PAOLA-1 trials was also not feasible due to differences in inclusion criteria, survival measures, and the previous receipt of chemotherapy/bevacizumab. Neither ITC met recommended guidelines for analysis; the results of such comparisons would not be considered appropriate evidence when selecting 1L maintenance options in ovarian cancer. ITCs in this setting should be performed cautiously, as many factors can preclude objective trial comparisons. [ABSTRACT FROM AUTHOR]

Objective To conduct a comprehensive assessment of the case-mix of patients admitted to tuberculosis hospitals and the reasons for their admission in four Russian regions: Ivanovo, Orel, Samara and Valadimir. We also sought to quantify the extent to which efficiency could be improved by reducing hospitalization rates and re-profiling hospital beds available in the tuberculosis-control system. Methods We used a standard questionnaire to determine how beds were being used and who was using the beds in tuberculosis facilities in four Russian regions. Data were collected to determine how 4306 tuberculosis beds were utilized as well as on the socioeconomic and demographic indicators, clinical parameters and reasons for hospitalization for 3352 patients. Findings Of the 3352 patients surveyed about 70% were male; the average age was 40; and rates of unemployment, disability and alcohol misuse were high. About one-third of beds were occupied by sear-positive or culture-positive tuberculosis patients; 20% were occupied by tuberculosis patients who were smear-negative and/or culture-negative; 20% were occupied by patients who no longer had tuberculosis; and 20% were unoccupied. If clinical and public health admissions criteria were applied then < 50% of admissions would be justified and < 50% of the current number of beds would be required. Up to 85% of admissions and beds were deemed to be necessary when social problems and poor access to outpatient care were considered along with clinical and public health admission criteria. Conclusion Much of the Russian Federation's large tuberculosis hospital infrastructure is unnecessary when clinical and public health criteria are used, but the large hospital infrastructure within the tuberculosis-control system has an important social support function. Improving the efficiency of the system will require the reform of health-system norms and regulations as they relate to resource allocation and clinical care and implementation of lower-cost approaches to case management for patients with social problems. Additionally closer attention will need to be paid to the management of staff numbers in the tuberculosis system. [ABSTRACT FROM AUTHOR]

Objectives To validate outcomes of presently available chronic obstructive pulmonary disease (COPD) cost-effectiveness models against results of two large COPD trials—the 3-year TOwards a Revolution in COPD Health (TORCH) trial and the 4-year Understanding Potential Long-term Impacts on Function with Tiotropium (UPLIFT) trial. Methods Participating COPD modeling groups simulated the outcomes for the placebo-treated groups of the TORCH and UPLIFT trials using baseline characteristics of the trial populations as input. Groups then simulated treatment effectiveness by using relative reductions in annual decline in lung function and exacerbation frequency observed in the most intensively treated group compared with placebo as input for the models. Main outcomes were (change in) total/severe exacerbations and mortality. Furthermore, the absolute differences in total exacerbations and quality-adjusted life-years (QALYs) were used to approximate the cost per exacerbation avoided and the cost per QALY gained. Result Of the six participating models, three models reported higher total exacerbation rates than observed in the TORCH trial (1.13/patient-year) (models: 1.22–1.48). Four models reported higher rates than observed in the UPLIFT trial (0.85/patient-year) (models: 1.13–1.52). Two models reported higher mortality rates than in the TORCH trial (15.2%) (models: 20.0% and 30.6%) and the UPLIFT trial (16.3%) (models: 24.8% and 36.0%), whereas one model reported lower rates (9.8% and 12.1%, respectively). Simulation of treatment effectiveness showed that the absolute reduction in total exacerbations, the gain in QALYs, and the cost-effectiveness ratios did not differ from the trials, except for one model. Conclusions Although most of the participating COPD cost-effectiveness models reported higher total exacerbation rates than observed in the trials, estimates of the absolute treatment effect and cost-effectiveness ratios do not seem different from the trials in most models. [ABSTRACT FROM AUTHOR]

Objectives: To assess how suitable current chronic obstructive pulmonary disease (COPD) cost-effectiveness models are to evaluate personalized treatment options for COPD by exploring the type of heterogeneity included in current models and by validating outcomes for subgroups of patients.Methods: A consortium of COPD modeling groups completed three tasks. First, they reported all patient characteristics included in the model and provided the level of detail in which the input parameters were specified. Second, groups simulated disease progression, mortality, quality-adjusted life-years (QALYs), and costs for hypothetical subgroups of patients that differed in terms of sex, age, smoking status, and lung function (forced expiratory volume in 1 second [FEV1] % predicted). Finally, model outcomes for exacerbations and mortality for subgroups of patients were validated against published subgroup results of two large COPD trials.Results: Nine COPD modeling groups participated. Most models included sex (seven), age (nine), smoking status (six), and FEV1% predicted (nine), mainly to specify disease progression and mortality. Trial results showed higher exacerbation rates for women (found in one model), higher mortality rates for men (two models), lower mortality for younger patients (four models), and higher exacerbation and mortality rates in patients with severe COPD (four models).Conclusions: Most currently available COPD cost-effectiveness models are able to evaluate the cost-effectiveness of personalized treatment on the basis of sex, age, smoking, and FEV1% predicted. Treatment in COPD is, however, more likely to be personalized on the basis of clinical parameters. Two models include several clinical patient characteristics and are therefore most suitable to evaluate personalized treatment, although some important clinical parameters are still missing. [ABSTRACT FROM AUTHOR]

To compare different chronic obstructive pulmonary disease (COPD) cost-effectiveness models with respect to structure and input parameters and to cross-validate the models by running the same hypothetical treatment scenarios. Methods COPD modeling groups simulated four hypothetical interventions with their model and compared the results with a reference scenario of no intervention. The four interventions modeled assumed 1) 20% reduction in decline in lung function, 2) 25% reduction in exacerbation frequency, 3) 10% reduction in all-cause mortality, and 4) all these effects combined. The interventions were simulated for a 5-year and lifetime horizon with standardization, if possible, for sex, age, COPD severity, smoking status, exacerbation frequencies, mortality due to other causes, utilities, costs, and discount rates. Furthermore, uncertainty around the outcomes of intervention four was compared. Results Seven out of nine contacted COPD modeling groups agreed to participate. The 5-year incremental cost-effectiveness ratios (ICERs) for the most comprehensive intervention, intervention four, was €17,000/quality-adjusted life-year (QALY) for two models, €25,000 to €28,000/QALY for three models, and €47,000/QALY for the remaining two models. Differences in the ICERs could mainly be explained by differences in input values for disease progression, exacerbation-related mortality, and all-cause mortality, with high input values resulting in low ICERs and vice versa. Lifetime results were mainly affected by the input values for mortality. The probability of intervention four to be cost-effective at a willingness-to-pay value of €50,000/QALY was 90% to 100% for five models and about 70% and 50% for the other two models, respectively. Conclusions Mortality was the most important factor determining the differences in cost-effectiveness outcomes between models. [ABSTRACT FROM AUTHOR]

Objective To facilitate mental health reform in one Russian oblast (region) using systematic approaches to policy design and implementation. Methods The authors undertook a three-year action-research programme across three pilot sites, comprising a multifaceted set of interventions combining situation appraisal to inform planning, sustained policy dialogue at federal and regional levels to catalyse change, introduction of multidisciplinary and intersectoral-working at all levels, skills-based training for professionals, and support for nongovernmental organizations (NGOs) to develop new care models. Findings Training programmes developed in this process have been adopted into routine curricula with measurable changes in staff skills. Approaches to care improved through multidisciplinary and multisectoral service delivery, with an increase in NGO activities, user involvement in care planning and delivery in all pilot sites. Hospital admissions at start and end of the study fell in two pilot sites, while the rate of readmissions in all three pilot sites by 2006 was below that for the region as a whole. Lessons learned have informed the development of regional and federal mental health policies. Conclusion A multifaceted and comprehensive programme can be effective in overcoming organizational barriers to the introduction of evidence-based multisectoral interventions in one Russian region. This can help facilitate significant and sustainable changes in policy and reduce institutionalization. [ABSTRACT FROM AUTHOR]