Patient perception of burden of disease and treatment preferences in non-small cell lung cancer: Results from a European survey.

OBJECTIVES: To understand European non-small cell lung cancer (NSCLC) patients' perceptions of disease burden, treatment, and future expectations of treatment and care. MATERIALS AND METHODS: A 32-item online survey was conducted on a sample of NSCLC patients across Europe. Descriptive statistics were used to analyse the data. Results were presented by disease stage (I-III vs. IV). RESULTS: NSCLC patients (N = 292) from 10 countries responded. Most patients resided in France, Spain, Italy, Germany and UK, with 16 patients from five other countries. Patients' knowledge of biomarker testing was limited (23% of 376 responses indicated no knowledge). Patients reported fear (stage I-III: 40%, stage IV: 27%), anxiety (stage I-III: 44%, stage IV: 33%) and depression (stage I-III: 24%, stage IV: 20%), but also hope (stage I-III: 57%, stage IV: 59%). Professional status was majorly impacted for 43% of stage I-III patients and 58% stage IV patients. Household finances were impacted for âˆ¼70% of all patients. Oral treatment was preferred (60%), and respondents understood dosing schedules (stage I-III: 82%, stage IV: 97%) remembering to take medications (stage I-III: 82%, stage IV: 87%). Most respondents were willing to take more pills, but some indicated that this would be difficult. CONCLUSION: Approximately half of the patients in this survey were aware of clinical trial options, but most lacked information about their molecular tumor profile, making it difficult for patients to engage in discussions about their care. The results also suggest that NSCLC patients have significant information and support needs, especially in the areas of emotional and financial burden. Action is needed to address these burdens associated with NSCLC. Furthermore, patients should be provided with the information needed to actively participate in treatment decisions.

Healthcare resource utilization and costs among patients with relapsed and/or refractory multiple myeloma treated with proteasome inhibitors in real-world clinical practice in Germany.

AIMS: To assess the real-world healthcare resource utilization (HRU) and costs associated with different proteasome inhibitors (PIs) for the treatment of patients with relapsed and/or refractory multiple myeloma (RRMM) in Germany. METHODS: We conducted a retrospective medical chart review of treatment patterns, outcomes, and HRU for patients with RRMM treated with bortezomib, carfilzomib, or ixazomib in second- or third-line (2L or 3L) therapy in Germany. Data were collected between 1 January 2017 and 30 June 2017. Costs were calculated based on drug prices and unit costs in Germany. RESULTS: Physicians provided data on 302 patients. Mean monthly total direct costs per patient receiving PI-based therapy were €7,925 and €10,693 for 2L and 3L, respectively, of which approximately 90% was anti-myeloma drug costs. Overall, the highest costs were associated with patients receiving 3L therapy. Regardless of treatment line, costs were higher for patients who had received a stem cell transplant (SCT) in a previous treatment line than for those who had not; the data suggest that this reflects the use of triplet regimens following a SCT. Patients with a complete response (CR) experienced no unplanned hospitalizations during the study period, whereas patients with progressive disease experienced the highest number of unplanned and planned hospitalizations. In 2L therapy, the highest proportion of patients with a CR was observed in those receiving carfilzomib (12% carfilzomib; 4% bortezomib; 0% ixazomib). LIMITATIONS: Patients with missing or incomplete follow-up data were included in the study and were accounted for using monthly cost estimates. CONCLUSIONS: Anti-myeloma drugs were the main contributor to total HRU costs associated with RRMM in Germany. Improved treatment response was associated with lower costs and reduced hospitalizations.

Sustainability of Biosimilars in Europe: A Delphi Panel Consensus with Systematic Literature Review.

INTRODUCTION: Biosimilars have the potential to enhance the sustainability of evolving health care systems. A sustainable biosimilars market requires all stakeholders to balance competition and supply chain security. However, there is significant variation in the policies for pricing, procurement, and use of biosimilars in the European Union. A modified Delphi process was conducted to achieve expert consensus on biosimilar market sustainability in Europe. METHODS: The priorities of 11 stakeholders were explored in three stages: a brainstorming stage supported by a systematic literature review (SLR) and key materials identified by the participants; development and review of statements derived during brainstorming; and a facilitated roundtable discussion. RESULTS: Participants argued that a sustainable biosimilar market must deliver tangible and transparent benefits to the health care system, while meeting the needs of all stakeholders. Key drivers of biosimilar market sustainability included: (i) competition is more effective than regulation; (ii) there should be incentives to ensure industry investment in biosimilar development and innovation; (iii) procurement processes must avoid monopolies and minimize market disruption; and (iv) principles for procurement should be defined by all stakeholders. However, findings from the SLR were limited, with significant gaps on the impact of different tender models on supply risks, savings, and sustainability. CONCLUSIONS: A sustainable biosimilar market means that all stakeholders benefit from appropriate and reliable access to biological therapies. Failure to care for biosimilar market sustainability may impoverish biosimilar development and offerings, eventually leading to increased cost for health care systems and patients, with fewer resources for innovation.

Patient Characteristics and Outcomes of Relapsed/Refractory Multiple Myeloma in Patients Treated with Proteasome Inhibitors in Germany.

INTRODUCTION: Real-world data reflects treatments and outcomes in clinical practice in contrast with controlled clinical trials. This study evaluates real-life multiple myeloma (MM) patients receiving proteasome inhibitor (PI)-based treatments in the second or third therapy line in 2017 in Germany. METHODS: This is a retrospective chart review on adult relapsed/refractory MM patients treated with ≥1 dose of a PI-based regimen in either the second or the third line of therapy. Participating physicians had ≥3 years of clinical experience in treating symptomatic MM patients and used PI according to the label. RESULTS: Distinct patient profiles for each PI-based regimen emerged. Younger, fitter, transplant-eligible patients received novel PI triplets such as carfilzomib in combination with lenalidomide and dexamethasone (KRd) or IRd. Patients receiving lenalidomide in first-line therapy mostly received lenalidomide-free regimens in second-line therapy. In high-risk patients, no clear treatment patterns could be ascertained. The complete response rates were highest with KRd (13.0%), followed by carfilzomib in combination with dexamethasone (Kd) (5.7%) and bortezomib (4.8%). The very good partial response rates were highest with IRd (76.9%), followed by KRd (53.7%), Kd (25.7%), and bortezomib (20.5%). None of the KRd- or IRd-treated patients responded below a partial response. DISCUSSION/CONCLUSION: Clear patient profiles for each PI type were observed. In second-line therapy, younger, fitter, transplant-eligible patients received novel-PI-based triplets, e.g., KRd or IRd. Patients treated with lenalidomide in first-line therapy mostly received lenalidomide-sparing regimens in second-line therapy. In high-risk patients no clear treatment patterns could be ascertained due to the limited sample size.

Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: external validation in a retrospective chart review.

OBJECTIVES AND DESIGN: A novel risk stratification algorithm estimating risk of death in patients with relapsed multiple myeloma starting second-line treatment was recently developed using multivariable Cox regression of data from a Czech registry. It uses 16 parameters routinely collected in medical practice to stratify patients into four distinct risk groups in terms of survival expectation. To provide insight into generalisability of the risk stratification algorithm, the study aimed to validate the risk stratification algorithm using real-world data from specifically designed retrospective chart audits from three European countries. PARTICIPANTS AND SETTING: Physicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm. METHODS: The performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke's R2, goodness of fit and the C-index. The risk stratification algorithm's ability to discriminate overall survival across four risk groups was evaluated using Kaplan-Meier curves and HRs. RESULTS: Consistent with the Czech registry, the stratification performance of the risk stratification algorithm demonstrated clear differentiation in risk of death between the four groups. As risk groups increased, risk of death doubled. The C-index was 0.715 (95% CI 0.690 to 0.734). CONCLUSIONS: Validation of the novel risk stratification algorithm in an independent 'real-world' dataset demonstrated that it stratifies patients in four subgroups according to survival expectation.

Management of patients with acute lymphoblastic leukemia in routine clinical practice: Minimal residual disease testing, treatment patterns and clinical outcomes in Belgium, Greece and Switzerland.

OBJECTIVES: To describe real-world management and clinical and economic outcomes of patients with B-cell precursor acute lymphoblastic leukemia (ALL) in Belgium, Greece and Switzerland. METHODS: This descriptive, retrospective medical chart review collected patient-level data in 2018 from adults with ≥1 minimal residual disease (MRD) test during front-line ALL treatment. Data were stratified by MRD status. RESULTS: Eighty-two patients were included (median age 44 years, 23 % Philadelphia chromosome-positive; MRD-positive: n = 17, MRD-negative: n = 50, MRD result unknown: n = 15). HyperCVAD (32 %) and HOVON (26 %) were the most frequently used front-line treatment protocols; 22 % of patients received stem cell transplantation. Overall, 76 % of ALL patients were hospitalized (mean 1.1 hospitalization/month). Complete hematological response (CRh) occurred in 66/82 patients (80 %). Median relapse-free survival from CRh was 32.7 months (MRD-positive: 11.7 months; MRD-negative: 33.3 months). Median overall survival from diagnosis was 28.9 months (MRD-positive: 15.3 months; MRD-negative: not reached). Most patients (88 %) were MRD tested during induction; testing rates considerably decreased thereafter (39 % during consolidation). CONCLUSIONS: B-cell precursor ALL represents a clinical burden and impacts healthcare resources; MRD-positive patients have worse prognosis than MRD-negative patients. Efforts should be made to adhere to recommendations for MRD testing in clinical guidelines.

Development and validation of a novel risk stratification algorithm for relapsed multiple myeloma.

Multiple myeloma (MM) is a malignancy with varying survival outcomes and drivers of disease progression. Existing MM staging tools were developed using data from newly diagnosed patients. As patient characteristics and disease-related factors change between diagnosis and the initiation of second-line (2L) treatment, an unmet need exists for a tool that can evaluate risk of death at first relapse. We have developed a risk stratification algorithm (RSA) using data from patients with MM who were at 2L. Hazard ratios for independent predictors of overall survival (OS) were derived from a Cox models, and individual patient scores were calculated for total risk. K-adaptive partitioning for survival was used to stratify patients into groups based on their scores. Relative risk doubled with ascending risk group; median OSs for patients in group 1 (lowest risk)-4 (highest risk) were 61·6, 29·6, 14·2 and 5·9 months, respectively. Differences in OS between risk groups were significant. Similar stratification was observed when the RSA was applied to an external validation data set. In conclusion, we have developed a validated RSA that can quantify total risk, frailty risk and disease aggressiveness risk, and stratify patients with MM at 2L into groups with profoundly different survival expectations.

Understanding mortality in multiple myeloma: Findings of a European retrospective chart review.

OBJECTIVES: This study aimed to provide real-world data on the characteristics and treatment of patients with multiple myeloma (MM) at the time of death. METHODS: The study was a retrospective patient chart review across France, Germany, Italy, Spain and the UK during 2016, and included patients who had died in the 3 months before the index date. RESULTS: Data from 786 patients were reviewed. At the time of death, 37% of patients were receiving active treatment, 12% were in a treatment-free interval and 51% were receiving only supportive care. Death before and during active first-line treatment was not uncommon (6% and 24% of patients, respectively) but these deaths were often not solely due to disease progression; factors such as renal failure and infection frequently played a role (in 30% and 20% of patients at first-line, respectively). Most deaths at later lines were due to progressive disease. Cox model results suggested that early deaths were associated with advanced disease stage, high-risk cytogenetics and poor response and relapse profiles. CONCLUSIONS: These real-world data could be used to help develop strategies for improving survival in patients with MM and to support management tailored to the stage of disease.

Development of an Initial Conceptual Model of Multiple Myeloma to Support Clinical and Health Economics Decision Making.

Background. We aimed to develop and validate a conceptual model of multiple myeloma (MM) that characterizes the attributes affecting disease progression and patient outcomes, and the relationships between them. Methods. Systematic and targeted literature reviews identified disease- and patient-specific attributes of MM that affect disease progression and outcomes. These attributes were validated by a Delphi panel of four international MM experts, and a physician-validated model was constructed. Real-world clinical data from the Czech Registry of Monoclonal Gammopathies (RMG) was used to confirm the relationships between attributes using pairwise correlations and multiple Cox regression analysis. Results. The Delphi panel reached consensus that most cytogenetic abnormalities influenced disease activity, which results in symptoms and complications and affects overall survival (OS). Comorbidities and complications also affect OS. The entire panel agreed that quality of life was influenced by comorbidities, age, complications, and symptoms. Consensus was not reached in some cases, in particular, the influence of del(17p) on complications. The relationships between attributes were confirmed using pairwise analysis of real-world data from the Czech RMG; most of the correlations identified were statistically significant and the strength of the correlations changed with successive relapses. Czech RMG data were also used to confirm significant predictors of OS included in the model, such as age, Eastern Cooperative Oncology Group performance status, and extramedullary disease. Conclusions. This validated conceptual model can be used for economic modeling and clinical decision making. It could also inform the development of disease-based models to explore the impact of disease progression and treatment on outcomes in patients with MM.

Methodology of a Novel Risk Stratification Algorithm for Patients with Multiple Myeloma in the Relapsed Setting.

INTRODUCTION: Risk stratification tools provide valuable information to inform treatment decisions. Existing algorithms for patients with multiple myeloma (MM) were based on patients with newly diagnosed disease, and these have not been validated in the relapsed setting or in routine clinical practice. We developed a risk stratification algorithm (RSA) for patients with MM at initiation of second-line (2L) treatment, based on data from the Czech Registry of Monoclonal Gammopathies. METHODS: Predictors of overall survival (OS) at 2L treatment were identified using Cox proportional hazards models and backward selection. Risk scores were obtained by multiplying the hazard ratios for each predictor. The K-adaptive partitioning for survival (KAPS) algorithm defined four groups of stratification based on individual risk scores. RESULTS: Performance of the RSA was assessed using Nagelkerke's R2 test and Harrell's concordance index through Kaplan-Meier analysis of OS data. Prognostic groups were successfully defined based on real-world data. Use of a multiplicative score based on Cox modeling and KAPS to define cut-off values was effective. CONCLUSION: Through innovative methods of risk assessment and collaboration between physicians and statisticians, the RSA was capable of stratifying patients at 2L treatment by survival expectations. This approach can be used to develop clinical decision-making tools in other disease areas to improve patient management. FUNDING: Amgen Europe GmbH.

Health-Related Quality of Life of Patients With Multiple Myeloma Treated in Routine Clinical Practice in France.

INTRODUCTION: New therapies for multiple myeloma (MM) have improved life expectancy, but health-related quality of life (HRQoL) data from patients with MM in the real-world setting are lacking. This study, conducted in France, explored the associations between treatment outcomes and HRQoL in patients with MM. PATIENTS AND METHODS: This observational, cross-sectional, multicenter study enrolled patients (≥ 18 years old) with symptomatic MM who had consulted a physician at least once between February and March 2016. HRQoL was assessed using the European Organization for Research and Treatment of Cancer (EORTC) Core Quality of Life questionnaire (QLQ-C30) and the Quality of Life Multiple Myeloma module (QLQ-MY20). RESULTS: In total, 445 patients were included in the study; 402 (90%) completed the EORTC QLQ-C30 and QLQ-MY20 questionnaires. HRQoL decreased significantly with treatment line. Patients in the first treatment-free interval had relatively high scores. At later lines, patients receiving active treatment had better scores than those whose treatment had ended. High EORTC QLQ-C30 global health status scores were associated with good treatment response, few adverse events, and long duration of treatment, and were strongly influenced by the Eastern Cooperative Oncology Group performance status. Global health status scores correlated well with the 4 items of the QLQ-MY20 (future perspective, 0.46; body image, 0.41; disease symptoms, -0.57; side effects of treatment, -0.53). CONCLUSION: Effective treatment options in MM can help maintain HRQoL by influencing treatment response levels and delaying disease progression.

Real-world Outcomes of Multiple Myeloma: Retrospective Analysis of the Czech Registry of Monoclonal Gammopathies.

INTRODUCTION: Real-world data on patient outcomes and treatment patterns in multiple myeloma (MM) are limited. MATERIALS AND METHODS: The present noninterventional, observational, retrospective analysis of prospectively collected Czech patient medical record data from the Registry of Monoclonal Gammopathies estimated real-world outcomes in adults with a diagnosis of symptomatic MM made between May 2007 and June 2014. RESULTS: In total, 2446 patients had initiated first-line treatment. The median overall survival since the diagnosis (primary endpoint) was 50.3 months (95% confidence interval, 46.1-54.5 months) and decreased with each successive treatment line. A similar trend was observed for progression-free survival and the depth of response. In line with European guidelines and clinical practice, bortezomib-, thalidomide-, and lenalidomide-based regimens were most commonly used across all treatment lines (42.3%, 28.9%, and 18.4%, respectively). In the first line, bortezomib and thalidomide were used most often, with lenalidomide the most commonly used agent in the relapse setting (second to fourth lines). Exploratory analyses revealed that younger age (≤ 65 years), lower international staging system stage, and previous stem cell transplantation were associated with significant improvements in overall and progression-free survival, especially in the early treatment lines. CONCLUSION: The present study is the first analysis of Czech data from the Registry of Monoclonal Gammopathies, and it provides important insights into the real-world management of MM for physicians and healthcare providers.

The start of a new wave: Developments in proteasome inhibition in multiple myeloma.

Multiple myeloma (MM) accounts for 10% of hematological cancers. Stem cell transplantation remains the cornerstone of first-line treatment for eligible patients, but historically, pharmaceutical treatment options for MM have been limited. The proteasome was identified as a target for MM therapy in the early 2000s and, in 2004, the boronic acid proteasome inhibitor bortezomib gained European approval. Bortezomib now plays a major role in MM treatment, but the duration of its use can be limited by toxicities such as peripheral neuropathy and the development of resistance. A new generation of proteasome inhibitors has since entered the treatment landscape: carfilzomib, an epoxyketone-based agent with a distinct mode of action, high clinical efficacy, and lower levels of peripheral neuropathy compared with bortezomib, received approval in 2015 for use in patients with relapsed and/or refractory MM (RRMM). Ixazomib, a second-generation, orally administered, boronic acid proteasome inhibitor, has also been approved for use in patients with RRMM. In just over a decade, proteasome inhibitor-based regimens have become an integral component of MM treatment; with more proteasome inhibitors in development, this remains a vibrant research area with potential to improve the lives of patients with MM in the years to come.

Long-term Outcomes in Patients With Multiple Myeloma: A Retrospective Analysis of the Dutch Population-based HAematological Registry for Observational Studies (PHAROS).

Registry data are important for monitoring the impact of new therapies on treatment algorithms and outcomes, and for guiding clinical decision making in multiple myeloma (MM). This observational study analyzed real-world data from patients in the Population-based HAematological Registry for Observational Studies who were treated for symptomatic MM from 2008 to 2013 in the Netherlands. The primary endpoint was overall survival (OS) from initiation of first-line treatment. Secondary endpoints included OS and progression-free survival per treatment line, treatment patterns, and treatment response. Between 2008 and 2013, 917, 583, 283, and 139 patients had initiated first, second, third, and fourth treatment lines, respectively. Thalidomide-based regimens were the most frequently used first-line treatment (66%); bortezomib- and lenalidomide-based regimens were most often used in the second line (41% and 27%, respectively). The median OS (95% confidence interval) ranged from 37.5 months (34.8-41.8 months) in the first line to 9.2 months (6.2-12.3 months) in the fourth line. Univariate analyses showed that survival benefits were most apparent in younger patients (≤65 vs >65 years). These analyses provide important real-world information on treatment patterns and outcomes in patients with MM.

Healthcare resource utilization among patients with relapsed multiple myeloma in the UK, France, and Italy.

AIMS: To assess the real-world healthcare resource utilization (HRU) and costs associated with different treatment regimens used in the management of patients with relapsed multiple myeloma in the UK, France, and Italy. METHODS: Retrospective medical chart review of characteristics, time to progression, level of response, HRU during treatment, and adverse events (AEs). Data collection started on June 1, 2015 and was completed on July 15, 2015. In the 3 months before record abstraction, eligible patients had either disease progression after receiving one of their country's most commonly prescribed regimens or had received the best supportive care and died. Costs were calculated based on HRU and country-specific diagnosis-related group and/or unit reference costs, amongst other standard resources. RESULTS: Physicians provided data for 1,282 patients (387 in the UK, 502 in France, 393 in Italy) who met the inclusion criteria. Mean [median] total healthcare costs associated with a single line of treatment were €51,717 [35,951] in the UK, €37,009 [32,538] for France, and €34,496 [42,342] for Italy, driven largely by anti-myeloma medications costs (contributing 95.0%, 90.0%, and 94.2% of total cost, respectively). During active treatment, the highest costs were associated with lenalidomide- and pomalidomide-based regimens. Mean cost per month was lowest for patients achieving a very good partial response or better. Unscheduled events (i.e. not considered part of routine management, whether or not related to multiple myeloma, such as unscheduled hospitalization, AEs, fractures) accounted for 1-9% of total costs and were highest for bendamustine. LIMITATIONS: The use of retrospective data means that clinical practice (e.g. use of medical procedures, evaluation of treatment response) is not standardized across participating countries/centers, and some data (e.g. low-grade AEs) may be incomplete or differently adjudicated/reported. The centers involved may not be fully representative of national practice. CONCLUSIONS: Drug costs are the main contributor to total HRU costs associated with multiple myeloma. The duration of active treatment may influence the average total costs, as well as response, associated with a single line of therapy. Improved treatment outcomes, and reductions in unscheduled events and concomitant medication use may, therefore, reduce the overall HRU and related costs of care in multiple myeloma.

Statistical Modeling of Disease Progression for Chronic Obstructive Pulmonary Disease Using Data from the ECLIPSE Study.

BACKGROUND: To develop statistical models predicting disease progression and outcomes in chronic obstructive pulmonary disease (COPD), using data from ECLIPSE, a large, observational study of current and former smokers with COPD. METHODS: Based on a conceptual model of COPD disease progression and data from 2164 patients, associations were made between baseline characteristics, COPD disease progression attributes (exacerbations, lung function, exercise capacity, and symptoms), health-related quality of life (HRQoL), and survival. Linear and nonlinear functional forms of random intercept models were used to characterize these relationships. Endogeneity was addressed by time-lagging variables in the regression models. RESULTS: At the 5% significance level, an exacerbation history in the year before baseline was associated with increased risk of future exacerbations (moderate: +125.8%; severe: +89.2%) and decline in lung function (forced expiratory volume in 1 second [FEV1]) (-94.20 mL per year). Each 1% increase in FEV1 % predicted was associated with decreased risk of exacerbations (moderate: -1.1%; severe: -3.0%) and increased 6-minute walk test distance (6MWD) (+1.5 m). Increases in baseline exercise capacity (6MWD, per meter) were associated with slightly increased risk of moderate exacerbations (+0.04%) and increased FEV1 (+0.62 mL). Symptoms (dyspnea, cough, and/or sputum) were associated with an increased risk of moderate exacerbations (+13.4% to +31.1%), and baseline dyspnea (modified Medical Research Council score ≥2 v. <2) was associated with lower FEV1 (-112.3 mL). CONCLUSIONS: A series of linked statistical regression equations have been developed to express associations between indicators of COPD disease severity and HRQoL and survival. These can be used to represent disease progression, for example, in new economic models of COPD.

Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model.

BACKGROUND: The recent joint International Society for Pharmacoeconomics and Outcomes Research / Society for Medical Decision Making Modeling Good Research Practices Task Force emphasized the importance of conceptualizing and validating models. We report a new model of chronic obstructive pulmonary disease (COPD) (part of the Galaxy project) founded on a conceptual model, implemented using a novel linked-equation approach, and internally validated. METHODS: An expert panel developed a conceptual model including causal relationships between disease attributes, progression, and final outcomes. Risk equations describing these relationships were estimated using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study, with costs estimated from the TOwards a Revolution in COPD Health (TORCH) study. Implementation as a linked-equation model enabled direct estimation of health service costs and quality-adjusted life years (QALYs) for COPD patients over their lifetimes. Internal validation compared 3 years of predicted cohort experience with ECLIPSE results. RESULTS: At 3 years, the Galaxy COPD model predictions of annual exacerbation rate and annual decline in forced expiratory volume in 1 second fell within the ECLIPSE data confidence limits, although 3-year overall survival was outside the observed confidence limits. Projections of the risk equations over time permitted extrapolation to patient lifetimes. Averaging the predicted cost/QALY outcomes for the different patients within the ECLIPSE cohort gives an estimated lifetime cost of £25,214 (undiscounted)/£20,318 (discounted) and lifetime QALYs of 6.45 (undiscounted/5.24 [discounted]) per ECLIPSE patient. CONCLUSIONS: A new form of model for COPD was conceptualized, implemented, and internally validated, based on a series of linked equations using epidemiological data (ECLIPSE) and cost data (TORCH). This Galaxy model predicts COPD outcomes from treatment effects on disease attributes such as lung function, exacerbations, symptoms, or exercise capacity; further external validation is required.

Development of a Conceptual Model of Disease Progression for Use in Economic Modeling of Chronic Obstructive Pulmonary Disease.

BACKGROUND: To develop and validate a new conceptual model (CM) of chronic obstructive pulmonary disease (COPD) for use in disease progression and economic modeling. The CM identifies and describes qualitative associations between disease attributes, progression and outcomes. METHODS: A literature review was performed to identify any published CMs or literature reporting the impact and association of COPD disease attributes with outcomes. After critical analysis of the literature, a Steering Group of experts from the disciplines of health economics, epidemiology and clinical medicine was convened to develop a draft CM, which was refined using a Delphi process. The refined CM was validated by testing for associations between attributes using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). RESULTS: Disease progression attributes included in the final CM were history and occurrence of exacerbations, lung function, exercise capacity, signs and symptoms (cough, sputum, dyspnea), cardiovascular disease comorbidities, 'other' comorbidities (including depression), body composition (body mass index), fibrinogen as a biomarker, smoking and demographic characteristics (age, gender). Mortality and health-related quality of life were determined to be the most relevant final outcome measures for this model, intended to be the foundation of an economic model of COPD. CONCLUSION: The CM is being used as the foundation for developing a new COPD model of disease progression and to provide a framework for the analysis of patient-level data. The CM is available as a reference for the implementation of further disease progression and economic models.

Multiple myeloma: patient outcomes in real-world practice.

With increasing number of therapies available for the treatment of multiple myeloma, it is timely to examine the course of patients' journeys. We investigated patient characteristics, treatment durations and outcomes, and symptom burden across the treatment pathway in Belgium, France, Germany, Italy, Spain, Switzerland and the UK. In total, 435 physicians retrospectively reviewed 4997 patient charts. Profiles of patients diagnosed with multiple myeloma during the last 12 months were similar across countries; bone pain was the most common presentation. Median duration of first-line therapy was 6 months, followed by a median treatment-free interval of 10 months; both these decreased with increasing lines of therapy, as did time to progression. Depth of response, as assessed by the treating physician, also decreased with each additional line of therapy: 74% of patients achieved at least a very good partial response at first line, compared with only 11% at fifth line. Deeper responses were associated with longer time to progression, although these were physician-judged. Toxicities and co-morbidities increased with later treatment lines, and were more likely to have led to discontinuation of treatment. These real-world data provide an insight into patient outcomes and treatment decisions being made in clinical practice.