Development of an Initial Conceptual Model of Multiple Myeloma to Support Clinical and Health Economics Decision Making. Issue 1 (January 2019) - Gonzalez-McQuire, Sebastian; Dimopoulos, Meletios-Athanassios; Weisel, Katja; Bouwmeester, Walter; Hájek, Roman; Campioni, Marco; Bennison, Craig; Xu, Weiwei; Pantiri, Krystallia; Hensen, Marja; Terpos, Evangelos; Knop, Stefan
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.