Immune marker changes and risk of multiple myeloma: a nested case-control study using repeated pre-diagnostic blood samples.

Biomarkers reliably predicting progression to multiple myeloma (MM) are lacking. Myeloma risk has been associated with low blood levels of monocyte chemotactic protein-3 (MCP-3), macrophage inflammatory protein-1 alpha (MIP-1α), vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), fractalkine, and transforming growth factor-alpha (TGF-α). In this study, we aimed to replicate these findings and study the individual dynamics of each marker in a prospective longitudinal cohort, thereby examining their potential as markers of myeloma progression. For this purpose, we identified 65 myeloma cases and 65 matched cancer-free controls each with two donated blood samples within the Northern Sweden Health and Disease Study. The first and repeated samples from myeloma cases were donated at a median 13 and 4 years, respectively, before the myeloma was diagnosed. Known risk factors for progression were determined by protein-, and immunofixation electrophoresis, and free light chain assays. We observed lower levels of MCP-3, VEGF, FGF-2, and TGF-α in myeloma patients than in controls, consistent with previous data. We also observed that these markers decreased among future myeloma patients while remaining stable in controls. Decreasing trajectories were noted for TGF-α (P=2.5 × 10-4) indicating progression to MM. Investigating this, we found that low levels of TGF-α assessed at the time of the repeated sample were independently associated with risk of progression in a multivariable model (hazard ratio = 3.5; P=0.003). TGF-α can potentially improve early detection of MM.

Regional differences in treatment and outcome for myeloma patients in Sweden: A population based Swedish myeloma register study.

BACKGROUND: We wanted to evaluate if health care for multiple myeloma (MM) patients is equal in different regions of Sweden. AIM: To study differences in survival for MM depending on health care region and early use of modern treatment. METHODS AND RESULTS: Data from the Swedish Myeloma Register from patients diagnosed between 2008 and 2017 was used. Cohorts were defined by the six healthcare regions (labeled A-F) in Sweden and modern initial treatment was defined as including certain drug combinations. To adjust for time to treatment bias, survival analyses were performed also for patients alive 6 months after diagnosis. In all treated MM patients (n = 5326), we observed a superior overall survival (OS) for region A compared to all other regions (p < .01 for all respectively). After adjusting for time to treatment there was also a superior survival in the region with highest use of modern initial treatment (region A) compared to the regions defined in the study as having intermediate and low use (p < .01 for both). In patients receiving autologous stem cell transplantation (ASCT) a superior survival was observed for region A compared to all regions besides region B. Similar results were seen when adjusting for a time to treatment bias. In patients not receiving ASCT, 75 years or older and adjusted for time to treatment bias, a difference was noted only between region A and E (log rank p = .04, HR 1.2, CI 1.00-1.44, p = .06). In multivariate analyses including age, international staging system stage and time period of diagnosis, differences in survival remained for patients receiving ASCT between region A versus C, D, E and F (p = .01, p < .01, p < .01, p = .03). CONCLUSION: We observed a superior survival in region A for patients receiving ASCT. Explanations may be higher usage of modern initial treatment or regional residual confounding. For patients not receiving ASCT, 75 years or older, differences in survival could be adjusted for.