Citations 2
Enhanced Risk Stratification of Smoldering Multiple Myeloma with Dynamic Biomarkers: A Multinational, Multicenter Study including 2,270 Participants (PANGEA 2.0)
Chabrun, Floris , Schwartz, Daniel L. , Gentile, Susanna, Elias, K. , Gupta, Tulika , Perry, Jacqueline , Santos, David M. Cordas dos , Hielscher, Thomas , Werly, Annika, Schmidt, Sophia, Liacos, Christine‐Ivy , Kanellias, Nikolaos , Gisbert, Noelia Collado, Chavda, Selina J , Ainley, Louise , Magistris, Claudio De, Pettine, Loredana , Timonian, Michael , Tobia, Catherine, Phan, Sally, Lamb, Jennifer, Silverio, Maria-Theresa, O’Donnell, Elizabeth , Mateos, María‐Victoria , Kumar, Shaji , Kastritis, Efstathis, Trippa, Lorenzo , Mai, Elias K , Santos, David Cordas Dos , Timonian, Michael , Alberge, Jean-Baptiste , Bolli, Niccolo' , Yong, Kwee , Kortüm, Martin , Einsele, Hermann , Mateos, María-Victoria , Kumar, Shaji K , San-Miguel, Jesus , Paiva, Bruno , Dimopoulos, Meletios A , Raab, Marc S , Ghobrial, Irene M , Schwartz, Daniel S. , Gentile, Susanna , Gupta, Tulika R. , Perry, Jacqueline, Schmidt, Sophia K., Theodorakakou, Foteini , Fotiou, Despina , Liacos, Christine Ivy, Martín‐Sánchez, Esperanza , Termini, Rosalinda , Waldschmidt, Johannes M , Ainley, Louise, Vià, Matteo Da , Alberge, Jean-Baptiste , Patel, Vidhi, Costello, Patrick , Tobia, Catherine, Phan, Sally, Lamb, Jennifer, Silverio, Maria-Theresa, Davis, Maya, Marinac, Catherine R. , Nadeem, Omar , Bolli, Niccolò , Yong, Kwee , Kortüm, K. Martin , Miguel, Jesús F. San , Paiva, Bruno , Kastritis, Efstathios , Dimopoulos, Meletios Α. , Raab, Marc S. , Ghobrial, Irene M.
No container title available | June 3, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69–0.84), even without biomarker history (C-statistics=0.69–0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).
Clinical features associated with COVID-19 outcome in multiple myeloma: first results from the International Myeloma Society data set
Chari, Ajai , Samur, Mehmet , Martínez‐López, Joaquín , Cook, Gordon , Biran, Noa , Yong, Kwee , Hungria, Vânia , Engelhardt, Monika , Feria, Ana García, Oliva, Stefania , Gozzetti, Alessandro , Rosenbaum, Cara A. , Kumar, Shaji , Stadtmauer, Edward A. , Beksaç, Meral , Mateos, María‐Victoria , Moreau, Philippe , Miguel, Jesús F. San , Munshi, Nikhil C. , Martinez-Lopez, Joaquin , Martinez-Lopez, Joaquin , Moreau, Philippe , Chari, Ajai , San-Miguel, Jesus , Hungria, Vania , Martinez-Lopez, Joaquin , Gozzetti, Alessandro , Beksac, Meral , Cook, Gordon , Oliva, Stefania , Yong, Kwee , Samur, Mehmet K , Gay, Francesca , Oostvogels, Rimke , Einsele, Hermann , Weisel, Katja C , Anderson, Kenneth C. , Avet‐Loiseau, Hervé
Blood | November 6, 2020 | Volume: 136 | Issue: 26 | Pages: 3033-3040
Abstract The primary cause of morbidity and mortality in patients with multiple myeloma (MM) is an infection. Therefore, there is great concern about susceptibility to the outcome of COVID-19–infected patients with MM. This retrospective study describes the baseline characteristics and outcome data of COVID-19 infection in 650 patients with plasma cell disorders, collected by the International Myeloma Society to understand the initial challenges faced by myeloma patients during the COVID-19 pandemic. Analyses were performed for hospitalized MM patients. Among hospitalized patients, the median age was 69 years, and nearly all patients (96%) had MM. Approximately 36% were recently diagnosed (2019-2020), and 54% of patients were receiving first-line therapy. Thirty-three percent of patients have died, with significant geographic variability, ranging from 27% to 57% of hospitalized patients. Univariate analysis identified age, International Staging System stage 3 (ISS3), high-risk disease, renal disease, suboptimal myeloma control (active or progressive disease), and 1 or more comorbidities as risk factors for higher rates of death. Neither history of transplant, including within a year of COVID-19 diagnosis, nor other anti-MM treatments were associated with outcomes. Multivariate analysis found that only age, high-risk MM, renal disease, and suboptimal MM control remained independent predictors of adverse outcome with COVID-19 infection. The management of MM in the era of COVID-19 requires careful consideration of patient- and disease-related factors to decrease the risk of acquiring COVID-19 infection, while not compromising disease control through appropriate MM treatment. This study provides initial data to develop recommendations for the management of MM patients with COVID-19 infection.