Risk factors of early disease progression and decreased survival for multiple myeloma patients after upfront autologous stem cell transplantation

多发性骨髓瘤患者接受自体干细胞移植后早期疾病进展和生存期缩短的风险因素

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Abstract

Multiple myeloma (MM) stands as the second most prevalent hematological malignancy, constituting approximately 10% of all hematological malignancies. Current guidelines recommend upfront autologous stem cell transplantation (ASCT) for transplant-eligible MM patients. This study seeks to delineate factors influencing post-ASCT outcomes in MM patients. Our cohort comprised 150 MM patients from Taipei Veterans General Hospital, with progression-free survival (PFS) as the primary endpoint and overall survival (OS) as the secondary endpoint. A Cox proportional hazards model was employed to discern potential predictive factors for survival. ASCT age ≥ 65 (hazard ratio [HR] 1.94, 95% confidence interval [CI] 1.08-3.47) and the presence of extramedullary disease (HR 2.53, 95% CI 1.53-4.19) negatively impacted PFS. Conversely, treatment response ≥ VGPR before ASCT (HR 0.52, 95% CI 0.31-0.87) and total CD34(+) cells collected ≥ 4 × 10(6) cells/kg on the first stem cell harvesting (HR 0.52, 95% CI 0.32-0.87) were positively associated with PFS. For OS, patients with ISS stage III (HR 2.06, 95% CI 1.05-4.04), the presence of extramedullary disease (HR 3.92, 95% CI 2.03-7.58), light chain ratio ≥ 100 before ASCT (HR 7.08, 95% CI 1.45-34.59), post-ASCT cytomegalovirus infection (HR 9.43, 95% CI 3.09-28.84), and a lower conditioning melphalan dose (< 140 mg/m(2); HR 2.75, 95% CI 1.23-6.17) experienced shorter OS. In contrast, post-ASCT day + 15 absolute monocyte counts (D15 AMC) > 500/µl (HR 0.36, 95% CI 0.17-0.79) and post-ASCT day + 15 platelet counts (D15 PLT) > 80,000/µl (HR 0.48, 95% CI 0.24-0.94) were correlated with improved OS. Significantly, early PLT and AMC recovery on day + 15 predicting longer OS represents a novel finding not previously reported. Other factors also align with previous studies. Our study provides real-world insights for post-ASCT outcome prediction beyond clinical trials.

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