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Circulating plasma cells as a predictive biomarker in Multiple myeloma: an updated systematic review and meta-analysis

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  • معلومة اضافية
    • بيانات النشر:
      Taylor & Francis Group, 2024.
    • الموضوع:
      2024
    • Collection:
      LCC:Medicine
    • نبذة مختصرة :
      AbstractBackground Circulating plasma cells (CPCs) are defined by the presence of peripheral blood clonal plasma cells, which would contribute to the progression and dissemination of multiple myeloma (MM). An increasing number of studies have demonstrated the predictive potential of CPCs in the past few years. Therefore, there is a growing need for an updated meta-analysis to identify the specific relationship between CPCs and the prognosis of MM based on the current research status.Methods The PubMed, Embase, and Cochrane Library databases were screened to determine eligible studies from inception to November 5, 2023. Publications that reported the prognostic value of CPCs in MM patients were included. Hazard ratios (HRs) with 95% confidence intervals (CIs) of overall survival (OS) and progression-free survival (PFS) were extracted to pool the results. Subgroup analyses were performed based on region, sample size, cut-off value, detection time, initial treatment, and data type. The association between CPCs level and clinicopathological characteristics, including the International Staging System (ISS), Revised-ISS (R-ISS), and cytogenetic abnormalities were also evaluated. Statistical analyses were conducted using STATA 17.0 software.Results Twenty-two studies with a total of 5637 myeloma patients were enrolled in the current meta-analysis. The results indicated that myeloma patients with elevated CPCs were expected to have a poor OS (HR = 2.19, 95% CI: 1.81–2.66, p
    • File Description:
      electronic resource
    • ISSN:
      07853890
      1365-2060
      0785-3890
    • Relation:
      https://doaj.org/toc/0785-3890; https://doaj.org/toc/1365-2060
    • الرقم المعرف:
      10.1080/07853890.2024.2338604
    • الرقم المعرف:
      edsdoj.9bbf4624838a424981c7341f182b93c8