ArticleJournal of inflammation research2023
Changes in Laboratory Indexes for Multiple Myeloma Patients Before and After Autologous Stem Cell Transplant.
Article in Journal of inflammation research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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6 authors at 2 institutions in 1 country.
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Abstract
Purpose: Outcomes after autologous stem cell transplantation (ASCT) are quite variable and difficult to predict. Second-generation flow, second-generation sequencing, and other tests are invasive and expensive for patients. In this study, we aimed to analyze laboratory data before and after transplantation to look for laboratory indicators that could predict disease progression in patients with newly diagnosed multiple myeloma (NDMM) patients underwent ASCT. Patients and Methods: Standard complete blood count (CBC) parameters, clinical biochemical, and immunological indicators on day -5 and day 90 after ASCT were obtained. Receiver-operating characteristic (ROC) curve was used to determine the cutoff values, we evaluated the predictive abilities of laboratory parameters for progression-free survival (PFS). Univariate and multivariate analyses were performed to evaluate the prognostic significance of variables associated with the PFS of 166 NDMM who underwent ASCT. Results: At day-5, a low absolute monocyte count (AMC, p=0.001), systemic inflammation response index<1.56 (SIRI, P=0.03), serum calcium (p=0.02), and albumin (p=0.006) can predict for superior PFS. At Day +90, a high absolute neutrophil count (ANC, p = 0.008) and lymphocyte-to-monocyte ratio (LMR, p = 0.02), a low neutrophil-to-lymphocyte ratio (NLR, p =0.02) and SIRI<0.41 (p=0.02) predicted for superior PFS. Conclusion: There are inflammation-related indicators derived from peripheral blood cell count (WBCC) - ANC, NLR, SIRI, and LMR - which can serve as potential biomarkers for predicting PFS of NDMM patients underwent ASCT.
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