ArticleDiscover oncology2026
A nutritional index model for predicting resistance and prognosis in multiple myeloma following autologous stem cell transplantation.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Pre-Transplant Endothelial Activation and Stress Index (EASIX) and Albumin-Modified mEASIX (mEASIX_alb) Predict Survival in Multiple Myeloma Patients Undergoing Autologous Stem Cell Transplantation.Medicina (Kaunas, Lithuania) · 2026Article
- The Current Role of Physiotherapy in Systemic Light-Chain (AL) Amyloidosis and Multiple Myeloma.Life (Basel, Switzerland) · 2026Review
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4 authors.
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Abstract
backgroundMultiple myeloma is one of the most common haematological malignancies worldwide and poses a serious threat to the life and health of the population. In recent years, more and more researchers have incorporated the prognostic nutritional index (PNI) into the prognostic studies of tumours and evaluated the nutritional status and predicted the long-term prognosis of patients by PNI.
methodsThe medical records of 245 patients with multiple myeloma who received autologous hematopoietic stem cell transplantation in our hospital from February 2011 to July 2018 were retrospectively analyzed. The optimal cut-off value was obtained by drawing the ROC curve, and the influencing factors of low PNI value and its impact on the prognosis of multiple myeloma patients were obtained. Besides, the influencing factors of prognosis of multiple myeloma treated by autologous hematopoietic stem cell transplantation were analyzed, and the nematic model was constructed and verified.
resultsROC curve showed that the best cut-off value of PNI in predicting the survival outcome of multiple myeloma autologous hematopoietic stem cell transplantation patients was 46.1. The 3-year survival rate of patients treated with autologous hematopoietic stem cell transplantation for multiple myeloma was 1.0% in the low PNI group and 11.6% in the high PNI group. Multivariate Cox regression model analysis showed that lactate dehydrogenase, PNI, disease status before transplantation, bone marrow invasion, and diabetes mellitus were independent factors influencing the prognosis of patients with multiple myeloma treated by autologous hematopoietic stem cell transplantation.
conclusionPNI has an important predictive value for the prognosis of patients treated with autologous haematopoietic stem cell transplantation for multiple myeloma, and the column chart constructed based on it is beneficial to the clinical prognosis of patients treated with autologous haematopoietic stem cell transplantation.
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