ArticleCancer medicine2023
Prognostic nomogram for multiple myeloma early relapse after autologous stem cell transplant in the novel agent era.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Real-world clinical outcomes of autologous stem cell transplantation in Chinese patients with newly diagnosed multiple myeloma: a systematic literature review.Therapeutic advances in hematology · 2026Review
- Impact of residual clonal plasma cells in S-phase at the time of autologous stem cell transplantation on clinical outcomes.Blood cancer journal · 2025Article
- Application of radiomics model based on FDG-PET/CT for the assessment of therapeutic effect in patients with newly-diagnosed multiple myeloma.Frontiers in oncology · 2025Article
- Construction and validation of nomogram prediction model for anxiety and depression in chemotherapy patients with multiple myeloma.Frontiers in psychiatry · 2025Article
- Prognostic nomogram for multiple myeloma early relapse after autologous stem cell transplant in the novel agent era.Cancer medicine · 2023Article
- Definers and drivers of functional high-risk multiple myeloma: insights from genomic, transcriptomic, and immune profiling.Frontiers in oncology · 2023Review
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Authors and funding
14 authors at 4 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe present study intended to establish a predictive nomogram for early relapse (ER) (<12 months) after autologous stem cell transplantation (ASCT) in the novel drug era for multiple myeloma (MM). PATIENTS AND
methodsThe nomogram was designed and constructed to a retrospective clinical data of newly diagnosed MM patients received novel agent induction therapy and subsequent ASCT at three centers in China from July 2007 to December 2018. The retrospective study was conducted among 294 patients in the training cohort and 126 in the validation cohort. The nomogram's predictive accuracy was evaluated by the concordance index, calibration curve and decision clinical curve.
resultsThe study cohort included 420 newly diagnosed MM patients, and 100 (23.8%) were identified as having ER, including 74 in the training cohort and 26 in the validation cohort. According to the result of multivariate regression in the training cohort, the prognostic variables included in the nomogram were high-risk cytogenetics, LDH > UNL, and response less than very good partial response (VGPR) after ASCT. The calibration curve showed good fitness between the nomogram predictions and the actual observations and the nomogram was further validated by a clinical decision curve. The nomogram's C-index achieved 0.75 (95% CI, 0.70-0.80), which was higher than that of the Revised International Staging System (R-ISS) (0.62), ISS (0.59), and Durie-Salmon (DS) staging system (0.52). The discrimination ability of the nomogram in the validation cohort was superior to that of the other staging systems (C-index: 0.73 vs. R-ISS (0.54), ISS (0.55), and DS staging system (0.53)). DCA showed the prediction nomogram adds much more clinical utility. Different scores of the nomogram draw a distinction of OS.
conclusionThe present nomogram could serve as a feasible and accurate prediction of ER in novel drug induction transplantation-eligible MM patients, which could help modify the post-ASCT strategy for patients at high risk of ER.
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