ArticleBioMed research international2019
Prognostic Nomogram for the Overall Survival of Patients with Newly Diagnosed Multiple Myeloma.
Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- A nomogram for predicting subsequent liver metastasis in patients with metastatic breast cancer.Frontiers in oncology · 2025Article
- Correlation between initial alkaline phosphatase levels and overall survival in newly diagnosed multiple myeloma patients.Translational cancer research · 2024Article
- Which factors are associated with adverse prognosis in multiple myeloma patients after surgery? - preliminary establishment and validation of the nomogram.World journal of surgical oncology · 2024Article
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- Calculated haemorheological profile and laboratory parameters in new diagnosed multiple myeloma patients: retrospective analysis according to survival.Therapeutic advances in hematology · 2024Article
- ML-based sequential analysis to assist selection between VMP and RD for newly diagnosed multiple myeloma.NPJ precision oncology · 2023Article
- Heterogeneity in long-term outcomes for patients with Revised International Staging System stage II, newly diagnosed multiple myeloma.Haematologica · 2023Article
- Comparison of clinical characteristics, treatment efficacy and survival in patients with newly diagnosed multiple myeloma with single- versus multi-site extramedullary invasion.Journal of cancer research and clinical oncology · 2023Article
- Integration of clinical features and sociodemographic factors: a simplified prognostic model for patients with multiple myeloma based on a double-center retrospective analysis.American journal of cancer research · 2023Article
- Autophagy-related genes affect the survival of multiple myeloma patients depending on chromosomal abnormality.Asian biomedicine : research, reviews and news · 2022Article
- Application of clinical nomograms to predicting overall survival and event-free survival in multiple myeloma patients: Visualization tools for prognostic stratification.Frontiers in public health · 2022Article
- Development and Comparison of Predictive Models Based on Different Types of Influencing Factors to Select the Best One for the Prediction of OSAHS Prevalence.Frontiers in psychiatry · 2022Article
- The Development of Predictive Nomogram of Recurrence for Patients With Endometrioma After Cystectomy Who Were Younger Than 45 Years Old and Received Postoperative Therapy.Frontiers in medicine · 2022Article
- Analysis of Serum IgG1 to Predict Progression and Therapeutic Effect in Patients with Multiple Myeloma.Journal of oncology · 2022Article
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- Nomogram Model for Dynamic and Individual Prediction of Cardiac Response and Survival for Light Chain Amyloidosis in 737 Patients With Cardiac Involvement.Frontiers in oncology · 2021Article
- Circulating Plasma Cells as a Biomarker to Predict Newly Diagnosed Multiple Myeloma Prognosis: Developing Nomogram Prognostic Models.Frontiers in oncology · 2021Article
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To establish a nomogram for predicting the overall survival (OS) of patients with newly diagnosed multiple myeloma (MM), 304 patients with newly diagnosed MM were recruited between June 1, 2010, and June 30, 2015, from the Beijing Chaoyang Hospital, Capital Medical University, and randomly divided into training (n=214) and validation (n=90) cohorts. The Kaplan-Meier method and the Cox proportional hazards regression model were used to evaluate the prognostic effects of multiple clinical and laboratory parameters on survival. Significant prognostic factors were combined to build a nomogram. The discriminative ability and predictive accuracy of the nomogram were evaluated using the index of concordance (C-index) and calibration curves and compared with the five staging systems currently used for MM. Multivariate analysis of the training cohort revealed that the age at diagnosis, clonal bone marrow plasma cells, serum lactate dehydrogenase, serum
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