Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram
<b>Background</b>: Patients with multiple myeloma (MM) who have a suboptimal response to induction therapy or early relapse are classified as functional high-risk (FHR) patients and have been shown to have a dismal prognosis. The aim of this study was to establish a predictive nomogram f...
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2025-01-01
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| author | Yanjuan Li Lifen Kuang Beihui Huang Junru Liu Meilan Chen Xiaozhe Li Jingli Gu Tongyong Yu Juan Li |
| author_facet | Yanjuan Li Lifen Kuang Beihui Huang Junru Liu Meilan Chen Xiaozhe Li Jingli Gu Tongyong Yu Juan Li |
| author_sort | Yanjuan Li |
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| description | <b>Background</b>: Patients with multiple myeloma (MM) who have a suboptimal response to induction therapy or early relapse are classified as functional high-risk (FHR) patients and have been shown to have a dismal prognosis. The aim of this study was to establish a predictive nomogram for patients with non-transplanted FHR MM. <b>Materials and Methods</b>: The group comprised 215 patients in our center between 1 January 2006 and 1 March 2024. To identify independent risk factors, univariate and multivariate logistic regression analyses were performed, and a nomogram was constructed to predict non-transplant FHR MM. To evaluate the nomogram’s predictive accuracy, we utilized bias-corrected AUC, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). <b>Results</b>: Multivariate logistic regression demonstrated that younger age at onset, a higher proportion of LDH (more than 220 U/L), pattern A + C of M protein decline patterns, a lower proportion of patients with induction treatment efficacy than VGPR, and those undergoing maintenance therapies were independent risk factors for patients with non-transplanted FHR MM. The AUC scores for the training and internal validation groups were 0.940 (95% CI 0.893–0.986) and 0.978 (95% CI 0.930–1.000). DCA and CIC curves were utilized to further verify the clinical efficacy of the nomogram. <b>Conclusions</b>: We developed a nomogram that enables early prediction of non-transplant FHR MM patients. Younger age at onset, LDH ≥ 220 U/L, an A + C pattern of M-protein decline, and induction therapy efficacy not reaching VGPR are more likely to be FHR MM patients. Patients who do not undergo maintenance therapy are prone to early progression or relapse. |
| format | Article |
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| institution | Kabale University |
| issn | 2227-9059 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Biomedicines |
| spelling | doaj-art-2a92be40fb994dc3bc7b9f820c1f86922025-01-24T13:24:10ZengMDPI AGBiomedicines2227-90592025-01-0113114510.3390/biomedicines13010145Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive NomogramYanjuan Li0Lifen Kuang1Beihui Huang2Junru Liu3Meilan Chen4Xiaozhe Li5Jingli Gu6Tongyong Yu7Juan Li8Department of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, ChinaDepartment of Haematology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China<b>Background</b>: Patients with multiple myeloma (MM) who have a suboptimal response to induction therapy or early relapse are classified as functional high-risk (FHR) patients and have been shown to have a dismal prognosis. The aim of this study was to establish a predictive nomogram for patients with non-transplanted FHR MM. <b>Materials and Methods</b>: The group comprised 215 patients in our center between 1 January 2006 and 1 March 2024. To identify independent risk factors, univariate and multivariate logistic regression analyses were performed, and a nomogram was constructed to predict non-transplant FHR MM. To evaluate the nomogram’s predictive accuracy, we utilized bias-corrected AUC, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). <b>Results</b>: Multivariate logistic regression demonstrated that younger age at onset, a higher proportion of LDH (more than 220 U/L), pattern A + C of M protein decline patterns, a lower proportion of patients with induction treatment efficacy than VGPR, and those undergoing maintenance therapies were independent risk factors for patients with non-transplanted FHR MM. The AUC scores for the training and internal validation groups were 0.940 (95% CI 0.893–0.986) and 0.978 (95% CI 0.930–1.000). DCA and CIC curves were utilized to further verify the clinical efficacy of the nomogram. <b>Conclusions</b>: We developed a nomogram that enables early prediction of non-transplant FHR MM patients. Younger age at onset, LDH ≥ 220 U/L, an A + C pattern of M-protein decline, and induction therapy efficacy not reaching VGPR are more likely to be FHR MM patients. Patients who do not undergo maintenance therapy are prone to early progression or relapse.https://www.mdpi.com/2227-9059/13/1/145multiple myelomanon-transplant candidatesnomogrampredictive modelM protein decline patterns |
| spellingShingle | Yanjuan Li Lifen Kuang Beihui Huang Junru Liu Meilan Chen Xiaozhe Li Jingli Gu Tongyong Yu Juan Li Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram Biomedicines multiple myeloma non-transplant candidates nomogram predictive model M protein decline patterns |
| title | Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram |
| title_full | Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram |
| title_fullStr | Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram |
| title_full_unstemmed | Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram |
| title_short | Early Identification of the Non-Transplanted Functional High-Risk Multiple Myeloma: Insights from a Predictive Nomogram |
| title_sort | early identification of the non transplanted functional high risk multiple myeloma insights from a predictive nomogram |
| topic | multiple myeloma non-transplant candidates nomogram predictive model M protein decline patterns |
| url | https://www.mdpi.com/2227-9059/13/1/145 |
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