Predictive value of a combined model based on immune indicators and clinical characteristics for the prognosis of patients with primary myelofibrosis
Abstract
Objective To explore the construction of a combined model based on immune indicators and clinical characteristics and its value in predicting the prognosis of patients with primary myelofibrosis(PMF),to support precise risk stratification and management. Methods A total of 71 patients with PMF treated at the People's Hospital of Ningxia Hui Autonomous Region from January 2016 to June 2024 were retrospectively selected as the research subjects.All patients were followed up for 1 year. Patients were divided into a good prognosis group(n=51)and a poor prognosis group(n=20)according to whether the patients deteriorated,relapsed or died. The immune indicators［CD4+ T cells,CD8+ T cells,interleukin - 6(IL - 6),immunoglobulin(Ig)G,IgA,IgM］and clinical data of the two groups were compared. Logistic regression analysis was used to examine the relationship between the above indicators and the prognosis of patients with PMF,and a combined model was constructed. The predictive performance of the combined model was evaluated using receiver operating characteristic(ROC)curve and Hosmer-Lemeshow goodness-of-fit test.Results Compared with the good prognosis group,the poor prognosis group had statistically significant differences in age,score of International Prognostic Scoring System(IPSS),transfusion dependence ratio,score of Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score(MPN-10),percentage of CD4+ T cells,and levels of IL-6,C-reactive protein(CRP),lactate dehydrogenase(LDH)and IgA(P<0.05). Multivariate logistic regression analysis showed that an IPSS score ≥3,transfusion dependence,and elevated levels of IL-6,LDH,and IgA were independently associated with poor prognosis in patients with PMF(P<0.05). The combined predictive model was expressed as:logit(P)= -6.856+0.812×IPSS score(≥3 points)+1.008×transfusion dependence+0.383×IL-6+0.008×LDH+0.820×IgA.The area under the ROC curve of the combined predictive model was 0.923(95% CI:0.860- 0.985). The Hosmer-Lemeshow test yielded a χ2 value of 4.812 with P=0.777. Conclusion The combined model constructed based on immune indicators and clinical characteristics has certain clinical value and holds promise as a potential biomarker for clinical assessment of the prognosis of patients with PMF.
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BibTeX
@article{juan2026predictive,
title = {{Predictive value of a combined model based on immune indicators and clinical characteristics for the prognosis of patients with primary myelofibrosis}},
author = {TIAN Juan and XUE Yimiao and WEI Yuping and GU Yihai and SONG Lijun},
journal = {Zhongguo linchuang yanjiu},
year = {2026},
month = oct,
doi = {10.13429/j.cnki.cjcr.2026.10.014},
url = {https://doi.org/10.13429/j.cnki.cjcr.2026.10.014},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Predictive value of a combined model based on immune indicators and clinical characteristics for the prognosis of patients with primary myelofibrosis
AU - TIAN Juan
AU - XUE Yimiao
AU - WEI Yuping
AU - GU Yihai
AU - SONG Lijun
PY - 2026
DA - 2026/10/26
JO - Zhongguo linchuang yanjiu
DO - 10.13429/j.cnki.cjcr.2026.10.014
UR - https://doi.org/10.13429/j.cnki.cjcr.2026.10.014
AB - Objective To explore the construction of a combined model based on immune indicators and clinical characteristics and its value in predicting the prognosis of patients with primary myelofibrosis(PMF),to support precise risk stratification and management. Methods A total of 71 patients with PMF treated at the People's Hospital of Ningxia Hui Autonomous Region from January 2016 to June 2024 were retrospectively selected as the research subjects.All patients were followed up for 1 year. Patients were divided into a good prognosis group(n=51)and a poor prognosis group(n=20)according to whether the patients deteriorated,relapsed or died. The immune indicators［CD4+ T cells,CD8+ T cells,interleukin - 6(IL - 6),immunoglobulin(Ig)G,IgA,IgM］and clinical data of the two groups were compared. Logistic regression analysis was used to examine the relationship between the above indicators and the prognosis of patients with PMF,and a combined model was constructed. The predictive performance of the combined model was evaluated using receiver operating characteristic(ROC)curve and Hosmer-Lemeshow goodness-of-fit test.Results Compared with the good prognosis group,the poor prognosis group had statistically significant differences in age,score of International Prognostic Scoring System(IPSS),transfusion dependence ratio,score of Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score(MPN-10),percentage of CD4+ T cells,and levels of IL-6,C-reactive protein(CRP),lactate dehydrogenase(LDH)and IgA(P<0.05). Multivariate logistic regression analysis showed that an IPSS score ≥3,transfusion dependence,and elevated levels of IL-6,LDH,and IgA were independently associated with poor prognosis in patients with PMF(P<0.05). The combined predictive model was expressed as:logit(P)= -6.856+0.812×IPSS score(≥3 points)+1.008×transfusion dependence+0.383×IL-6+0.008×LDH+0.820×IgA.The area under the ROC curve of the combined predictive model was 0.923(95% CI:0.860- 0.985). The Hosmer-Lemeshow test yielded a χ2 value of 4.812 with P=0.777. Conclusion The combined model constructed based on immune indicators and clinical characteristics has certain clinical value and holds promise as a potential biomarker for clinical assessment of the prognosis of patients with PMF.
SN - 1674-8182
ER -