Objective: To investigate the correlation between bone marrow microvascular density, angiogenesis factors and bortezomib resistance in multiple myeloma (MM).
Methods: The data of 200 patients with MM treated in our hospital from January 2020 to August 2023 were retrospectively analyzed, and the patients with MM were divided into drug-resistant group(n=68) and non-drug-resistant group(n=132) according to their drug resistance during bortezomib treatment. The univariate and multivariate logistic analysis were used to screen the independent influencing factors of bortezomib resistance in MM patients during treatment. The receiver operating characteristic (ROC) curve and clinical decision curve (DCA) were used to evaluate the predictive performance and clinical application value of the risk prediction model, the consistency between the actual incidence rate and the predicted incidence rate was judged by validating the calibration chart, and the goodness-of-fit of the model was judged by H-L test.
Results: 68 of the 200 MM patients developed resistance and poor clinical efficacy during bortezomib treatment, and the clinical resistance rate of bortezomib was 34.0%. The results of multivariate analysis showed that high bone marrow microvessel density (MVD) and high bone marrow supernatant VEGF, HGF, and bFGF expression levels were independent risk factors for bortezomib resistance in MM patients (P < 0.05). The area under the ROC curve (AUC) of the model jointly constructed by bone marrow MVD, serum VEGF, HGF, bFGF and TNF-α levels was 0.924, and its sensitivity and specificity were 92.6% and 78.8%, which were higher than those of the bone marrow MVD model (AUC=0.743) and the vasogenesis factor model (AUC=0.878). The calibration curve of the joint prediction model was close to the standard curve, indicating that the model is more consistent. The results of H-L goodness -of - fit test showed χ2=14.748， P =0.164, the joint prediction model had a good fit. The DCA curve showed that the clinical net benefit of intervention in the range of 0.0~1.0 was greater than that of full intervention and no intervention.
Conclusion: The prediction model based on bone marrow MVD and vasogenesis factors (VEGF, HGF, bFGF) in MM patients has higher clinical evaluation performance and predictive value.
题目: 骨髓微血管密度及血管相关生成因子与多发性骨髓瘤硼替佐米耐药的相关性研究.
目的: 探讨骨髓微血管密度及血管相关生成因子与多发性骨髓瘤（MM）硼替佐米耐药的相关性。.
方法: 回顾性分析2020年1月至2023年8月于本院收治的200例MM患者的相关资料，并根据MM患者硼替佐米治疗期间耐药情况分为耐药组与未耐药组。单因素和多因素Logistic分析筛选MM患者硼替佐米治疗期发生耐药的独立影响因素。以受试者工作特征曲线（ROC）和临床决策曲线（DCA）评估风险预测模型的预测效能和临床应用价值；通过验证校准图判断实际发生率和预测发生率的一致性；并采用H-L检验判断模型的拟合优度。.
结果: 200例MM患者中有68例在接受硼替佐米治疗期间出现耐药且临床疗效不佳的情况，硼替佐米临床耐药率为34.0%。多因素分析结果显示，MM患者高骨髓微血管密度（MVD）、高骨髓上清VEGF、HGF、bFGF表达水平等血管相关生成因子均是接受硼替佐米治疗期间发生耐药的独立危险因素（P < 0.05）。由骨髓MVD、血清VEGF、HGF、bFGF和TNF-α水平联合构建的模型ROC曲线下面积（AUC）为0.924，其敏感度为92.6%,特异度为78.8%，联合预测模型AUC高于骨髓MVD（AUC=0.743）和血管相关生成因子（AUC=0.878）独立预测模型。绘制联合预测模型校准图当中校准曲线贴近于标准曲线，提示该模型一致性较好。H-L拟合优度检验结果显示 χ 2=14.748，P =0.164，说明联合预测模型拟合度好。DCA曲线提示干预在0.0~1.0区间的临床净收益大于全干预和不干预。.
结论: 以MM患者骨髓MVD和血管相关生成因子（VEGF、HGF、bFGF）联合构建的预测模型具备更高的临床评估效能和预测价值。.
Keywords: bone marrow microvascular density; angiogenesis factors; multiple myeloma; bortezomib; drug resistance; predictive models.