[Correlation between Bone Marrow Microvascular Density, Angiogenesis Factors and Bortezomib Resistance in Multiple...

To investigate the correlation between bone marrow microvascular density, angiogenesis factors and bortezomib resistance in multiple myeloma (MM).

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.

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.

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.