A short-term prognostic model based on urinary IgG, CO2CP and TP for newly diagnosed multiple myeloma.

This study aimed to establish a short-term risk assessment model for patients with newly diagnosed multiple myeloma (NDMM), to augment the current prognosis assessments of MM patients. This model serves as a reference for evaluating the short-term remission of patients. Between January 2013 and March 2023, a total of 232 NDMM patients were enrolled in the Hematology department. The cohort between January 2013 and October 2020 was selected as the training set (n=165) and the cohort between November 2020 and March 2023 was used as the internal validation set (n=67). Using univariate and multivariate forward stepwise Cox analysis, the determined prognostic factors were urinary immunoglobulin G (IgG), carbon dioxide combining power (CO2CP), and total protein (TP). A 3-prognostic factor Nomogram model was established based on Cox regression. The area under the curve (AUC) of the Nomogram in 4-, 5- and 6-month complete remission (CR) was 0.777, 0.722, and 0.708, and the C index was 0.691 (0.661-0.721). Kaplan-Meier curve analysis indicated that the CR rate of the high-risk group was lower than the low-risk group (training set P<0.001, internal validation set P=0.018), which exhibited a better stratification of patients than the International Staging System (ISS, training set P=0.850, internal validation set P=0.900), Revised International Staging System (R-ISS, training set P=0.740, internal validation set P=0.720) and the Second Revision of the ISS (R2-ISS, training set P=0.480, internal validation set P=0.590). This study effectively constructed a Nomogram for short-term risk assessment of NDMM patients based on three widely used clinical markers, thereby enriching factors related to NDMM prognosis and aiding in the evaluation of the short-term complete remission.