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Background

Predicting survival in newly diagnosed multiple myeloma (NDMM) patients accurately remains challenging. Although mSMART3.0 is widely used it has not been rigorously tested for prediction accuracy.

Methods

We analysed clinical and laboratory variables in 1,008 NDMM patients, randomly split into a training set (n = 704) and a validation set (n = 304). Univariable and multivariable Cox regression analyses identified independent prognostic factors, forming a baseline survival model. For patients with available mSMART3.0 data, we integrated it with the baseline nomogram to enhance predictive accuracy. Time-dependent area under the receiver-operator characteristic curve (timeROC), calibration plots as well as comparisons with other survival prediction systems were used to estimated model performance.

Results

The baseline models, incorporating eight factors, achieved 5-year survival AUCs of 0.77 (95% CI: 0.72–0.81) in the training set and 0.73 (95% CI: 0.66–0.80) in the validation set. In the training set, 5-year survival was 34% (95% CI: 28–41%) in the high-risk group versus 72% (95% CI: 67–78%) in the low-risk group (p < 0.001), with similar differences observed in the validation set. The model exhibited excellent discrimination and calibration in both sets. In the training cohort the merged nomogram increased the 5-year survival AUCs of mSMART3.0 from 0.64 (0.57, 0.71) to 0.75 (0.67, 0.83; p = 0.003), better than the other staging systems of MM.

Conclusions

The proposed nomograms increased the survival prediction accuracy in patients with NDMM.