2.3. Construction and validation of the nomogram

In the design of the nomogram, we incorporated clinical features and inflammatory factors as prognostic features. These factors included age, gender, performance status (ECOG), Ann Arbor stage, extranodal involvement, LDH, LMR, ALB, β2-MG, CRP, sIL-2R, IL-6, IL-8, IL-10 and TNF-α. We used least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation to select the most useful predictive variables via minimum criteria for nomogram of overall survival (OS) from the training cohort. Nomogram validation comprised several stages. Internal validation was first undertaken, with a concordance index (C-index) being estimated. Next, calibration curves were plotted to determine whether the predicted and observed probabilities for survival time were in concordance. Bootstrap resampling (1000 resamples) was used for this plot. Finally, external validation was performed, in which the nomogram was used to assess each patient in the validation cohorts, and Cox regression analysis in total score of each patient as an independent factor. The regression analysis was then carried out to derive the C-index and the calibration curve. Comparisons between nomogram and other prognostic models were evaluated by C-index.