Objective·To construct and validate a nomogram for distinguishing primary Sj?gren's syndrome(PSS)from immunoglobulin G4-related sialadenitis(IgG4-RS)based on ultrasound scoring parameters and clinical indicators.Methods·A total of 141 patients with PSS and 31 patients with IgG4-RS were retrospectively recruited from Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine from January 2018 to December 2023.The ultrasound scoring parameters,including parotid gland ultrasound(PGUS)score,submandibular gland ultrasound(SMGUS)score,and salivary gland ultrasound(SGUS)score,along with clinical indicators such as gender,age,anti-SSB/La antibody,anti-SSA/Ro60 antibody,anti-SSA/Ro52 antibody,IgG,and rheumatoid factor(RF),were collected.The optimal US scoring parameters and clinical indicators were screened by least absolute shrinkage and selection operator(LASSO)regression,and a nomogram model was constructed to distinguish PSS from IgG4-RS.The internal validation of the model was carried out through bootstrap method.Receiver operator characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to estimate the discrimination,calibration,and clinical utility of the nomogram model,respectively.Results·LASSO regression identified six major variables:gender,age,anti-SSA/Ro60 antibody,anti-SSA/Ro52 antibody,PGUS score,and SMGUS score.These variables were used to construct the nomogram.ROC curve of the nomogram showed that the area under the curve(AUC)was 0.976,indicating the nomogram had strong discrimination ability.The bootstrap method was used for internal validation with 1 000 resampling iterations,and the average absolute error was 0.018.Calibration curve demonstrated good agreement between predicted and observed values.DCA indicated that the nomogram had certain clinical utility.Conclusion·The nomogram based on ultrasound scoring parameters and clinical indicators demonstrates excellent discrimination and calibration in differentiating PSS from IgG4-RS.It has the potential to assist in clinical diagnosis and decision-making.

Objective·To construct and validate a nomogram for distinguishing primary Sj?gren's syndrome(PSS)from immunoglobulin G4-related sialadenitis(IgG4-RS)based on ultrasound scoring parameters and clinical indicators.Methods·A total of 141 patients with PSS and 31 patients with IgG4-RS were retrospectively recruited from Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine from January 2018 to December 2023.The ultrasound scoring parameters,including parotid gland ultrasound(PGUS)score,submandibular gland ultrasound(SMGUS)score,and salivary gland ultrasound(SGUS)score,along with clinical indicators such as gender,age,anti-SSB/La antibody,anti-SSA/Ro60 antibody,anti-SSA/Ro52 antibody,IgG,and rheumatoid factor(RF),were collected.The optimal US scoring parameters and clinical indicators were screened by least absolute shrinkage and selection operator(LASSO)regression,and a nomogram model was constructed to distinguish PSS from IgG4-RS.The internal validation of the model was carried out through bootstrap method.Receiver operator characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to estimate the discrimination,calibration,and clinical utility of the nomogram model,respectively.Results·LASSO regression identified six major variables:gender,age,anti-SSA/Ro60 antibody,anti-SSA/Ro52 antibody,PGUS score,and SMGUS score.These variables were used to construct the nomogram.ROC curve of the nomogram showed that the area under the curve(AUC)was 0.976,indicating the nomogram had strong discrimination ability.The bootstrap method was used for internal validation with 1 000 resampling iterations,and the average absolute error was 0.018.Calibration curve demonstrated good agreement between predicted and observed values.DCA indicated that the nomogram had certain clinical utility.Conclusion·The nomogram based on ultrasound scoring parameters and clinical indicators demonstrates excellent discrimination and calibration in differentiating PSS from IgG4-RS.It has the potential to assist in clinical diagnosis and decision-making.