Novel SGUS score identifies SjD patients in need, or not, of biopsy

Use of the salivary gland-based predictive model may guide decision-making in labial minor salivary gland biopsy in patients with Sjögren disease (SjD) through the combination of imaging and clinical variables that allows personalized risk stratification, suggests a study.

Researchers applied a novel semiquantitative salivary gland ultrasound (SGUS) scoring system to 449 prospectively recruited patients and identified the predictors of labial focus score (FS) ≥1 using multivariable logistic regression. These predictors were then integrated into a risk stratification matrices model, which underwent both internal (n=139) and external validation (n=57).

Of the 449 patients (mean age 44.0 years, 94.7 percent female) included in the derivation cohort, 284 (63.3 percent) had labial FS score ≥1. Those with FS ≥1 tended to be older and have higher total SGUS scores and hyperglobulinaemia.

In multivariable logistic regression, SGUS score (odds ratio [OS], 1.44), age (OR, 1.51), and hyperglobulinaemia (OR, 1.91) independently predicted FS score ≥1. These factors were incorporated into an age-stratified prediction model categorizing patients into high-, moderate-, and low-risk groups across three age brackets.

The model demonstrated robust predictive value for labial FS ≥1 in both high- and low-risk populations (area under the curve [AUC], 0.91, 95 percent confidence interval, 0.87‒0.96; p<0.001). Its specificity was 81 percent and sensitivity 95 percent, with positive and negative predictive values of 92 percent and 87 percent, respectively.

Furthermore, the model did well in both internal (AUC, 0.90) and external validation (AUC, 0.83).

“[The novel SGUS scoring system] effectively identifies high-risk patients needing biopsy and low-risk patients who can avoid unnecessary procedures, offering a significant diagnostic advance,” the researchers said.