Development and Validation of the ALARN Model: A Predictive Mortality Score for Antisynthetase Syndrome

Objective To develop and validate a prognostic model for predicting all‐cause mortality in patients with antisynthetase syndrome (ASyS). Methods This retrospective study included 1,194 patients with ASyS from three independent institutions in China. The Cox proportional hazards (CPH) method and random survival forest (RSF) algorithm were used for developing a mortality risk prediction model in the derivation cohort (n = 763). The optimal model was simplified into a scoring system and validated in an external cohort of 431 patients from two institutions. Results The model constructed using the CPH method in the training cohort incorporated five prognostic factors: age at onset, lactate dehydrogenase, albumin, respiratory failure, and neutrophil‐to‐lymphocyte ratio. This model demonstrated better performance than the model developed using the RSF algorithm in the internal validation cohort and was subsequently transformed into a simplified scoring system, termed the ALARN score. The ALARN model achieved time‐dependent areas under the receiver operating characteristic curves of 0.914 (95% confidence interval [CI] 0.866–0.955), 0.867 (95% CI 0.829–0.906), 0.839 (95% CI 0.789–0.885), and 0.854 (95% CI 0.789–0.909) for predicting 1‐, 3‐, 5‐, and 10‐year mortality, respectively. Moreover, patients were effectively stratified into low‐, intermediate‐, and high‐risk groups (ALARN scores of 0–2, 3–5, and 6–8, respectively) with significantly different survival outcomes (log‐rank P < 0.0001). Internal and external validation confirmed the robustness of the ALARN score in predicting overall mortality in ASyS. Conclusion The ALARN score incorporates five readily available clinical parameters and provides a simple, practical tool for predicting mortality risk in patients with ASyS.