Inflammatory myopathies

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

Arthritis RheumatolPublished Retrospective cohort study

Authors' conclusion

The ALARN score incorporates five readily available clinical parameters and provides a simple, practical tool for predicting mortality risk in patients with ASyS.

Study context

Population
Patients with antisynthetase syndrome (ASyS) from three independent institutions in China
Participants
1,194 patients3 institutions
Exposure
Derivation vs External
  • Derivationn = 763
  • Externaln = 431
Outcome
All-cause mortality
Methodological detailsprognostic model development and validation, multicentre, external validation, Cox proportional hazards, random survival forest
  • Prognostic model development and validation
  • Multicentre
  • External validation
  • Cox proportional hazards
  • Random survival forest

Main finding

As reported in the abstract

ALARN model discrimination for mortality (time-dependent AUC)

Time-dependent AUC, 1-year mortality

0.914

95% CI 0.866–0.955

Time-dependent AUC, 3-year mortality

0.867

95% CI 0.829–0.906

Time-dependent AUC, 5-year mortality

0.839

95% CI 0.789–0.885

Time-dependent AUC, 10-year mortality

0.854

95% CI 0.789–0.909

Observational data: associations, not effects.

Further findings

Risk stratification: low- (ALARN 0-2), intermediate- (3-5), high-risk (6-8)

Significantly different survival outcomes across risk groups
log-rank P < 0.0001

Cox proportional hazards (CPH) vs random survival forest (RSF) model performance

CPH model better performance than RSF model in internal validation cohort

Original publication

Development and Validation of the ALARN Model: A Predictive Mortality Score for Antisynthetase Syndrome. Arthritis Rheumatol. Published 9 June 2026. doi:10.1002/art.70249

Composed by AI from the published abstract and checked against it. How Briefs are made →

Get them every week

New studies on this topic in My Week and in your Monday e-mail.

We e-mail you a sign-in link and a code. No password, no spam.