Risk and Factors associated with disease manifestations in systemic lupus erythematosus - lupus nephritis (RIFLE-LN): a ten-year risk prediction strategy derived from a cohort of 1652 patients

ObjectivesLupus nephritis (LN) remains one of the most severe manifestations in patients with systemic lupus erythematosus (SLE). Onset and overall LN risk among SLE patients remains considerably difficult to predict. Utilizing a territory-wide longitudinal cohort of over 10 years serial follow-up data, we developed and validated a risk stratification strategy to predict LN risk among Chinese SLE patients - Risk and Factors associated with disease manifestations in systemic Lupus Erythematosus - Lupus Nephritis (RIFLE-LN). MethodsDemographic and longitudinal data including autoantibody profiles, clinical manifestations, major organ involvement, LN biopsy results and outcomes were documented. Association analysis was performed to identify factors associated with LN. Regression modelling was used to develop a prediction model for 10-year risk of LN and thereafter validated. ResultsA total of 1652 patients were recruited: 1382 patients were assigned for training and validation of the RIFLE-LN model; while 270 were assigned for testing. The median follow-up duration was 21 years. In the training and validation cohort, 845 (61%) of SLE patients developed LN. Cox regression and log rank test showed significant positive association between male sex, age of SLE onset and anti-dsDNA positivity. These factors were thereafter used to develop RIFLE-LN. The algorithm was tested in 270 independent patients and showed good performance (AUC = 0 & BULL;70). ConclusionBy using male sex, anti-dsDNA positivity, age of SLE onset and SLE duration; RIFLE-LN can predict LN among Chinese SLE patients with good performance. We advocate its potential utility in guiding clinical management and disease monitoring. Further validation studies in independent cohorts are required.

Automated summary

A risk stratification strategy (RIFLE-LN) was developed to predict the risk of lupus nephritis (LN) among Chinese SLE patients, using male sex, anti-dsDNA positivity, age of SLE onset, and SLE duration. The algorithm was validated in an independent cohort.