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Abstract: FR-PO1105

A Proposal for Outcome Prediction in Lupus Nephritis Based on Bayesian Statistics

Session Information

Category: Glomerular Diseases

  • 1203 Glomerular Diseases: Clinical, Outcomes, and Trials

Authors

  • Mejia-Vilet, Juan M., Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico, Mexico
  • Tamez Pedroza, Luis, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico, Mexico
  • Rodriguez, Sonia, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico, Mexico
  • Correa-Rotter, Ricardo, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico, Mexico
  • Morales-Buenrostro, Luis E., Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico, Mexico
Background

A focus in lupus nephritis (LN) is to define the best criteria for response to therapy based on hard renal outcomes. The definition of resistant disease remains heterogeneous.

Methods

The aim of the study was to determine the prognostic value of clinical parameters to predict renal survival and progression to ESRD. Clinical predictors were evaluated at 6/12 months after treatment as absolute values, absolute or percentage changes and predictor’s value normalization. The best cutoff was defined as the value where positive likelihood ratios (+LR) were persistently >3.0 for renal survival (response) or ESRD development (resistance).

Results

Of 248 patients with proteinuria >2.0g/g and complete induction treatment, we included 133 patients with >5 years follow-up. 36 (27.1%) progressed to ESRD. The best predictors for response were creatinine or eGFR at 6/12 months (AUC 0.798/0.856), proteinuria at 6/12 months (0.735/0.832) and hemoglobin at 6/12 months (AUC 0.689/ AUC 0.786). Predictors for resistance after 6 months of treatment included creatinine or eGFR (AUC 0.815), proteinuria percentage change (0.735), and albumin percentage change (AUC 0.599). Hematuria and serological parameters (dsDNA-antibodies, C3, C4) were not appropriate prognostic predictors. After censoring at different times of follow-up, it was observed that the longer the follow-up, the cutoff for each parameter had a lower valule. The best prognosis for renal survival was given by 12-month proteinuria <0.75g/g (+LR=3.08), eGFR>82ml/min (+LR=3.00) and hemoglobin>12g/dl (+LR=3.04). The best predictors for resistance were 6-month eGFR<61ml/min (+LR=3.13), proteinuria decrease <10% (+LR=3.29) and increase of serum albumin <0.3g/dl (+LR=3.39).

Conclusion

Likelihood ratios may be used to define the best values for response and resistance to therapy in LN. Proteinuria, renal function and hemoglobin at 12-months predict renal survival while proteinuria, eGFR and change in serum albumin may define resistant disease.