Characterization, outcome and identification of prognostic factors for patients with systemic immunoglobulin light-chain amyloidosis requiring dialysis prior to initial anti-clonal therapy

AL amyloidosis is a serious disease characterized by the deposition of immunoglobulin light chains in multiple organs. Renal involvement occurs in up to 70% of patients, but only a minority require dialysis before initiating anti-clonal treatment. Understanding the occurrence of end-stage organ damage is crucial to pave the way for reversing deposition. Currently, there is no detailed analysis available for this rare patient subgroup. We conducted a systematic search across three amyloidosis centers and characterized 68 biopsy-proven AL amyloidosis patients who required dialysis prior to initial anti-clonal therapy. In our cohort, the second most affected organ was the heart. Renal parameters exhibited variability. Residual urine output and proteinuria ranged widely, while anuria had developed in only a few patients. Among the treated patients, 84% received bortezomib as first-line therapy. The median overall survival (OS) was 44.8 months, with a median event-free survival (EFS) of 16.8 months. Our univariate statistical analysis revealed that underlying clonal disease, indicated by plasma cell infiltration, but not the difference between involved (amyloidogenic) and uninvolved free light chain, impacted OS. Importantly, higher levels of Troponins were associated with worse OS, confirmed by multivariate analysis, whereas N-terminal pro-natriuretic peptide type B levels and classical echocardiographic parameters, such as septal thickness and longitudinal strain, did not demonstrate significant prognostic value. This study provides crucial insights into this unique cohort of dialysis-dependent AL amyloidosis patients. The underlying clonal disease and markers of cardiac damage are important prognostic criteria. These findings emphasize the need to refine prognostic scoring systems for dialysis-dependent AL amyloidosis patients to better stratify risk and optimize treatment approaches.