Clinical and imaging predictors of 1-year and long-term mortality in light chain (AL) amyloidosis: a 5-year follow-up study.

Light chain amyloidosis (AL) involves multiorgan failure induced by amyloidogenic light chain proteins, and is associated with high mortality. We aimed to identify clinical, laboratory, and imaging parameters that would predict 1-year and long-term AL mortality. Forty-four biopsy-proven AL patients (61.5 ± 12 years, 20 females) underwent clinical evaluation including laboratory assays, echocardiography, and contrast cardiac magnetic resonance imaging (CMR, n = 31) prior to chemotherapy. Patients were prospectively followed for median duration of 62.7 months (interquartile range 35.5 months). Clinical and laboratory parameters were compared between 1-year survivors and nonsurvivors. Univariate Kaplan-Meier survival plots were calculated followed by stepwise logistic regression analysis to assess independent predictors of long-term survival. Eighteen (40.9 %) patients died within 1 year and an additional 10 subjects died during long-term follow-up. Patients who expired within 1 year presented with more advanced class of heart failure, higher alkaline phosphatase and uric acid, lower limb lead voltage on electrocardiography, shorter left ventricular ejection time (ET) on echocardiography, and a higher proportion of late gadolinium enhancement on CMR. On multivariable analysis, only ET ≤240 ms on echocardiography (hazard ratio (HR) 5.07, 95 % confidence interval (CI) 1.83-14.1, P = 0.002) and New York Heart Association functional class II-IV presentation (HR 1.0058, 95 % CI 1.0014-1.0103, P = 0.01) were independent predictors of AL mortality. In conclusion, AL amyloidosis is associated with high 1-year and long-term mortality. Among clinical, laboratory, and imaging parameters tested, an echocardiographic finding of ET ≤240 ms has independent and additive prognostic value to clinical heart failure evaluation in determining long-term survival of AL patients. This result may be important in the early identification of patients at risk.