Glucocorticoid-Responsive Cold Agglutinin Disease in a Patient with Rheumatoid Arthritis

A 57-year-old man with rheumatoid arthritis developed severe anemia during treatment with adalimumab plus methotrexate. Cold agglutinin disease was diagnosed because haptoglobin was undetectable, cold agglutinin was positive (1 : 2048), and the direct Coombs test was positive (only to complement). Although the cold agglutinin titer was normalized (1 : 64) after treatment with prednisolone (0.7 mg/kg/day for two weeks), the patient’s hemoglobin did not increase above 8 g/dL. When cold agglutinins were reexamined using red blood cells suspended in bovine serum albumin, the titer was still positive at 1 : 1024. Furthermore, the cold agglutinin had a wide thermal amplitude, since the titer was 1 : 16 at 30°C and 1 : 1 at 37°C. This suggested that the cold agglutinin would show pathogenicity even at body temperature. After the dose of prednisolone was increased to 1 mg/kg/day, the patient’s hemoglobin rapidly returned to the normal range. The thermal amplitude test using red blood cells suspended in bovine serum albumin is more sensitive than the standard test for detecting pathogenic cold agglutinins

A novel method predicting clinical response using only background clinical data in RA patients before treatment with infliximab

<p><i>Objectives</i>: The aim of the present study was to generate a novel method for predicting the clinical response to infliximab (IFX), using a machine-learning algorithm with only clinical data obtained before the treatment in rheumatoid arthritis (RA) patients.</p> <p><i>Methods</i>: We obtained 32 variables out of the clinical data on the patients from two independent hospitals. Next, we selected both clinical parameters and machine-learning algorithms and decided the candidates of prediction method. These candidates were verified by clinical variables on different patients from two other hospitals. Finally, we decided the prediction method to achieve the highest score.</p> <p><i>Results</i>: The combination of multilayer perceptron algorithm (neural network) and nine clinical parameters shows the best accuracy performance. This method could predict the good or moderate response to IFX with 92% accuracy. The sensitivity of this method was 96.7%, while the specificity was 75%.</p> <p><i>Conclusions</i>: We have developed a novel method for predicting the clinical response using only background clinical data in RA patients before treatment with IFX. Our method for predicting the response to IFX in RA patients may have advantages over the other previous methods in several points including easy usability, cost-effectiveness and accuracy.</p

Additional file 1: Figure S1. of A longitudinal genome-wide association study of anti-tumor necrosis factor response among Japanese patients with rheumatoid arthritis

Regional plots showing association results from GEE models at 6q15, 6q27 and 10q25.3, when the analyses were restricted to patients with moderate or severe disease activity at baseline (n = 413). (PDF 350 kb

Additional file 2: Figure S2. of A longitudinal genome-wide association study of anti-tumor necrosis factor response among Japanese patients with rheumatoid arthritis

Regions showing moderate evidence of association (p < 1x10−5) with anti-TNF response (GEE models). (PDF 324 kb