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The diagnostic utility of myositis autoantibody testing for predicting the risk of cancer-associated myositis
  1. Hector Chinoy (hector.chinoy{at}
  1. University of Manchester, United Kingdom
    1. Noreen Fertig (fertig{at}
    1. University of Pittsburgh, United States
      1. Chester V Oddis (oddis{at}
      1. University of Pittsburgh, United States
        1. William ER Ollier (william.ollier{at}
        1. University of Manchester, United Kingdom
          1. Robert G Cooper (robert.g.cooper{at}
          1. University of Manchester, United Kingdom


            Objectives: There is a known association between myositis and cancer. The risk is greater in dermatomyositis than polymyositis, although reliable methods to predict cancer risk in specific myositis patients are not presently available. This study was undertaken to determine whether risk of developing cancer in myositis is predictable by antibody profiling.

            Methods: A cross-sectional study of UK Caucasian adults with polymyositis (PM, n=109), dermatomyositis (DM, n=103) and connective tissue disease overlap (myositis/CTD-overlap, n=70). Patients were tested for a comprehensive range of myositis-specific/associated autoantibodies (MSA/MAAs). Sensitivity and specificity analyses were performed for optimal identification of cancer risk.

            Results: Sixteen patients had cancer-associated myositis (CAM) (15 DM, 1 myositis/CTD-overlap). CAM patients were older at disease onset, and patients without MSA/MAAs on ‘routine’ laboratory testing (negative for anti-Jo-1, -PM-Scl, -U1-RNP, -U3-RNP, -Ku antibodies) had a significantly increased risk of CAM. Possession of the antibody (Ab) against 155kDa and 140kDa protein specificities (anti-155/140 Ab) represented a significant risk factor for CAM, this doublet being found exclusively in DM. A positive anti- 155/140 Ab result proved highly specific, moderately sensitive, with high negative predictive value (NPV) for CAM. A ‘negative routine myositis Ab panel’ result was highly sensitive, with high NPV for CAM. The combination of these two approaches was 94% sensitive, detecting 15/16 CAM, with 100% sensitivity and NPV in DM.

            Conclusions: These results may help clinicians predict which myositis patients are at greater risk of developing cancer, thus identifying those requiring aggressive diagnostic evaluation and intensive cancer surveillance at myositis onset and follow-up.

            • autoantibodies
            • cancer
            • dermatomyositis
            • polymyositis
            • sensitivity and specificity

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