FRI0446 Initial predictors for mortality in patients with cancer-associated myositis: a multicenter retrospective cohort in japan
Authors: H. Kadota, T. Gono, Y. Yamaguchi, E. Watanabe, Y. Okazaki, Y. Nakajima, S. Kobayashi, Y. Shirai, M. Takeno, C. Terai, M. Kuwana
Journal: Annals of the Rheumatic Diseases (2018)

<h3>Background</h3> Concomitant malignancy is one of the prognostic factors in patients with myositis,<sup>1</sup> but clinical parameters for mortality still remain unknown in patients with cancer-associated myositis (CAM). <h3>Objectives</h3> Initial predictors for mortality were examined using a multicenter cohort of CAM patients. <h3>Methods</h3> This retrospective study enrolled 67 consecutive patients diagnosed as having CAM in 3 referral hospitals between 1995 and 2017. Clinical data at diagnosis of myositis as well as treatment regimens and outcomes of myositis and malignancy were collected by review of medical charts. Myositis-specific autoantibodies (MSAs) were comprehensively detected using RNA immunoprecipitation (IP), enzyme-linked immunosorbent assay, and IP-immunoblotting. We initially conducted a univariate analysis to select variables that were different between survivors and dead cases. In multivariate analysis, the Cox proportional hazard model with backward selection method (p&gt;0.20) was employed to identify factors independently associated with mortality. Explanatory variables were chosen based on the following three models. The Model 1 included age at diagnosis of myositis, gender and candidate variables (p&lt;0.1) selected by the univariate analysis. The Model 2 included age, gender, prognostic factors previously reported in myositis, such as dermatomyositis, dysphasia, interstitial lung disease (ILD), anti-ARS, and anti-MDA5, and malignancy type and staging, as explanatory variables. In the Model 3, age, gender, disease duration before diagnosis of myositis, period between diagnosis of myositis and tumour, myositis classification, MSAs, dysphasia, ILD, myositis disease activity after treatment, and malignancy type and staging were used as explanatory variables. Cumulative survivals calculated using the Kaplan-Meier method were compared between the patients with and without risk factors. <h3>Results</h3> The median age at diagnosis of myositis was 63 years, and 62% were female. MSAs were detected in 47 patients: anti-TIF1-γ in 27, anti-ARS in 6, anti-MDA5 in 5, anti-Mi-2 in 3, anti-NXP2 in 3, anti-SAE in 2, and anti-SRP in 1. During the median observation period of 2 years, 19 (28%) of 67 CAM patients were dead due to tumour in 16, ILD in 1, and an unknown cause in 2. The univariate analysis identified significant poor prognostic factors (p&lt;0.1) as follows: male (p=0.04), elder age at diagnosis of myositis (p=0.08), longer period between diagnosis of myositis and tumour (p=0.07), absence of breast cancer (p=0.001), malignancy stage III/IV (p=0.006). In multivariate analysis, male (HR 8.1, 95% CI 2.6–25.2; p&lt;0.001) and malignancy stage III/IV (HR 12.1, 95% CI 3.3–44.9; p&lt;0.001) were identified as independent risk factors for mortality in the Model 1, and identical variables were identified in the Models 2 and 3. Cumulative survival rates of patients with 0, 1, or 2 risk factors were 100%, 93%, and 69% at 1 year, and 100%, 82%, and 0% at 3 years, respectively. Cumulative survival rates were statistically different between the groups stratified by the number of risk factors (figure 1). <h3>Conclusions</h3> Male and progression of malignancy at diagnosis of myositis were identified as predictors of survivals in CAM patients. <h3>Reference</h3> [1] Callen JP. Dermatomyositis. Lancet2000;355:53–7. <h3>Disclosure of Interest</h3> H. Kadota: None declared, T. Gono: None declared, Y. Yamaguchi: None declared, E. Watanabe: None declared, Y. Okazaki: None declared, Y. Nakajima: None declared, S. Kobayashi: None declared, Y. Shirai: None declared, M. Takeno: None declared, C. Terai: None declared, M. Kuwana Grant/research support from: Astellas, Speakers bureau: Astellas and Japan Blood Products Organisation