FRI0146 Correlation between the rheumatoid factor positivity and the higher discontinuation rate of biological therapy in rheumatoid arthritis: a fine-grey proportional hazard regression analysis
Authors: Y. Ogawa, N. Takahashi, T. Kojima, N. Ishiguro
Journal: Annals of the Rheumatic Diseases (2018)

<h3>Background</h3> As quantifying the occurrence of outcome over time holds vital importance in clinical medicine, the presence of competing risks must be considered when assessing the impact of prognostic factors on the incidence of an outcome over time. A competing risk is defined as an event that precludes the occurrence of an event of interest. For example, event arising from adverse effect causes is a competing risk when evaluating the effect of risk factors on the incidence of discontinuation of biological therapy because of inadequate response. The presence of biassed estimates of the effect of covariates on the incidence in the presence of competing risks is attributed to the naïve use of the conventional Cox proportional hazards model that censors the competing event. Fine and Grey developed the subdistribution hazard model that facilitates modelling the effects of covariates on the cumulative incidence function in the presence of competing risks. <h3>Objectives</h3> The discontinuation of biological therapy in rheumatoid arthritis (RA) is attributed to several reasons, including inadequate response, adverse effect, remission, and changing hospital. In particular, inadequate response constitutes a principal and compelling reason. This study aims to investigate the correlation between covariates, including the rheumatoid factor (RF) positivity and the discontinuation of biological therapy due to inadequate response in bio-naïve patients with RA using the Fine–Grey proportional hazard regression for competing events. <h3>Methods</h3> In this study, we enrolled patients in the Tsurumai Biologic Communication Registry that comprises Nagoya University and 15 affiliated institutions in Japan. We assessed the correlation between individual characteristic components and patient outcomes using the Fine–Grey proportional hazard regression for competing events. Apparently, time-based models estimate the effects of various characteristics (e.g., RF positivity, sex, and age) on time to develop events of interest, including the discontinuation owing to inadequate response. The Fine–Grey proportional hazard regression considered competing events, implying that this model generated separate hazard ratios for each competing event. All analyses were conducted in EZR version 1.36. <h3>Results</h3> A higher crude discontinuation rate was observed due to inadequate response in RF-positive patients than that in RF-negative patients using the cumulative incidence function of competing events and Grey test (figure 1). After adjusting for the baseline characteristics, including age, sex, stage, disease at the baseline, methotrexate use, prednisolone use, and tumour necrosis factor inhibitor (TNFi) or non-TNFi (HR, 1.57; 95% CI: 1.01–2.43; p&lt;0.05; table 1), the difference was significant in the Fine–Grey proportional hazard regression analysis. <h3>Conclusions</h3> Using the Fine–Grey proportional hazard regression for competing events, this study demonstrated a correlation between the RF positivity and inadequate response to biological therapy on bio-naïve patients with RA. <h3>Disclosure of Interest</h3> None declared