Factors associated with the retention of secukinumab in patients with axial spondyloarthritis in real-world practice: results from a retrospective study (FORSYA).

BACKGROUND: Secukinumab efficacy and retention data are emerging in patients with axial spondyloarthritis (axSpA) in real-world settings. However, limited data are available on the predictive factors that affect the retention rate. The key objective was to determine whether objective signs of inflammation (OSI) were predictive of secukinumab retention at 1 year. METHODS: FORSYA is a French, multicentric, non-interventional, retrospective study in adult axSpA patients who received secukinumab treatment between its launch (11 August 2016) and 31 August 2018. The time to secukinumab discontinuation and retention were analysed using a Kaplan-Meier (KM) analysis. OSI was predefined by at least one of the criteria: C reactive protein ≥5 mg/L or erythrocyte sedimentation rate ≥28 mm/hour at secukinumab initiation or MRI inflammation at the sacroiliac or spine level. RESULTS: In total, 906 patients from 48 centres were included in the analysis, 42.2% of whom were men, with a mean age of 46.2±11.7 years and a mean disease duration of 9.3±9.1 years. The 1-year KM retention rate (95% CI) for secukinumab was 59% (55%-62%), whereas for patients with and without OSI, it was 58% (54%-62%) and 63% (53%-73%), respectively. In multivariate analysis, lack of prior exposure to tumour necrosis factor inhibitor (TNFi), absence of OSI and inflammatory bowel disease (IBD) were associated with a better retention of secukinumab at 1 year. CONCLUSION: Following its approval in France, ~59% of axSpA patients retained secukinumab in daily practice, at 1 year. Prior exposure to TNFi, OSI and IBD were identified as risk factors for secukinumab discontinuation.

Impact of disease activity outcome measures reporting in the medical records of patients with axial spondyloarthritis on the retention rates of biological treatment: the example of secukinumab use in daily practice in France.

OBJECTIVES: To estimate the frequency of reporting composite indices evaluating axial spondyloarthritis (axSpA) disease activity in daily practice and to assess its impact on the secukinumab (SEC) retention rate. METHODS: Study design: Retrospective, multicentre. DATA COLLECTED: (1) Recommended composite indices: Bath Ankylosing Spondyltitis Disease Activity Index (BASDAI) +C reactive protein or Ankylosing Spondylitis Disease Activity Score (ASDAS) at the time of initiation of SEC and at least once during the first year of follow-up; (2) Drug retention rate: percentage of patients still on SEC over time according to whether at least one recommended composite index had been optimally reported. RESULTS: A recommended composite index has been collected in 22% of the 906 enrolled axSpA patients. The percentage of patients still on treatment after 1, 2 and 3 years of follow-up was greater in those for whom at least one composite index had been optimally reported (respectively, 64% (57-71) vs 57% (54-61), 55% (48-62) vs 41% (38-45) and 52% (44-59) vs 38% (34-42), log rank test, p=0.016) with a lower risk of SEC discontinuation for these patients (HR: 0.70 (95% CI 0.5 to 0.88), Cox model, p=0.003). CONCLUSION: This study suggests that reporting of recommended composites indices for monitoring axSpA might be associated with higher retention rates of biological therapies.

Automated Spatial Pattern Analysis for Identification of Foot Arch Height From 2D Foot Prints.

Arch height is an important determinant for the risk of foot pathology, especially in an aging population. Current methods for analyzing footprints require substantial manual processing time. The current research investigated automated determination of foot type based on features derived from the Gabor wavelet utilizing digitized footprints to allow timely assessment of foot type and focused intervention. Two hundred and eighty footprints were collected, and area, perimeter, curvature, circularity, 2nd wavelet moment, mean bending energy (MBE), and entropy were determined using in house developed MATLAB codes. The results were compared to the gold standard using Spearman's Correlation coefficient and multiple linear regression models with significance set at 0.05. The proposed approach found MBE combined with foot perimeter to give the best results as shown by ANOVA (F(2,211) = 10.18, p < 0.0001) with the mean ±SD of low, normal, and high arch being, respectively, 0.26 ± 0.025,.24 ± 0.021, and 0.23 ± 0.024. A clinical review of the new cut off values, as set by the first and the third quartiles of our sample, lead to reliability up to 87%. Our results suggest that automated wavelet-based foot type classification of 2D binary images of the plantar surface of the foot is comparable to current state-of-the-art methods providing a cost and time effective tool suitable for clinical diagnostics.