scholarly journals AB0397 Abatacept shows better sustainability than tnf inhibitors when used following initial biologic dmard failure in the treatment of rheumatoid arthritis: 8 years of real-world observations from the rhumadata® clinical database and registry

2017 ◽  
Author(s):  
D Choquette ◽  
L Bessette ◽  
E Alemao ◽  
B Haraoui ◽  
F Massicotte ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Real World ◽  
Tnf Inhibitors ◽  
Clinical Database ◽  
Biologic Dmard

scholarly journals Predicting Response to Tocilizumab Monotherapy in Rheumatoid Arthritis: A Real-World Data Analysis Using Machine Learning

2020 ◽  
Author(s):  
Fredrik D Johansson ◽  
Jamie E Collins ◽  
Vincent Yau ◽  
Hongshu Guan ◽  
Seoyoung C Kim ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Logistic Regression ◽  
Real World ◽  
Prediction Models ◽  
External Validation ◽  
Similar Efficacy ◽  
Prediction Score ◽  
Real World Data ◽  
World Data ◽  
Biologic Dmard

Abstract Background Tocilizumab (TCZ) had similar efficacy when used as monotherapy or in combination with other treatments for rheumatoid arthritis (RA) in randomized controlled trials (RCT). Recently, we derived a remission prediction score for TCZ monotherapy (TCZm) using RCT data. Herein, we describe external validation and several extensions of the prediction score using “real world data” (RWD).MethodsWe identified patients in Corrona-RA who used TCZm (n=453), matching the design and patients from four RCTs used in previous work (n=853). Patients were followed to determine remission status at 24 weeks. We compared the performance of remission prediction models in RWD, first based on variables determined in our prior work in RCTs, and then using an extended variable set, comparing logistic regression and random forest models. We included patients on other biologic DMARD monotherapies (bDMARDm) to improve prediction.ResultsThe fraction of patients observed reaching remission on TCZm by their follow-up visit was 12% (n=53) in RWD vs 15% (n=127) in RCTs. Discrimination was good in RWD for the risk score developed in RCTS with AUROC of 0.70 (95% CI 0.64, 0.77). Fitting the same logistic regression model to all bDMARDm patients in the RWD improved the AUROC on TCZm patients to 0.73 (95% CI 0.64, 0.82). Extending the variable set and adding regularization further increased it to 0.77 (95% CI 0.68, 0.85).ConclusionThe remission prediction scores, derived in RCTs, discriminated patients in RWD about as well as in RCTs. Discrimination was further improved by retraining models on RWD, including a larger variable set and learning from patients on similar therapies.

scholarly journals O32 Serious infection with tocilizumab compared to TNF-inhibitors and other bDMARDS in rheumatoid arthritis patients: does line of therapy matter?

Rheumatology ◽  
2021 ◽  
Vol 60 (Supplement_1) ◽  
Author(s):  
Kim Lauper ◽  
Lianne Kearsley-Fleet ◽  
Rebecca Davies ◽  
Kath Watson ◽  
Mark Lunt ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Real World ◽  
Disease Duration ◽  
Tnf Inhibitors ◽  
World Population ◽  
Research Support ◽  
Serious Infection ◽  
Number Of Patients ◽  
Serious Infections ◽  
Line Of Therapy

Abstract Background/Aims  In the real-world, tocilizumab is prescribed to a population of patients different from those prescribed TNF-inhibitors, often older with longer disease duration, worse functional status and more previous b- or tsDMARDs. The aim of this study was to evaluate if and how the risk of serious infection on tocilizumab and other bDMARDs differs when stratifying by line of therapy in a real-world population of rheumatoid arthritis patients. Methods  We included patients registered in the BSRBR-RA treated with tocilizumab, etanercept, adalimumab, infliximab, certolizumab, abatacept or rituximab, including biosimilars. Primary outcome was the occurrence of a serious infection (defined as infection requiring hospitalisation, intravenous antibiotics or resulting in death). Primary covariate of interest was line of therapy (from first to fifth line of therapy). Every change to another b- or tsDMARD was considered a new line of therapy, but not a change between a bio-original and a biosimilar. Hazard ratios (HR) of serious infections were estimated using an inverse probability weighted Cox regression, based on a propensity score including baseline patient and disease characteristics, and adjusting for time in study (see table). The reference group was etanercept, which included the highest number of patients. Treatment exposure was analysed without and with stratification by line of therapy. Results  A total of 33,916 treatment courses were included (Table) contributing to 62,532 years of follow-up. Compared to etanercept, participants starting abatacept, tocilizumab and rituximab were older, had more previous bDMARDs, longer disease duration and more comorbidities. The crude HR of serious infections were higher with infliximab and adalimumab, lower with certolizumab and rituximab, and not significantly different for abatacept and tocilizumab compared to etanercept. After adjustment, HR of serious infections were higher with tocilizumab, adalimumab and infliximab. However, when stratified by line of therapy, HR were no longer significantly different compared to etanercept for tocilizumab, adalimumab and infliximab for most lines of therapy. Conclusion  Whilst initially there appears to be a difference in rates of serious infections between biologic therapies, line of therapy may be a confounding factor when comparing the risk of serious infections between bDMARDs. Disclosure  K. Lauper: Honoraria; Gilead-Galapagos. Grants/research support; AbbVie. Other; AbbVie, Pfizer. L. Kearsley-Fleet: None. R. Davies: None. K. Watson: None. M. Lunt: None. K.L. Hyrich: Honoraria; AbbVie. Grants/research support; Pfizer, BMS.

scholarly journals Predicting Response to Tocilizumab Monotherapy in Rheumatoid Arthritis: A Real-World Data Analysis Using Machine Learning

2021 ◽  
pp. jrheum.201626
Author(s):  
Fredrik D. Johansson ◽  
Jamie E. Collins ◽  
Vincent Yau ◽  
Hongshu Guan ◽  
Seoyoung C. Kim ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Logistic Regression ◽  
Real World ◽  
Prediction Models ◽  
External Validation ◽  
Similar Efficacy ◽  
Prediction Score ◽  
Real World Data ◽  
World Data ◽  
Biologic Dmard

Objective Tocilizumab (TCZ) had similar efficacy when used as monotherapy or in combination with other treatments for rheumatoid arthritis (RA) in randomized controlled trials (RCT). We derived a remission prediction score for TCZ monotherapy (TCZm) using RCT data and now performed an external validation of the prediction score using “real world data” (RWD). Methods We identified patients in Corrona-RA who used TCZm (n=453), matching the design and patients from four RCTs used in previous work (n=853). Patients were followed to determine remission status at 24 weeks. We compared the performance of remission prediction models in RWD, first based on variables determined in our prior work in RCTs, and then using an extended variable set, comparing logistic regression and random forest models. We included patients on other biologic DMARD monotherapies (bDMARDm) to improve prediction. Results The fraction of patients observed reaching remission on TCZm by their follow-up visit was 12% (n=53) in RWD vs 15% (n=127) in RCTs. Discrimination was good in RWD for the risk score developed in RCTS with AUROC of 0.69 (95% CI 0.62, 0.75). Fitting the same logistic regression model to all bDMARDm patients in the RWD improved the AUROC on held-out TCZm patients to 0.72 (95% CI 0.63, 0.81). Extending the variable set and adding regularization further increased it to 0.76 (95% CI 0.67, 0.84). Conclusion The remission prediction scores, derived in RCTs, discriminated patients in RWD about as well as in RCTs. Discrimination was further improved by retraining models on RWD.

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