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Treatment strategy introducing immunosuppressive drugs with glucocorticoids ab initio or very early in giant cell arteritis: A multicenter retrospective controlled study.

ABSTRACT: Objective: Glucocorticoids (GC) are associated with side effects in giant cell arteritis (GCA). Immunosuppressive therapies (ITs) have given conflicting results in GCA, regarding GC sparing effect. Primary endpoint is to evaluate whether very early introduction of ITs in GCA minimize the rate of GC-induced adverse events, in terms of infections, new onset systemic arterial hypertension, GC-induced diabetes and osteoporotic fractures.

Methods: A multicenter retrospective case-control study included 165 patients. One group included 114 patients who were treated with at least one IT given at diagnosis or within 3 months from the start of GC. A second group included 51 GCA who received only GC or an IT more than 3 months later.

Results: The most frequently used ITs were: methotrexate (138 patients), cyclophosphamide (48 patients) and tocilizumab (27 patients). No difference was observed as concerns the follow-up time between groups [48.5 (IQR 26-72) vs 40 (IQR 24-69), p ?= ?0.3)]. The first group showed a significantly lower incidence of steroid-induced diabetes (8/114, 7% vs 12/51, 23.5%; p ?= ?0.003) and no differences for the rate of infections (p ?= ?0.64). The group was also exposed to lower doses of GC at first (p ?< ?0.0001) and third (p ?< ?0.0001, rank-sum test) month. Forty-four patients in the first group (38.6%) compared with 34 in the second one (66.7%) experienced at least one relapse (p ?= ?0.001).

Conclusion: Very early introduction of IT in GCA lowered the incidence of steroid-induced diabetes, possibly due to the lower doses of GC in the first three months. Relapse rate was even lower.

SUBMITTER: Quartuccio L

PROVIDER: S-EPMC7718148 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Treatment strategy introducing immunosuppressive drugs with glucocorticoids ab initio or very early in giant cell arteritis: A multicenter retrospective controlled study.

Quartuccio Luca L Isola Miriam M Bruno Dario D Treppo Elena E Gigante Laura L Angelotti Francesca F Capecchi Riccardo R Vitiello Gianfranco G Cavallaro Elena E Tavoni Antonio A Bosello Silvia Laura SL Cammelli Daniele D De Vita Salvatore S Gremese Elisa E

Journal of translational autoimmunity 20201128

<h4>Objective</h4>Glucocorticoids (GC) are associated with side effects in giant cell arteritis (GCA). Immunosuppressive therapies (ITs) have given conflicting results in GCA, regarding GC sparing effect. Primary endpoint is to evaluate whether very early introduction of ITs in GCA minimize the rate of GC-induced adverse events, in terms of infections, new onset systemic arterial hypertension, GC-induced diabetes and osteoporotic fractures.<h4>Methods</h4>A multicenter retrospective case-control ...[more]

PMID: 33305250

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Project description:BackgroundInferential statistical methods failed in identifying reliable biomarkers and risk factors for relapsing giant cell arteritis (GCA) after glucocorticoids (GCs) tapering. A ML approach allows to handle complex non-linear relationships between patient attributes that are hard to model with traditional statistical methods, merging them to output a forecast or a probability for a given outcome.ObjectiveThe objective of the study was to assess whether ML algorithms can predict GCA relapse after GCs tapering.MethodsGCA patients who underwent GCs therapy and regular follow-up visits for at least 12 months, were retrospectively analyzed and used for implementing 3 ML algorithms, namely, Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF). The outcome of interest was disease relapse within 3 months during GCs tapering. After a ML variable selection method, based on a XGBoost wrapper, an attribute core set was used to train and test each algorithm using 5-fold cross-validation. The performance of each algorithm in both phases was assessed in terms of accuracy and area under receiver operating characteristic curve (AUROC).ResultsThe dataset consisted of 107 GCA patients (73 women, 68.2%) with mean age ( ± SD) 74.1 ( ± 8.5) years at presentation. GCA flare occurred in 40/107 patients (37.4%) within 3 months after GCs tapering. As a result of ML wrapper, the attribute core set with the least number of variables used for algorithm training included presence/absence of diabetes mellitus and concomitant polymyalgia rheumatica as well as erythrocyte sedimentation rate level at GCs baseline. RF showed the best performance, being significantly superior to other algorithms in accuracy (RF 71.4% vs LR 70.4% vs DT 62.9%). Consistently, RF precision (72.1%) was significantly greater than those of LR (62.6%) and DT (50.8%). Conversely, LR was superior to RF and DT in recall (RF 60% vs LR 62.5% vs DT 47.5%). Moreover, RF AUROC (0.76) was more significant compared to LR (0.73) and DT (0.65).ConclusionsRF algorithm can predict GCA relapse after GCs tapering with sufficient accuracy. To date, this is one of the most accurate predictive modelings for such outcome. This ML method represents a reproducible tool, capable of supporting clinicians in GCA patient management.

Dataset Information

Treatment strategy introducing immunosuppressive drugs with glucocorticoids ab initio or very early in giant cell arteritis: A multicenter retrospective controlled study.

Publications

Treatment strategy introducing immunosuppressive drugs with glucocorticoids ab initio or very early in giant cell arteritis: A multicenter retrospective controlled study.

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