Predictors of remission in rheumatoid arthritis patients treated with biologics: a systematic review and meta-analysis

Abstract

Biologics have emerged as an effective treatment of rheumatoid arthritis (RA). However, there is a significant proportion of patients who fail to respond to biologics. Identifying the predictors that affect the response to biologics remains challenging. A comprehensive literature search of PubMed, Embase, and Web of Science databases was conducted through May 1, 2022. We included all studies that used a multivariate model to assess for the predictors of remission in RA patients treated with biologics. We calculated pooled odds ratios (OR) with 95% confidence intervals (CI) for risk factors reported in ≥ 3 studies using a random-effects model. A total of 16,934 patients with RA who were treated with biologics were included in twenty-one studies. Our study showed that old age (OR 0.98 (0.97, 0.99), P < 0.00001), female gender (OR 0.66 (0.56, 0.77), P < 0.00001), smoking history (OR 0.86 (0.75, 0.99), P 0.04), obesity (OR 0.95 (0.91, 0.99), P 0.02), poor functional status (OR 0.62 (0.48, 1.27), P < 0.00001), high disease activity (OR 0.90 (0.85, 0.96), P 0.0005), and elevated erythrocyte sedimentation rate (OR 0.99 (0.98, 1.00), P 0.009) were poor predictors of remission. On the other hand, positive anti-citrullinated protein antibodies (OR 2.52 (1.53, 4.12), P 0.0003) was associated with high remission rate. Old age, female gender, obesity, smoking history, poor functional status, high disease activity, and elevated ESR at the time of diagnosis have been associated with poor response to biologics. Our findings could help establish a risk stratification model for predicting the remission rate in RA patients receiving biologics.

Orthorexia Nervosa Practices in Rheumatoid Arthritis: The DORA Study

“…Due to the heterogenous manifestations of the disease, remission and prognosis are difficult to predict [ 70 ]. Subsequently, contradictory factors have been associated with remission in the literature among patients with RA, including older age, female gender, obesity status, history of smoking, comorbidities, fewer EAMs, use of DMARDs, treatment with GC, poor functional status, increased disease activity and erythrocyte sedimentation rate (ESR) at the time of diagnosis [ 41 , 71 , 72 , 73 ]. All of the evidence points to the fact that relapse in RA is difficult to predict.…”

“…In addition, a multivariable logistic model was built with remission as the dependent variable, and with the following independent variables: gender (male versus female), BMI (kg/m 2 ), educational level (up to high school versus higher education), smoking status (no versus yes) and RA duration (years) [ 41 , 42 ], plus the ORTO-15. Age was left out of this model due to 15 missing/illegible values.…”

Translational immunology: Applying fundamental discoveries to human health and autoimmune diseases

“…No single therapy works for everyone, therapeutic efficacy varies among patients, and targeting a single immune pathway is rarely 100% effective. Again, turning to RA, 30-40% of treatment naïve patients do not have adequate responses to current therapies [20][21][22][23][24][25]. This is despite tremendous advances in the treatment of RA and the growing number of types of drugs available in the clinic.…”

Harmonizing Medicine and Surgery in the Pursuit of Boolean Remission: A Rheumatological Magnum Opus

“…Advanced imaging techniques, such as musculoskeletal ultrasound and magnetic resonance imaging, can provide detailed assessments of joint inflammation and damage [ 31 ]. Biomarkers, including genetic markers and novel serological indicators, may enhance the accuracy and specificity of Boolean remission criteria [ 32 ]. These innovations can lead to more precise disease monitoring and treatment optimization.…”