LDL-cholesterol decrease by anti-PCSK9 monoclonal antibodies: systematic review, meta-analysis and meta-regression of randomized controlled trials

Background

PCSK9 antibodies are novel potent and expansive lipid lowering agents that demonstrated clinical benefit in high risk patients. We hypothesized that optimization of dose and administration schedule, ideally adapted to the target population, could reduce costs while maintaining the clinical benefit.

Objective

To explore the relationship between LDL-Cholesterol (LDL-C) decrease by anti-PCSK9 monoclonal antibodies and several covariates such as drug dose, administration schedule, baseline LDL-C, population and statins.

Methods

We performed systematic review, meta-analysis and meta-regression of randomized controlled trials that compared alirocumab or evolocumab to placebo or no treatment and reported LDL-C decrease, with a minimum follow-up of 12 weeks and with a sample size of 30 patients or more. Electronic searches of MEDLINE, EMBASE, CENTRAL and ClinicalTrials.gov from inception to March 2019. We evaluated the quality of included studies and extracted aggregate data. We used random effect models and multivariate multilevel meta-regression to explore factors influencing LDL-C decrease. All analyses were performed with R.

Results

From 1479 references identified and screened on title/abstract, the full texts of 72 articles were screened. We included 32 studies (31 references.) Anti-PCSK9 mAbs decreased LDL-C by 53%, 95% CI (−56% to −50%), with no significant difference between the two drugs (p=0.07). In univariate meta-regressions, higher baseline LDL-C level, monthly administration, higher percentage of patients with high-dose statins were associated with a lower LDL-C decrease (p<0.0001, p=0.02 and p=0.006 respectively). Drug dose and population did not influence LDL-C decrease in univariate analysis, but with a significant statistical interaction between drug dose and administration schedule (p=0.03). In multivariate meta-regression, LDL-C decrease remained significantly and negatively influenced by baseline LDL-C level

(p<0.0001) and the percentage of patients with high-dose statins (p=0.0009), and was significantly and positively influenced by drug dose (p<0.0001).

Conclusion

Alirocumab and evolocumab showed substantial LDL-C reductions in clinical trials, without significant differences in their biological efficacies. A higher baseline LDL-C, higher intensity of statin co-treatment and a lower dose seemed to negatively influence LDL-C decrease.

Funding Acknowledgement

Type of funding source: None

AB0310 TROUGH CONCENTRATION AND ESTIMATED CLEARANCE CAN DETECT IMMUNOGENICITY TO ADALIMUMAB IN RA PATIENTS: A PROSPECTIVE LONGITUDINAL MULTICENTRE STUDY

Background:

Anti-Drug Antibodies (ADA) to adalimumab increase drug clearance in rheumatoid arthritis (RA).

Objectives:

To study the ability of drug concentration or estimating clearance to identify ADA to adalimumab.

Methods:

Adalimumab concentration was measured with a validated ELISA. ADA was measured using a capture ELISA (Theradiag®) and the Meso scale discovery (MSD) platform. Using a bayesian PK model, adalimumab clearance was estimated at 1, 3, 6 and 12 months. Predictions for ADA presence were calculated, and the correlation between ADA and adalimumab clearance was analysed.

Results:

We analyzed 108 samples from 53 RA patients. Serum concentrations and clearance estimates showed good prediction performance for ADA presence (Table 1). There was a correlation between adalimumab clearance and ADA (Figure 1).

Table 1.

Immunogenicity prediction of adalimumab, using trough concentration or estimated clearance

Time of visitADA methodAdalimumab trough concentrationAdalimumab estimated clearanceAUC ROCp-valueAUC ROCp-valueMonth 1THER.55.6411.52.8358MSD.65.0821.61.1872Month 3THER.89.0006.91.0003MSD.73.0096.72.0131Month 6THER.95.0035.95.0035MSD.85.0004.84.0006Month 12THER.87.0045.86.0057MSD.88.0002.88.0002Figure 1.

correlation between adalimumab estimated clearance and ADA as provided by the Meso scale discovery (MSD) plateform

Conclusion:

Adalimumab concentration and clearance should be considered as reliable predictors for ADA presence in RA patients.

Acknowledgments:

Measurement of adalimumab serum concentrations was performed within the ‘Centre pilote de suivi biologique des anticorps thérapeutiques’ (CePiBAc)– Pilot centre for therapeutic antibodies monitoring platform of Tours University Hospital, which was cofinanced by the European Regional Development Fund (ERDF). We thank Oscar Knight, Delphine Delord and Fabien Giannoni (ABIRISK lab technician), Caroline Brochon and Anne Claire Duveau (CePIBAc), Aliette Decock-Giraudaud (Centre de ressource-Biobank), Sophie Tourdot (ABRISIK Project manager), Aline Doublet (Assistance Publique Hopitaux de Paris, Agnès Hincelin-Méry (Sanofi, Chilly-Mazarin, France). This work has received support from the Innovative Medicines Initiative Joint Undertaking (IMI JU) under grant agreement no. 115303, the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies’ in-kind contributions.

Disclosure of Interests:

David Ternant Consultant of: Sanofi and Amgen., Jamal Elhasnaoui: None declared, Natacha Szely: None declared, Salima Hacein-Bey: None declared, Aude Gleizes: None declared, Christophe Richez Consultant of: Abbvie, Amgen, Mylan, Pfizer, Sandoz and UCB., Jessica Manson: None declared, Martin SOUBRIER: None declared, Olilvier Brocq: None declared, Jérôme Avouac: None declared, Anna Fogdell-Hahn Grant/research support from: Biogen Idec and Pfizer., Consultant of: Pfizer, Biogen, Merck-Serono, and Sanofi-Genzyme., Pierre Dönnes: None declared, Gilles Paintaud Grant/research support from: Amgen, Genzyme (Sanofi), Lilly, Merck, Novartis, and Roche Pharma., Consultant of: Chugai, Novartis and Shire (Takeda), with remunerations received by his institution., Céline Desvignes: None declared, Florian Deisenhammer: None declared, Sebastian Spindeldreher Employee of: Novartis, Marc Pallardy: None declared, Xavier Mariette Consultant of: BMS, Gilead, Medimmune, Novartis, Pfizer, Servier, UCB, Denis Mulleman Grant/research support from: Non-governmental organisation Lions Club Tours Val de France, French Society for Rheumatology., Consultant of: Pfizer, Novartis.