Network meta-analysis (NMA) is becoming increasingly important for decision makers to assess the comparative efficacy and safety of interventions and is integral to health technology assessment (HTA). Trials included within an NMA should be comparable in terms of potential effect modifiers across all interventions (or analyses should adjust for these). The exploration of covariate effects is important in NMA because the presence of unaccounted treatment‑covariate interactions can invalidate the assumptions which underlie NMA and bias results. Further, the inclusion of covariates in NMA has implications for precision medicine as it allows estimates of relative treatment effect beyond an overall mean – facilitating more tailor‑made patient decisions (i.e. where optimal treatment will differ for patients depending on their characteristics).

Meta‑regression methods allow for differences on study‑level characteristics to be adjusted by including a treatment effect interaction term in the NMA model. Meta‑regression allows a holistic analysis exploring the impact of covariates on all of the data and can be applied to allow the simultaneous consideration of multiple covariates.

In a recently published paper, we present a series of exploratory network-meta-regression analyses for stroke prevention in atrial fibrillation as part of a collaborative project with leading academics at Leicester University (1). We highlight that evidence networks of recent NMAs in this indication have been restricted to comparators of primary interest to decision makers (2-6). This limits the size of the network so that robust meta-regression analyses are not feasible – despite the authors of these studies acknowledging the presence of heterogeneity within their networks (2-6). Our research demonstrates the potential benefit of extending decision problems to include additional comparators, not simply those of primary interest to the decision maker. This could provide sufficient statistical power to allow the application of meta-regression methods. Covariates explored in our research included the proportion of patients with a previous stroke, proportion of males, mean age, the duration of study follow‑up, and the underlying risk of stroke.

The approach presented in our publication highlights the potential benefit of extending the decision problems in any indication to permit the exploration of network heterogeneity using meta‑regression methods. In addition, it was also concluded in a recently published case study that extending an evidence network up to three times did not increase heterogeneity or inconsistency in the dataset (7). It is recommended that the extension of a decision problem should be considered alongside the potential introduction of additional heterogeneity.

For further information on any aspects of SR and NMA please contact our in-house experts by emailing Access@TeamDRG.com

 

References

  1. Batson S, Sutton A, K A. Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect. PLoS One. 2016;11(8):e0161864.
  2. Cameron C, Coyle D, Richter T, Kelly S, Gauthier K, Steiner S, et al. Systematic review and network meta-analysis comparing antithrombotic agents for the prevention of stroke and major bleeding in patients with atrial fibrillation. BMJ open. 2014;4(6):e004301.
  3. Fu W, Guo H, Guo J, Lin K, Wang H, Zhang Y, et al. Relative efficacy and safety of direct oral anticoagulants in patients with atrial fibrillation by network meta-analysis. J Cardiovasc Med (Hagerstown). 2014;15(12):873-9.
  4. Messori A, Fadda V, Maratea D, Trippoli S, Marinai C. Testing the therapeutic equivalence of novel oral anticoagulants for thromboprophylaxis in orthopedic surgery and for prevention of stroke in atrial fibrillation. Int J Clin Pharmacol Ther. 2015;53(3):211-9.
  5. Verdecchia P, Angeli F, Bartolini C, De Filippo V, Aita A, Di Giacomo L, et al. Safety and efficacy of non-vitamin K oral anticoagulants in non-valvular atrial fibrillation: a Bayesian meta-analysis approach. Expert Opin Drug Saf. 2015;14(1):7-20.
  6. Lip GY, Mitchell SA, Liu X, Liu LZ, Phatak H, Kachroo S, et al. Relative efficacy and safety of non-Vitamin K oral anticoagulants for non-valvular atrial fibrillation: network meta-analysis comparing apixaban, dabigatran, rivaroxaban and edoxaban in three patient subgroups. International Journal of Cardiology 2015.
  7. Dequen P, Sutton AJ, Scott DA, Abrams KR. Searching for indirect evidence and extending the network of studies for network meta-analysis: case study in venous thromboembolic events prevention following elective total knee replacement surgery. Value Health. 2014;17(4):416-23.

 

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