Indirect comparisons of ranibizumab and dexamethasone in macular oedema secondary to retinal vein occlusion

BMC Medical Research Methodology

Alberto Ferreira²  Richard M Nixon²  Gorana Capkun²  Howard HZ Thom¹ 

[1]School of Social and Community Medicine, University of Bristol, Bristol, UK

[2]Novartis Pharma, Basel, Switzerland

关键词: Indirect comparison;    Evidence synthesis;    Macular oedema;    Branch retinal vein occlusion;    Central retinal vein occlusion;    Retinal vein occlusion;    Dexamethasone;    Ranibizumab;   

Others  :  1090160
DOI  :  10.1186/1471-2288-14-140

 received in 2014-09-10, accepted in 2014-12-19,  发布年份 2014

【 摘 要 】

Background

Two treatments, ranibizumab and dexamethasone implant, for visual impairment due to macular oedema (ME) secondary to retinal vein occlusion (RVO) have recently been studied in clinical trials. There have been no head to head comparisons of the two treatments, and improvement measured as gain in Best Corrected Visual Acuity (BCVA) was reported using different outcomes thresholds between trials. To overcome these limitations, and inform an economic model, we developed a combination of a multinomial model and an indirect Bayesian comparison model for multinomial outcomes.

Methods

Outcomes of change from baseline in BCVA for dexamethasone compatible with those available for ranibizumab, reported by 4 randomised controlled trials, were estimated by fitting a multinomial distribution model to the probability of a patient achieving outcomes in a range of changes from baseline in BCVA (numbers of letters) at month 1. A Bayesian indirect comparison multinomial model was then developed to compare treatments in the Branch RVO (BRVO) and Central RVO (CRVO) populations.

Results

The multinomial model had excellent fit to the observed results. With the Bayesian indirect comparison, the probabilities of achieving ≥20 letters, with 95% credible intervals, at month 1 in patients with BRVO were 0.191 (0.130, 0.261) with ranibizumab and 0.093 (0.027, 0.213) with dexamethasone. In patients with CRVO, probabilities were 0.133 (0.082, 0.195) (ranibizumab) and 0.063 (0.016, 0.153) (dexamethasone). Probabilities of a gain in ≥10 letters in BRVO patients were 0.500 (0.365, 0.650) v 0.459 (0.248, 0.724) and in CRVO patients 0.459 (0.332, 0.602) v 0.498 (0.263, 0.791) for ranibizumab and dexamethasone treatments respectively. The comparisons also favoured ranibizumab at month 6 although changes to therapies after month 3 may have introduced bias.

Conclusion

The newly developed combination of multinomial and indirect Bayesian comparison models indicated a trend for ranibizumab association with a greater percentage of ME patients achieving visual gains than dexamethasone at months 1 and 6 in a common clinical context, although results were not classically significant. The method was a useful tool for comparisons of probability distributions between clinical trials that reported events on different categorical scales and estimates can be used to inform economic models.

【 授权许可】

   
2014 Thom et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

【 参考文献 】

• [1]Klein R: Retinopathy in a population-based study. Trans Am Ophthalmol Soc 1992, 90:561-594.
• [2]Gewaily D, Greenberg PB: Intravitreal steroids versus observation for macular edema secondary to central retinal vein occlusion. Cochrane Database Syst Rev 2009., 1http://www.ncbi.nlm.nih.gov/pubmed/19160332 webcite
• [3]Reshak J, Reshak M: Branch retinal vein occlusion: pathogenisis, visual prognosis, and treatment modalities. Curr Eyes Res 2008, 33:111-131.
• [4]Group CRVOS: Natural history and clinical management of central retinal vein occlusion. Arch Ophthalmol 1997, 115:486-491.
• [5]Group SSR: A randomized trial comparing the efficacy and safety of intravitreal triamcinolone with standard care to treat vision loss associated with macular edema secondary to branch retinal vein occlusion: the Standard Care vs Corticosteroid for Retinal Vein Occlusion (SCORE) Study report 6. Arch Ophthalmol 2009, 127:1115-1128.
• [6]Mohamed Q, McIntosh RL, Saw SM, Wong TY: Interventions for central retinal vein occlusion: an evidence-based systematic review. Ophthamology 2007, 114:507-519,524.
• [7]Campochiaro PA, Heier JS, Feiner L, Gray S, Saroj N, Rundle AC, Murahashi WY, Rubio RG: Ranibizumab for macular edema following branch retinal vein occlusion. Six-month primary End point results of a phase III study. Ophthamology 2010, 117:1102-1112.
• [8]Brown DM, Campochiaro PA, Singh RP, Li Z, Gray S, Saroj N, Rundle AC, Rubio RG, Murahashi WY: Ranibizumab for macular edema following central retinal vein occlusion. Six-month primary End point results of a phase III study. Ophthamology 2010, 117:1124-1133.
• [9]Haller JA, Bandello F, Belfort R Jr, Blumenkranz MS, Gillies M, Heier J, Loewenstein A, Yoon YH, Jacques ML, Jiao J, Li XY, Whitcup SM, OZURDEX GENEVA Study Group: Randomized, sham-controlled trial of dexamethasone intravitreal implant in patients with macular edema Due to retinal vein occlusion. Ophthamology 2010, 117:1134-1136.
• [10]Allergan: Dexamethasone Intravitreal Implant (Ozurdex®) for the Treatment of Macular Oedema Caused by Retinal Vein Occlusion. Single Technology Appraisal. London, UK: National Institute for Health and Care Excellence; 2010.
• [11]Abel K, Black D, Bryden D: TA229 Dexamethasone intravitreal implant for the treatment of macular oedema caused by retinal vein occlusion (RVO). NICE Technology Appraisals 2011.
• [12]Matza LS, Rousculp MD, Malley K, Boye KS, Oglesby A: The longitudinal link between visual acuity and health-related quality of life in patients with diabetic retinopathy. Health Qual Life Outcomes 2008., 6http://www.hqlo.com/content/6/1/95 webcite
• [13]Kinge B, Stordahl PB, Forsaa V, Fossen K, Haugstad M, Helgesen OH, Seland J, Stene-Johansen I: Efficacy of ranibizumab in patients with macular edema secondary to central retinal vein occlusion: results from the sham-controlled ROCC study. Am J Ophthalmology 2010, 150:310-314.
• [14]NICE: Single Technology Appraisal (STA). Specification for Manufacturer/Sponsor Submission of Evidence. National Institute for Health and Clinical Excellence; 2009.
• [15]Lasdon LS, Waren AD, Jain A, Ratner M: Design and testing of a generalized reduced gradient code for nonlinear programming. ACM Transactions on Mathematical Software 1978, 4:34-50.
• [16]Ades A, Mavranezouli M, Dias S, Welton N, Whittington C, Kendall T: Network meta-analysis with competing risk outcomes. Value Health 2010, 13:976-983.
• [17]Trikalinos T, Olkin I: A method for the meta-analysis of mutually exclusive binary outcomes. Statistcs in Medicine 2008, 27:4279-4300.
• [18]Dias S, Welton NJ, Sutton AJ, Ades AE: NICE DSU Technical Support Document 2: A Generalised Linear Modelling Framework for Pairwise and Network Meta-Analysis of Randomised Controlled Trials, 2011. National Institute for Health and Care Excellence; 2014. last updated April 2014; available from http://www.nicedsu.org.uk webcite
• [19]Bucher HC, Guyett GH, Griffith LE, Walter SD: The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol 1997, 50:683-691.
• [20]Lunn DJ, Thomas A, Best N, Spiegelhalter D: WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 2000, 10:325-337.
• [21]Caldwell DM, Ades AE, Higgins JPT: Simultaneous comparison of multiple treatments: combining direct and indirect evidence. BMJ 2005, 331:897-900.
• [22]Lu G, Ades AE: Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 2004, 23:3105-3124.
• [23]Welton NJ, Sutton AJ, Cooper NJ, Abrams KR, Ades AE: Evidence Synthesis for Decision Making in Healthcare. Chichester, West Sussex, UK: John Wiley and Sons; 2012.
• [24]Sweeting MJ, Sutton AJ, Lambert PC: What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. Stat Med 2004, 23:1351-1375.
• [25]Sutton A, Ades AE, Cooper N, Abrams K: Use of indirect and mixed treatment comparisons for technology assessment. Pharmacoeconomics 2008, 26:753-767.
• [26]Turner RM, Spiegelhalter DJ: Bias modelling in evidence synthesis. JR Statist Soc A 2009, 172:21-47.