Advanced Issues in Multiple Treatment Comparison Meta-analysis

Transcription

1 Advanced Issues in Multiple Treatment Comparison Meta-analysis Edward Mills PhD, MSc, MSt (1,2) Kristian Thorlund PhD, MStat (2) John Ioannidis MD, DSc (3) 1) Faculty of Health Sciences, University of Ottawa 2) Dept of Clinical Epidemiology & Biostatistics, McMaster University 3) Stanford Prevention Research Center

2 Indirect comparisons Drug A Drug B Drug C 2

3 Additive treatment effects First proposed by Yusuf in 2002 (1) More recently evaluated in polypill metaanalysis and subsequent RCTs (2,3) Requires certain assumptions 1) Yusuf S Two decades of progress in preventing vascular disease. Lancet, 2002, 360:2-3. 2) Wald NJ, Law MR A strategy to reduce cardiovascular disease by more than 80%. BMJ, 2003, 326: ) Yusuf S, Pais P, Afzal R, Xavier D, Teo K, Eikelboom J, et al. s of a polypill (Polycap) on risk factors in middle-aged individuals without cardiovascular disease (TIPS): a phase II, double-blind, randomised trial. Lancet, 2009, 373:

4 Additive treatment effects Combination drug A, B, C RR A vs placebo RR 0.80 B vs placebo RR 0.85 C vs placebo RR x 0.85 x 0.85 = 0.58

5 Additivity A B AB

6 Antagonistic A B A AB B

7 B Synergetic A B A AB

8 Additivity ICS vs. Placebo (RR = 0.81) ICS + LABA (RR = 0.81x0.87 = 0.70) LABA vs. Placebo (RR = 0.87) ICS + LABA vs. Placebo (RR = 0.72)

9 Assumptions required Additivity assumption should be reasonable. Drugs working on similar pathways are more likely to interfere with each other, leading to interactions. For drugs working on different pathways, interaction is less likely. Both for drugs and for other types of interventions, clinical and other evidence should also need to be considered on whether interactions may exist.

10 Potential biases in effects of single treatments comprising the combination should be scrutinized. Biases affecting evidence on direct and indirect comparisons of single treatments can affect also secondarily the calculations of the effect sizes for combinations of these treatments. If such biases are demonstrated or speculated, interpretation of additive effects obtained from biased component effects should be very cautious.

11 Whenever MTC is used to obtain additive effects, the assumptions underlying the MTC should be tenable. MTC makes several assumptions that underlie the ability to combine data from different trials and comparisons performed in different populations and settings with potentially different baseline risk and background standards of care among others; it is important that the combined pieces are consistent and no major statistical inconsistency is demonstrated.

12 Additive effects should be expressed along with their accompanying uncertainty (95% CIs or CrI) and this can often be large. Large uncertainty may be common when the components of the evidence that feed in the additivity calculations have large uncertainty by themselves. In the presence of large uncertainty, interpretation should be extra cautious.

13 Wherever possible, the additive effects should be compared to direct combination effects. We need more empirical evidence on whether direct and additive effects tend to give similar or dissimilar results.

14 Sample network ICS( ICS+LABA( Roflumilast+LABA( LABA( Placebo( Roflumilast( Roflumilast+LAMA( LAMA( LABA+LAMA( ICS+LABA+LAMA(

15 Assumptions with COPD 1) Is the additivity assumption reasonable? Although both LABAs and LAMAs exert a therapeutic effect by targeting smooth muscle, they work through different pathways and evidence from RCTs indicates that they offer different therapeutic advantages, thus interaction is unlikely.

16 2) Are there potential biases in the effects of the single treatments? No major problems with the quality of reporting Some small sample sizes The evidence is not evenly spread across all comparisons.

17 3) Are the assumptions underlying an MTC appropriate? Populations included within each agent, those with moderate to severe chronic obstructive pulmonary disease, are considered similar enough to combine in meta-analyses, and none of the direct comparisons have very high estimates of statistical heterogeneity.

18 4) Are the treatment findings presented with accompanying uncertainty? We present results using the IRR of exacerbations (ratio of the total number of exacerbations per patient-years in the two compared arms) with accompanying confidence intervals.

19 5) Are the additive effects consistent with the direct combination effects? Check with direct estimates Eyeballing Statistical tests unlikely to be informative

20 PDE4-i + LABA vs. LABA ( ) PDE4-i vs Placebo * ( ) 0.84( ) ICS + LABA vs LABA ( ) ICS vs Placebo * ( ) 0.82( ) PDE4-i + LAMA vs. LAMA ( ) PDE4-i vs Placebo* ( ) 0.84( ) LABA + LAMA vs. LAMA ( ) LABA vs Placebo * ( ) 0.86( ) ICS + LABA + LAMA vs LABA + LAMA ( ) ICS vs Placebo * ( ) 0.82( ) ICS + LABA vs Placebo ( ) ICS vs Placebo + LABA vs Placebo ( ) 0.71( ) ICS + LABA + LAMA vs LAMA ( ) ICS vs Placebo + LABA vs Placebo * ( ) 0.71( ) ICS + LABA vs LAMA ( ) ICS + LABA vs Placebo - LAMA vs Placebo ( ) 0.96( )

21 Interpretation Additive effects will require further validation Adverse events should be considered Are they elevated? Additive effects appear to be real in COPD, migraine, BP

22 Thank you