Indirect Evidence: Indirect Treatment Comparisons in Meta-analysis

Transcription

1 Evdence: Treatment Comparsons n Meta-analyss analyss George Wells, Shagufta Sultan, L Chen, Doug Coyle Current Issues for Health Technology Assessment n Canada An Invtatonal Symposum for HTA Researchers and Polcy Maers Aprl 25-26, 26, 2005 Ottawa, Onatro

2 The Problem Drect Comparson: RCT A B Comparson: RCT B RCT A C

3 The Problem Snce placebo controlled trals are usually suffcent for acqurng regulatory approval of a new drug, there s no motvaton from the commercal sector to compare the new drug wth exstng actve treatments Placebo New Drug Exstng Drug

4 The Problem If current standard treatment s effectve then placebo controlled trals may not be possble and new drugs are compared only wth actve treatments and there s no comparson of the new drug to placebo yeldng the true effect of the drug Standard New Drug Placebo

5 Methods Proposed Bucher approach for ndrect comparsons (Bucher et al J Cln Epdemol 997) Networ meta-analyss for ndrect comparsons (Lumley Statstcs n Medcne 2002) Models for mult-parameter synthess and consstency of evdence (Ades Statstcs n Medcne 2003) Combnaton of drect and ndrect evdence n mxed comparsons (Lu Statstcs n Medcne 2004)

6 Objectves The objectves are: to derve methods and procedures for contnuous outcomes to develop approaches for more complex webs of evdence for both dscrete and contnuous outcomes to mae ths methodology more readly avalable to revewers

7 A 2 A 3 A A 4 Estmate Drect Estmates A 5 A A 6

8 Methods effect estmators and tests of assocaton for the effect measures odds rato, relatve rs, rs dfference and mean dfference were algebracally derved Usng Monte Carlo smulatons the dstrbutonal propertes of the ndrect effect estmators were assessed A revewer-frendly program was developed to facltate the evaluaton of ndrect evdence for revewers

9 Methods effect estmators and tests of assocaton for the effect measures odds rato, relatve rs, rs dfference and mean dfference were algebracally derved Usng Monte Carlo smulatons the dstrbutonal propertes of the ndrect effect estmators were assessed A revewer-frendly program was developed to facltate the evaluaton of ndrect evdence for revewers

10 Methods: Theory effect estmators and tests of assocaton A generalzaton of the approach for the ndrect odds rato by Bucher et al for more complex webs of evdence nvolvng drect comparsons was developed Ths generalzed approach was then consdered for the relatve rs, rs dfference and mean dfference.

11 OR A 2 A 3 OR A A 2 A 2 A 3 OR A 3 A 4 A Odds Rato A 4 Estmate OR = OR + OR A 4 A 5 A 5 A A 6 OR A 5 A 6 ORA A

12 RR A 2 A 3 RR A A 2 A 2 A 3 RR A 3 A 4 A Relatve Rs A 4 Estmate RR = RR + RR A 4 A 5 A 5 A A 6 RR A 5 A 6 RRA A

13 RD A 2 A 3 RD A A 2 A 2 A 3 RD A 3 A 4 A Rs Dfference A 4 Estmate RD = RD + RD A 4 A 5 A 5 A A 6 RD A 5 A 6 RDA A

14 MD A 2 A 3 MD A A 2 A 2 A 3 MD A 3 A 4 A Mean Dfference A 4 Estmate MD = MD + MD A 4 A 5 A 5 A A 6 MD A 5 A 6 MDA A

15 MD A A α 2 A A + + ± Z / Var MD ) ( Effect Sze Estmators Estmator Confdence Interval Estmator OR OR = OR + exp ln( OR ) ± Z (ln( )) + α / 2 Var ORA A + RR RR = RR + exp ln( RR ) ± Z (ln( )) + α / 2 Var RRA A + RD RD = RD + RD ± + Z α / 2 Var( RDA ) A + MD MD = MD + MD ± + Z α / 2 Var( MDA ) A +

16 Test Statstc for Assocaton Test Statstc for Assocaton = = + + ± 2 / ) ( A A MD Var Z MD α = = = = + = = = , 2 2 ',, 2 ' ' ' ' ' ' ) ( h j j A A h j j A A h j j assocaton AA A A AA W EM EM W W χ Effect measure (EM): OR, RR, RD, MD

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18 Methods effect estmators and tests of assocaton for the effect measures odds rato, relatve rs, rs dfference and mean dfference were algebracally derved Usng Monte Carlo smulatons the dstrbutonal propertes of the ndrect effect estmators were assessed A revewer-frendly program was developed to facltate the evaluaton of ndrect evdence for revewers

19 Methods: Smulatons Descrpton of the Smulaton Process (e.g. =3 for RR)

20 Bas and Mean Square Error Frequency dstrbuton of drect and ndrect estmates (=3) Drect Relatve Rs

21 Bas and Mean Square Error Frequency dstrbuton of drect and ndrect estmates (=3) Drect Odds Rato

22 Bas and Mean Square Error Frequency dstrbuton of drect and ndrect estmates (=3) Drect Rs Dfference

23 Bas and Mean Square Error Frequency dstrbuton of drect and ndrect estmates (=3) Drect Mean Dfference

24 Bas and Mean Square Error Bas: Drecton of bas for drect and ndrect estmates (=3)

25 Bas and Mean Square Error Bas: Drecton of bas for drect and ndrect estmates (=4)

26 Bas: Drect

27 MSE: Drect

28 Methods effect estmators and tests of assocaton for the effect measures odds rato, relatve rs, rs dfference and mean dfference were algebracally derved Usng Monte Carlo smulatons the dstrbutonal propertes of the ndrect effect estmators were assessed A revewer-frendly program was developed to facltate the evaluaton of ndrect evdence for revewers

29 Program Input:. Chec crcle ndcatng effect estmate of nterest 2. Select the number treatments (maxmum 0) 3. For each consecutve par of treatments provde the drect estmates of the measure of assocaton and the 95% lower and upper confdence lmts. The order of entry of the treatment pars must follow the exact sequence ndcated wth the brdgng comparson groups lnng the treatment pars

30 Illustraton Gven the weghted relatve rs of non-vetebral fracture after treatment wth a bsphosphonate (etdronate or alendronate) compared to placebo the relatve rs of a head to head comparson of alendronate to raloxfne Then Usng the ndrect treatment comparson method s used to evaluate a comparson of etdronate to raloxfne the placebo and alendronate as the brdgng groups n the 2-step comparson (=4)

31 Etdronate.07(0.72,.60) Placebo (0.64, (0.48,5.62) 0.92).30 (.09,.56) Alendronate Raloxfene.8 (0.38,3.80)

32 Illustraton estmate of Relatve Rs (RR) of non-vertebral fracture (secondary preventon): Etdronate and Raloxfene # of Trals # of Partcpants (trt / control) RR (95%CI) Etdronate: 5 32 / (0.72,.60) Placebo Placebo: / (.09,.56) Alendronate Alendronate: 246 / 24.8 (0.38,3.80) Raloxfene Etdronate:.64 (0.48,5.62) Raloxfene

33 Concluson A methodology for ndrect evdence for both contnuous and dscrete outcomes have been developed Bas and mean square error for the ndrect estmates ndcate that care must be taen n nterpretng these estmates A program to execute the requred computatons when consderng ndrect evdence was developed

34 Evdence: Treatment Comparsons n Meta-analyss analyss George Wells, Shagufta Sultan, L Chen, Doug Coyle The authors acnowledge the capacty buldng grant from CCOHTA for fundng ths research The vews expressed heren represent the vews of the authors and do not necessarly represent the vews of Health Canada or any provncal or terrtoral government