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Why and how to target treatment? Use of subgroup analysis and risk modelling

Why and how to target treatment? Use of subgroup analysis and risk modelling. Peter M Rothwell JLA/Lancet Conference June 2007. Treating individuals. Is this trial relevant to my patient? External validity Is the overall average treatment effect likely to be relevant to my patient?

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Why and how to target treatment? Use of subgroup analysis and risk modelling

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  1. Why and how to target treatment? Use of subgroup analysis and risk modelling Peter M Rothwell JLA/Lancet Conference June 2007

  2. Treating individuals • Is this trial relevant to my patient? • External validity • Is the overall average treatment effect likely to be relevant to my patient? • Subgroup analysis (similar characteristics) • Risk modelling (similar risks)

  3. Clinicians “Anyone who believes that anything can be suited to everyone is a great fool, because medicine is practised not on mankind in general, but on every individual in particular” Henri de Monville, 1320

  4. Methodologists “It is right for each physician to want to know about the behaviour to be expected from the intervention or therapy applied to his individual patient … it is not right, however, for a physician to expect to know this” John W Tukey, 1986 “…. it would be unfortunate if desire for the perfect (i.e. knowledge of exactly who will benefit from treatment) were to become the enemy of the possible (i.e. knowledge of the direction and approximate size of the effects of treatment of wide categories of patient).” Salim Yusuf, Rory Collins & Richard Peto, 1984

  5. Indications for targeting treatment Heterogeneity of treatment effect related to risk • Differences in risks of treatment • Differences in risk without treatment Heterogeneity of treatment effect related to pathophysiology • Multiple pathologies underlying a clinical syndrome • Differences in the biological response to a single pathology • Genetic variation Clinically important questions related to the use of treatment • Does benefit differ with severity of disease? • Does benefit differ with stage in the natural history of disease? • Is benefit related to the timing of treatment after a clinical event? • Is benefit dependent on comorbidity?

  6. Benefit from endarterectomy for symptomatic 50-69% stenosis b n=75 a n=12 d n=7 c n=6 Treatment beneficial Treatment harmful 1 0.1 10 Definite harm Definite benefit Odds ratio and 95% CI

  7. Medicine and the Criminal Justice System Miscarriages of justice versus “Miscarriages of treatment” Wrongful conviction versus “Wrongful treatment”

  8. Population Systematic Review Large Simple Trial Single Variable Subgroup Analysis Small Pragmatic Trial Factorial Subgroup Analysis Small Explanatory Trial Risk Modelling N=1 Trial Individual

  9. Two myths • Subgroup analysis is unreliable • The overall treatment effect is a useful measure of the likely effect of treatment in the average patient

  10. Chance findings in subgroups Astrological Deaths 2P birth sign Aspirin vs Placebo ________________________________________ Libra or Gemini 150 147 ns All other signs 645 869 <0.000001 ________________________________________

  11. 108 50 40 Lacunar stroke 268 Non-lacunar stroke 30 20 884 Absolute risk reduction (95% CI) 453 566 253 10 0 -10 -20 > 30 30-69 70-99 Degree of carotid stenosis (%) C.E.T.C. subgroup analysis: presentation with lacunar vs non-lacunar stroke

  12. 50.0 32.7 70-99% 50-69% 40.0 16.0 30.0 13.8 9.4 11.2 20.0 3.4 ARR (%), 95% CI -2.9 0.0 10.0 0.0 -10.0 -20.0 0-2 2-4 4-12 12+ Weeks between symptomatic event and randomisation Effect of carotid endarterectomy stratified by time from last event to randomisationIpsilateral ischaemic stroke and operative stroke or death Lancet 2004; 363: 915-24

  13. Events / Patients ARR (%) 95% CI Surgical Medical 50-69% stenosis group Fast centres 17 / 174 21 / 127 8.3 -0.1-16.7 Slow centres 29 / 206 11 / 139 -5.6 -12.6-1.4 TOTAL 46 / 380 32 / 266 0.9 -4.5-6.4 -10 0 10 20 30 % Absolute Risk Reduction (95%CI) 70-99% stenosis group Fast centres 11 / 162 31 / 106 23.6 13.7-33.5 Slow centres 35 / 173 30 / 113 6.2 -4.3-16.6 TOTAL 46 / 335 61 / 219 14.7 7.4-21.9 -10 0 10 20 30 % Absolute Risk Reduction (95% CI) Setting: external validity of randomised trials in different healthcare systems

  14. . Events / Patients ARR ECST Subgroup 95% CI Surgical Medical (%) NASCET Age < 65 38 / 374 44 / 271 6.6 1.2-12.1 46 / 345 48 / 276 4.2 -1.7-10.1 65-74 32 / 279 28 / 179 5.1 -1.6-11.8 41 / 318 81 / 362 9.7 3.8-15.7 75+ 6 / 46 9 / 31 18.8 -0.3-37.9 9 / 95 33 / 121 19.2 8.9-29.5 TOTAL 172 / 1454 243 / 1240 8.5 5.7-11.4 -10 0 10 20 30 % Absolute Risk Reduction (95% CI) . Effect of surgery on 5-year risk of ipsilateral ischaemic stroke plus surgical stroke or death 50-99% stenosis Lancet 2004; 363: 915-24

  15. Events/Patients Placebo Trial Active RR 95% CI % ARR 95% CI MRC Trial 109 / 8654 60 / 8700 0.55 0.40 - 0.75 0.12 0.06 - 1.17 STOP Trial 53 / 815 29 / 812 0.53 0.33 - 0.86 1.45 0.45 - 2.45 1 2 0.25 Heterogeneity: p = 0.90 Heterogeneity: p = 0.009 Relative Risk (95% CI) Events/Patients Subgroup Medical % ARR 95% CI Surgical RR 95% CI 5.10 -1.6 - 11.8 Ocular events only 25 / 173 20 / 218 0.63 0.37 - 1.10 16.20 10.7 - 21.6 Cerebral event 118 / 431 70 / 485 0.53 0.40 - 0.69 Heterogeneity: p=0.55 1 0.25 2 Heterogeneity: p=0.01 Relative Risk (95% CI) Absolute risk reductions versus relative risk reductions Lancet 2005; 365; 256-65

  16. Examples of subgroup effects which have subsequently been shown to be false • Aspirin is ineffective in women • Antihypertensive treatment is ineffective for primary prevention in women and in the elderly • Beta-blockers are ineffective after acute MI in the elderlyand in patients with inferior MI • Thrombolysis is inneffective >6 hours after acute MI and in patients with a previous MI • Tamoxifen is ineffective in women aged <50 years Lancet 2005; 365; 176-86

  17. Events / Patients ARR 95% CI (%) Surgical Medical TIME SINCE LAST EVENT < 2 weeks 13 / 112 26 / 75 24.7 12.3-37.1 27 / 213 62 / 224 15.9 8.3-23.5 40 / 325 88 / 299 18.5 12.1-24.9 2-4 weeks 17 / 136 13 / 81 4.4 -5.5-14.2 14 / 132 31 / 134 13.1 4.0-22.2 31 / 268 44 / 215 9.8 3.0-16.5 4-12 weeks 29 / 271 31 / 216 4.1 -2.0-10.2 34 / 289 50 / 282 6.4 0.4-12.5 63 / 560 81 / 498 5.5 1.2-9.8 > 12 weeks 20 / 196 12 / 113 0.7 -6.5-8.0 21 / 125 19 / 119 -3.1 -13.3-7.2 41 / 321 31 / 232 0.8 -5.2-6.8 TOTAL 175 / 1474 244 / 1244 8.5 5.6-11.3 -10 0 10 20 30 ECST NASCET % Absolute Risk Reduction (95% CI) TOTAL Effect of carotid endarterectomy stratified by time from last event to randomisation (50-99% stenosis) Lancet 2004; 363: 915-24

  18. Population Systematic Review Large Simple Trial Single Variable Subgroup Analysis Small Pragmatic Trial Factorial Subgroup Analysis Small Explanatory Trial Risk Modelling N=1 Trial Individual

  19. 50-69% stenosis 70-99% stenosis Age < 65 years 65-74 years 75+ years TOTAL -20 -10 0 10 20 -10 0 10 20 30 40 % Absolute Risk Reduction (95% CI) Effect of surgery on the 5 year risk of ipsilateral ischaemic stroke and surgical stroke or death .

  20. Events/Patients Subgroup Surgical Medical RR 95% CI Time since last event: males <2 weeks 20 / 178 52 / 185 0.39 0.33 - 0.47 2-4 weeks 16 / 139 33 / 136 0.45 0.35 - 0.58 4-12 weeks 37 / 365 60 / 317 0.52 0.43 - 0.64 >12 weeks 19 / 208 27 / 146 0.47 0.36 - 0.61 Time since last event: females <2 weeks 10 / 106 28 / 84 0.28 0.23 - 0.33 2-4 weeks 13 / 94 8 / 57 1.00 0.44 - 2.26 4-12 weeks 19 / 147 16 / 133 1.04 0.54 - 1.99 >12 weeks 17 / 89 3 / 72 4.30 1.48 - 12.46 Total 151 / 1326 227 / 1130 0.55 0.50 - 0.62 0.2 1 5 Relative Risk (95% CI) Effect of carotid endarterectomy stratified by time from last event to randomisation and sexIpsilateral ischaemic stroke and operative stroke or death Interaction: p<0.001 Stroke 2004:35: 2855-61.

  21. Risk model for recently symptomatic carotid stenosis __________________________________________________________ Parameter Hazard Variable DF estimate P ratio __________________________________________________________ Degree of stenosis 1 0.01381 <0.0001 1.014 Near-occlusion 1 -0.84765 0.01 0.428 Male sex 1 0.18913 0.10 1.208 Age (years) 1 0.01509 0.01 1.015 Time since event (d) 1 -0.00445 0.0002 0.996 Presenting event: Ocular event <0.0001 1.0 Single TIA 1 0.09799 1.103 Multiple TIAs 1 0.37263 1.452 Minor stroke only 1 0.43510 1.545 Major stroke 1 0.69452 2.003 Diabetes 1 0.21258 0.08 1.237 Plaque ulcer 1 0.24311 0.01 1.275 Previous MI 1 0.24759 0.06 1.281 Peripheral vasc dis. 1 0.21163 0.09 1.236 Treated hypertension 1 0.36377 0.0004 1.439 __________________________________________________________ Lancet 1999; 353: 2105-10.

  22. Two myths • Subgroup analysis is unreliable • The overall treatment effect is a useful measure of the likely effect of treatment in the average patient

  23. OCSP 25 14 Definite TIAs 12 20 OXVASC 10 15 8 OXVASC Risk of stroke (%) 6 10 Hospital clinic 4 All referrals TIA 5 2 Minor stroke 0 0 0 30 60 90 0 7 14 21 28 Days Days Cumulative risk of stroke after TIA Cumulative risk of stroke TIA vs minor stroke Lancet 2005; 366: 29-36 BMJ 2004; 328: 326-8

  24. Area under curve (95% CI) 0.85 (0.78-0.91) 0.91 (0.86-0.95) 0.80 (0.72-0.89) OXVASC all referrals OXVASC definite TIAs Hospital clinic referrals Validation in US cohorts Risk of stroke at 7 days stratified by ABCD score: OXVASC Lancet 2007;369:283-92 Lancet 2005; 366: 29-36

  25. Risk model for recently symptomatic carotid stenosis __________________________________________________________ Parameter Hazard Variable DF estimate P ratio __________________________________________________________ Degree of stenosis 1 0.01381 <0.0001 1.014 Near-occlusion 1 -0.84765 0.01 0.428 Male sex 1 0.18913 0.10 1.208 Age (years) 1 0.01509 0.01 1.015 Time since event (d) 1 -0.00445 0.0002 0.996 Presenting event: Ocular event <0.0001 1.0 Single TIA 1 0.09799 1.103 Multiple TIAs 1 0.37263 1.452 Minor stroke only 1 0.43510 1.545 Major stroke 1 0.69452 2.003 Diabetes 1 0.21258 0.08 1.237 Plaque ulcer 1 0.24311 0.01 1.275 Previous MI 1 0.24759 0.06 1.281 Peripheral vasc dis. 1 0.21163 0.09 1.236 Treated hypertension 1 0.36377 0.0004 1.439 __________________________________________________________ Lancet 1999; 353: 2105-10.

  26. Lancet 2005; 365; 256-65.

  27. Benefit from endarterectomy for symptomatic 50-69% stenosis b n=75 a n=12 d n=7 c n=6 Treatment beneficial Treatment harmful 1 0.1 10 Definite harm Definite benefit Odds ratio and 95% CI

  28. Two myths • Subgroup analysis is unreliable • The overall treatment effect is a useful measure of the likely effect of treatment in the average patient

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