PRE-STRATIFIED RANDOMIZATION IS NOT NECESSARY FOR LARGE CLINICAL TRIALS Brent Leininger, Patrick Kurkiewicz, Lifeng Lin, Xiang Li, Bryan Trottier Jr, Yuanyuan.

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Presentation transcript:

PRE-STRATIFIED RANDOMIZATION IS NOT NECESSARY FOR LARGE CLINICAL TRIALS Brent Leininger, Patrick Kurkiewicz, Lifeng Lin, Xiang Li, Bryan Trottier Jr, Yuanyuan Wang

Pre-stratification is Insurance

Risk of Chance Imbalance As Sample Size Increases…..

1 Allocation Schedule per Strata 1 stratification variable with 2 levels Increased potential for errors Administrative Burden

Misclassification of Strata Multi-center variability Timing

Pocock SJ, Assmann SE, Enos LE, Kasten LE. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Stat Med Oct 15;21(19):

111 of 258 trials balanced on prognostic factors (other than center) 36% of trials accounted for stratification in the analysis Accounting for stratification variables in the analysis is recommended by both ICH and CONSORT guidelines

Pocock SJ, Assmann SE, Enos LE, Kasten LE. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Stat Med Oct 15;21(19):

Alternatives Post-stratification (i.e. adjusted analysis) Efficiency Loss vs. Pre-Stratification? 4 strata, 80 patients per strata Efficiency loss is <4% McHugh R, Matts J. Post-stratification in the randomized clinical trial. Biometrics Mar;39(1):

Post-Stratification Criticism Define covariates ‘a priori’ OR….. Define plan for covariate selection ‘a priori’ Pocock SJ, Assmann SE, Enos LE, Kasten LE. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Stat Med Oct 15;21(19):

Conclusions

CLAIM: PRE-STRATIFIED RANDOMIZATION IS OFTEN NECESSARY FOR LARGE (N > 100 PER GROUP) CLINICAL TRIALS Helps ensure that compared groups are similar with respect to known important prognostic factors Potential benefits, even in large clinical trials 1 Protection against Type 1 Error Reduction of sample size in equivalence trials Facilitation of interim analyses Identification of subgroups prior to analysis Protection against treatment assignment imbalance with recruitment-center dropout in multicenter trial 1 Kernan et al. J Clin Epidemiol (1999)

UGANDA STUDY: IMMEDIATE VS. DELAYED IRON IN SEVERE MALARIA Children with severe malaria randomized to immediate or delayed iron Primary outcome = frequency of hospital admissions in next 12 months Severe malaria includes cerebral malaria and severe malarial anemia Children with severe malarial anemia have greater risk of readmission to hospital

UGANDA STUDY: IMMEDIATE VS. DELAYED IRON IN SEVERE MALARIA 79 CM 40 Immediate39 Delayed R 77 SMA 39 Immediate38 Delayed R THISNOT THIS 156 SEVERE MALARIA 78 Immediate ?? SMA ?? CM 78 Delayed ?? SMA ?? CM R Pre-stratified randomizationUn-stratified randomization

BENEFITS OF PRE-STRATIFICATION Protection against Type 1 error 1 1 Feinstein and Landis in Kernan et al. J Clin Epidemiol (1999)

BENEFITS OF PRE-STRATIFICATION Smaller sample size in equivalence trials Reduction in sample size by 12-42% over a range of assumptions (Nam, Stat Med 1995) Significant savings in both cost and time Facilitation of interim analyses Interim DSMB meeting for iron/malaria study March 2013 (!) 79 CM (40 I, 39 D) ; 78 SMA (39 I, 38 D) Frequency of serious adverse events in I vs. D. If not balanced, potential safety concern undetected

BENEFITS OF PRE-STRATIFICATION Subgroup analysis Strata identified before start of study Protects against multiple comparisons Strengthens a finding of treatment effectiveness within subgroups Multicenter study—protection against drop-out Because patients in each center are balanced for treatment assignment, withdrawal of a center will not result in imbalance among remainder of patients.

CLAIM: PRE-STRATIFIED RANDOMIZATION IS OFTEN NECESSARY FOR LARGE (N > 100 PER GROUP) CLINICAL TRIALS Against 1.Too many strata 2.Challenge to implement 3.Not necessary For 1.Protection against Type 1 error 2.Reduced sample size in equivalence trials 3.Balanced interim analyses 4.Pre-specified subgroup analyses 5.Protection against drop-out in multicenter studies