2019 Joint Statistical Meetings at Denver Using the retrieved dropout approach for estimating a treatment policy estimand Ruvie Martin* and Bjoern Bornkamp 30 July 2019, Denver, Colorado 2019 Joint Statistical Meetings

Outline ICH E9(R1) Addendum Study Information and Estimand for the Primary Objective Using the Retrieved Dropout Approach Implementation Conclusion

ICH E9 (R1) Addendum

ICH E9 Addendum on estimands and sensitivity analysis in clinical trials More detailed description of the treatment effect of interest and the trial objective is required. Intercurrent events have to be taken into account at the estimand/"trial objective" level not the statistical analysis/missing data-handling level. The difference of intercurrent events and missing data

Estimand Estimand description Together these attributes describe the defining the target of estimation Intercurrent event strategies Treatment policy strategy Composite strategy Hypothetical strategy Principal stratum strategy While on treatment strategy Bretz (2017) How the ICH E9 addendum around estimands may impact our clinical trials. Cancer Drug Development Forum

Study Information and Estimand for the Primary Objective

Background A 2-year open label study to compare Treatment A versus Treatment B Endpoint of Interest – imaging endpoint done by independent readers measured at Week 104 The primary objective is to demonstrate the proportion of subjects on Treatment A with successful response at Week 104 is superior to subjects on Treatment B

Estimand of the Primary Objective The primary objective is to demonstrate the proportion of subjects on Treatment A with successful response at Week 104 is superior to subjects on Treatment B. Population – defined through appropriate inclusion/exclusion criteria to reflect the targeted disease population Variable of Interest – binary response variable indicating successful response Intercurrent event – details on the next slides Population-level summary – treatment difference in proportions of responders between Treatment A and Treatment B FAS is the analysis set, what will be used for analysis while population is the group of patients Business Use Only

Expected Intercurrent Events Subject switching to commercial drug (non study drug) Subject not taking the study drug nor commercial drug because of tolerability issues Subject discontinuing study drug nor taking commercial drug because of the following: adverse event/s, pregnancy, physician decision, subject/guardian decision

Which intercurrent event handling strategy? Health Authority suggested using the treatment policy strategy since it will be reflective of clinical practice and thus will provide a clinically meaningful estimate Treatment policy strategy will be used for all intercurrent events The occurrence of the intercurrent event is irrelevant; the value for the variable of interest is used regardless of whether or not the intercurrent event occurs

Treatment Policy Strategy and Study Conduct Treatment policy strategy can only be implemented when values for the variable after the intercurrent events exist To help minimize missing data (1) protocol and ICF clearly differentiate treatment discontinuation from study withdrawal (2) site investigators are trained to understand the importance of subject retention and the prevention of missing data (3) consent forms include a statement educating subjects about the continued scientific importance of their data even if they discontinue study treatment early (4) the protocol recommends that attempts be made to contact subjects who fail to actively maintain contact with the investigator

Breakdown of subjects Subjects who will finish the study and provide Week 104 data Retrieved Dropout Subjects Subjects who will discontinue study drug but will remain in the study and provide Week 104 data Subjects who will discontinue the study drug and the study and will not provide Week 104 data Both groups experienced intercurrent event Subjects in yellow box have data Subjects in green box have missing data

Using the Retrieved Dropout Approach

Why “retrieved dropout approach”? From the ICH E9 Addendum under treatment policy strategy “For example, missing data may be imputed based on similar subjects who remained in the trial. Similarity may be established based on the same baseline covariates, the same randomised treatment arm, the same measurement history and information on the intercurrent event.” Imputation based on the retrieved dropout subjects for the subjects with missing Week 104 data would get us close to the handling of the intercurrent events under the treatment policy strategy

EMA Guidance on Missing Data in Confirmatory Clinical Trials

EMA Guidance Section 5.1

Handling of Missing Data Missing Week 104 data for a given subject who discontinued in the study will be imputed using an imputation model based on the observed data of subjects in the same randomized arm who also discontinued study treatment but for whom Week 104 data are available (‘retrieved dropout approach’, EMA 2010) and based on the observed data of the given subject.

Implementation

Implementation A logistic regression model will be fitted to the Week 104 data for the retrieved dropout subjects, while adjusting for treatment, baseline score and post- baseline slope in the score. The post-baseline slope is defined as the last available post-baseline change in score divided by study day on which the assessment was taken PROC MCMC will be used for fitting the logistic regression model and multiple imputation of the Week 104 value with weakly informative priors

Conclusion

Conclusion Even if a study is implementing the “treatment policy strategy” we still need to do imputation for the subjects with missing data. The choice of handling intercurrent event have an impact on the trial conduct. Imputation based on the retrieved dropout subjects for the subjects with missing data is an appropriate way to the handle the intercurrent events under the treatment policy strategy.

The 17th century 64-gun warship Vasa (Stockholm, Sweden)