Chrissie Fletcher Amgen Ltd HTA 1-day scientific meeting 25 th Sept 2014 Bayer, Berlin Subgroups for Regulatory vs HTA – Methods and Perspectives

Disclaimer (Chrissie Fletcher)  The views expressed herein represent those of the presenter and do not necessarily represent the views or practices of Amgen or the views of the general Pharmaceutical Industry. 2

Outline  Who is interested in subgroup analyses?  Challenges with subgroup analyses  Guidance on methods and perspectives from regulators  Guidance on methods and perspectives from HTA agencies (effectiveness and cost-effectiveness)  Trends in R&D and market access influencing use of subgroup analyses  Recommendations for optimising use of subgroups in drug development 3

Who is interested in subgroup analyses  Pharmaceutical Industry –Demonstrating the benefit-risk profile supports the proposed population  Regulatory agencies –Is the evidence supporting benefit-risk acceptable to grant approval for the proposed population  Reimbursement agencies –Is the incremental balance of benefit-risk better than existing standard of care (e.g. IQWiG) –Is the incremental balance of benefit-risk worth paying for (e.g. NICE)  Patient –Will I benefit from the treatment and what potential side effects may I experience? 4

What questions can be addressed by subgroup analyses?  Does the drug work in a particular subset of patients?  Is the drug effect consistent across different patient subsets?  Is the drug effect (or balance of benefit-risk) more pronounced in a particular subset of patients? 5

Subgroup analyses have numerous challenges  Subgroup analysis definition and pre-specification  Consistency of effects and subgroup by treatment interactions  Multiplicity and replication  Presenting and interpreting subgroup results  Meeting needs for regulators and reimbursement agencies 6

Guidance on methods and perspectives from regulators  Subgroup analyses are covered in numerous regulatory guidance documents –ICH –EMA draft ‘Guideline on the investigation of subgroups in confirmatory clinical trials –FDA –+ other countries (e.g. Switzerland, Australia, Canada) 7

ICH relevant guidelines  ICH E9 Statistical Principles for Clinical Trials  ICH E5 Ethnic Factors in the Acceptability of Foreign Clinical Data  ICH Gender Considerations in the conduct of clinical trials 8

ICH E9 Statistical Principles for Clinical Trials  Subgroup effects should be pre-specified in the protocol as part of the planned analyses  In most cases, subgroup analyses are exploratory, e.g. explore uniformity of treatment effects  When exploratory, results should be interpreted cautiously  A conclusion of treatment efficacy/safety (or lack of) based solely on exploratory subgroups unlikely to be accepted  Dangers of over-interpretation of unplanned subgroup analyses are well known 9

EMA draft guideline on subgroups in confirmatory clinical trials 10  Pre-agreement with regulatory authorities on important subgroups prior to starting trials (key vs exploratory)  Subgroup characteristics should be easy to measure and scale is important  Defining how to assess consistency of effect difficult  Interaction tests are a possible way of approaching subgroup analyses and should be presented with estimates of size of effect in addition to p-values.  Replication across >1 trial can help with interpretation  Analyses depend on heterogeneity in target population  Forest plots are useful for visual display  Bayesian approaches may be potentially useful in some situations

EMA draft guideline on subgroups in confirmatory clinical trials – Industry views 11  EFSPI/PSI submitted comments (~ 18 pages), for example further clarification regarding: −Rare diseases −Subgroups for reimbursement −Dose adjustment for different subgroups… and the impact on benefit/risk −Use of subgroups in adaptive designs −Role of Bayesian methods −Confirmatory subgroups vs exploratory subgroups  EFPIA submitted comments (~ 42 pages), for example further clarification regarding: −Assessing safety in subgroups (+ benefit-risk) −Pre-specification and labelling −Multiplicity, credibility, replication…. −Guideline for assessors and Industry or just assessors?

FDA  Guideline for the Format and Content of the Clinical and Statistical Sections of New Drug Applications emphasized the importance of conducting subset analyses on data from clinical studies submitted in new drug applications (NDAs) – focus on race and ethnicity  Guideline for the Study and Evaluation of Gender Differences in the Clinical Evaluation of Drugs. The guidance specifically called for analyzing trials by gender and for evaluating pharmacokinetics in women. 12

FDA Guideline for the Format and Content of the Clinical and Statistical Sections of New Drug Applications  Evidence to support labeling for specific subgroups (for example, pediatrics, geriatrics, patients with renal failure)  Subgroup hypotheses should be stated explicitly. It should be noted whether the objectives were pre-planned or formulated during or after completion of the study. –Not pre-planned, usually not considered adequate for definite conclusions  If the size of the study permits, relevant demographic or baseline value-defined subgroups should be examined for unusually large or small responses and the results presented, e.g., comparison of effects by severity groups, by age, sex, or race, or by history of prior treatment with a drug of the same class. –not intended to “salvage” an otherwise non-supportive study –may suggest hypotheses worth examining in other studies or –refining labelling information, patient selection, dose selection, etc. 13

Guidance on methods and perspectives from HTA agencies  Subgroup analyses are covered in numerous HTA agency guidance documents –EUnetHTA (network of HTA agencies across Europe) –NICE (England/Wales) –IQWiG (Germany) –+ other countries (e.g. France, Australia, Canada) 14

EUnetHTA Applicability of evidence in the context of a relative effectiveness assessment of pharmaceuticals  “Metaregression, subgroup analysis, and/or separate applicability summary tables may help reviewers, and those using the reports see how well the body of evidence applies to the question at hand.”  “In large clinical trials it is possible to have reliable subgroup analyses which may help prescribers to relate the trial’s findings more closely to patients for whom they are trying to select appropriate therapies”  “Moderators: Are there any analyses of moderator effects—including different subgroups of participants and types of intervention — to assess robustness versus specificity of effects? ” 15

NICE  Require estimates of clinical and cost effectiveness by subgroups  Clearly defined subgroups ideally identified based on expected differential clinical or cost effectiveness because of known biological/other justified factors –Biological plausibility for why subgroups may differ  Ideally pre-defined (e.g. at scoping stage) with rationale for expected subgroup effects, –subgroups could be identified later (post-scoping) –‘relevant subgroups may be identified in terms of differences in 1 or more contributors to absolute treatment effects’ –‘post-hoc data dredging in search of subgroup effects should be avoided and will be viewed sceptically’ 16

NICE  Careful consideration for choice of scale  Statistical precision of all subgroup effects reflected in analysis of parameter uncertainty  Differences in relative effects between subgroups due to chance could be high when multiple subgroups reported  Credibility will be enhanced when expected subgroup effect has pre-specified rationale and consistent across studies) –Quality of analysis, representativeness of evidence and relevance to decision problem important  Subgroups not considered based solely on differential treatment costs 17

IQWiG  Pre-specification –Subgroup analyses rarely planned a priori –Post-hoc results cannot be regarded as confirmatory  Multiplicity –Caution with interpreting results from several subgroups  Lack of power –Subgroup sizes often too small to detect moderate differences (unless included in sample size calculations)  Testing for homogeneity  Despite limitations, subgroups may represent best scientific evidence  Written into law “show a therapeutically relevant added benefit” in patient subgroups –Gender, age, disease severity and disease state required 18

Comparing regulatory and HTA agency method guidelines Similarities  Prospectively defined and statistically powered (ideal)  Biologic rationale  Small number of subgroups tested  Assessment of heterogeneity  Replication Differences  Important subgroups could be identified post-design (HTA)  Advice on required subgroups from regulators and HTA agencies available at different stages  Robustness (sensitivity) and levels of uncertainty (HTA) 19

Trends in R&D and market access influencing use of subgroup analyses  Personalised/stratified medicine –Biomarkers  Adaptive licensing –Accumulating evidence  Increased data transparency –Evaluating new subgroups  Real world data –Evaluating effectiveness  Economic pressures in healthcare systems –Rationalising treatment decisions 20

Principles and best practices for subgroup analyses (Paget et al) 21  Subgroups pre-specification & definition  Subgroup by treatment interaction  Multiplicity issues  Sensitivity analyses  Replication  Source of evidence  Presenting and reporting subgroup results

Relevance for cost-effectiveness subgroup analyses (Fletcher et al) Clinical effectiveness  Sensitivity analyses  Presenting and reporting  Replication  Source of evidence  Subgroups pre- specifications  Multiplicity issues  Subgroup by trt interaction Cost-effectiveness Desirable Less important Extremely important Important All data sources Transparency trt: treatment 22

Recommendations for optimal use of subgroups in drug development Subgroup analyses remains a difficult area Plan for subgroups in design and analysis −Individual RCTs −Across product development program −Benefit-risk assessments Present and interpret subgroup results appropriately Discuss subgroup analysis strategies with regulatory agencies and reimbursement agencies −Assess if different strategies are needed in different regions/countries −Understand how each stakeholder will view subgroup results 23

Conclusions  Subgroup analyses are important for regulatory and HTA decision making  Variety of guidance on methods for subgroup analyses from regulatory and HTA agencies  Whilst there is agreement on key principles, there are differences in perspectives between these stakeholders  Discussing subgroup strategies with regulators and HTA agencies should be a priority (via scientific advice and early dialogue)  Statisticians add strategic value in optimising the use of subgroup analyses for regulatory and HTA decision making 24

References  ICH E9 Statistical principles for clinical trials eline.pdf eline.pdf  ICH E5 Ethnic Factors in the Acceptability of Foreign Clinical Data 1__Guideline.pdf 1__Guideline.pdf  ICH E7 Studies in support of special populations: geriatrics eline.pdf eline.pdf  ICH E11 Clinical investigation of medicinal products in the pediatric population ideline.pdf ideline.pdf  ICH Gender considerations in the conduct of clinical trials: 87.pdf 87.pdf  E17: General principle on planning/designing Multi-Regional Clinical Trials ncept_Paper_July_2014.pdf ncept_Paper_July_2014.pdf  EMA draft ‘Guideline on the investigation of subgroups in confirmatory clinical trials’ 23.pdf) pdf 25

References  FDA Guideline for the Format and Content of the Clinical and Statistical Sections of New Drug Applications  FDA Guideline for the Study and Evaluation of Gender Differences in the Clinical Evaluation of Drugs.  EUnetHTA (network of HTA agencies across Europe) Guidelines for Rapid Relative Effectiveness Assessment of Pharmaceuticals:  NICE (England/Wales) Methods guide to Health Technology Assessment: appraisal-2013-pdf appraisal-2013-pdf  IQWiG (Germany) General Methods (Version 4.1)  Questioning Patient Subgroups for Benefit Assessment: Challenging the German Gemeinsamer Bundesausschuss Approach :  Paget, Chuang-Stein, Fletcher, Reid. Subgroup analyses of clinical effectiveness to support health technology assessments. Pharmaceut. Statist. 2011, –538  Fletcher C, Chuang-Stein C, Paget MA, Reid C, Hawkins N. Subgroup analyses in cost- effectiveness analyses to support health technology assessments. Pharm.Stat Jul- Aug;13(4):