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Registration Studies. Registration studies – Phase III. Objectives To gain regulatory approval Robustness of trial and endpionts are paramount Design of trial can be discussed with regulatory agency To assess the efficacy of the drug compared to existing ‘gold standard’
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Registration studies – Phase III Objectives • To gain regulatory approval • Robustness of trial and endpionts are paramount • Design of trial can be discussed with regulatory agency • To assess the efficacy of the drug compared to existing ‘gold standard’ • To assess the toxicity of the drug compared to existing ‘standard of care’ • Collect QOL where appropriate • Collect relevant pharmaco-economic data
Phase III Studies – Patient selection Regulatory authorities wish the population to be as homogenous as possible . Specific tumour type • Stage, grade, target expression, geographical location increasingly important • Biomarkers may be mandatory • Good performance status • Any exclusion criteria based on population and any toxicities seen in earlier studies • Informed consent • Ability to read and write - QOL
Phase III Studies – Study Design • Consider choice of endpoints- PFS, OS (RECIST, BIR) • Consider duration of therapy • Consider design • Parallel • Factorial • Crossover • Consider mode of randomisation - reduces selection bias • Equal/unequal • Stratification
Phase III Studies – Study Design • Consider degree of blinding - reduces reporting bias • Open label studies are common • Single • Double • Sample size calculations • "Is my trial large enough to demonstrate a clinically significant difference between the groups if one is truly present?"
Sample size calculation • In oncology studies, this calculation determines the number of events, not the number of patients, required • Depends on: • Natural intra-patient variability - less important in oncology • Minimum difference between groups considered important by investigator • Acceptable levels of α and β • Remember effect of interim analyses
Overall Survival - time to death from any cause Progression-free survival - time to first observation of disease progression Time to treatment failure- time to first observation of disease progression, death or discontinuation Duration of response – time to first observation of response to progression / death Quality of Life- mainlyfor blinded studies. Endpoints
Quality of Life • 2 main instruments used • Functional Assessment of Cancer Therapy- General ( FACT-G) • European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire- C30 ( EORTC- C30) • Both modular set up with generic core questionnaires in combination with disease specific modules • Generic core includes: • Physical functioning and well-being, social functioning, social / family well-being etc
Health Outcomes • Instruments commonly used and accepted: • SF-36 • Health utility Index • EQ-5D • Increasing importance due to reimbursement / cost containment
Basis for NDA Approval • Demonstration of efficacy with acceptable safety in adequate and well-controlled studies • Ability to generate product labeling that • Defines an appropriate patient population for treatment with the drug • Provides adequate information to enable safe and effective use of the drug
Accelerated Approval, Fast Track, Priority Review • Accelerated Approval • serious or life-threatening disease • demonstrable benefit over available therapy. • use of surrogate markers • mandated phase IV trials • Fast Track • life-threatening disease • potential to address unmet medical need • Priority review • drug would be a significant improvement compared to available drugs • Review of filing in 6 months
Challenges for Oncology Drug Regulations • New “targeted therapies” • Re-define definitions of diseases (based on mechanism of pathogenesis, genetics) • Greater efficacy in selected population may result in smaller patient populations • Novel surrogates to be validated • Dosing aimed at target rather than MTD • Dose studies, chronic administration
EGFR biomarkers were discovered late in the gefitinib development programme ISEL, INTEREST: Unselected trials in pre-treated setting ISEL Gefitinib registration Japan INTEREST IPASS 2002 2005 2007 2009 EGFR protein expression IPASS: Clinically selected trial in first line setting EGFR gene copy number EGFR mutations
Gefitinib Placebo The real challenge was to determine which tumours were really dependent on the EGFR pathway ISEL study: Median follow-up 7 months (range 3-15), 58% deaths Median, months 1-year survival, % Log-rank HR (95% CI), 0.89 (0.77, 1.02); p=0.087Cox analysis, p=0.030 Gefitinib 5.6 27 Placebo 5.1 21 Proportionsurviving 1.0 0.8 0.6 0.4 0.2 0.0 0 2 4 6 8 10 12 14 16 Time (months) 1692 1347 877 485 252 104 31 At risk Thatcher et al 2005
The dangers of dilution…….. Probability of success in pivotal trial in the presence of a non-responsive subgroup Assumes responders have 33% effect and non-responders 0% effect, trial sized assuming all patients have a 33% effect
ISEL: Rigorously predefined subgroups showed a statistically significant increase in survival Never smoked (n=375) Ever smoked (n=1317) 1.0 HR 0.67; 95% CI 0.49, 0.92; p=0.012 HR 0.92; 95% CI 0.79, 1.06; p=0.242 Gefitinib 0.8 Placebo 0.6 Proportion surviving 0.4 0.2 0.0 0 2 4 6 8 10 12 14 16 0 2 4 6 8 10 12 14 16 Asian origin (n=342) Non-Asian origin (n=1350) 1.0 HR 0.66; 95% CI 0.48, 0.91; p=0.010 HR 0.92; 95% CI 0.80, 1.07; p=0.294 0.8 0.6 Proportion surviving 0.4 0.2 0.0 0 2 4 6 8 10 12 14 16 0 2 4 6 8 10 12 14 16 Time (months) Cox regression analysis Thatcher et al 2005
IPASS: Phase III study of gefitinib versus doublet chemotherapy in first line NSCLC Gefitinib250 mg/day 1:1 randomization Carboplatin AUC 5 or 6 and Paclitaxel 200mg/m2 3 wkly Endpoints • Patients • Adenocarcinoma histology • Never smokers or light ex-smokers* • PS 0-2 • Provision of tumour sample for biomarker analysis strongly encouraged • Primary • Progression free survival (non-inferiority) • Secondary • Objective response rate • Quality of life • Disease related symptoms • Overall survival • Safety and tolerability • Exploratory • Biomarkers • EGFR mutation • EGFR gene copy number • EGFR protein expression • 1217 patients from East Asian countries *Never smokers:<100 cigarettes in lifetime; light ex-smokers: stopped 15 years agoand smoked 10 pack yrs Carboplatin/paclitaxel was offered to gefitinib patients upon progression PS, performance status; EGFR, epidermal growth factor receptor
IPASS: Superior PFS and ORR with gefitinib vs doublet chemotherapy; PFS effect not constant over time Probabilityof PFS Carboplatin / paclitaxel 1.0 Gefitinib N Events 609 453 (74.4%) 608 497 (81.7%) 0.8 HR (95% CI) = 0.741 (0.651, 0.845) p<0.0001 0.6 5.874%48%7% Median PFS (months)4 months progression-free6 months progression-free12 months progression-free 5.761%48%25% 0.4 Primary objective exceeded: Gefitinib demonstrated superiority relative to carboplatin / paclitaxel in terms of PFS 0.2 0.0 0 4 8 12 16 20 24 Months At risk : Gefitinib 609 363 76 24 5 0 212 Carboplatin / paclitaxel 608 412 118 22 3 1 0 Objective response rate 43% vs 32% p=0.0001 Primary Cox analysis and logistic regression with covariates; ITT population HR <1 implies a lower risk of progression on gefitinib
IPASS: Gefitinib has a more favourable tolerability profile than doublet chemotherapy Most common AEs (10% on either treatment) with >3% difference between treatments Gefitinib (N=607) Carboplatin/paclitaxel (N=589) #Absolute neutrophil count, white blood cell count, or haemoglobin worsened from baseline to CTC grade 3/4; gefitinib N=599, carboplatin / paclitaxel N=577 *Grouped term (sum of several preferred terms)
IPASS: EGFR mutation is a strong predictor for differential PFS benefit between gefitinib and doublet chemotherapy Gefitinib EGFR M+ (n=132)Gefitinib EGFR M- (n=91)Carboplatin / paclitaxel EGFR M+ (n=129) Carboplatin / paclitaxel EGFR M- (n=85) Probabilityof PFS 1.0 EGFR M+HR=0.48, 95% CI 0.36, 0.64 p<0.0001 EGFR M- HR=2.85, 95% CI 2.05, 3.98 p<0.0001 0.8 Treatment by subgroup interaction test, p<0.0001 0.6 0.4 0.2 0.0 0 4 8 12 16 20 24 Time from randomisation (months) M+, mutation positive; M-, mutation negative
Mutation status causes conformational change and increased activation WT EGFR Mutant EGFR Ligand Extracellular domain Trans-membrane domain ATP Tyrosine kinase domain Tyrosine phosphorylation Ras-Raf-MAPK Proliferation Pi3K-AKT Survival EGFR internalisation Degradation/recycling EGFR signals longer at the cell membrane
IPASS: Superior quality of life and symptom improvement rates for gefitinib in EGFR mutation positive patients p<0.0001 p=0.0003 p<0.0001 % patientswith sustained clinically relevant improvement p-values from logistic regression with covariates. Post-hoc analysis, EFQ populationClinically relevant improvement pre-defined as 6-point improvement for FACT-L and TOI;2-point improvement for LCS, maintained for at least 21 days. EFQ, evaluable for quality of life; FACT-L, Functional Assessment of Cancer Therapy-Lung; TOI, Trial Outcome Index; LCS, Lung Cancer Subscale
Conclusions – phase III trial considerations • Patient selection • Activity in specific subsets • Study design • Experimental (& control!) arm – dose, duration of treatment • Frequency of evaluations • Study endpoints • Survival vs PFS? • Use of biomarkers? • Qol • Health economics • Post phase III plans • Early access • Phase IIIb/IV • Investigator Initiated Studies
STAMPEDE: Systemic Therapy in Advancing or Metastatic Prostate cancer: Evaluation of Drug Efficacy Sponsor number: MRC PR08ISRCTN number: ISRCTN78818544EUDRACT number: 2004-000193-31CTA number: 00316/0026/001-0001 Slide set (abridged)
Design rationale STAMPEDE is multi-arm, multi-stage trial 3 investigational drugs in original design Intergroup randomised controlled trial Using Multi-Arm Multi-Stage methodology MAMS design
Design rationale Many interesting agents Different classes and modes of action Many used in later stages of disease Others new No clear reason to choose a particular one Many choices Don’t want to choose arbitrarily Want to assess all interesting agents Quicker and efficient to use MAMS design Start by test many agents Focus to more active agents using LOB analyses
Why Multi-arm, Multi-stage trials? Typical (academic) Phase III trial Hundreds or thousands of patients 5 to 10 years from idea to result Hundreds of research staff Cost millions in development Years of investment from the key players High chance of finding new treatment is not superior Whether to continue testing a new treatment?
MAMS vs traditional T1 Traditional Approach Multi-arm, Multi-stage T2 Phase II T3 C T1 T2 T3 T4 T4 Phase II C T1 Phase III C T3 C T4 Phase III
Trial Design Stages Stage Outcome Measures Primary Secondary (Pilot) (Safety) (Feasibility) ActivityI-IIIFailure-free survival Overall survival (phase II) Toxicity (safety) Skeletal-related events EfficacyIVOverall survival Failure-free survival (phase III) Toxicity (safety) Skeletal-related events Quality of life
Intermediate Analysis – Potential Outcomes Arms/Drugs might be dropped for Safety Reasons All patients on that arm/drug stop treatment Arms/Drugs might be dropped for lack of activity Patients on that arm/drug could continue treatment depending on the results seen TSC recommended that patients that were still being treated on celecoxib-containing arms stopped celecoxib. However, decision ultimately left to patient.
STAMPEDE DESIGN Slide set (abridged)
STAMPEDE original design Man with high-risk prostate cancer starting long-term hormone therapy Trial IDs MRC PR08 CRUK/06/019 ISRCTN78818544 NCT00268476 Slide set (abridged)
STAMPEDE: A FLEXIBLE TRIAL Slide set (abridged)
Flexibility • Adaptive trial design • Uses lack-of-benefit analyses to focus accrual away from insufficiently active arm • Require evidence of activity to continue accrual • Accrual to both celecoxib-containing arms was stopped on IDMC recommendation at 2nd intermediate analysis Slide set (abridged)
Flexibility • Can include new research arms • Use same intermediate hurdles for new arms • Compare against common control arm • New arm added in Nov-2011 • Abiraterone Acetate • Further new arm planned for 2012 • Local radiotherapy for M1 patients Slide set (abridged)
Past accrual Possible future accrual Accrual 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 • Following slides show accrual activity over time Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A B C D E F Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual: initial plans 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A ADT-alone B ADT + zoledronic acid C ADT + docetaxel D ADT + celecoxib E ADT + zoledronic acid + docetaxel F ADT + zoledronic acid + celecoxib Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual: end of Pilot Phase 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A ADT-alone B ADT + zoledronic acid C ADT + docetaxel D ADT + celecoxib E ADT + zoledronic acid + docetaxel F ADT + zoledronic acid + celecoxib Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual: end of Activity Stage I 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A ADT-alone B ADT + zoledronic acid C ADT + docetaxel D ADT + celecoxib E ADT + zoledronic acid + docetaxel F ADT + zoledronic acid + celecoxib Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual: end of Activity Stage II 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A ADT-alone B ADT + zoledronic acid C ADT + docetaxel D ADT + celecoxib E ADT + zoledronic acid + docetaxel F ADT + zoledronic acid + celecoxib Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual: from Nov-2011 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A ADT-alone B ADT + zoledronic acid C ADT + docetaxel D ADT + celecoxib E ADT + zoledronic acid + docetaxel F ADT + zoledronic acid + celecoxib G ADT + abiraterone Follow-up Slide set (abridged)
Past accrual Possible future accrual Accrual: plans from late 2012 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 A ADT-alone B ADT + zoledronic acid C ADT + docetaxel D ADT + celecoxib E ADT + zoledronic acid + docetaxel F ADT + zoledronic acid + celecoxib G ADT + abiraterone M1 only H ADT + RT Follow-up Slide set (abridged)
STAMPEDE’s future • Original research arms will stop accrual within 18m • Stop early at 3rd intermediate analysis for lack-of-benefit • Complete accrual to end of Efficacy Stage 4 • Active, original research arms will present data in around 3 years • HT vs HT + abiraterone will recruit up to Nov-2014 • HT vs HT + local RT will start in 2012 • Further arms considered Slide set (abridged)
Further Reading • Thatcher N et al, Gefitinib plus best supportive care in previously treated patients with refractory non-small-cell lung cancer: results from a randomisd, placebo controlled, multicentre study (Iressa Survival Evaluation in lung Cancer). Lancet 2005;366:1527-1537. • Chang A et al, Gefitinig (IRESSA) in patients of Asian origin with refractory advanced non-small cell lung cancer: subset analysis from the ISEL study. J ThoracOncol 2006;1:847-855. • Kelloff GJ et al, New science-based endpoints to accelerate oncology drug development. Eu J Can 2005;41:491-501 • Booth CM et al, Reflections on Medical Oncology: 25 years of clinical trials – where have we come & where are we going. J ClinOncol 2008;26(1):6-8 • Gutierrez ME et al, Next generation oncology drug development: opportunities & challenges. Nat Rev ClinOncol 2009;6:259-265 • Nathan DG. The Cancer Treatment Revolution, Wiley & Sons, Inc., 2007 • Mukherjee S. The emperor of all maladies. A biography of cancer. Fourth Estate, 2010 • James ND et al, Celecoxib plus hormone therapy versus hormone therapy alone for hormone-sensitive prostate cancer: first results from the STAMPEDE multiarm, multistage randomised controlled trial. Lancet Oncol 2012;13(5):549-558 • Sydes et al, Flexible trial design in practice – stopping arms for lack-of-benefit and adding research arms mid-trial in STAMPEDE: a multi-arm multi-stage randomized controlled trial. Trials 2012;13:168
Clinical Trial Design • Stratification: Categorizing subjects into subgroups by specific characteristics • Enables researchers to look into separate subgroups to see whether differences exist