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Critical Methological Issues in Recent Randomised Trials Paolo Bruzzi Epidemiologia Clinica IRCCS AUO San Martino IST MSO – ROMEa November 23, 2012.

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Presentazione sul tema: "Critical Methological Issues in Recent Randomised Trials Paolo Bruzzi Epidemiologia Clinica IRCCS AUO San Martino IST MSO – ROMEa November 23, 2012."— Transcript della presentazione:

1 Critical Methological Issues in Recent Randomised Trials Paolo Bruzzi Epidemiologia Clinica IRCCS AUO San Martino IST MSO – ROMEa November 23, 2012

2 Topics 1.Changes in the methodology of the Phases of cancer trials 2.Efficacy: Do we still need (Large) Randomised Controlled Trials? 3.Perspectives ?

3 Topics 1.Changes in the methodology of the Phases of cancer trials 2.Efficacy: Do we still need (Large) Randomised Controlled Trials? 3.Perspectives ?

4 Conventional Methodology - Phase I: dose increases -> MTD -Phase II: Uncontrolled -> % Response in metastatic pts with a specific cancer -Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

5 Conventional Methodology - Phase I: dose increases -> MTD The More the Better? DOSE –RESPONSE! PHASE I-II TRIALS

6 Conventional Methodology -Phase II: Uncontrolled -> % Response in metastatic pts with a specific cancer

7 Conventional Methodology -Phase II: Uncontrolled -> % Response in metastatic pts with a specific cancer -Response? Direct anticancer effect? -Metastatic pts? -Activity in pts with less disease burden -Need of repeated biopsies

8 Modern Methodology -Phase II trials: -Biological Endpoints -Window-of-opportunity studies- Neoadjuvant trials – Locally advanced dis. -Randomised Controls

9 Conventional Methodology - Phase I: dose increases -> MTD -Phase II: Uncontrolled -> % Response in metastatic pts with a specific cancer -Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

10 Topics 1.Changes in the methodology of the Phases of cancer trials 2.Efficacy: Do we still need (Large) Randomised Controlled Trials? 3.Perspectives ?

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12 Conventional Methodology - Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

13 Conventional Methodology - Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

14 Conventional Methodology - Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

15 Conventional Methodology - Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

16 Conventional Methodology - Phase III: Large RCTs in relatively heterogeneous pts: OS (or EFS)

17 Reasons for the need of Randomised Control groups a)Inability to predict individual outcome b)Inability to predict group outcome c)Inability to predict effect of treatments based on mechanisms

18 Reasons for the need of Randomised Control groups a)Inability to predict individual outcome b)Inability to predict group outcome c)Inability to predict effect of treatments based on mechanisms STILL TRUE!

19 On the other hand...

20 if a new drug, -with a well-identified molecular target -which is present in subgroups of cancers in different sites -produces a strong benefit in one of these cancers, …it may become ETHICALLY unacceptable to run a randomised trial in other cancers with the same target

21 Example Mortality Tumor X Nil vs A 15% vs 12.5% N=12000 P = H0 Rejected: A is effective in X

22 Example Mortality Tumor X Nil vs A 15% vs 12.5% N=12000 P = Tumor Y Nil vs A 15% vs 7.5% N= 240 P=0.066 H0 not rejected: A not shown effective in y

23 Prior Information: Mortality Tumor X Nil vs A 15% vs 12.5% N=12000 P = Tumor Y Nil vs A 15% vs 7.5% N= 240 P=0.066

24 Prior Information: tumors X and Y are BRAF+ Mortality Tumor X Nil vs A 15% vs 12.5% N=12000 P = Tumor Y Nil vs A 15% vs 7.5% N= 240 P=0.066

25 Prior Information: tumors X and Y are BRAF+ A = Anti BRAF Mortality Tumor X Nil vs A 15% vs 12.5% N=12000 P = Tumor Y Nil vs A 15% vs 7.5% N= 240 P=0.066 Interpretation?

26 Prior Information: tumors X and Y are BRAF+ A = Anti BRAF I have to plan a trial in the rare tumor Z, which is usually BRAF+, and for which there is no effective treatment Do I need a randomised control group? Is it ethically acceptable?

27 GLEEVEC CML -> Large RCT GIST -> Large uncontrolled trial Chordomas -> Case Series

28 New paths to drug use Large RCT in a frequent cancer with the target - Proof of principle – Toxicity Uncontrolled (but formal) trial(s) in other cancers with the target Off label use in individual cases with the target

29 New paths to drug use Large RCT in a frequent cancer with the target - Proof of principle – Toxicity Uncontrolled (but formal) trial(s) in other cancers with the target Off label use in individual cases with the target Acceptable? Methodology?

30 Topics 1.Changes in the methodology of the Phases of cancer trials 2.Efficacy: Do we still need (Large) Randomised Controlled Trials? 3.Perspectives?

31 3. Perspectives a)Adaptive trials b)Personalised Medicine c)New Statistical Approaches

32 3. Perspectives Adaptive trials Personalised Medicine New Statistical Approaches

33 3. Perspectives a)Adaptive trials b)Personalised Medicine c)New Statistical Approaches Radical changes in the way cancer trials are designed and analysed

34 Three modern revolutions 1950 Randomized Clinical Trial 1985 Evidence Based Medicine 1990 Molecular Medicine

35 Three modern revolutions 1950 Randomized Clinical Trial 1985 Evidence Based Medicine 1990 Molecular Medicine

36 Empirical Approach Preclinical work + Clinical observations Clinical rationale

37 Empirical Approach Preclinical work + Clinical observations Clinical rationale CLINICAL STUDIES INTERPRETATION

38 Fondamenti della sperimentazione clinica randomizzata Protezione da risultati falsamente positivi: –Randomizzazione –Protocolli rigidi/Piano statistico predeterminato –Intention to treat –(doppio cieco) Protezione da risultati falsamente negativi –Dimensioni

39 Fondamenti della sperimentazione clinica randomizzata Protezione da risultati falsamente positivi: –Randomizzazione –Protocolli rigidi/Piano statistico predeterminato –Intention to treat –(doppio cieco) Protezione da risultati falsamente negativi –Dimensioni

40 RCT -> EBM in Oncology Golden Age Rigid protocols –Drugs – Doses – Cycles –Modifications for toxicity or progression/relapse Generic Selection Criteria –Site (e.g. Stomach) –Histology (ADK vs Lymphoma) –Stage (early vs late)

41 RCT -> EBM in Oncology Golden Age Large and Simple Clinical Trials - Systematic Reviews – Meta-analyses Clinical Guidelines/Recommendations – Generic Flexibility in pt management not considered

42 Evidence Based Medicine Cookbook Medicine?

43 New Century Technological advances – Discoveries –Cellular functions –Molecular mechanisms/pathways –Genes/Mutations /Gene Functions –Genomics/Proteomics/(Metabolomics) –Targeted Drugs Patients Heterogeneity New Approaches!

44 3. Perspectives a)Adaptive trials b)Personalised Medicine c)New Statistical Approaches

45 a) Adaptive design FDAs draft guidance for industry on adaptive design clinical trials (http://www.fda.gov/downloads/Drugs/Guida nceComplianceRegulatoryInformation/Guid ances/UCM pdf).http://www.fda.gov/downloads/

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47 Adaptive design clinical trial FDAs Definition: … a study that includes a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypotheses based on analysis of data (usually interim data) from subjects in the study

48 Why adaptive designs are so attractive? Early Responses Effects in Subgroups of patients Toxicity It is possible to obtain, during the trial, crucial information to improve some of its design features

49 Most conventional trials have an adaptive component Stopping rules based on interim analyses : Toxicity Rejection of null-hypothesis Futility

50 Conventional Trials Few, if any, planned interim analyses 1.Change selection criteria ? 2.Change treatment protocol ? 3.NO Change of the Endpoint 4.NO Change of the Statistical Plan

51 Adaptive designs Interim analyses critical in study design 1.Change selection criteria 2.Change treatment protocol 3.Change Endpoint 4.Change Statistical Plan

52 Adaptive designs Interim analyses 1.Change selection criteria (target) 2.Change treatment protocol 3.Change Endpoint 4.Change Statistical Plan

53 3. Perspectives a)Adaptive trials b)Personalised Medicine c)New Statistical Approaches

54 Adaptive designs Interim analyses 1.Change selection criteria (target) 2.Change treatment protocol 3.Change Endpoint 4.Change Statistical Plan

55 3. Perspectives a)Adaptive trials b)Personalised Medicine c)New Statistical Approaches

56 New Statistical approaches Bayesian statistics (rare tumors and subgroups) Changing the null hypothesis (Sobrero & Bruzzi, ) Statistical methods for uncontrolled trials

57 New Statistical approaches Bayesian statistics (rare tumors and subgroups) Changing the null hypothesis (Sobrero & Bruzzi, ) Statistical methods for uncontrolled trials

58 Metodologia dei trials clinici: Elementi critici Primary Aim(s) Endpoint(s) Selection of patients Study Design Randomization Assessment of outcome Statistics (Statistical plan, ITT analysis)

59 Metodologia dei trials clinici: Prospettive Validita Interna (Statistica) = Assenza di bias Validita Esterna = Implicazioni -Generalizzazioni (Proof of Principle) -Applicazioni (pratica clinica, sanita, ricerca,…)

60 Metodologia dei trials clinici: Elementi critici Primary Aim(s) Endpoint(s) Selection of patients Study design Randomization Assessment of outcome Statistics (Statistical plan, ITT analysis) Validita Interna (Assenza di Bias)

61 Industry-Sponsored Trials Randomizzazione Valutazione outcome Statistica I moderni trial dellindustria, nella stragrande maggioranza, sono studi di altissima qualita, privi di bias rilevanti } Tecnicamente perfetti !

62 Metodologia dei trials clinici: Elementi critici 1.Primary Aim(s) 2.Endpoint(s) 3.Selection of patients 4.Study Design 5.Randomization 6.Assessment of outcome 7.Statistics (Statistical plan, ITT analysis)

63 Metodologia dei trials clinici: Elementi critici 1.Scopo/i Primario/i 2.Endpoint(s) 3.Selezione dei pazienti 4.Disegno di studio Validita Esterna = = Rilevanza Clinica e di Sanita Pubblica

64 1. Scopo Possibili scopi di un Trial Clinico Valutare: -(Attivita – meccanismi -> Fase II) -Efficacy (proof of principle) -Effectiveness (benefici clinici concreti)

65 Industry-Sponsored Trials Scopo Primario: Rifiutare lipotesi nulla H0: P<0.05 H0: Trattamento Sperimentale (con/senza treatment (with/without standard) identico allo Standard

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72 Significativita Statistica P = Probabilita di osservare, per caso, un differenza grande quanto quella osservata o piu grande se i due trattamenti sono identici (H0) Nota: Nei trials di fase III, H0 spesso non plausibile (precedenti trials di fase II, in altre malattie/stadi)

73 Significativita Statistica P = Probabilita di osservare, per caso, un differenza grande quanto quella osservata o piu grande se i due trattamenti sono identici (H0) Rilevanza Clinica: Beneficio per i pazienti sufficiente per far adottare il trattamento sperimentale come standard (considerando costi, tossicita, rischi)

74 Trials Sponsorizzati dalle industrie farmaceutiche 1. Scopo: Trovare una differenza statisticamente significativa 2. Endpoint 3. Criteri di Selezione 4. Disegno di Studio a)Sample Size b)Collocazione temporale delle analisi

75 2. Endpoints Endpoints naturali nei trials di efficacia: = Scopi del trattamento: Aumentare Quantita e/o di vita Qualita

76 2. Endpoints Endpoints naturali nei trials di efficacia: Overall Survival Quality of Life (Qualy)

77 2. Endpoints Endpoints spesso usati nei trials di efficacia: Endpoints di attivita Endpoints Surrogati non sempre validati

78 Endpoints Surrogati in oncologia Relapse-Free Survival, Disease-Free Survival nella malattia operata Progression-Free Survival nella malattia metastatica

79 Perche i trials dellindustria si basano cosi fortemente su endpoints surrogati ?

80 -Per abbreviare il tempo alle analisi ad interim e finale (piu eventi) (Basterebbe aspettare) -Effetto piu forte! soprattutto nel periodo iniziale del follow-up - Maggiore potenza e rilevanza clinica

81 3. Popolazione in studio Pazienti selezionati (es. Eta) – Compliance –Suscettibili agli effetti del trattamento –Meno sensibili alla tossicita –Massimizzare gli effetti del trattamento Possibilita di extrapolare a popolazioni di pazienti differenti? (Trials adiuvanti nel BC - eta mediana : 50years)

82 4. Disegno di Studio a) Sample Size b) Timing delle analisi ad interim e finale

83 4. Study Design a) Sample Size : Aumentando le dimensioni dello studio, differenze Clinicamente poco importanti -> Statisticamente significative Es. Molti farmaci targeted con effetti sul PFS<3 mesi in vari tumori solidi e p<0.001

84 HR MCWE, H1 Conventional Trial No Difference, H 0 HR =0.8 Power= 80% 635 events HR=0.86 P=0.05

85 HR MCWE, H1 Conventional Trial No Difference, H 0 HR =0.8 Power= 95% 1050 events HR=0.89 P=0.05

86 HR MCWE, H1 Conventional Trials No Difference, H 0 HR =0.8 Power= 95% 1050 events HR=0.89 Confidence Limits: From No Effect to MCWE

87 P<0.03

88 4. Study design b) Timing delle analisi: Interim Analisi precoci –Effetti precoci molto plausibili (Attivita) –Effetti maggiori e minore focalizzazione sui fallimenti a lungo termine (tumori avanzati) –Minore focalizzazione sulla tossicita a lungo termine (malattia precoce)

89 Typical treatment effect in advanced solid tumors Interim Analysis

90 Interim analyses I metodi di correzione della p usati nella analisi ad interim servono a preservare solo lerrore alfa Per vari motivi statistici, gli studi interrotti per interim analisi positive tendono a fornire SOVRASTIME dellefficacia del trattamento sperimentale Queste stime quindi non dovrebbero essere usate per valutazioni cliniche e costi/benefici

91 Case-study: Aromatase Inhibitors in early breast cancer Three original papers Anastrozole alone or in combination with tamoxifen versus tamoxifen alone for adjuvant treatment of postmenopausal women with early breast cancer: first results of the ATAC randomised trial - Lancet 2002 A Randomized Trial of Letrozole in Postmenopausal Women after Five Years of Tamoxifen Therapy for Early- Stage Breast Cancer – NEJM Nov A Randomized Trial of Exemestane after two to three years of Tamoxifen therapy in postmenopausal women with primary Breast Cancer – NEJM March 2004

92 Trials results (1 st analysis) TrialStageSample Size F-upEventsDFS red. % Tam vs Anastro vs A+T Postmenop 61% N- 84% HR (2/3 arms) 2.7 years % (-14%) Letro vs Placebo 5-yrs Tam Postm ER+ 50% N years207 (73) - 43% Tam vs Exem. 2-3yrs Tam Postm/ER+ ? 51% N years449 (199) -32%

93 Effetti - a lungo termine? - su mortalita? Cross-over programmato Altre terapie Diluzione effetto? Tecniche statistiche non ITT

94 Ultima Generazione di trials sponsorizzati dallindustria Trials sovradimensionati per garantire P significativa ad effetti moderati Analisi concentrate su endpoints surrogati e/o nelle analisi ad interim Effetti precoci spesso plausibili, ma benefici e tossicita a lungo termine? Endpoints Surrogati + Interim Analyses: Sovrastima del beneficio?

95 Trials sponsorizzati dall Industria I moderni trials: virtualmente privi di difetti dal punto di vista metodologico e statistico Disegnati per massimizzare la probabilita di osservare un effetto statisticamente signficativo del farmaco sperimentale, a prescindere dalla rilevanza clinica delleffetto reale

96 Trials sponsorizzati dall Industria (2) Questi trials forniscono una prospettiva distorta sulla reale efficacia dei nuovi farmaci Ciononostante, sulla base di questi risultati, spesso le agenzie regolatorie approvano questi farmaci, scaricando il problema degli alti costi x benefici limitati sui sistemi sanitari locali

97 Soluzioni? Trials Indipendenti (?) Contrattazione forte tra agenzie sanitarie- comunita scientifica internazionale e Big Pharma Nuovi requisiti per lapprovazione dei farmaci

98 Proposals of new statistical designs for phase III cancer trials A. Sobrero, P. Bruzzi

99 Sintesi della proposta -Trials di efficacia -Scopo : rifiutare H0: Delta < MCWE (Minimal Clinically Worthwhile Effect)

100 Example Metastatic Colorectal Cancer Expected Overall Survival: 24 months Experimental treatment: Limited toxicity and costs MCWE: increase in OS = 3 months (HR= 0.9)

101 HR MCWE, H 0 New proposal APPROVE Discard LIMBO H 0: No effect

102 Issues to discuss 1.Choice of the MCWE 2.P value computation 3.Power/required sample size 4.Analysis and interpretation of the results 5.Adaptive designs/Interim analyses

103 Conclusione La metodologia delle sperimentazioni cliniche e dellintero processo di sviluppo delle terapie oncologiche e destinata a modificarsi radicalmente nei prossimi anni per rispondere alle esigenze che derivano dai progressi nella quantita e nel tipo delle conoscenze disponibili

104 Processo di sviluppo delle nuove metodologie Esperti + Stakeholders Pazienti (assoc.) CliniciRicercatoriStatistici Agenzie Regolatorie Cost-efficacy

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106 Bevacizumab (BEV) plus chemotherapy (CT) continued beyond first progression in patients with metastatic colorectal cancer (mCRC) previously treated with BEV + CT: Results of a randomised phase III intergroup study – TML (ML18147) D Arnold 1, T Andre 2, J Bennouna 3, J Sastre 4, P Österlund 5, R Greil 6 E Van Cutsem 7, R von Moos 8, I Reyes-Rivera 9, B Bendahmane 10, S Kubicka 11 on behalf of the AIO, GERCOR, FFCD, UNICANCER GI, TTD, GEMCAD and AGMT groups 1 Hamburg, Germany; 2 Paris, France; 3 Nantes, France; 4 Madrid, Spain 5 Helsinki, Finland; 6 Salzburg, Austria; 7 Leuven, Belgium; 8 Chur, Switzerland 9 South San Francisco, USA; 10 Basel, Switzerland; 11 Reutlingen, Germany

107 Aims and objectives The efficacy and safety of BEV continued after first PD has not been investigated in a randomised clinical trial TML (ML18147) is the first randomised phase III study to evaluate BEV continued with standard second-line CT in patients with mCRC who progressed after BEV plus standard first-line CT

108 Statistical considerations Study initiated as AIO KRK 0504 then transferred to Roche (after enrolment of 261 patients ) – Primary endpoint changed from PFS to OS – Sample size increased from 572 to 810 patients Designed to detect 30% (HR 0.77) improvement in median OS (90% power, 2- sided 5%) 613 events required for analysis OS curves estimated using Kaplan–Meier method, differences assessed using unstratified log-rank tests – Unstratified Cox regression model used to estimate HR for OS – Stratified log-rank tests and Cox regression analyses used as supportive analyses

109 Main eligibility criteria Inclusion Patients 18 years with histologically confirmed diagnosis of mCRC Eastern Cooperative Oncology Group (ECOG) PS 0–2 PD (1 measurable lesion according to RECIST v1 assessed by investigator, documented by CT or MRI), 4 weeks prior to start of study treatment Previously treated with BEV plus standard first-line CT, not candidates for primary metastasectomy Exclusion Diagnosis of PD >3 months after last BEV administration First-line patients with PFS in first-line of <3 months Patients receiving <3 consecutive months of BEV in first-line

110 Characteristic CT (n=411) BEV + CT (n=409) Male, %6365 Age, median years63 ECOG performance status, % First-line PFS, % 9 months >9 months First-line CT, % Irinotecan-based Oxaliplatin-based Demographic and baseline characteristics: Randomised patients Patients were accrued between February 2006 and June 2010

111 Demographic and baseline characteristics: Randomised patients (contd) a Patient population refers to sequential enrolment of patients in original AIO study and subsequent enrolment in ML18147 when study was transferred to Roche Characteristic CT (n=411) BEV + CT (n=409) Duration from last BEV dose to randomisation, % 42 days >42 days Patient population a, % AIO ML Liver metastasis only, % No Yes No. of organs with metastasis, % 1 >

112 Second-line chemotherapy during study: Randomised patients Second-line CT regimen, % CT (n=407) BEV + CT (n=407) Irinotecan-based CT4342 FOLFIRI1416 LV5FU2 + CPT11 (Douillard regimen 1 )77 XELIRI12 Other regimens107 Oxaliplatin-based CT5758 FOLFOX4 / mFOLFOX41819 FOLFOX61316 FUFOX96 XELOX1114 Other regimens64 1. Douillard et al. Lancet 2000;355:1041–7

113 Primary endpoint: overall survival

114 OS: ITT population OS estimate Time (months) No. at risk CT BEV + CT CT (n=410) BEV + CT (n=409) 9.8 mo11.2 mo Unstratified a HR: 0.81 (95% CI: 0.69–0.94) p= (log-rank test) Stratified b HR: 0.83 (95% CI: 0.71–0.97) p= (log-rank test) a Primary analysis method; b Stratified by first-line CT (oxaliplatin-based, irinotecan-based), first-line PFS (9 months, >9 months), time from last dose of BEV (42 days, >42 days), ECOG performance status at baseline (0, 1) Median follow-up: CT, 9.6 months (range 0–45.5); BEV + CT, 11.1 months (range 0.3–44.0)

115 Subsequent anti-cancer therapies: Safety population Subsequent therapy, % CT (n=409) BEV + CT (n=401) Patients who received 1 subsequent anti-cancer therapy Subsequent anti-cancer therapies BEV Anti-EGFR Other EGFR: epidermal growth factor receptor

116 Subgroup analysis of OS: ITT population a Patient population refers to sequential enrolment of patients in original AIO and subsequent enrolment in ML18147 when study was transferred to Roche. All patients listed under AIO were included in primary analysis CategorySubgroupnHR (95% CI) All (0.69–0.94) Patient population a AIO (0.67–1.11) ML (0.64–0.94) GenderFemale (0.77–1.28) Male (0.60–0.88) Age<65 years (0.65–0.98) 65 years (0.66–1.04) ECOG performance status (0.59–0.94) (0.71–1.06) First-line PFS9 months (0.73–1.09) >9 months (0.58–0.92) First-line CTOxaliplatin-based (0.62–1.00) Irinotecan-based (0.67–1.00) Time from last BEV42 days (0.69–0.97) >42 days (0.55–1.06) Liver metastasis onlyNo (0.67–0.97) Yes (0.59–1.05) No. of organs with metastasis (0.64–1.08) > (0.64–0.94) HR

117 Subgroup analysis of PFS (ITT population) a Patient population refers to sequential enrolment of patients in original AIO and subsequent enrolment in ML18147 when study transferred to Roche. All patients listed under AIO were included in primary analysis CategorySubgroupnHR (95% CI) All (0.59–0.78) Patient population a AIO (0.51–0.84) ML (0.58–0.82) GenderFemale (0.67–1.07) Male (0.50–0.72) Age<65 years (0.55–0.80) 65 years (0.57–0.87) ECOG PS (0.48–0.74) (0.63–0.92) First-line PFS9 months (0.62–0.90) >9 months (0.47–0.72) First-line CTOxaliplatin-based (0.55–0.85) Irinotecan-based (0.56–0.81) Time from last BEV42 days (0.61–0.85) >42 days (0.41–0.75) Liver metastasis onlyNo (0.57–0.80) Yes (0.52–0.89) No. of organs with metastasis (0.59–0.94) > (0.53–0.77) HR

118 Summary BEV + standard second-line CT, crossed over from BEV + standard first-line CT, significantly prolongs OS and PFS –OS Median: BEV + CT 11.2 months, CT 9.8 months HR: 0.81 (95% CI: 0.69–0.94), p= a –PFS Median: BEV + CT 5.7 months, CT 4.1 months HR: 0.68 (95% CI: 0.59–0.78), p a Findings from subgroup analyses for OS generally consistent with overall population –Treatment effect according to gender appeared to be different; however, treatment-gender interaction test was not statistically significant Differences in best overall response rate not statistically significant; low response rate in both treatment groups AEs not increased when continuing BEV beyond PD; AE profile consistent with previous findings

119 Conclusions First randomised clinical trial that prospectively investigated the impact of continued VEGF inhibition with BEV beyond first progression Study confirms that continuing BEV beyond first progression while modifying CT is beneficial for patients with mCRC and leads to a significant improvement in OS and PFS This provides a new second-line treatment option for patients who have been treated with BEV + standard CT in first line while maintaining an acceptable safety profile Findings indicate a potential new model for treatment approaches through multiple lines and this is currently being investigated in other tumour types

120 OS: ITT population OS estimate Time (months) No. at risk CT BEV + CT CT (n=410) BEV + CT (n=409) 9.8 mo 11.2 mo Unstratified a HR: 0.81 (95% CI: 0.69–0.94) p= (log-rank test) Stratified b HR: 0.83 (95% CI: 0.71–0.97) p= (log-rank test) a Primary analysis method; b Stratified by first-line CT (oxaliplatin-based, irinotecan-based), first-line PFS (9 months, >9 months), time from last dose of BEV (42 days, >42 days), ECOG performance status at baseline (0, 1) Median follow-up: CT, 9.6 months (range 0–45.5); BEV + CT, 11.1 months (range 0.3–44.0)

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125 Long term benefit?

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127 2 mos

128 2-3 months 3.5 months

129 Clinically Worthwhile Effect? Median follow-up: 3.8 vs 2.3 months HR = 0.37 ( ): Meaningless! Long term benefit: None (Mature data?) Increase in median survival: 2 months Average benefit:< 2 months –30% of the pts: 3 months –30% of the pts: 2 months –40% of the pts: 0 } Clinically worthwhile?

130 Conclusions The medical research community should rethink the terms of cooperation with industry in clinical trials, taking into account a wider clinical and public health perspective.

131 Conclusions The medical research community should rethink the terms of cooperation with industry in clinical trials, taking into account a wider clinical and public health perspective. Our health systems risk bankruptcy for the skyrocketing costs of drugs that were developed on their own patients, using strategies that ignore the patients needs and priorities.

132 Conclusions The medical research community should rethink the terms of cooperation with industry in clinical trials, taking into account a wider clinical and public health perspective. Our health systems risk bankruptcy for the skyrocketing costs of drugs that were developed on their own patients, using strategies that ignore the patients needs and priorities. Governments, health systems, and regulatory agencies must identify new paths for drug development and set new standards for drug approval


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