BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 15.4//EN BEGIN:VTIMEZONE TZID:GMT Standard Time BEGIN:STANDARD DTSTART:20251002T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=2;BYMINUTE=0;BYMONTH=10 TZNAME:GMT Standard Time TZOFFSETFROM:+0100 TZOFFSETTO:+0000 END:STANDARD BEGIN:DAYLIGHT DTSTART:20250301T010000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=1;BYMINUTE=0;BYMONTH=3 TZNAME:GMT Daylight Time TZOFFSETFROM:+0000 TZOFFSETTO:+0100 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Determining the appropriate sample size is an important part of good clinical trial design. When there is uncertainty about some of the d esign parameters (e.g. variability\, control rate\, model parameters)\, it can be challenging to determine up front the number of subjects required for robust evaluation of the study objectives. The aim of this PSI one day meeting is to present an overview of available methods for sample size re -estimation together with several case studies where such methods have bee n used in late phase clinical trials. \; There will be plenty of oppor tunity for discussion and interaction with other statisticians working in this area. \; Registration is now closed.  \;Please contact the s ecretariat if you wish to inquire. \; Time  \;Session  \;Pr esentation  \;9.30 - 9.55  \;Registration \;  \; &nb sp\;9.55 - 10.00  \;Welcome and Introduction  \;  \;10.00 - 10.45  \;Sample Size Re-estimation in Clinical Trials  \;Chris Jennison Presentation  \;  \;Prof Chris Jennison : University of Bath  \;  \;10.45 - 11.30 Sample Size Re-Estimation &ndash\; Some random observations  \;Simon Day Presentation  \;  \; Simon Day: Clinical Trials Consulting &\;Training Limited  \; &n bsp\;11.30 &ndash\; 12.15  \;Blinded sample-size re-estimation in mul tiple sclerosis clinical trials  \;Heinz Schmidli Presentation &nbs p\;  \;Heinz Schmidli: Novartis  \;  \;12.15 &ndash\; 1.15  \;Lunch  \;  \;1.15 &ndash\; 2.00  \;Do we need more patients? \; Your statistics should be correct. \; Make sure you communicate effectively!  \;Mike Greenwood Presentation  \; &nb sp\;Mike Greenwood : AstraZeneca \;  \;  \;2.00 &ndash\; 2. 45  \;An experience in implementing the Promising Zone sample size re -estimation methodology in a phase 3 oncology study  \;Nikhil Chauhan Presentation  \;  \;Nikhil Chauhan: BTG International Ltd &nbs p\;  \;2.45- 3.00  \;Coffee  \;  \;3.00 &ndash\; 3.4 5  \;Blinded sample size re-estimation in a Phase III study investiga ting Progression Free Survival  \;David Morgan\, Nilani Liyanage\, Alison Langley Presentation  \; David Morgan: Pharmaceutical Medicin e Group\, King&rsquo\;s College London Nilani Liyanage: Ipsen Alison Langl ey: Independent Consultant  \;  \;3.45-4.30  \;Sample Size Re-estimation \;: «\; \;De-risking \;»\; a crucial stage of clinical development  \;Benjamin Esterni Presentation &nbs p\;  \;Pantelis Vlachos: Cytel  \;  \;4.30-4.45  \;Clo se  \;  \;  \;Speaker  \;Title  \;Abstracts \ n Prof Chris Jennison\n University of Bath Sample S ize Re-estimation in Clinical Trials There are two distinct reasons for sa mple size re-estimation in clinical trials: the first is to maintain power when trial data indicate the response variance has been under-estimated\; the second is to adapt to interim estimates of the treatment effect. I sh all explain how a combination test can be used to ensure rigorous protecti on of the type I error rate when sample size is adapted in the light of ob served data. I shall describe methods for increasing sample size to mainta in power when response variance is higher than expected\, based on either blinded or unblended variance estimates. I shall discuss the relationship between trial designs that adjust sample size in response to the estimated treatment effect and group sequential designs\, which start with a higher maximum sample size but stop early when the data support such a decision. In particular\, I shall describe the &ldquo\;promising zone&rdquo\; appro ach of Mehta and Pocock (Statistics in Medicine\, 2011) and show how to mo dify this procedure in order reduce the average sample size and achieve si milar performance to an efficient group sequential design. \; \n Simon Day\n Clinical Trials Consulting &\;Training Ltd Sample Size Re-Estimation &ndash\; Some random observations I was an author on one of the very early papers on sample size re-estimation (Birke tt and Day\, Stats in Med\, 1994\; 13: 2455&ndash\;2463) and have since fo llowed the field with much interest\, some despair\, and more than a littl e exasperation.This talk will illustrate some of these facets &ndash\; mos tly based around such methods used in a regulatory context. \; Several personal experiences will be included (particularly the ones that went wr ong) as well as some of the approaches and myths I see in my regular consu lting work. \; What&rsquo\;s &ldquo\;allowed&rdquo\; and what&rsquo\;s not? \; What makes sense and what doesn&rsquo\;t? \n Hei nz Schmidli\n Novartis Blinded sample-size re-estimation in mu ltiple sclerosis clinical trials Multiple sclerosis (MS) is a progressive\ , degenerative disease. MS is the most common disorder of the CNS in adult s\, affecting up to 2.5 million people worldwide. Clinical trials in MS us e count\, recurrent event and time-to-event primary endpoints. Methodology for blinded sample size re-estimation with such endpoints is briefly revi ewed. A case study illustrates how to implement blinded sample size re-est imation in a confirmatory MS trial. \n Mike Greenwood\, Astra Zeneca Do we need more patients? \; Your statistics should be correct.  \; Make sure you communicate effectively!  \;We performed a blind ed estimation of the pooled exacerbation rate and shape parameter from a n egative binomial model in a COPD exacerbation study. \; This talk will briefly cover the statistics\, the practical aspects and focus on the imp ortance of clear (and understandable to non-statisticians) communication o f the results and their implications \n Nikhil Chauhan\, BTG International Ltd An experience in implementing the Promising Zone sample size re-estimation methodology (Mehta and Pocock\, 2011) in a phase 3 onc ology study I will share my experience in implementing the Promising Zone sample size re-estimation methodology (Mehta and Pocock\, 2011) in a phase 3 oncology study for the purposes of obtaining a US FDA marketing approva l. I will outline how we decided on using this study design\, how the samp le size calculation was performed\, and how the promising zone boundaries were set. \; I will also share our experience in demonstrating the acc eptability of the study design to FDA\, in terms of showing control of Typ e I error. Reference: Mehta\, CR and Pocock\, SJ (2011)\, Adaptive increas e in sample size when interim results are promising: A practical guide wit h examples. Statist. Med.\, 30: 3267&ndash\;3284. doi: 10.1002/sim.4102 \n David Morgan (King&rsquo\;s College London)\, \n Nilani Liyanage (Ipsen)\, \n Alison Langley\, (Independent Cons ultant) Blinded sample size re-estimation in a Phase III study investigat ing Progression Free Survival The CLARINET study investigated the effect o f lanreotide compared to placebo in the treatment of metastatic enteropanc reatic neuroendocrine tumours with progression free survival as primary en dpoint. \; We will describe the design of the study\, the justificatio n for the blinded sample-size re-estimation and some practical aspects of carrying out that decision\, including communication within the company\, with the DSMB and with regulatory authorities. \n Pantelis Vl achos\n Cytel Sample Size Re-estimation \;: «\; \ ;De-risking \;»\; a crucial stage of clinical development Develop ing cancer treatments is a high-stakes endeavor &ndash\; especially for em erging biotechs and specialty pharmas with limited portfolios. Conventiona l phase 3 trial designs are &ldquo\;all or nothing&rdquo\; propositions an d well over 50% of these pivotal studies end in failure. Unlike convention al studies\, adaptive approaches allow beneficial design changes following interim analysis (IA). \; A Sample Size Re-estimation design allows s election of the strategy most likely to succeed. We present a case study o f such an adaptive approach used to both effectively &ldquo\;de-risk&rdquo \; the final clinical stage as well as be accepted by FDA reviewers based on the concept of the &ldquo\;Promising Zone&rdquo\;.  \;Rather than c ommitting to a larger sample size up front\, the decision is deferred unti l the clinical evidence justifies cost of added subjects. The strategy pro vided the confidence company leaders &ndash\; and investors &ndash\; neede d to launch the final development effort toward approval.  \; Registration \; Early Bird Rate (until 14th October 2016) After 14 th October 2016 PSI Member £\;120 + VAT £\;160 + VAT Non-Member £\;160 + VAT £\;220 + VAT Academic £\ ;60 + VAT £\;90 + VAT Registration closes on 26th October 2016 \nPlease contact the PSI secretariat on psi@mci-group.com \;if you ha ve any queries. \; \nRegistration \;is now closed.  \;Please c ontact the secretariat if you wish to inquire. DTEND:20161102T164500Z DTSTAMP:20260812T023105Z DTSTART:20161102T093000Z LOCATION: SEQUENCE:0 SUMMARY:PSI One Day Meeting: Sample Size Re-estimation – dealing with those known unknowns! UID:RFCALITEM639220986653807544 X-ALT-DESC;FMTTYPE=text/html:

Determining the appropriate sample size is an important part of good clinical trial design. When there is uncertainty about some of the design parameters (e.g. variability\, control rate\, mo del parameters)\, it can be challenging to determine up front the number o f subjects required for robust evaluation of the study objectives. The aim of this PSI one day meeting is to present an overview of available method s for sample size re-estimation together with several case studies where s uch methods have been used in late phase clinical trials. \; There wil l be plenty of opportunity for discussion and interaction with other stati sticians working in this area. \;

Registration is now closed. &n bsp\;Please contact the secretariat if you wish to inquire. \;

Time  \;Session  \;Presentation  \;9.30 - 9.55
 \;Registration \;
 \; < td class="PSI-default-tableTableFirstCol"> \;9.55 - 10.00
 \;Welcome and Introduction< br />  \; < tr class="PSI-default-tableTableOddRow">  \;10.00 - 10.45  \;Sample Size Re-estimation in Clinical Trials
 \;Chris Jennison Presentation< /td>  \;  \;Prof Chris Jennison : University of Bath
 \;  \;10.45 - 11.30

Sample Size Re-Estimation &ndash\; Some random observations

 \;Simon Day Presentation  \;  \;Simon Day: C linical Trials Consulting &\;Training Limited
 \;  \;11.30 &n dash\; 12.15
 \; Blinded sample-size re-estimation in multiple sclerosis clinical trials
 \;Heinz Schmidli Pre sentation  \;  \;Heinz Schmidli: Novartis
 \;  \;12.15 & ndash\; 1.15
 \; Lunch
 \; < /tr>  \;1.15 &ndash\; 2.00
 \;Do we need more patients? \; Yo ur statistics should be correct. \; Make sure you communicate effectiv ely!
 \;Mike Green wood Presentation  \;  \;Mike Greenwood : AstraZeneca \;
 \;  \;2.00 &ndash\; 2.45
 \;An experience in implementing the Promising Zone sample size re-estimation methodology in a phase 3 oncology study
 \;Nikh il Chauhan Presentation  \;  \;Nikhil Chauhan: BTG International Lt d
 \;  \;2.45- 3.00
 \;Coffee
 \;  \;3.00 &ndash\; 3.45
< td class="PSI-default-tableTableLastCol"> \;Blinded sample size re-est imation in a Phase III study investigating Progression Free Survival
 \;David Morgan\, Nilani Liyanage \, Alison Langley Presentation  \; David Morgan: Pharmaceutical Medicine Group\, King&rsquo\ ;s College London

Nilani Liyanage: Ipsen
Alison Langley: Independent Consultant

 \; &n bsp\;3.45-4.30
  \;Sample Size Re-estimation \;: «\; \;De-risking \;» \; a crucial stage of clinical development
 \;Benjamin Esterni Presentation  \;  \;Pantelis Vlachos: Cytel
 \; < td class="PSI-default-tableTableFirstCol"> \;4.30-4.45
 \;Close
 \;

&n bsp\;

< tr class="PSI-default-tableTableOddRow">
&n bsp\;Speaker  \;Ti tle  \;Abstracts< /td>
< span data-sfref="[images|OpenAccessDataProvider]1107b7ff-3ad6-65b3-a176-ff 00001f6b97" class="sfImageWrapper">Chris Jennison
\n Prof Chris Jennison
\n University of Bath
 Sample Size Re-estimation in Clinical Trials There are two disti nct reasons for sample size re-estimation in clinical trials: the first is to maintain power when trial data indicate the response variance has been under-estimated\; the second is to adapt to interim estimates of the trea tment effect. I shall explain how a combination test can be used to ensure rigorous protection of the type I error rate when sample size is adapted in the light of observed data. I shall describe methods for increasing sam ple size to maintain power when response variance is higher than expected\ , based on either blinded or unblended variance estimates. I shall discuss the relationship between trial designs that adjust sample size in respons e to the estimated treatment effect and group sequential designs\, which s tart with a higher maximum sample size but stop early when the data suppor t such a decision. In particular\, I shall describe the &ldquo\;promising zone&rdquo\; approach of Mehta and Pocock (Statistics in Medicine\, 2011) and show how to modify this procedure in order reduce the average sample s ize and achieve similar performance to an efficient group sequential desig n. \;
Simon Day
\n Simon Day
\n Clinical Trials Consulting &am p\;Training Ltd
 Sample Size Re-Estimation &ndash\; Some random observations I was a n author on one of the very early papers on sample size re-estimation (Bir kett and Day\, Stats in Med\, 1994\; 13: 2455&ndash\;2463) and have since followed the field with much interest\, some despair\, and more than a lit tle exasperation.This talk will illustrate some of these facets &ndash\; m ostly based around such methods used in a regulatory context. \; Sever al personal experiences will be included (particularly the ones that went wrong) as well as some of the approaches and myths I see in my regular con sulting work. \; What&rsquo\;s &ldquo\;allowed&rdquo\; and what&rsquo\ ;s not? \; What makes sense and what doesn&rsquo\;t?
Heinz Schmidli
\n Heinz Schmidli
\n Novartis
 Blinded sample-size re-estimation in multiple sclerosis clinical trials Multiple sclerosis (MS) is a progressive \, degenerative disease. MS is the most common disorder of the CNS in adul ts\, affecting up to 2.5 million people worldwide. Clinical trials in MS u se count\, recurrent event and time-to-event primary endpoints. Methodolog y for blinded sample size re-estimation with such endpoints is briefly rev iewed. A case study illustrates how to implement blinded sample size re-es timation in a confirmatory MS trial.
Mike
\n Mike Greenwood\, AstraZeneca		 Do we need more patients? \; Your statistics should be correct.  \; Make sure you communicate effectively!  \;We performed a blinded estimation of t he pooled exacerbation rate and shape parameter from a negative binomial m odel in a COPD exacerbation study. \; This talk will briefly cover the statistics\, the practical aspects and focus on the importance of clear ( and understandable to non-statisticians) communication of the results and their implications
Nikhil Chauhan
\n Nikhil Chauhan\, BTG International Ltd		 An experience in implementing the Promising Zo ne sample size re-estimation methodology (Mehta and Pocock\, 2011) in a ph ase 3 oncology study I will share my expe rience in implementing the Promising Zone sample size re-estimation method ology (Mehta and Pocock\, 2011) in a phase 3 oncology study for the purpos es of obtaining a US FDA marketing approval. I will outline how we decided on using this study design\, how the sample size calculation was performe d\, and how the promising zone boundaries were set. \; I will also sha re our experience in demonstrating the acceptability of the study design t o FDA\, in terms of showing control of Type I error. Reference: Mehta\, CR and Pocock\, SJ (2011)\, Adaptive increase in sample size when interim re sults are promising: A practical guide with examples. Statist. Med.\, 30: 3267&ndash\;3284. doi: 10.1002/sim.4102
David Morgan
\n David Morgan (King&rsquo\;s College London)\,

Nilani Liyanage
\n Nilani Liyanage (Ipsen)\,
Alison Langley
\n Alison Langley\, (Ind ependent Consultant)

 Blinded sample s ize re-estimation in a Phase III study investigating Progression Free Surv ival The CLARINET study investigated the effect of lanreotide compared to placebo in the treatment of metastatic en teropancreatic neuroendocrine tumours with progression free survival as pr imary endpoint. \; We will describe the design of the study\, the just ification for the blinded sample-size re-estimation and some practical asp ects of carrying out that decision\, including communication within the co mpany\, with the DSMB and with regulatory authorities.
Mike
\n Pante lis Vlachos
\n Cytel
 Sample Size Re-estimation \;: «\; \;De-risking \;» \; a crucial stage of clinical development Developing cancer treatments is a high-stakes end eavor &ndash\; especially for emerging biotechs and specialty pharmas with limited portfolios. Conventional phase 3 trial designs are &ldquo\;all or nothing&rdquo\; propositions and well over 50% of these pivotal studies e nd in failure. Unlike conventional studies\, adaptive approaches allow ben eficial design changes following interim analysis (IA). \; A Sample Si ze Re-estimation design allows selection of the strategy most likely to su cceed. We present a case study of such an adaptive approach used to both e ffectively &ldquo\;de-risk&rdquo\; the final clinical stage as well as be accepted by FDA reviewers based on the concept of the &ldquo\;Promising Zo ne&rdquo\;.  \;Rather than committing to a larger sample size up front \, the decision is deferred until the clinical evidence justifies cost of added subjects. The strategy provided the confidence company leaders &ndas h\; and investors &ndash\; needed to launch the final development effort t oward approval.

 \;

Registration \;

Early Bird Rate ( until 14th October 2016)

After 14th October 2016

PSI M ember

£\;120 + VAT

£\;160 + VAT

Non-Member

£\;160 + VAT

£\;220 + VAT

Academic

£\;60 + VAT

£\;90 + VAT

Registration closes on 26th October 2016

\nPlease contact th e PSI secretariat on psi@mci-group.com \;if you hav e any queries. \;

\nRegistration&nbs p\;is now closed.  \;Please contact the secretariat if you wish to inq uire.
END:VEVENT END:VCALENDAR