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:Are you estimating what you think you are?\nDe-mystifying Estim ands  \; \; \; \; \; \; \; \; \; \ ; \; \; \; \; \; \; \; \; \; \;&nb sp\;  \; Monday 28th September 2015\, Hertfordshire Please click belo w to see the speaker slides from the meeting: Rob Hemmings AnnKristinLeuc hs Chrissie Fletcher Frank Bretz James Carpenter JamesRoger \nControversy and confusion exist on the definition and selection of appropriate estima nds in the clinical trial context. As a result the ICH Steering Committee endorsed a final Concept Paper in October 2014 with the goal of developing a new regulatory guidance\, suggested to be an Addendum to ICH E9. The ai m of the addendum is to promote harmonised standards on the choice of esti mands in clinical trials and an agreed framework for planning\, conducting and interpreting sensitivity analyses of clinical trial data. A working g roup sponsored by ICH has been established to develop the addendum and is due to report findings in December 2015. This meeting will provide a forum to hear about the latest developments and discussions on this topic.  \; Speakers include members of the ICH working group as well as representa tives from academia\, European regulatory bodies and industry. The day wil l end with a panel discussion including all speakers. Presenters include: Rob Hemmings\nStatistics and Pharmacokinetics Unit Manager\, MHRA\, UK Ann -Kristen Leuchs\nFederal Institute for Drugs and Medical Devices\, Bonn\, Germany Chrissie Fletcher\n \;Executive Director\, Global Biostatistic al Science\, Amgen Ltd\, UK Frank Bretz\nGlobal Head Statistical Methodolo gy group\, Novartis\, Basel\, Switzerland James Carpenter\nProfessor\, Lon don School of Hygiene and Tropical Medicine\, UK James Roger\nDirector\, LiveData (UK) Ltd 8.45-9.10 Arrival/Registration and Coffee &nbs p\; 9.10-9.15 Welcome and introduction  \; 9.15-10.00 Ro bert Hemmings (MHRA) Estimands at ICH 10.00-10.45 Frank Bretz (Nov artis) Estimands and their role in clinical trials 10.45-11.00 Cof fee  \; 11.00-11.45 James Carpenter (LSHTM &\; MRC) Estim ands\, Randomisation and Sensitivity Analysis 11.45-12.30 Plamen Ko zlovski (Medical Director at Novartis) Estimands in Diabetes Trials &nda sh\; what are different stakeholders interested in? 12.30-1.30 Lunch  \; 1.30-2.15 Chrissie Fletcher (Amgen) The importance of t he proposed ICH E9 addendum on estimands and sensitivity analyses to the P harmaceutical Industry 2.15-3.00 James Roger (Livedata) Whether to use MMRM as primary estimand. 3.00-3.15 Coffee  \; 3.15-4 .00 Ann-Kristen Leuchs (BfArM) Estimands in clinical trials and how th ey influence trial planning: a regulatory view 4.00-4.30 Panel Discu ssion  \; 4.30 Close  \;  \; Abstracts Rob Hemmi ngs (Statistics and Pharmacokinetics Unit Manager\, MHRA\, UK) Estimands a t ICH After a number of years discussing the problem of &lsquo\;missing da ta&rsquo\;\, solutions arose and became widespread practice\, but these so lutions seemed to violate the ITT principle as it is described in ICH E9.& nbsp\; Attention turned to identifying a precise answer to the question &l squo\;what should we seek to estimate to demonstrate drug effects in a cli nical trial&rsquo\;? \; The breadth of this question called for an ans wer on a global scale and hence a concept paper was drafted\, and eventual ly adopted\, for a group to draft an addendum to ICH E9. \; The talk w ill provide some more background on how the discussions came to be\, the I CH process\, the future plans of the group for developing the guidance and some initial thoughts from one regulator on what might be achieved and wh ere further research work still needs to be done. Frank Bretz (Global Head Statistical Methodology group\, Novartis\, Basel\, Switzerland) Estimands and their role in clinical trials Defining the primary objective of a cli nical trial in the presence of non-compliance or non-adherence to the assi gned treatment is crucial for the choice of design\, the statistical analy sis and the interpretation of the results. At first glance this seems obvi ous\, however\, primary objectives stated in clinical trial protocols ofte n fail to give a precise definition of the measure of intervention effect. The impact of potential confounding\, e.g. due to non-compliance\, missin g data\, treatment switching / discontinuation or intake of rescue medicat ion\, is frequently not taken into account when defining the intervention effect of interest. The need for a structured framework to specify the pri mary estimand (i.e. &ldquo\;what is to be estimated&rdquo\;) was highlight ed in the context of missing data in the National Academy of Science docum ent "The Prevention and Treatment of Missing Data in Clinical Trials"(2010 ). However\, the need for clearly defined estimands applies to a broader s etting. In this talk we will discuss the need for this framework\, using r eal and hypothetical examples. James R Carpenter (Professor LSHTM and MRC Clinical Trials Unit) Estimands\, Randomisation and Sensitivity Analysis T he increased focus on estimands - not just for sensitivity analysis\, but for the primary analysis - is a welcome development\, because it helps cla rify the assumptions necessary for the analysis\, and which of them can be verified. However\, it does raise a number of questions: - 1. How tightly should the estimand be defined? In other words\, when is a sensitivity an alysis actually changing the estimand? 2. What is the role of randomisati on based inference? 3. To what extent should we worry if the sensitivity analysis violates the assumptions of the primary analysis? I will argue th at the way we answer these questions lead us to two different paradigms: ( a) Follow the established approach\, where the primary analysis does not m odel deviations\, and explore how robust inferences are to different assum ptions about post-deviation behaviour (b) Adopt a more formal causal appr oach to the primary analysis\, in which the deviation process is explicitl y accounted for. If we shift to (b)\, we are moving decisively away from r andomisation based inference. If we want to do this\, it \;should be i ntentional\, not accidental! Plamen Kozlovski (Associate Global Program Me dical Director at Novartis Pharma AG) Estimands in Diabetes Trials &ndash\ ; what are different stakeholders interested in? Diabetes is a progressive disease which is associated with serious complications resulting from chr onic exposure to elevated blood glucose levels and other metabolic abnorma lities. Good blood glucose control assessed by glycated haemoglobin (HbA1C ) is a key goal of treatment\, as it has been demonstrated that near-norma lization in HbA1c can prevent or delay the diabetic complications. This go al should be achieved without deterioration of the quality of life. Howeve r\, when it comes to decision-making on priorities\, the different parties involved in diabetes care &ndash\; patients\, health professionals\, regu latory agencies\, payers and pharmaceutical companies - may have different perspectives and needs. These differences in perspectives may imply diffe rent estimands &ndash\; this may lead to challenges when designing a clini cal development programme that aims to address the needs of all stakeholde rs. Chrissie Fletcher (Executive Director\, Global Biostatistical Science\ , Amgen Ltd\, UK): The importance of the proposed ICH E9 addendum on estim ands and sensitivity analyses to the Pharmaceutical Industry In recent yea rs\, there have been different perspectives emerging between regulators an d Industry in terms of what estimand and measure of the intervention effec t is of primary interest to be estimated for confirmatory trials supportin g Marketing authorisations. \; Choices made in how to deal with non-ad herence issues\, such as missing data or taking rescue medication\, in the study design and planned analyses influences what is actually being estim ated in the clinical trial.  \; \;In addition\, sensitivity analys es conducted to support the conclusions from confirmatory trials can somet imes be misaligned with the estimand of primary interest\, leading to diff iculties in interpretation of results from confirmatory trials. \; The results of a recent survey conducted by the ICH E9 working group who are developing the addendum will be presented highlighting current practices r elating to choices of primary estimands\, techniques for preventing and mi nimising missing data\, and common sensitivity analyses used to support pr imary analyses. \; Challenges with current practice in these areas and recommendations for overcoming these challenges will be discussed. \;  \; A summary of key topics debated in the ICH E9 working group will b e provided including considerations for how the addendum will align with t he current ICH E9 guidance. \; James Roger (Director\, LiveData (UK) L td) Whether to use MMRM as primary estimand. \nThere are two main impacts of early withdrawal on study results\; first the potential selection bias caused by those withdrawing being different from the remaining subjects\, and second the fact that subjects may receive alternative treatments after withdrawal. The most common method for handling early withdrawal in clini cal studies is MMRM or some other form of missing at random (MAR) based an alysis. The motivation behind MMRM is to solve the first issue while addre ssing an on-treatment question\, i.e. what happens if a typical patient co mpletes their assigned treatment. It does this by conditioning on the prev ious observations and other covariates that may inform on both missingness and outcome. So what is the scientific question of interest\, i.e. the es timand that it targets? This cannot be answered without considering the se cond aforementioned issue which is related to treatment switching or modif ication after withdrawal. If the design of the study\, in terms of treatme nt after withdrawal from randomized treatment\, matches the estimand\, the n collection of data after treatment withdrawal allows direct analysis. Th en later absolute study termination after switching (truly missing data) c an be handled via a modified MMRM approach. But when the design of the stu dy after treatment withdrawal does not match the estimand any analysis mus t depend upon additional unverifiable information or assumptions. This is a whole new area of potential statistical research. Several of the more re cent proposals ignore the first issue of selection bias. Any coherent appr oach must address both issues. Ann-Kristen Leuchs (Federal Institute for D rugs and Medical Devices\, Bonn\, Germany) Estimands in clinical trials an d how they influence trial planning: a regulatory view Estimands\, which a re precise definitions of that which is being estimated\, are currently di scussed in clinical research\, especially in cases where post-randomizatio n events such as non-adherence to treatment complicate the interpretation of trial results. Considering suitable estimands addressing the desired ob jectives and satisfying regulatory requirements is only the first step in appropriately planning clinical trials. The choice of estimand has consequ ences for various other factors to be considered during any trial&rsquo\;s planning phase. After deciding on the primary estimand\, a trial design t hat enables addressing this estimand should be discussed. This\, for examp le\, includes considering measures to enhance retrieval of data or adheren ce to treatment. Following the specification of an appropriate design\, an adequate primary analysis method that directly addresses the chosen estim and is to be selected including the use of retrieved data and missing data handling. The robustness of the primary analysis to deviations from its a ssumptions should be addressed in a final step by defining sensitivity ana lyses still addressing the primary estimand but using a different set of a ssumptions (internal validity). Moreover\, sensitivity analyses aiming at alternative estimands can be considered to address the robustness with res pect to the generalizability of results (external validity). This process is proposed as a suitable way to incorporate estimands in clinical develop ment and \;illustrated with relevant examples from clinical practice a nd regulatory experience. Registration Costs \; Fee includes lunch &am p\; refreshments \n* event is co-organised by PSI and\nlocated in the UK F or information regarding the scientific content\, contact:\nCarly Barnett& nbsp\;\nTel: +44 208 990 3781 Carly.m.barnett@gsk.com Egbert Biesheuvel&nb sp\;\nTel: +31 6 46869728 Egbert.biesheuvel@danone.com DTEND:20150928T163000Z DTSTAMP:20260516T075712Z DTSTART:20150928T080000Z LOCATION: SEQUENCE:0 SUMMARY:European Statistical Meeting on Estimands UID:RFCALITEM639145150325970455 X-ALT-DESC;FMTTYPE=text/html:

Are you estimating what you think you are?
\nDe-mystifying Estimands

 \; \; \;  \; \; \; \; \; \; \; \; \; \;&nbs p\; \; \; \; \; \; \; \;

 \;

Mo nday 28th September 2015\, Hertfordshire

Ple ase click below to see the speaker slides from the meeting:

Rob Hemmings
AnnKristinLeuchs
Chrissie Flet cher
Frank Bretz
James Carpenter
JamesRoger


\nControversy and confusion exist on the definition and selection of appropriate estimands in the clinical trial context.

As a result t he ICH Steering Committee endorsed a final Concept Paper in October 2014 w ith the goal of developing a new regulatory guidance\, suggested to be an Addendum to ICH E9. The aim of the addendum is to promote harmonised stand ards on the choice of estimands in clinical trials and an agreed framework for planning\, conducting and interpreting sensitivity analyses of clinic al trial data. A working group sponsored by ICH has been established to de velop the addendum and is due to report findings in December 2015.

This meeting will provide a forum to hear about the latest developments an d discussions on this topic. \; Speakers include members of the ICH wo rking group as well as representatives from academia\, European regulatory bodies and industry. The day will end with a panel discussion including a ll speakers.

Presenters include:

Rob Hemmings
\nStatistics and Pharmacokinetics Unit Manager\, MHRA\, UK

Ann-Kristen Leuchs
\nFederal Institute for Drugs and Medical Devices\, Bonn\, Germany

Chrissie Fletcher
\n \;Executive Director\, Global Biostatistical Science\, Amgen Ltd\, UK

Frank Bretz
\nGlobal Head Statistic al Methodology group\, Novartis\, Basel\, Switzerland

James Carpenter
\nProfessor\, London School of Hygiene and Tropic al Medicine\, UK

James Roger
\nDirector \, LiveData (UK) Ltd

< tr>

8. 45-9.10

Arrival/Regi stration and Coffee

 \;

9. 10-9.15

Welcome and introduction

 \;

9.15-10.0 0

Robert Hemmings (M HRA)

Estimands at IC H

10.00-10 .45

Frank Bretz (Nov artis)

Estimands and their role in clinical trials

10.45-11.00

Coffee

 \;

11 .00-11.45

James Carp enter (LSHTM &\; MRC)

Estimands\, Randomisation and Sensitivity Analysis

11.45-12.30

Plamen Kozlovski (Medical Director at Novartis)

Estiman ds in Diabetes Trials &ndash\; what are different stakeholders interested in?

12.30- 1.30

Lunch

 \;

1.30-2.15

Chrissie Fletcher (Amgen)

The importance of the proposed ICH E9 addendum on estimands and sensitivity analyses to the Pharmaceutical In dustry

2.1 5-3.00

James Roger ( Livedata)

Whether to use MMRM as primary estimand.

3.00-3.15

Coffee

&n bsp\;

3.15 -4.00

Ann-Kristen Le uchs (BfArM)

Estiman ds in clinical trials and how they influence trial planning: a regulatory view

4.00- 4.30

Panel Discussio n

 \;

4.30

Close

 \;

&nbs p\;

Abstracts

Rob Hemmings (Statistics and Pharmac okinetics Unit Manager\, MHRA\, UK)

Estimands at ICH

After a number of years discussing the problem of &lsquo\;missin g data&rsquo\;\, solutions arose and became widespread practice\, but thes e solutions seemed to violate the ITT principle as it is described in ICH E9. \; Attention turned to identifying a precise answer to the questio n &lsquo\;what should we seek to estimate to demonstrate drug effects in a clinical trial&rsquo\;? \; The breadth of this question called for an answer on a global scale and hence a concept paper was drafted\, and even tually adopted\, for a group to draft an addendum to ICH E9. \; The ta lk will provide some more background on how the discussions came to be\, t he ICH process\, the future plans of the group for developing the guidance and some initial thoughts from one regulator on what might be achieved an d where further research work still needs to be done.

Frank Bretz (Global Head Statistical Methodology group\, Novartis\, Ba sel\, Switzerland)

Estimands and their role in clinical tri als

Defining the primary objective of a clinical trial in the presence of non-compliance or non-adherence to the assigned treatment is crucial for the choice of design\, the statistical analysis and the int erpretation of the results. At first glance this seems obvious\, however\, primary objectives stated in clinical trial protocols often fail to give a precise definition of the measure of intervention effect. The impact of potential confounding\, e.g. due to non-compliance\, missing data\, treatm ent switching / discontinuation or intake of rescue medication\, is freque ntly not taken into account when defining the intervention effect of inter est. The need for a structured framework to specify the primary estimand ( i.e. &ldquo\;what is to be estimated&rdquo\;) was highlighted in the conte xt of missing data in the National Academy of Science document "The Preven tion and Treatment of Missing Data in Clinical Trials"(2010). However\, th e need for clearly defined estimands applies to a broader setting. In this talk we will discuss the need for this framework\, using real and hypothe tical examples.

James R Carpenter (Professor LSHTM and MRC Clinical Trials Unit)

Estimands\, Randomisation an d Sensitivity Analysis

The increased focus on estimands - not just for sensitivity analysis\, but for the primary analysis - is a we lcome development\, because it helps clarify the assumptions necessary for the analysis\, and which of them can be verified.

However\, it doe s raise a number of questions: -

1. How tightly should the estimand be defined? In other words\, when is a sensitivity analysis actually chan ging the estimand?

2. What is the role of randomisation based infe rence?

3. To what extent should we worry if the sensitivity analys is violates the assumptions of the primary analysis?

I will argue t hat the way we answer these questions lead us to two different paradigms:< /p>

(a) Follow the established approach\, where the primary analysis do es not model deviations\, and explore how robust inferences are to differe nt assumptions about post-deviation behaviour

(b) Adopt a more for mal causal approach to the primary analysis\, in which the deviation proce ss is explicitly accounted for.

If we shift to (b)\, we are moving decisively away from randomisation based inference. If we want to do this\ , it \;should be intentional\, not accidental!

Plamen K ozlovski (Associate Global Program Medical Director at Novartis P harma AG)

Estimands in Diabetes Trials &ndash\; what are di fferent stakeholders interested in?

Diabetes is a progress ive disease which is associated with serious complications resulting from chronic exposure to elevated blood glucose levels and other metabolic abno rmalities. Good blood glucose control assessed by glycated haemoglobin (Hb A1C) is a key goal of treatment\, as it has been demonstrated that near-no rmalization in HbA1c can prevent or delay the diabetic complications. This goal should be achieved without deterioration of the quality of life. How ever\, when it comes to decision-making on priorities\, the different part ies involved in diabetes care &ndash\; patients\, health professionals\, r egulatory agencies\, payers and pharmaceutical companies - may have differ ent perspectives and needs. These differences in perspectives may imply di fferent estimands &ndash\; this may lead to challenges when designing a cl inical development programme that aims to address the needs of all stakeho lders.

Chrissie Fletcher (Executive Director\, Glo bal Biostatistical Science\, Amgen Ltd\, UK):

The importance of the proposed ICH E9 addendum on estimands and sensitivity analyses to the Pharmaceutical Indu stry

In recent years\, there have been different perspecti ves emerging between regulators and Industry in terms of what estimand and measure of the intervention effect is of primary interest to be estimated for confirmatory trials supporting Marketing authorisations. \; Choic es made in how to deal with non-adherence issues\, such as missing data or taking rescue medication\, in the study design and planned analyses influ ences what is actually being estimated in the clinical trial.  \;  \;In addition\, sensitivity analyses conducted to support the conclusions from confirmatory trials can sometimes be misaligned with the estimand of primary interest\, leading to difficulties in interpretation of results fr om confirmatory trials. \; The results of a recent survey conducted by the ICH E9 working group who are developing the addendum will be presente d highlighting current practices relating to choices of primary estimands\ , techniques for preventing and minimising missing data\, and common sensi tivity analyses used to support primary analyses. \; Challenges with c urrent practice in these areas and recommendations for overcoming these ch allenges will be discussed. \; \; A summary of key topics debated in the ICH E9 working group will be provided including considerations for how the addendum will align with the current ICH E9 guidance. \;

< p>James Roger (Director\, LiveData (UK) Ltd)

Whether to use MMRM as primary estimand.

\nThere a re two main impacts of early withdrawal on study results\; first the poten tial selection bias caused by those withdrawing being different from the r emaining subjects\, and second the fact that subjects may receive alternat ive treatments after withdrawal. The most common method for handling early withdrawal in clinical studies is MMRM or some other form of missing at r andom (MAR) based analysis. The motivation behind MMRM is to solve the fir st issue while addressing an on-treatment question\, i.e. what happens if a typical patient completes their assigned treatment. It does this by cond itioning on the previous observations and other covariates that may inform on both missingness and outcome. So what is the scientific question of in terest\, i.e. the estimand that it targets? This cannot be answered withou t considering the second aforementioned issue which is related to treatmen t switching or modification after withdrawal.

If the design of the study\, in terms of treatment after withdrawal from randomized treatment\, matches the estimand\, then collection of data after treatment withdrawal allows direct analysis. Then later absolute study termination after switc hing (truly missing data) can be handled via a modified MMRM approach. But when the design of the study after treatment withdrawal does not match th e estimand any analysis must depend upon additional unverifiable informati on or assumptions. This is a whole new area of potential statistical resea rch. Several of the more recent proposals ignore the first issue of select ion bias. Any coherent approach must address both issues.

A nn-Kristen Leuchs (Federal Institute for Drugs and Medical Device s\, Bonn\, Germany)

Estimands in clinical trials and how th ey influence trial planning: a regulatory view

Estimands\, which are precise definitions of that which is being estimated\, are curr ently discussed in clinical research\, especially in cases where post-rand omization events such as non-adherence to treatment complicate the interpr etation of trial results. Considering suitable estimands addressing the de sired objectives and satisfying regulatory requirements is only the first step in appropriately planning clinical trials. The choice of estimand has consequences for various other factors to be considered during any trial& rsquo\;s planning phase. After deciding on the primary estimand\, a trial design that enables addressing this estimand should be discussed. This\, f or example\, includes considering measures to enhance retrieval of data or adherence to treatment. Following the specification of an appropriate des ign\, an adequate primary analysis method that directly addresses the chos en estimand is to be selected including the use of retrieved data and miss ing data handling. The robustness of the primary analysis to deviations fr om its assumptions should be addressed in a final step by defining sensiti vity analyses still addressing the primary estimand but using a different set of assumptions (internal validity). Moreover\, sensitivity analyses ai ming at alternative estimands can be considered to address the robustness with respect to the generalizability of results (external validity). This process is proposed as a suitable way to incorporate estimands in clinical development and \;illustrated with relevant examples from clinical pr actice and regulatory experience.

Registration Costs \;

Fee includes lunch &\; refreshments

\n* event is co-or ganised by PSI and
\nlocated in the UK

For information regardi ng the scientific content\, contact:
\nCarly Barnett \;
\nTe l: +44 208 990 3781
Carly.m .barnett@gsk.com

Egbert Biesheuvel \;
\nTel: +31 6 468 69728
Egbert.biesheuve l@danone.com

END:VEVENT END:VCALENDAR