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BEGIN:VEVENT
DESCRIPTION:Date: Tuesday 13th October 2020\nTime: 14:00 - 15:30 (BST)\nSpe
akers: Sheila Dickinson\, Rachael DiSantostefano\, and \;Gaë\;lle
Saint-Hilary.\nRegistration\nYou can now register for this event. Registra
tion will close at 12:00 on 12th October 2020.\nPSI Members: Free to atten
d\nNon-Members: £\;20+VAT\nTo register your place\, please click here
.\n\nOverview\nPatient preference studies are becoming more frequently use
d in drug development. In this webinar you will hear an introduction to wh
at a patient preference study is as well as an overview of where this type
of study can inform regulatory decision making. This will be followed by
2 examples looking at potential approaches to eliciting patient preference
demonstrating how such studies can be designed and analysed.\nSpeaker Det
ails\n\n\n\n \n \n \n Speaker\n
\n \n Biography\n \n \n
Abstract\n \n \n \n \n
\n \n \n \n \n \n
\n \n \n \n \n
Sheila Dickinson\n \n \n Sheila D
ickinson is a Senior Expert Quantitative Safety Scientist at Novartis Phar
ma AG. She is on the management board of the IMI PREFER project\, which is
working on developing guidelines about when and how to perform patient pr
eference studies to support medical product decision-making. Her other res
ponsibilities include supporting patient preference study activities withi
n Novartis\, and promoting and supporting the use of a structured benefit-
risk approach by project teams.\n Sheila holds a degree in math
ematics from Imperial College\, London and an MSc in Medical Statistics fr
om the London School of Hygiene and Tropical Medicine. \n After
joining Novartis in 1997\, she worked as a statistician supporting projec
ts in the various disease areas including both diabetes and malaria\, befo
re moving to the Quantitative Safety group in 2013.\n Prior to
joining Novartis Pharma\, Sheila worked as a statistician for Pfizer.\n
 \;\n \n \n How patient pref
erence studies can inform decisions during drug development.\n
Patient associations\, industry\, regulators and HTA bodies agree that pat
ients&rsquo\; views should inform drug development activities. Patient pre
ference studies are one way to assess patients&rsquo\; views\, and can be
particularly helpful in 2 types of scenario: where there is a need to unde
rstand which issues in a disease matter to patients\, and where there is a
need to understand the acceptability to patients of a benefit-risk trade-
off (i.e. it&rsquo\;s not clear that a particular drug is going to be the
obvious choice for all patients e.g. because this particular drug offers s
trong benefits at the expense of important side-effects\; because patients
need to make a choice between very different alternatives such as surgery
vs. drug therapy etc.). This presentation describes how patient preferenc
e studies can inform routine regulatory decisions\, and discusses an examp
le patient preference study assessing which endpoints matter to patients w
ith COPD. It also introduces a framework that offers a structure to guide
a preference study sponsor through key issues when design\, conducting and
analysing a patient preference study\, and that supports the discussion b
etween industry\, regulators and HTA bodies about preference studies inten
ded to inform medical product decision-making.\n  \;\n
\n \n \n \n \n \n
\n \n \n \n \n
\n \n \n \n Rachael DiSan
tostefano\n \n \n Rachael L. DiSantostefa
no\, MS PhD\, is a Senior Director of Benefit-Risk in the Epidemiology Dep
artment within Janssen Pharmaceuticals\, R&\;D\, LLC. She has more than
25 years of pharmaceutical research experience across the quantitative di
sciplines of epidemiology\, biostatistics\, and health outcomes. Currently
\, she focuses on benefit-risk assessment and quantitative patient prefere
nce research. Dr. DiSantostefano is also an active member of PREFER\, a 5-
year public-private partnership that examines how and when to perform and
include patient preference studies in decision making during the medical p
roduct life cycle. Her research interests also include drug safety\, obser
vational studies\, and innovation in observational studies.\n &
nbsp\;\n \n \n Parent Preferences for Del
aying Insulin Dependence in Children: A Discrete Choice Experiment.\n
Authors: Rachael L DiSantostefano1\, Jessie Sutphin2\, Joseph A Hed
rick3\, Kathleen Klein2\, Carol Mansfield2\n 1Janssen Research
&\; Development\, LLC\, Titusville\, New Jersey.\n 2RTI Heal
th Solutions\, Research Triangle Park\, North Carolina.\n 3Jans
sen Research &\; Development\, LLC\, Raritan\, New Jersey.\n
Background: Screening for auto-antibodies can identify children at increa
sed risk of progression to type-1 diabetes (T1D) that requires insulin. \n
Objectives: We investigated parents' preferences for treatment
s to delay the onset of insulin dependence in children who are at high ris
k. \n Methods: A web-based survey (n = 1501) was administered t
o a stratified sample of parents (children <\;18 years) in the United St
ates from an online panel. Parents were told to hypothetically assume that
their youngest child would become insulin dependent within 6 months or 2
years and were offered a series of choices between no treatment and two hy
pothetical treatments that would delay insulin dependence. Random-paramete
rs logit analysis and latent class analysis were used to evaluate the rela
tive importance of treatment benefits and risks overall and by groups of p
arents with unique preference sets. \n Results: Most parents ch
ose at least one active treatment. For parents of children without T1D (n
= 901)\, delaying insulin dependence and reducing the risk of long-term he
alth complications and serious infection were the most important treatment
attributes. There was some heterogeneity of preferences. \n Co
nclusions: When told to assume their child would develop T1D\, most parent
s considered active treatments to delay progression. For medicines under d
evelopment to delay insulin dependence in T1D\, the preferences expressed
in this survey provide guidance on acceptable benefit-risk trade-offs.\n
\n \n \n \n \n \n
\n \n \n \n \n
\n \n \n \n Gaë\;l
le Saint-Hilary\n \n \n Gaë\;lle Sain
t-Hilary is Statistical Methodologist at Servier (France) since 2018. She
started in 2006 as statistician on clinical projects\, first at Servier an
d then at Novartis Oncology\, where she was responsible for the clinical d
evelopment and the licensing of medicinal products in neuropsychiatry and
leukemia. Passionate statistician\, she decided to go back to university\,
and she obtained in 2018 a PhD on &ldquo\;Quantitative Decision-Making in
Drug Development&rdquo\; at the Polytechnic University of Turin (Italy)\,
where she continues to conduct research projects. Her main scientific int
erests are benefit-risk assessment\, knowledge and preference elicitation\
, historical data and quantitative decision-making.\n  \;\n
\n \n Graphical Elicitation Framework fo
r Trade-Offs and Preferences (GEF-TOP).\n Authors - Gaë\;ll
e Saint-Hilary (Servier\, Polytechnic University of Turin)\; Pavel Mozguno
v (Lancaster University)\n Multi-criteria decision analyses (MC
DA) have been proposed to perform drug benefit-risk assessments\, incorpor
ating preferences of the decision-makers regarding the relative importance
of the criteria. These approaches require upstream work to capture the tr
ade-offs the stakeholders make between multiple benefits and risks. Discre
te Choice Experiment (DCE) and Swing-Weighting (SW) are the most popular m
ethods for eliciting criterion weights from contributors (patients\, exper
ts...) in benefit-risk analyses. While DCE requires a large sample size an
d might not be appropriate in situations where the number of stakeholders
is limited\, SW permits to collect preferences from a panel of few partici
pants. However\, SW usually necessitates noticeable cognitive requirements
\, as the contributors are asked to quantify the relative importance of ch
anges on the criteria\, which may be difficult to provide. Moreover\, many
implementations of SW require a consensus to be reached by the stakeholde
rs. Therefore\, SW may be demanding to be applied in practice. To address
these concerns\, we propose a Graphical Elicitation Framework for Trade-Of
fs and Preferences (GEF-TOP) as an alternative to SW for preference elicit
ation in the setting with a small number of stakeholders. Via the visual r
epresentation of the benefits and risks criteria and few simple questions
phrased in terms of treatment performances\, the approach permits to limit
the participant effort while ensuring accurate capture of the preference
information. The questions are constructed to maximize the precision of th
e weight estimates. We present the application of the approach to linear a
nd non-linear benefit-risk aggregation methods\, and study its patterns of
behavior compared to SW in a comprehensive simulation study.\n
\n \n \n\n \;
DTEND:20201013T143000Z
DTSTAMP:20240329T051638Z
DTSTART:20201013T130000Z
LOCATION:
SEQUENCE:0
SUMMARY:PSI Webinar: Patient preference studies
UID:RFCALITEM638472861989534439
X-ALT-DESC;FMTTYPE=text/html:Date: Tuesday 13th October 20
20
\nTime: 14:00 - 15:30 (BST)
\nSpeake
rs: Sheila Dickinson\, Rachael DiSantostefano\, and \;Gaë
\;lle Saint-Hilary.
\n
Patient preference studies are becoming more frequentl y used in drug development. In this webinar you will hear an introduction to what a patient preference study is as well as an overview of where this type of study can inform regulatory decision making. This will be followe d by 2 examples looking at potential approaches to eliciting patient prefe rence demonstrating how such studies can be designed and analysed.
\n\n
Speaker \n | \n <
td valign="top" style="width: 244px\;">\n \n Abstract \n \n | |
\n
| \n \n Sheila Dickinson is a Senior Expert Qu antitative Safety Scientist at Novartis Pharma AG. She is on the managemen t board of the IMI PREFER project\, which is working on developing guideli nes about when and how to perform patient preference studies to support me dical product decision-making. Her other responsibilities include supporti ng patient preference study activities within Novartis\, and promoting and supporting the use of a structured benefit-risk approach by project teams . \nSheila holds a degree in mathematics from Imperial C ollege\, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. \nAfter joining Novarti s in 1997\, she worked as a statistician supporting projects in the variou s disease areas including both diabetes and malaria\, before moving to the Quantitative Safety group in 2013. \nPrior to joining N ovartis Pharma\, Sheila worked as a statistician for Pfizer. \n \; \n | \n \n How patient preference studies c an inform decisions during drug development. \nPatient associations\, industry\, regulators and HTA bodies agree that pat ients&rsquo\; views should inform drug development activities. Patient pre ference studies are one way to assess patients&rsquo\; views\, and can be particularly helpful in 2 types of scenario: where there is a need to unde rstand which issues in a disease matter to patients\, and where there is a need to understand the acceptability to patients of a benefit-risk trade- off (i.e. it&rsquo\;s not clear that a particular drug is going to be the obvious choice for all patients e.g. because this particular drug offers s trong benefits at the expense of important side-effects\; because patients need to make a choice between very different alternatives such as surgery vs. drug therapy etc.). This presentation describes how patient preferenc e studies can inform routine regulatory decisions\, and discusses an examp le patient preference study assessing which endpoints matter to patients w ith COPD. It also introduces a framework that offers a structure to guide a preference study sponsor through key issues when design\, conducting and analysing a patient preference study\, and that supports the discussion b etween industry\, regulators and HTA bodies about preference studies inten ded to inform medical product decision-making. \n \; \n | \n
\n
| \n
\n Rachael L. DiSantostefano\, MS PhD\, is a Senior Director of Benefit-Risk in the E pidemiology Department within Janssen Pharmaceuticals\, R&\;D\, LLC. Sh e has more than 25 years of pharmaceutical research experience across the quantitative disciplines of epidemiology\, biostatistics\, and health outc omes. Currently\, she focuses on benefit-risk assessment and quantitative patient preference research. Dr. DiSantostefano is also an active member o f PREFER\, a 5-year public-private partnership that examines how and when to perform and include patient preference studies in decision making durin g the medical product life cycle. Her research interests also include drug safety\, observational studies\, and innovation in observational studies. \n \; \n | \n \n Parent Preferences for Delaying Insulin Dependence in Children: A Discrete Choice Experiment . \nAuthors: Rachael L DiSantostefano strong>1\, Jessie Sutphin2\, Joseph A Hedrick3< /sup>\, Kathleen Klein2\, Carol Mansfield2 \n1Janssen Research &\; Development\, LLC\, Titusville\, New J ersey. \n2RTI Health Solutions\, Research Triangle Park\ , North Carolina. \n3Janssen Research &\; Development \, LLC\, Raritan\, New Jersey. \nBackground: Screening f
or auto-antibodies can identify children at increased risk of progression
to type-1 diabetes (T1D) that requires insulin. | \n
\n
| \n
\n Gaë\;lle Saint-Hilary is Statistical Methodologist at Servier (France) since 2018. She started in 2006 as statistician on clinical projects\, first at Servi er and then at Novartis Oncology\, where she was responsible for the clini cal development and the licensing of medicinal products in neuropsychiatry and leukemia. Passionate statistician\, she decided to go back to univers ity\, and she obtained in 2018 a PhD on &ldquo\;Quantitative Decision-Maki ng in Drug Development&rdquo\; at the Polytechnic University of Turin (Ita ly)\, where she continues to conduct research projects. Her main scientifi c interests are benefit-risk assessment\, knowledge and preference elicita tion\, historical data and quantitative decision-making. \n \; \n | \n \n Graphical Elicitation Framework for Trade-Offs and Preferences (GEF-TOP). \nAuthors - Gaë\;lle Saint-Hilary (Servier\, Polytechnic Unive rsity of Turin)\; Pavel Mozgunov (Lancaster University) \n < p>Multi-criteria decision analyses (MCDA) have been proposed to perform dr ug benefit-risk assessments\, incorporating preferences of the decision-ma kers regarding the relative importance of the criteria. These approaches r equire upstream work to capture the trade-offs the stakeholders make betwe en multiple benefits and risks. Discrete Choice Experiment (DCE) and Swing -Weighting (SW) are the most popular methods for eliciting criterion weigh ts from contributors (patients\, experts...) in benefit-risk analyses. Whi le DCE requires a large sample size and might not be appropriate in situat ions where the number of stakeholders is limited\, SW permits to collect p references from a panel of few participants. However\, SW usually necessit ates noticeable cognitive requirements\, as the contributors are asked to quantify the relative importance of changes on the criteria\, which may be difficult to provide. Moreover\, many implementations of SW require a con sensus to be reached by the stakeholders. Therefore\, SW may be demanding to be applied in practice. To address these concerns\, we propose a Graphi cal Elicitation Framework for Trade-Offs and Preferences (GEF-TOP) as an a lternative to SW for preference elicitation in the setting with a small nu mber of stakeholders. Via the visual representation of the benefits and ri sks criteria and few simple questions phrased in terms of treatment perfor mances\, the approach permits to limit the participant effort while ensuri ng accurate capture of the preference information. The questions are const ructed to maximize the precision of the weight estimates. We present the a pplication of the approach to linear and non-linear benefit-risk aggregati on methods\, and study its patterns of behavior compared to SW in a compre hensive simulation study.\n | \n
 \;
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