Speaker
\nBio
graphy
Abstract< u5:p>
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\n Rachel Hodge
\n Astrazenec
a
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\n Session chair: \;Fabio Rigat\, \;Janssen. \;
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Rachel Hodge is Director and Biometric Te am Leader at AstraZeneca which she joined 6 years ago. Rachel led the deve lopment of Tagrisso in NSCLC through its multiple filings and designed sev eral studies. Rachel is also the statistical lead for the ctDNA workstream at AstraZeneca. Previously\, Rachel worked at GSK where she designed and reported several phase 2 and phase 3 oncology trials. Rachel holds an MSc in Statistics from the University of Sheffield.
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\n In this introduction\, two main uses of
ctDNA will be presented and discussed. Firstly\, ctDNA as a measure of mi
nimal residual disease (MRD) allows to detect patients at higher of diseas
e relapse. Multiple ctDNA assay may be required and personalised assay can
be developed. This has various implications for study designs focusing on
patients with MRD. Secondary\, ctDNA can serve as response evaluation cri
teria. Many examples exist in leukemia. The challenges to use ctDNA as sur
rogate endpoint in solid tumors will be discussed. \;
\n Thomas Jaki
\n MRC Biostatistics Unit
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\n Session chair: \;Rhiannon Maudsley\, \
;AstraZeneca.
Thoughts on Late-Onset Toxi cities in dose-finding studies
\nPhase I dose-finding trials often seek to ide
ntify the maximum tolerated dose\; the dosewith a particular risk of toxic
ity and only toxicities during the first cycle of therapy are used for thi
s purpose.A course of treatment frequently consists of multiple cycles of
therapy\, however\, so that theoverall risk of toxicity for a given treatm
ent is not fully encapsulated by observations from the first cycle. This t
alk will discuss the challenges that arise when the toxicity period is ext
ended and discuss different methods to account for such late onset toxicit
ies
\n Archan Bha
ttacharya
\n Janssen
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Session chair: \;Thomas Jaki\, \;M
RC Biostatistics clinical trial unit.
Archan Bhattacharya is a clinical statistician at Janssen\, working on de
sign and analysis of lung cancer trials. Prior to joining Janssen\, Archan
worked at PAREXEL where he supported oncology development programs target
ing solid tumours and multiple myeloma with small molecules\, drug-antibod
y conjugates and T-cell therapy. Prior to working in oncology\, Archan was
a CRO statistician on phase III/IV rheumatoid arthritis trials. He receiv
ed his PhD in Statistics from the University of Georgia focusing in on Bay
esian inference and computation. He has been a research fellow at the Univ
ersity of Nottingham\, working on the identification of contributing facto
rs in osteoarthritis to reduce disease burden through life-style changes a
nd social awareness. He taught Statistics at different levels in universit
ies in India.
Integration of real
world data in oncology early development studies
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\n Single arm phase 1 trials are important in early cl
inical development process across all therapeutic area and in oncology as
well. Lack of control arms always raise the question of ability to general
ise its findings as well. Health authorities are more keen to know about p
erformance of novel treatment as compared to what has been available. Not
to mention\, it has become an integral part of health economics modelling
and market access applications. I am going to go through my recent experie
nce about an external control arm study starting from real world data acqu
isition\, data quality\, protocol development\, covariate balancing\, proc
ess development and dissemination.
\n Nigel Stallard\n University of Warwick
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Session chair: \;Emma Clark\, \;Roche.
Nigel St
allard is Professor of Medical Statistics\, Head of the Statistics and Epi
demiology Group and Deputy Head of the Division of Health Sciences at Warw
ick Medical School. Professor Stallard's primary research interests are in
the statistical design and analysis of clinical trials. In particular\, h
e has worked on optimal trial design and on methodology for clinical trial
s with interim analyses and adaptations such as treatment selection. His m
ost recent work involves the use of short-term endpoint data for decision-
making during the course of a clinical trial and the development of innova
tive methods for clinical trials in small populations.
Multiplicity in con firmatory clinical trials with master protocol designs
\nRecent advances in tumour biology and targeted therapies have le d to clinical trials considering treatment effects in multiple subgroups o f the patient population. These can lead to efficiency gains by testing se veral statistical hypotheses in the same clinical trial. Recently proposed approaches include adaptive enrichment\, umbrella and basket trial design s. Although much of the development of novel designs has been in explorato ry phase II trials\, there is growing interest in such methods in confirma tory randomized controlled trials. These might be phase III trials with su bgroup analyses or phase II/III trials combining exploratory and confirmat ory elements. In such a setting\, the multiple hypothesis tests can lead t o statistical error rate inflation and hence to the question of when stati stical correction for multiplicity should be implemented. This talk will s urvey the novel design approaches for clinical trials with subgroups and e xplore the multiplicity issues that arise. Based on this\, a proposal will be made for when multiplicity corrections are needed for confirmatory tri als employing such innovative designs.
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\n Emma Clark
\n
Roche
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\n Session c
hair: Kirsty Hicks\, GSK.
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FDA Complex Innovative Design Pilot: experi
ence of using external control data to analyse secondary endpoints
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\n Randomized phase 3 studies are co
nsidered the gold standard for registrational purposes. On the other hand\
, inclusion of external controls has perceived benefits in terms of costs\
, timelines\, and sparing new patients from control arm treatment but also
comes with potential risks such as Type 1 error inflation. Health Authori
ties are understandably cautious of approving such designs. This talk will
focus on our experience of collaborating with the FDA on the design of a
phase 3 study in 1L Diffuse Large B-Cell Lymphoma (DLBCL)\, incorporating
a hybrid external control arm using Bayesian dynamic borrowing with propen
sity score matching for the analysis of overall survival\, a key secondary
endpoint\, through the FDA&rsquo\;s Complex Innovation Trial Designs (CID
) Pilot Meeting Program. The proposed design brings in the key secondary a
nalysis with increased power and a label-enabling potential at the same ti
me as the primary endpoint.
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