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A B S T R A C T S
can be collected during routine follow up and help determine
the impact of treatment toxicity on patients’ reported quality
of life following radical treatment for prostate cancer.
The purpose of this study was to explore the effect of age
on patient reported quality of life following radical prostate
radiotherapy using the EPIC-CP tool.
Objectives:
The purpose of this study is to explore the
effect of age on late (
3 months post radiotherapy) patient
reported quality of life following radical prostate radiotherapy
using the EPIC-CP.
Methods:
All men who received radical prostate radio-
therapy with intensity-modulated radiation therapy (IMRT)
for localized prostate cancer between 2011 and 2015 at
University College London Hospital were identified. Baseline
demographics, disease specific parameters and treatment
details were collected. EPIC-CP questionnaires were distri-
buted to all men on this database attending follow up at
University College London Hospital between January and
May 2016. The EPIC-CP was self-administered and assessed
urinary and bowel symptoms and erectile function. Urinary,
bowel and sexual function domains and overall EPIC-CP score
were analyzed according to age.
Results:
One hundred and three complete questionnaires
were analysed; 3 patients had incomplete questionnaires and
were excluded. All patients had completed radiotherapy at
least 3 months previously. The median age was 70 (50-85). The
majority of patients (83/100) had high risk disease according
to D’Amico risk stratification. Radiotherapy treatment was
as follows: external beam radiotherapy to prostate and
seminal vesicles 83/100; external beam radiotherapy to
prostate, seminal vesicles and pelvic lymph nodes with HDR
brachytherapy boost 22/100; prostate bed 17/100.
The mean overall and domain specific EPIC-CP scores for all
patients and age specific subgroups are presented in Table 1.
Conclusion:
In our patient population we found no
statistically significant difference in patient reported toxicity
outcomes according to age following radical prostate
radiotherapy. This may indicate reasonable tolerance of
prostate radiotherapy in the elderly. To investigate further we
recommend ongoing prospective collection of quality of life
data at baseline and at follow up intervals after radiotherapy.
Disclosure of interest:
A. Nuhoglu Savas: None declared,
L. Sellers: None declared, A. Al-Abdullah: None declared, R.
Ramiswami: None declared, R. Davda Grant/Research Support
from: Astellas, Jansen andTakeda, Paid Instructor for: Astellas,
A. Mitra: None declared, H. Payne Grant/Research Support
from: received honoraria for advisory boards or lectures or
travel expenses to attend medical meetings from Janssen,
Astellas, Sanofi, Sandoz, Astra Zeneca, Takeda, Ipsen, Bayer
and Ferring
Keywords:
EPIC-CP, patient reported outcomes, prostate,
bladder, kidney, genitourinary cancers, radiotherapy
P068
HOWTO ADDRESS THE HETEROGENEITY IN THE DESIGN OF
PHASE II CLINICAL TRIALS IN GERIATRIC ONCOLOGY?
B. Cabarrou
1,
*, E. Leconte
2
, L. Mourey
3
, P. Sfumato
4
, L. Balardy
5
,
C. Bellera
6,7
, J.-P. Delord
3
, J.-M. Boher
4
, T. Filleron
1
1
Department of Biostatistics, Insititut Claudius Regaud - IUCT-O,
2
TSE-R, Université Toulouse 1 Capitole,
3
Department of Oncology,
Insititut Claudius Regaud - IUCT-O, Toulouse,
4
Department of
Biostatistics, Institut Paoli Calmettes, Marseille,
5
Department of
Oncology, CHU, Toulouse,
6
Elderly and Cancer Platform - French
League Against Cancer,
7
Department of Biostatistics, Institut
Bergonié - Comprehensive Cancer Center, Bordeaux, France
Introduction:
With the overall aging population and the
increased incidence of cancer, incidence of cancer in
75 years
patients is greater than 30%. However, this heterogeneous
population is often excluded from clinical trials and the
lack of prospective data makes difficult the management of
these patients. Many publications highlight the importance
to conduct clinical trials in this population (Pallis, 2011).
As classical single-arm phase II designs (Fleming, 1982;
Simon, 1989) do not take into account the heterogeneity,
elderly specific phase II clinical trials are very uncommon
and generally conducted in specific groups defined by
geriatric criteria which increases the number of patients to
be included and thus reduces the feasibility. Several designs
have been proposed in the literature to address the patients’
heterogeneity in phase II trials for target therapy. In practice,
these adaptive designs remain unknown from the clinicians
and are rarely applied in geriatric oncology.
Objectives:
The main objective of this work is to
present phase II clinical trials designs that take into
account the heterogeneity of the population and to make
recommendations on the methodology to be used in phase II
clinical trials in geriatric oncology.
Methods:
Alternative methods have been proposed in
the literature to deal with stratification in phase II clinical
trials and identification of the best target population will be
presented and compared to classical designs (one study in
each specific subset of patients). Characteristics of adaptive
and classical designs will be illustrated through theoretical or
real examples of elderly specific phase II clinical trials.
Results:
Depending on the hypotheses of the study, the use
of adaptive designs could reduce the sample size compared
to classical designs. For example, assume an elderly specific
clinical trial designed as two parallel single-arm phase II
studies, one including patients with G8
14 and the other
including patients with G8
14. Uninterested feasibility rate is
fixed at 20% in each group and desired feasibility rates are
fixed at 35% and 45% in G8
14 and G8
14 groups, respectively.
Using a two-stage optimal Simon design for each group with
=2.5% (overall
=5%) and power=85%, a maximum of 129
patients have to be included. Under the same hypotheses,
a maximum of 103 patients have to be included using the
adaptive design proposed by Parashar (Parashar, 2016) which
allow the possibility to enrol patients of both groups (G8
14 or
G8
14) in the same study. Stopping rules at interim and final
analysis are presented in Figure 1.