Annual Meeting Proceedings Part 1 - American Society of Clinical ...

152s Developmental Therapeutics—Clinical Pharmacology and Immunotherapy
2541 General Poster Session (Board #1D), Mon, 8:00 AM-12:00 PM
Relationship of variability in tumor measurement and response assessment.
Presenting Author: Binsheng Zhao, Department of Radiology, Columbia
University Medical Center, New York, NY
Background: RECIST is widely used to evaluate anti-cancer therapy efficacy.
This study explored variability in reporting tumor change and
response to therapy due to both target lesion selection and measurement.
Methods: 2256 measurements were performed in CT scans of chest,
abdomen and pelvis from 30 patients retrospectively taken from a multicenter
Phase II/III colorectal clinical trial. Using RECIST, three radiologists
interpreted baseline, 6-wk and 12-wk scans in the following manner: (1)
Radiologists independently selected and measured target lesions, (2) one
radiologist’s target lesions were re-measured by the other two and (3) one
radiologist re-measured the same scans in the above manner at an interval
of greater than a month to prevent memory recall. Measurement variability
in total tumor burden (TTB) on relative changes at 6-wk and 12-wk from
baseline was analyzed for inter- and intra-reader target lesion selection,
inter- and intra-reader measurement using Bland-Altman method, and
agreements on RECIST categorical responses were assessed by kappa
coefficient. Results: When the same target lesions were used, inter- and
intra-reader variability in TTB on relative changes at 6-wk and 12-wk from
baseline were similar; all had 95% limits of agreement within (-15%,
15%). Kappa coefficients for RECIST were 0.74 (6-wk) and 0.87 (12-wk)
for inter-reader and 0.64 (6-wk) and 0.88 (12-wk) for intra-reader to report
responses. When radiologists independently selected and measured target
lesions, variability in relative changes was within (-17%, 16%) at 6-wk and
(-24%, 23%) at 12-wk for inter-reader and (-16%, 16%) at 6-wk and
(-14%, 18%) at 12-wk for intra-reader interpretations. Kappa coefficients
were 0.66 (6-wk) and 0.75 (12-wk) for inter-reader and 0.63 (6-wk) and
0.80 (12-wk) for intra-reader to report responses. Conclusions: Differences
exist in measuring tumor change. The magnitude of change in categorical
RECIST response is quantifiable. The largest differences are when radiologists
independently select and measure target lesions, the smallest when
one radiologist repeats measurements on identical target lesions. The
variability may impact the reporting of categorical responses and trial
results, especially in a single arm study.
2543 General Poster Session (Board #1F), Mon, 8:00 AM-12:00 PM
Clinical importance of including new and nontarget lesion assessment of
disease progression (PD) to predict overall survival (OS): Implications for
randomized phase II study design. Presenting Author: William Leonard
Mietlowski, Novartis Oncology, Florham Park, NJ
Background: Fridlyand (2011) retrospectively compared PFS vs. change in
tumor burden as a primary endpoint in phase II non-small cell lung cancer
(NSCLC) trials to inform phase III decision making and found the use of
PFS was superior. Since the classic tumor burden model only uses
measurements of target lesions, we investigated whether the model could
be strengthened by incorporating new and non-target lesion progression.
The ability to use a strong tumor burden model has the benefit of potentially
earlier decision making and considerable timeline savings. Methods: We
analyzed five phase III trials of combination chemotherapy � targeted
therapies with an OS primary endpoint: 1st, 2nd line NSCLC (ATTRACT-1,
-2), 1st, 2nd line colorectal carcinoma (CONFIRM-1, -2), and 2nd line
ovarian cancer (EPO906A2303). We applied Cox’s proportional hazards
model to OS using the covariates of baseline tumor burden, 1st tumor
assessment percentage change from baseline, new lesions, and non-target
PD. Results: See table. Conclusions: We show that predictive models for OS
should consider new and non-target lesions for PD, as well as target lesion
tumor burden, findings independently corroborated by Suzuki (2011). We
propose a longitudinal rank-based randomized phase II design, ranking a
patient’s risk of death, differentially weighting PDs by type and time of PD,
and percentage change in tumor burden. This may be more informative for
phase II decision making for phase III trials based on OS, than PFS which
only uses time of PD. Further studies with other tumor types and treatment
modalities are warranted.
Study
Baseline
tumor burden*
Estimated hazard ratio (Wald test p value)
% change
from baseline* New lesion
Non-target
lesion PD
ATTRACT-1 1.36 (p�0.001) 1.37 (p�0.001) 3.37 (p�0.001) 1.95 (p�0.001)
ATTRACT-2 1.21 (p�0.001) 1.49 (p�0.001) 3.91 (p�0.001) 1.19 (p�0.332)
EPO906A2303 1.09 (p�0.053) 1.12 (p�0.046) 2.20 (p�0.001) 1.67 (p�0.001)
CONFIRM-1 1.31 (p�0.001) 1.38 (p�0.001) 3.02 (p�0.001) 1.40 (p�0.087)
CONFIRM-2 1.41 (p�0. 001) 1.47 (p�0.001) 2.54 (p�0.001) 1.81 (p�0.001)
* Unit of measurement is one standard deviation.
2542 General Poster Session (Board #1E), Mon, 8:00 AM-12:00 PM
A multicenter phase II neoadjuvant trial of bevacizumab combined with
docetaxel plus carboplatin in the treatment of triple-negative breast cancer:
Korean Cancer Study Group (KCSG-BR 0905, NCT 01208480). Presenting
Author: Hye Ryun Kim, Division of Medical Oncology, Department of
Internal Medicine, Yonsei University College of Medicine, Seoul, South
Korea
Background: Triple negative breast cancer (TNBC) is dismal disease that is
ineligible for endocrine or anti-HER2 therapy. We have conducted a phase
II neoadjuvant trial to evaluate efficacy and tolerability of bevacizumab
combined with docetaxel plus carboplatin in TNBC. Methods: Women with a
histologically confirmed stage II or III TNBC were eligible. Hormone
receptors and HER2 negativity were confirmed by immunohistochemistry
and/or fluorescence in situ hybridization. Patients received 6 cycles of
docetaxel 75 mg/m2 , carboplatin AUC 5, and bevacizumab 15 mg/kg on
day1 every 21 days. Bevacizumab was omitted in the last cycle to avoid
wound complication. The primary endpoint was pathologic complete
response (pCR) rate in both breast and axillary lymph node and secondary
endpoints were clinical response rate, toxicity profiles, and breast conserving
surgery (BCS) rate. Results: Forty-five TNBC patients were recruited
from 7 institutes in the Korean Cancer Study Group (KCSG) between
October 2010 and August 2011. The median age of the patients was 45
years (30-72 years). The T1, T2, and T3 were 4.4 %, 68.9 %, and 26.7 %,
respectively and axillary lymph node was positive in 80% by breast MRI.
Among 45 patients, 44 patients completed 6 cycles of therapy followed by
surgery and one patient was withdrawn due to patient’s refusal of further
therapy after 3rd cycle. The pCR rate was 42.2 % (19/45) and clinical
response rate was 95.5 % (43/45) (CR, n� 6; PR, n�37; SD, n�1; not
evaluable, n�1) based on RECIST criteria 1.1. BCS was undertaken in
77.7 % (35/45). The grade 3 or 4 adverse events were neutropenia (38),
febrile neutropenia (4), vomiting (3), nausea (2), anemia (1), thrombocytopenia
(1), stomatitis (1), gastrointestinal bleeding (1), and increased ALT
(1). Only one patient experienced delayed wound healing after breast
surgery. Conclusions: Bevacizumab in combination with docetaxel and
carboplatin as neoadjuvant treatment provided an encouraging pCR rate
(42.2 %) and a negligible wound healing problem after surgery. The
adverse events were manageable.
2544 General Poster Session (Board #1G), Mon, 8:00 AM-12:00 PM
How to run survival-endpoint phase II trials with 25% to 40% fewer
patients. Presenting Author: Michael J. Schell, H. Lee Moffitt Cancer
Center & Research Institute, Tampa, FL
Background: New molecular information, whether arising from expression
profiling, identification of key mutations, or proteomic analyses is making
the personalization of therapy increasingly feasible. This leads to the
fragmentation of common disease entities into multiple molecular subtypes.
Having sufficient numbers of patients to demonstrate the effectiveness
of novel targeted therapies for each subtype has therefore become
challenging, essentially impeding progress. Methods: Use of sample size
determination software allows for comparison of phase II trials with a target
survival proportion at a given time T based upon Kaplan-Meier versus
exponential survival methods. Results: The use of exponential survival
fitting methods, in lieu of the currently implemented trial designs, to single
arm phase II studies can routinely reduce patient numbers by 25-40%
(Table) without compromising the statistical power. The biggest advantage
is that survival information both before and after time T reduces the
variability for the exponential fit estimate. This approach will lead to the
saving of financial and patient resources for researchers. Moreover, the
time saved will accelerate the approval of agents making the proposed trial
designs ethically attractive. However, this approach is only applicable if the
exponential distribution assumption behind the approach is valid.
Conclusions: The exponential survival fitting method should replace the
current standard approach in all instances unless the exponential distribution
assumption is known to be false. Detailed examples and analysis will
be presented.
Percent savings obtained by using the exponential fit approach.
(T,T*)
HR (1,1) (2,2) (3,3) (4,4) (1,1.5) (1,2) (2,3) (2,4)
2.0 5 15 25 36 30 41 31 38
1.83 8 15 26 40 31 42 30 36
1.67 9 12 28 38 32 42 28 33
1.50 6 16 23 38 30 40 30 36
Avg. 7 14 26 38 31 41 30 36
T is scaled so T�1 is the median survival time; T* is the time through which the
exponential fit is used; HR is the ratio of the alternative to null hypothesis
median survival times.
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