A Phase III, Randomized Clinical Trial of Standard Adjuvant Endocrine Therapy +/- Chemotherapy in Patients With 1-3 Positive Nodes, Hormone Receptor-Positive and HER2-Negative Breast Cancer With Recurrence Score (RS) of 25 or Less. RxPONDER: A Clinical Trial Rx for Positive Node, Endocrine Responsive Breast Cancer
Phase: PHASE3
Conditions: Breast Ductal Carcinoma In Situ, Invasive Breast Carcinoma, Multicentric Breast Carcinoma, Multifocal Breast Carcinoma, Synchronous Bilateral Breast Carcinoma
Sponsor: National Cancer Institute (NCI)

 
 
 
December 10, 2021 
 
 
Adult CIRB - Late Phase Emphasis 
 
RE: 
S1007, "A Phase III, Randomized Clinical Trial of Standard Adjuvant Endocrine Therapy +/- 
Chemotherapy in Patients with 1-3 Positive Nodes, Hormone Receptor-Positive and HER2-
Negative Breast Cancer with Recurrence Score (RS) of 25 or Less. RxPONDER: A Clinical Trial 
Rx for Positive Node, Endocrine Responsive Breast Cancer.”  Study Chairs: Drs. K. Kalinsky, 
J.R. Gralow, F. Meric-Bernstam, G.N. Hortobagyi, K.S. Albain and W. Barlow. 
 
RESPONSE TO CTEP REVIEW COMMENTS (Protocol Version Date: 10/08/21)  
 
Dear CTEP,  
 
Thank you for your consideration of the above-referenced SWOG protocol.  The following concerns were 
expressed by CTEP in review of S1007 protocol Revision #18 (Version Date 10/08/21). 
 
Please find the study team responses and associated modifications below. 
I. 
Comments Requiring a Response – CTEP Stipulations: 
# 
Section 
Comments 
1.  
18.2 
Although GEM ExTrA is a reasonable platform for the investigators to use and 
using a single platform for genomic signature analyses will increase 
comparability across signatures, it is unclear how the investigators intend to 
calculate the scores from the signatures they lift. While the loci used to 
determine each score are known, the exact risk score calculations are 
proprietary information. If the investigators intend to “reinvent” the signatures 
using these data, their analysis plan should detail the procedures they intend 
to use (e.g., separating the data into training/validation sets, models, etc.) and 
address the limitations of this approach. Otherwise, the investigators should 
confirm that they have access to the information necessary to calculate the risk 
scores for the signatures of interest. 
Study Team Response:  
In the correlative proposal, we will be using GEM ExTrA platform to assess 
expression of multiple genes sets, proposed to be prognostic or predictive in 
breast cancer. We realize this approach has a few caveats: 
• 
Most of the gene sets were originally discovered by microarray technology. 
In preliminary studies we compared the concordance of RNA expression 
measurements based on Agilent custom gene expression arrays and 
Illumina RNA sequencing platforms that have been previously 
published(PMID: 26451490). We used breast cancer patients’ samples 
spanning all breast cancer subtypes from the TCGA project (N=421). Only 
the samples with both microarray and RNA sequencing data were included 
in the analysis. We demonstrated the high correlation between log 
transformed RNAseq and microarray measurements suggesting with 
proper transformation both data platforms are provided may be adapted 
for risk predictions. The plots below are for the genes ERBB2, ESR1, 
MKI67, ERBB2 and PGR (Figure 1), demonstrating significant correlations 
between RNA expression by array and RNAseq approaches. 

 
S1007 
 
Response to CTEP Review Comments on Revision #18 (Version Date:10/8/21) (contd.) 
 
Page 2 
 
 
 
 
• 
There are currently several prognostic and predictive signatures proposed 
for use in breast cancer. Many of these gene sets differ in the genes 
included and it is not possible to test the contribution of other gene sets 
without using a central platform approach:  
  
• 
Using a RNAseq based approach rather than using selected multigene 
panel commercial assays will be more tissue sparing, allowing us to test 
multiple gene sets and will also leave to potential for new signature 
discovery (as an exploratory endpoint). Importantly the RNAseq and WES 
will be made publicly available after the initial publication of our biomarker 
work and will provide an unparalleled resource for discovery to the 
scientific community to address additional questions about breast cancer. 
• 
We appreciate the concern raised that derived signatures would not be 
able to calculate risk scores in the same way that other commercial assays 
would. With our approach we will be deriving “pseudoscores” using 
principal component analysis. In the revised protocol we expanded the 
analysis section to clarify the methodology we will be using with references 
to prior work. The new section is included below: 
Discovery Analysis Methods 
Genes considered will be all the constituent genes (except reference genes, 
where present) from the MammaPrint, PAM50, SET Index, Endopredict, Breast 
Cancer Index and Recurrence Score tests. For each set of genes examined, a 
score will be constructed using the first principal component of the gene set.  
For assessment of chemotherapy effect prediction, a Cox proportional hazards 
regression model will be fit with endpoint iDFS and terms for the gene set score, 
treatment and the interaction of the gene set score with treatment. The log 
standardized hazard ratio for interaction (Crager 2020) and its variance will be 
computed for each gene set score. 
For assessment of prognosis, a Cox model will be fit with a single term for the 
gene score using the patients who were randomized to endocrine therapy 
alone. For assessment of residual risk, the same procedure will be used for 
patients randomized to chemo-endocrine therapy.   

 
S1007 
 
Response to CTEP Review Comments on Revision #18 (Version Date:10/8/21) (contd.) 
 
Page 3 
 
 
 
False discovery rates (Storey 2002) and log standardized hazard ratios with 
correction for regression to the mean (Crager 2010, Crager 2012) will be 
calculated using model space sampling considering the universe of gene set 
scores selected from all genes under consideration and gene sets from 1 to 40 
genes.  
If prognostic gene sets are discovered at FDR 10%, their prognostic efficacy 
will be described using predictiveness curves (Huang, Pepe and Feng, 2007) 
corrected for regression to the mean.   
If predictive gene sets are discovered at FDR 10%, their predictive efficacy will 
be described using treatment effect predictiveness curves, that is, 
predictiveness curves applied to the distribution of estimated treatment hazard 
ratio with correction for regression to the mean.  Potential gene set score cut-
points for identifying patients with substantial treatment benefit versus no 
substantial benefit will be assessed based on these curves. 
These discovery analyses will be conducted separately for pre-menopausal 
patients and post-menopausal patients. 
Pseudoscores were previously constructed using RNASeq of the SWOG 8814 
study and the constituent genes of the MammaPrint®, Prosigna®, 
EndoPredict®, Genomic Grade Index, Breast Cancer Index® and Sensitivity 
Endocrine Treatment (SET) scores as well as the Oncotype DX Recurrence 
Score®. Each pseudoscore was constructed using the coefficients of the first 
principal component of the constituent genes. These pseudoscores will be 
evaluated and compared as continuous numeric biomarkers for prognosis of 
iDFS and prediction of the effect of chemotherapy using the RxPONDER data 
set and standardized hazard ratios. Categorical analyses for both prognosis 
and prediction will use equivalent cut-points using population quantiles.  Since 
SWOG 8814 included only post-menopausal women, the pseudoscores will be 
re-derived separately using pre-menopausal and post-menopausal women in 
RxPONDER and the scores compared between pre- and post-menopausal 
women. If it is concluded that the premenopausal pseudoscores are sufficiently 
different from the postmenopausal pseudoscores, then it may require 
regeneration of the first principal component weights using five-fold cross-
validation. Overall, it is recognized that the pseudoscores are not an exact 
match for the actual gene signatures, as they use different coefficients and 
analytical platforms, so that the performance of the actual signatures might be 
different. This analysis seeks to generally evaluate the information content of 
the constituent genes in each gene list.     
Because of the restriction of the S1007 study population to patients with 
Recurrence Score result 0 – 25, it is recognized that the estimated prediction 
of effects of genes from the Recurrence Score and other genes substantially 
correlated with these genes will be biased downward. 
References 
Crager MR (2010). Gene identification using true discovery rate degree of 
association sets and estimates. Statistics in Medicine 29:33-45. 
Crager MR (2012). Generalizing the standardized hazard ratio to multivariate 
proportional hazards regression, with an application to clinical-genomic 
studies. Journal of Applied Statistics 39:399-417. 
Crager MR (2020). Extensions of the absolute standardized hazard ratio and 
connections with measures of explained variation and variable importance.  
Lifetime Data Analysis 26:872-892. 

 
S1007 
 
Response to CTEP Review Comments on Revision #18 (Version Date:10/8/21) (contd.) 
 
Page 4 
 
 
 
Huang Y, Pepe MS, Feng Z. Evaluating the predictiveness of a continuous 
marker. Biometrics 63:1181-1188. 
Storey JD (2002). A direct approach to false discovery rates. Journal of the 
Royal Statistical Society Series B. 64:479–498. 
2.  
18.2 
No statistical plan is provided for the cfDNA analyses; additionally, it is unclear 
whether the bespoke ctDNA analysis intended by the investigators performs 
comparably between EDTA and Streck-preserved specimens, and the 
investigators state that they intend to use both types of specimens for this 
analysis. The investigators should consider amending the protocol to add these 
analyses at a later date, when they have a full statistical plan and have assay 
validation data confirming that the EDTA and Streck tubes have good 
concordance. 
Study Team Response:  
Thank you. The cfDNA analyses have been removed per CTEP request. 
3.  
18.2 
Please indicate the funding secured for performing the described analyses. 
Study Team Response:  
Thank you. The contract with Exact Sciences is still in process. Exact Sciences 
Corporation has agreed to perform analytic assays (as described above) in kind 
and has agreed to perform sequencing on approximately 2,500-3,000 S1007 
study specimens using GEM ExTra whole exome analysis of tumor and normal 
tissue, and RNAseq sequencing of tumor tissue. 
The cost of the hormone analyses will be offset by the Biobanking and 
Biomarker Validation Core (part of the Kansas Institute for Precision Medicine 
COBRE), with reagent costs offset via Hematology and Medical Oncology-
associated funds provided by the Winship Cancer Institute of Emory University. 
 
 
Please direct any inquiries to my attention at the SWOG Operations Office. 
 
Sincerely, 
 
 
 
Alicia Aranda 
Protocol Project Manager 
PC/aa 
 
Enclosures:  
Protocol (Version Date: 12/10/2021) 
 
 
Consent – Main (Version Date: 12/10/2021) 
cc: 
  Charles D. Blanke, M.D. 
  Nathan Eriksen 
Kevin Kalinsky, M.D. 
Funda Meric-Bernstam, M.D. 
Lajos Pusztai, M.D.  
Casey Dawson 
Edie Van Putten, J.D. 
Tameka Lewis 
William Barlow, Ph.D. 
Danika Lew, M.A. 
Jieling Miao, M.S. 
Dani Weatherbee 
Pat Mize, M.B.A. 
Dana B. Sparks, M.A.T. 
Crystal Miwa 
Cathy Rankin  

 
 
 
Version Date:  December 10, 2021 
 
TO: 
ALL NATIONAL CLINICAL TRIALS NETWORK (NCTN) MEMBERS (U.S.) 
 
FROM: 
Cara Laubach, Lead Protocol Coordinator (E-mail:  claubach@swog.org) 
 
RE: 
S1007, "A Phase III, Randomized Clinical Trial of Standard Adjuvant Endocrine Therapy +/- 
Chemotherapy in Patients with 1-3 Positive Nodes, Hormone Receptor-Positive and HER2-
Negative Breast Cancer with Recurrence Score (RS) of 25 or Less. RxPONDER: A Clinical Trial 
Rx for Positive Node, Endocrine Responsive Breast Cancer.”  Study Chairs: Drs. K. Kalinsky, 
J.R. Gralow, F. Meric-Bernstam, G.N. Hortobagyi, K.S. Albain and W. Barlow. 
 
REVISION #18 
 
Study Chair: Kevin Kalinsky, M.D.   
Phone number: 212/305-1945 
E-mail: S1007question@swog.org  
 
IRB Review Requirements 
(  ) 
Expedited review allowed 
 
Protocol changes 
(  )  
Scientific / Statistical Consideration changes 
(  )  
Editorial / Administrative changes    
 
Sites using the CIRB as their IRB of record:  The protocol and/or informed consent form 
changes have been approved by the CIRB and must be activated within 30 days of the CIRB 
posting of this notice.  
 
Sites not using the NCI CIRB:  Per CTMB Guidelines, the protocol updates and/or informed 
consent changes must be approved by local IRBs within 90 days of distribution of this notice. 
 
 
REVISION #18 
 
Revision 18 was prepared to incorporate update to integrated translational medicine objectives for planned 
integrated biomarker analyses to be completed on already banked samples and to add integrated hormone 
level analyses (on samples previously collected at baseline) (Sections 1.2, 2.3, 18.2, 18.3 and 18.9). 
 
Protocol Changes: 
The following specific changes were incorporated into the protocol: 
 
1. 
General: Formatting, hyperlinks, and intra-document section references were updated and/or 
corrected throughout the protocol.  
 
2. 
The Version Date and Table of Contents were updated.  
 
3. 
Sections 1.2c and 1.2h were updated and Section 1.2l was inserted. These changes were also 
reflected in the secondary objectives included at the onset (sub section 1.4) of Section 18.3. 
 
4. 
Section 2.3 was inserted to provide background on integrated translational medicine objectives to 
be completed on already banked samples. 
 
5. 
Sections 5.3 and 15.3b were updated to better clarify that two separate collection kits must be 
ordered for the CBALR substudy. 
 

 
S1007 
 
Revision #18 (contd.) 
 
Page 2 
 
 
 
6. 
Section 10.7 was inserted to provide the definition of Invasive Breast Cancer-Free Survival that will 
be utilized in association with translational medicine analyses. The subsequent section was 
renumbered. 
 
7. 
Section 18.2: This section was updated in entirety to be reflective of current analytical technologies 
that will be utilized to accomplished planned integrated objectives. The updated section title was 
also reflected in Section 18.0. 
 
8. 
Section 18.8e: Additional clarification was inserted regarding planned utilization of samples banked 
in association with the CBALR substudy for cfDNA analyses, pending the forthcoming statistical 
plan that will be included with a future revision. 
 
9. 
Section 18.9: Distribution instructions (for samples that are already banked at the SWOG 
Biospecimen Repository) were inserted. 
 
Model Consent Form Changes: 
The S1007 Model Consent Forms were updated as follows: 
 
• 
The Version Date of the consent documents has been updated for congruence with the protocol. 
There were no substantive changes to the S1007 Model Consent Forms for Step 1, Step 2, or Step 
3 registration. 
 
The updated protocol (Version Date: 12/10/2021) and Model Consent Forms (Version Date: 12/10/2021) 
can be accessed from the CTSU website (www.ctsu.org).  Please discard any previous versions of the 
protocol and attach this memorandum to the front of your copy of S1007. 
 
This study has been reviewed and approved by the NCI’s Central Institutional Review Board (CIRB).  
 
This memorandum serves to notify the NCI, CIRB, and SWOG Statistics and Data Management Center. 
 
cc: 
PROTOCOL & INFORMATION OFFICE 
 
Ruth Campo – GEICAM 
 
Jerome Lemonnier - UNICANCER 
 

S1007 
Page 1 
Version Date 12/10/2021 
 
 
 
PRIVILEGED COMMUNICATION 
Activation January 15, 2011 
FOR INVESTIGATIONAL USE ONLY 
 
 
 
SWOG CANCER RESEARCH NETWORK 
TITLE 
A PHASE III, RANDOMIZED CLINICAL TRIAL OF STANDARD ADJUVANT ENDOCRINE THERAPY 
+/- CHEMOTHERAPY IN PATIENTS WITH 1-3 POSITIVE NODES, 
HORMONE RECEPTOR-POSITIVE AND HER2-NEGATIVE BREAST CANCER  
WITH RECURRENCE SCORE (RS) OF 25 OR LESS. RXPONDER:  A CLINICAL TRIAL RX FOR 
POSITIVE NODE, ENDOCRINE RESPONSIVE BREAST CANCER 
 
NCT#01272037 
 
STUDY CHAIRS:  
(CTEP IND-) 
 
Principal Investigator 
Co-investigators 
 
 
Kevin Kalinsky, M.D. (Medical Oncology) 
Gabriel N. Hortobagyi, M.D. (Medical Oncology) 
Emory University 
M.D. Anderson Cancer Center  
Winship Cancer Institute  
Department of Breast Med/Onc, Unit 1354 
1365 Clifton Road  
1515 Holcombe Boulevard / PO Box 301439 
Atlanta, GA 30322 
Houston, TX 77230-1439 
Phone:  404/778-1900 
Phone: 713/563-0732 
FAX:  404/778-2177 
FAX: 713/563-0903 
E-mail:  S1007question@swog.org 
E-mail: S1007question@swog.org 
 
  
Funda Meric-Bernstam, M.D. (Translational Medicine) Kathy S. Albain, M.D. (Medical Oncology) 
M.D. Anderson Cancer Center 
Professor of Medicine 
 
1515 Holcombe Blvd 
Loyola University Medical Center  
 
Unit 444 
Cancer Center, Bldg. 112, Rm 109 
 
Houston, TX 77030-1439 
2160 South First Ave 
 
Phone: 713/745-4453 
Maywood, IL 60153-5589 
 
FAX: 713/745-4626 
Phone: 708/327-3102 
 
E-mail: S1007question@swog.org  
FAX: 708/327-2210 
 
 
E-mail: S1007question@swog.org  
 
 
BIOSTATISTICIANS: 
COMPARATIVE EFFECTIVENESS AND 
 
HEALTH RELATED QUALITY OF LIFE: 
William Barlow, Ph.D. (Biostatistics) 
 
Cancer Research and Biostatistics 
Scott D. Ramsey, M.D., Ph.D. 
1505 Westlake Ave. N., Ste. 750 
Fred Hutchinson CRC  
Seattle, WA 98109 
1100 Fairview Avenue N, MS-B232 
Phone: 206/839-1761 
PO Box 19024 
FAX: 206/652-4612 
Seattle, WA  98109  
 
E-mail: williamb@crab.org  
Phone:  206/667-7846 
 
FAX:  206/667-5977 
Danika Lew, M.A. (Biostatistics) 
E-mail:  sramsey@fhcrc.org 
Jieling Miao, M.S. 
SWOG Statistics and Data Management Center  
Carol M. Moinpour, Ph.D. 
1100 Fairview Ave N, M3-C102 
SWOG Statistics and Data Management Center 
PO Box 19024 
1100 Fairview Ave N, M3-C102 
Seattle, WA 98109-1024 
PO Box 19024 
Phone: 206/667-4623 
Seattle, WA  98105 
FAX: 206/667-4408 
Phone:  206/667-4604     
E-mail: dlew@fredhutch.org 
FAX:  206/667-4408     
E-mail: jmiao@fredhutch.org 
E-mail:  cmoinpou@fhcrc.org   
 
 

S1007 
Page 2 
Version Date 12/10/2021 
 
 
 
 
ALLIANCE CHAIRS: 
ECOG-ACRIN CHAIR: 
 
 
Nancy U. Lin, M.D. 
Lori J. Goldstein, M.D. 
Dana Farber Cancer Institute  
Fox Chase Cancer Center  
450 Brookline Avenue  
333 Cottman Avenue  
Boston, MA  02215 
Philadelphia, PA  19111-2497 
Phone:  617/632-2335 
Phone:  215/728-2689 
FAX:  617/632-1930 
FAX:  215/728-3639  
E-mail:  nlin@partner.org   
E-mail:  lori.goldstein@fcc.edu 
 
 
Edith A. Perez, M.D. 
GEICAM CHAIR: 
Mayo Clinic  
 
4500 San Pablo Road  
Emilio Alba Conejo, M.D. 
Jacksonville, FL  32224-9980 
Hospital Clinico Universitario Virgen de la Victoria  
Phone:  904/953-7080 
Medical Oncology Department  
FAX:  507/284-5280  
Colonia Santa Ines s/n  
E-mail:  perez.edith@mayo.edu 
Campus Universitario Teatinos   
 
Malaga, 29010 ES 
NCIC-CTG CHAIR: 
Phone:  34 951 032000 
 
E-mail:  emilioalbac@gmail.com 
Stephen Chia, M.D. 
(see Section 18.5 for a list of approved UNICANCER  
BCCA-Vancouver Cancer Center  
and GEICAM sites and participating investigators) 
600 West 10th Avenue  
 
Vancouver, British Columbia  
UNICANCER CHAIR: 
Canada V5Z-4E6 
 
Phone:  604/877-6000 ext. 2752 
Suzette DeLaloge, M.D., M.Sc. 
E-mail:  schia@bccancer.bc.ca 
Chef du Comite de Pathologie Mammaire  
 
Head, Breast Cancer Group   
Sukhbinder Dhesy-Thind, M.D. 
Institut Gustave Roussy  
Juravinski Cancer Centre 
Phone:  01 42 11 42 11 
at Hamilton Health Sciences  
FAX:  01 42 11 52 74 
699 Concession Street  
E-mail:  suzette.delaloge@gustaveroussy.Fr   
Hamilton, ON  
(see Section 18.5 for a list of approved 
Canada L8V-5C2 
UNICANCER and GEICAM sites and  
Phone:  905/387-9495 ext.64431 
participating investigators) 
FAX:  905/575-6324 
 
E-mail:  bindi.dhesy@jcc.hhsc.ca 
 
   
 
NRG CHAIR: 
 
 
Priya Rastogi, M.D. 
 
Four Allegheny Center–5th Floor 
 
Pittsburgh, PA  15212-5234 
  
Phone:  412/330-4600 
 
FAX:  412/330-4660 
E-mail:  rastogip@upmc.edu  
 

S1007 
Page 3 
Version Date 12/10/2021 
 
 
 
 
 
PARTICIPANTS 
 
ALLIANCE/Alliance for Clinical Trials in Oncology 
ECOG-ACRIN/ECOG-ACRIN Cancer Research Group 
NRG/NRG Oncology 
NCIC-CTG/NCIC Clinical Trials Group 
SWOG/SWOG Cancer Research Network 
GEICAM/GEICAM (Spain) 
UNICANCER/UNICANCER (France) 
 
 
(see Section 18.5 for a list of approved UNICANCER and GEICAM sites and participating investigators) 
 
 
 

S1007 
Page 4 
Version Date 12/10/2021 
 
 
 
 
TABLE OF CONTENTS 
TITLE ………………………………………………………………………………………………………………..1 
PARTICIPANTS ............................................................................................................................................ 3 
TABLE OF CONTENTS ............................................................................................................................... 4 
S1007 PROTOCOL CONTACT INFORMATION ......................................................................................... 6 
CANCER TRIALS SUPPORT UNIT (CTSU) ADDRESS AND CONTACT INFORMATION ....................... 7 
SCHEMA ....................................................................................................................................................... 8 
1.0 
OBJECTIVES .................................................................................................................................. 9 
1.1 
Primary Objective ............................................................................................................................. 9 
1.2 
Secondary Objectives ...................................................................................................................... 9 
1.3 
Banking Objective .......................................................................................................................... 10 
2.0 
BACKGROUND ............................................................................................................................. 10 
2.1 
Background / Rationale .................................................................................................................. 10 
2.2 
Inclusion of Women and Minorities ................................................................................................ 16 
2.3 
Rationale for Additional Biomarker Analysis .................................................................................. 16 
2.4 
Rationale for Circulating Biomarker Assessment for Late Relapse Translational Medicine 
Substudy ........................................................................................................................................ 18 
2.5 
Rationale for Utilization of Remote Consent Procedures for Patient Consent to the Circulating 
Biomarker Assessment for Late Relapse Translational Medicine (CBALR TM) Substudy ........... 19 
3.0 
DRUG INFORMATION .................................................................................................................. 20 
4.0 
STAGING CRITERIA ..................................................................................................................... 20 
5.0 
ELIGIBILITY CRITERIA ................................................................................................................ 20 
5.1 
STEP 1 REGISTRATION (Oncotype DX® Screening) .................................................................. 20 
5.2 
STEP 2 REGISTRATION (Randomization) ................................................................................... 23 
5.3 
STEP 3 REGISTRATION (U.S. Sites Only) – CBALR TM Substudy ......................................... 23 
6.0 
STRATIFICATION FACTORS ....................................................................................................... 24 
6.1 
Patients will be randomized between Arm 1 (chemotherapy and endocrine therapy) and Arm 2 
(endocrine therapy alone) using a dynamic balancing algorithm.  ()  Treatment arms will be 
balanced with respect to the following stratification factors: .......................................................... 24 
7.0 
TREATMENT PLAN ...................................................................................................................... 24 
7.1 
General Consideration/Concomitant Therapies ............................................................................. 24 
7.2 
Oncotype DX® Assay .................................................................................................................... 25 
7.3 
Arm 1 (chemotherapy and endocrine therapy) .............................................................................. 26 
7.4 
Arm 2 (endocrine therapy alone) ................................................................................................... 28 
7.5 
Criteria for Removal from Protocol Treatment (Step 2) ................................................................. 28 
7.6 
Discontinuation of Treatment ......................................................................................................... 28 
7.7 
Follow-Up Period ............................................................................................................................ 28 
8.0 
TOXICITIES TO BE MONITORED AND DOSAGE MODIFICATIONS ........................................ 29 
8.1 
NCI Common Terminology Criteria for Adverse Events ................................................................ 29 
8.2 
General Considerations ................................................................................................................. 29 
8.3 
Dose Modifications ......................................................................................................................... 29 
8.4 
Adverse Event Reporting ............................................................................................................... 29 
9.0 
STUDY CALENDAR ...................................................................................................................... 30 
10.0 
CRITERIA FOR EVALUATION AND ENDPOINT DEFINITIONS ................................................. 32 
10.1 
Invasive Recurrence ...................................................................................................................... 32 
10.2 
Sites of first invasive recurrence .................................................................................................... 32 
10.3 
Invasive Disease-Free Survival ..................................................................................................... 32 
10.4 
Distant Disease-Free Survival ....................................................................................................... 32 
10.5 
Local Disease-Free Interval ........................................................................................................... 32 
10.6 
Overall Survival .............................................................................................................................. 32 
10.7 
Invasive Breast Cancer-Free Survival ........................................................................................... 33 
10.8 
Performance Status ....................................................................................................................... 33 
11.0 
STATISTICAL CONSIDERATIONS .............................................................................................. 33 
11.1 
Accrual Goal ................................................................................................................................... 33 
11.2 
Accrual Rate ................................................................................................................................... 34 
11.3 
Randomization and Stratification ................................................................................................... 34 
11.4 
Summary of Analytic Plan .............................................................................................................. 34 

S1007 
Page 5 
Version Date 12/10/2021 
 
 
 
 
11.5 
Compliance and Dropout ............................................................................................................... 35 
11.6 
Early Termination for Futility .......................................................................................................... 35 
11.7 
Summary of Revised Analytic Plan ................................................................................................ 35 
11.8 
Interim Analysis .............................................................................................................................. 36 
11.9 
Translational Medicine ................................................................................................................... 36 
11.10 
Data and Safety Monitoring Committee ......................................................................................... 36 
12.0 
DISCIPLINE REVIEW .................................................................................................................... 37 
13.0 
REGISTRATION GUIDELINES ..................................................................................................... 37 
13.1 
Registration Timing ........................................................................................................................ 37 
13.2 
Investigator/Site Registration ......................................................................................................... 37 
13.3 
OPEN Registration Requirements ................................................................................................. 38 
13.4 
Registration Procedures................................................................................................................. 39 
13.5 
Exceptions to SWOG registration policies will not be permitted. ................................................... 40 
14.0 
DATA SUBMISSION SCHEDULE ................................................................................................ 40 
14.1 
Data Submission Requirement ...................................................................................................... 40 
14.2 
Master Forms ................................................................................................................................. 40 
14.3 
Data Submission Procedures ........................................................................................................ 41 
14.4 
Data Submission Overview and Timepoints .................................................................................. 41 
15.0 
SPECIAL INSTRUCTIONS............................................................................................................ 43 
15.1 
Oncotype DX® Testing Requirements ........................................................................................... 43 
15.2 
Correlative Studies and Banking .................................................................................................... 44 
15.3 
Specimens for Circulating Biomarker Assessment for Late Relapse Translational Medicine 
(CBALR TM) Substudy (REQUIRED IF PATIENT CONSENTS): ................................................. 45 
15.4 
SPECIMEN LABELING AND SHIPPING ....................................................................................... 56 
16.0 
ETHICAL AND REGULATORY CONSIDERATIONS ................................................................... 58 
16.1 
Adverse Event Reporting Requirements ........................................................................................ 60 
17.0 
BIBLIOGRAPHY ............................................................................................................................ 63 
18.0 
APPENDIX ..................................................................................................................................... 68 
18.1 
Comparative Effectiveness and Health Related Quality of Life (U.S. INSTITUTIONS ONLY) 
(Permanently closed to accrual effective 12/1/12.) ................................................................... 69 
18.2 
Prospective Validation of Other Prognostic/Predictive Indices of Breast Cancer Outcomes and 
Evaluation of Pre-treatment Hormone Levels ................................................................................ 87 
18.3 
Statistical Analysis Plan ............................................................................................................... 100 
18.4 
Determination of Expedited Adverse Event Reporting Requirements ......................................... 118 
18.5 
Participation Procedures for the International Collaborating Institutions ..................................... 120 
18.6 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, Hormone-
Receptor Positive, Her2 Negative, Operable Breast Cancer Translational Medicine Substudy 
(U.S. INSTITUTIONS ONLY) – CELLSEARCH ANALYSES (Menarini Silicon Biosystems) . 139 
18.7 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, Hormone-
Receptor Positive, Her2 Negative, Operable Breast Cancer Translational Medicine Substudy 
(U.S. INSTITUTIONS ONLY) – EPIC SCIENCES CTC DETECTION PLATFORM ................... 149 
18.8 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, Hormone-
Receptor Positive, Her2 Negative, Operable Breast Cancer Translational Medicine Substudy 
(U.S. INSTITUTIONS ONLY) – NON-CTC ANALYSES – FUTURE ANALYSES ...................... 159 
18.9 
Instructions for the SWOG Biospecimen Bank – Lab #201, Solid Tissue, Myeloma and 
Lymphoma Division ...................................................................................................................... 164 
 
 
 

S1007 
Page 6 
Version Date 12/10/2021 
 
 
 
 
S1007 PROTOCOL CONTACT INFORMATION 
Eligibility and Data Submission Questions: 
SWOG Statistics and Data Management Center  
E-mail:  breastquestion@crab.org   
206/652-2267 
Medical Queries (treatment or toxicity related 
questions): 
Study Chairs:  
E-mail:  S1007question@swog.org  
Regulatory, Protocol, Informed Consent: 
SWOG Operations Office: 
E-mail:  protocols@swog.org 
Phone:  210/614-8808 
Specimen Tracking System (STS) 
Amendments, Errors, Connectivity Issues and 
Technical issues with the SWOG CRA 
Workbench: 
E-mail:  technicalquestion@crab.org 
Ordering Circulating Biomarker Assessment for 
Late Relapse Translational Medicine (CBALR 
TM) Substudy sample collection kits: 
 
 
Sample Collection Kit Ordering questions: 
Streck cfDNA and CellSave® kits may be ordered by 
using the SWOG Biospecimen Bank Kit Management 
Application at:  https://kits.bpc-apps.nchri.org 
 
E-mail:  bpcbank@nationwidechildrens.org 
Phone: 614/722-2865 
Circulating Biomarker Assessment for Late 
Relapse Translational Medicine (CBALR TM) 
Substudy Sample Shipping questions:  
For questions pertaining to the two Streck cfDNA 
tubes being shipped to Epic Sciences Lab, 
contact: Lab #236:  
Epic Sciences via 
Email: partners@epicsciences.com / Attn: S1007 
 
For questions pertaining to the the two Streck 
cfDNA tubes being shipped to the SWOG 
Biospecimen Bank, contact: Lab #201: SWOG 
Biospecimen Bank – Solid Tissue, Myeloma and 
Lymphoma Division, Lab #201 via  
E-mail:  bpcbank@nationwidechildrens.org 
Attn: S1007 
 
For questions pertaining to the Cellsave® tube 
collection or shipping contact: Lab #122: Menarini 
Silicon Biosystems Labs via 
Email: msb-labservicesus@siliconbiosystems.com   
Attn: S1007 
Cancer Therapy and Evaluation Program - 
Identity and Access Management (CTEP-IAM): 
CTEP-IAM account can be checked or new accounts 
can be created and updated: 
https://ctepcore.nci.nih.gov/iam/index.jsp 
Serious Adverse Event Reporting questions:  
See Protocol Section 16.1  
Email: adr@swog.org  
Patient Transfers: 
patienttransfer@crab.org   

S1007 
Page 7 
Version Date 12/10/2021 
 
 
 
 
CANCER TRIALS SUPPORT UNIT (CTSU) ADDRESS AND CONTACT INFORMATION 
To submit site registration 
documents: 
For patient 
enrollments:  
Submit study data directly to the Lead 
Cooperative Group unless otherwise 
specified in the protocol:  
 
CTSU Regulatory Office 
1818 Market Street,  
Suite 1100 
Philadelphia, PA 19103 
 
Phone:  1-866-651-CTSU 
Fax:  215-569-0206 
 
Refer to the patient 
enrollment section of 
the protocol for 
instructions on using 
the Oncology Patient 
Enrollment Network 
(OPEN). OPEN is 
accessed at 
https://www.ctsu.org/O
PEN_SYSTEM/  or 
https://OPEN.ctsu.org. 
 
Contact the CTSU Help 
Desk with any OPEN 
related questions by 
phone or email : 1-888-
823-5923, or 
ctsucontact@westat.co
m. 
 
Online Data Submission:  Institutions 
participating through the CTSU are required to 
submit and amend their data electronically via 
Online Data Submission.  Access the SWOG 
Workbench using your CTSU user ID and 
password at the following url:  
https://crawb.crab.org/TXWB/ctsulogon.aspx. 
 
Exceptions:  Data items that are not available 
for online submission (operative and 
pathology reports, scan reports, etc.) may be 
submitted by fax at 800-892-4007.   
 
Do not submit data or forms to CTSU Data 
Operations.  Do not copy the CTSU on data 
submissions. 
   
The most current version of the study protocol and all related forms and documents must be 
downloaded from the protocol-specific Web page of the CTSU Member Web site located at 
https://www.ctsu.org.  Access to the CTSU members’ website is managed through the Cancer Therapy 
and Evaluation Program - Identity and Access Management (CTEP-IAM) registration system and 
requires user log on with CTEP-IAM username and password. 
 
CTSU sites should follow procedures outlined in the protocol for Site registration, Patient Enrollment, 
Adverse Event Reporting, Data Submission (including ancillary studies), and Drug Procurement. 
For patient eligibility or data submission questions contact the SWOG Statistics and Data 
Management Center by phone at 206/652-2267 or by email at breastquestion@crab.org.   
 
For clinical questions (treatment or toxicity related) contact the Study Chairs at 
S1007question@swog.org. 
For non-clinical questions (unrelated to patient eligibility, treatment, or clinical data submission) 
contact the CTSU Help Desk by phone or e-mail:  
CTSU General Information Line – 1-888-823-5923, or ctsucontact@westat.com. All calls and 
correspondence will be triaged to the appropriate CTSU representative.  
For detailed information on the regulatory and monitoring procedures for CTSU sites please 
review the CTSU Regulatory and Monitoring Procedures policy located on the CTSU members’ website  
https://www.ctsu.org education and resources tab > CTSU Operations Information >CTSU Regulatory 
and Monitoring Policy.  
The CTSU Web site is located at   https://www.ctsu.org  
 
 
 

S1007 
Page 8 
Version Date 12/10/2021 
 
 
 
 
SCHEMA 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
RS > 25 
RS ≤ 25 
 
 
 
Accept 
 
 
 
 
 
 
 
 
Refuse 
 
 
 
 
 
 
Patient 
Consent 
 
 
 
 
 
Node-positive (1-3 nodes) HR-positive and HER2-negative breast cancer 
RS already available and ≤ 25. 
Physician and patient discuss 
randomization knowing the RS 
Recurrence 
Score 
Discuss 
alternative 
trials for high 
risk patients 
Physician and 
patient discuss 
randomization 
knowing the RS 
Step 2 Registration/ 
Randomization 
stratified by: 
1.  RS 0-13 vs. 14-25 
2.  Menopausal  
     Status 
3.  Axillary node  
     Dissection vs.  
     Sentinel node  
     biopsy 
Chemotherapy; 
endocrine therapy 
No Chemotherapy; 
endocrine therapy 
Record chosen 
therapy  
Patients consent to Recurrence Score (RS) testing, 
discussion of potential randomization on this trial. 
Step 1 
Registration 
Step 1 Registration and tumor 
tissue submission for RS testing 
If disease-free at 
time of IRB approval 
of Revision 16, offer 
participation in 
correlative CTC TM 
Assessment) 
Step 3 
Registration 

S1007 
Page 9 
Version Date 12/10/2021 
 
 
 
 
1.0 
OBJECTIVES 
 
1.1 
Primary Objective 
 
a. 
To determine the effect of chemotherapy in patients with node positive breast 
cancer who do not have high Recurrence Scores (RS) by Oncotype DX®. In 
patients with 1-3 positive nodes, and hormone receptor (HR)-positive, HER2-
negative breast cancer with RS ≤ 25 treated with endocrine therapy we will test 
whether the difference in disease-free survival for patients treated with 
chemotherapy compared to no chemotherapy depends directly on the magnitude 
of RS.  If benefit depends on the RS score, the trial will determine the optimal 
cutpoint for recommending chemotherapy or not. 
 
1.2 
Secondary Objectives 
 
a. 
To compare overall survival (OS), distant disease-free survival (DDFS) and local 
disease-free interval (LDFI) by receipt of chemotherapy or not and its interaction 
with RS. 
 
b. 
To compare the toxicity across the treatment arms. 
 
c. 
To perform other molecular assays or test other signatures that measure prognosis 
and potential benefit of chemotherapy and compare them to Oncotype DX®. 
 
d. 
To determine the impact of management with Oncotype DX® on patient-reported 
anxiety (co-primary Health-Related Quality of Life [HRQL] outcome) prior to 
screening, after disclosure of test results, and during the randomized trial. 
 
e. 
To determine the impact of Oncotype DX® on the initial management cost of node-
positive, HR-positive, HER2-negative breast cancer. 
 
f. 
To compare patient-reported utilities (e.g., QOL) for those randomized to 
chemotherapy versus no chemotherapy. 
 
g. 
Using modeling and DFS information from the trial, to estimate the cost-
effectiveness of management with Oncotype DX® vs. usual care. 
 
h. 
To determine the role of other assays as predictors of DFS, DDFS and LDFI for 
patients randomized to chemotherapy versus no chemotherapy. 
 
i. 
To determine the impact of treatment with chemotherapy versus no chemotherapy 
on patient-reported fatigue and cognitive concerns (secondary HRQL outcomes). 
 
j. 
To determine the impact of management with Oncotype DX® on patient-reported 
decision conflict, perceptions regarding Oncotype DX® testing, and survivor 
concerns prior to screening, after disclosure of test results, and during the 
randomized trial (secondary HRQL outcomes). 
 
k. 
The presence of circulating tumor cells (CTC+) using two CTC platforms will be 
assessed at up to two time points to assess late recurrence in those still at risk for 
the primary outcome. Invasive disease-free survival (IDFS) will be compared 
between CTC+ versus CTC-, incorporating use of endocrine therapy. 
 
l. 
To compare clinically reported menopausal status with status categorized by 
serum hormone levels determined from baseline serum in women under age 55 
years and to assess subsequent association with outcomes. 
 
 

S1007 
Page 10 
Version Date 12/10/2021 
 
 
 
 
1.3 
Banking Objective 
 
To bank specimens for future correlative studies. 
 
2.0 
BACKGROUND 
 
2.1 
Background / Rationale 
 
Prospective randomized trials indicate that patients with Hormone Receptor (HR)-positive 
primary breast cancer benefit from the addition of chemotherapy to adjuvant endocrine 
treatment overall. (1) The meta-analysis of randomized trials demonstrates that the 
addition of taxanes to anthracycline-base therapy improves Disease Free Survival (DFS) 
and Overall Survival (OS) in all patients with node-positive breast cancer. (2) However, 
several retrospective analyses of prospective clinical trials indicate that some patients may 
not benefit from chemotherapy; specifically, patients with well-differentiated tumors, low 
grade, those with high expression of HR, or those with low or intermediate Recurrence 
Score (RS) as defined by the Oncotype DX® assay.  (3,4,5,6) Other retrospective analyses 
indicate that not all breast cancer groups may benefit equally from the addition of taxanes, 
i.e. patients with Estrogen Receptor (ER)-positive disease may benefit the least. (7) At the 
same time, these patients still have a substantial risk of death or recurrence despite 
effective endocrine therapy; such risk reaches 40% at 10 years for node-positive, low RS 
tumors.  (8) Therefore, there is a need to develop additional, effective treatments for this 
population.  Therefore, although current state-of-the-art chemotherapy appears to be more 
effective than the chemotherapy used in SWOG-8814, evidence is not strong that it is 
efficacious in all subsets of breast cancer. (9)  Nevertheless, and in order to derive optimal 
benefit from chemotherapy, this trial will use the regimens that have proven to be of greater 
benefit than earlier chemotherapy regimens in modern randomized trials.  The study will 
use a simple parallel two-group randomization to chemotherapy followed by endocrine 
therapy or endocrine therapy alone in a lower risk, 1-3 node-positive population (identified 
by intermediate or low Recurrence Score) to determine if modern chemotherapy is 
efficacious and to identify those patients who will benefit from the addition of 
chemotherapy. 
 
Multi-gene tumor assays have provided clinically useful prognostic information for patients 
with node-negative breast cancer.  The 21-gene RS has been shown to be both prognostic 
for patients with ER-positive disease if treated with tamoxifen alone, as well as predictive of 
benefit from adding chemotherapy. In retrospective analyses, patients with high RS appeared 
to benefit greatly from the addition of standard chemotherapy to tamoxifen, whereas those 
with low RS did not. (10,11) This assay now helps guide patient and physician decision-
making for determining therapy for patients with node-negative, HR-positive disease. 
Analytical performance data on the RS assay were published by Cronin and colleagues in 
2007. (12) Furthermore, retrospective and prospective studies indicate that RS results change 
the adjuvant recommendation in an average of 30% of the time in clinical practice. (13,14)  
However, to generate additional data about the clinical utility of the Oncotype DX® assay, a 
large, multicenter, prospective randomized trial will recruit > 11,000 patients with lymph node-
negative primary breast cancer and randomize those with mid-range RS to endocrine therapy 
alone or the sequential administration of chemotherapy and endocrine therapy. Preliminary 
evidence now exists that RS may also allow determination of chemotherapy benefit in node-
positive, HR-positive disease. The evidence is stronger for low RS while debatable for 
intermediate RS of 18-30. (15) This trial will to use the same upper limit of 25 as used by the 
ECOG PACCT-1 (TAILORx) trial to both avoid confusion and to avoid the potential risk to 
patients with RS > 25. While SWOG-8814 suggests no statistically significant benefit overall 
in RS 14-25, this trial will restrict the analysis to nodes 1-3 where an efficacious effect of 
chemotherapy has not been demonstrated.  The retrospective analysis suggests that RS 19 
may be the point of equivalence and that some benefit of chemotherapy could emerge in RS 
values greater than 19. It is necessary emphasize that this retrospective analysis was at best 
hypothesis-generating and should not be used for clinical decision-making until prospectively 

S1007 
Page 11 
Version Date 12/10/2021 
 
 
 
 
validated. Modern chemotherapy may indeed show a benefit for higher RS starting 
somewhere in the 20 to 30 range. If this trial can demonstrate that there is little benefit to 
chemotherapy for women with lower RS (e.g.  RS ≤ 25), it will be possible to eliminate the 
morbidity and costs of chemotherapy in approximately 67% of patients with HR-positive breast 
cancers and 1-3 node-positive lymph nodes, but continue to give effective chemotherapy to 
the 33% of women with RS > 25. However, the RS cutpoint of 25 is used here only for 
illustration purposes as the point of equivalence and the actual value for decision making will 
be estimated from the trial data. 
 
Since the development of the Oncotype DX® assay, other prognostic and predictive molecular 
indices have been developed. Some of these indices have been tested in multiple 
retrospective sets, but lack the validation of a prospective trial.  (16)  One of the objectives of 
this protocol is to validate these early findings with some of these additional molecular 
predictive tests/assays. Further, since tissues and serum will be banked, it will be possible to 
test other molecular profiles that are developed when the study is on-going or subsequent to 
study completion. 
 
Overall SWOG-8814 Results (17) 
 
Until recently, there was no information on the potential value of the RS assay in patients with 
positive axillary nodes and HR-positive disease from a study that contains a similar tamoxifen-
alone control arm since today these patients are routinely treated with adjuvant chemotherapy 
as well as adjuvant endocrine therapy. SWOG-8814 was a practice-changing Phase III trial 
for postmenopausal women with node-positive, ER-positive breast cancer which 
demonstrated that cyclophosphamide, doxorubicin (Adriamycin) and 5-fluorouracil (CAF) 
chemotherapy added significant survival benefit to tamoxifen (T), especially in the 
sequential setting, with CAF preceding the initiation of tamoxifen therapy. The study had 
optional specimen banking that yielded tumor specimens for RS determination by the 
Oncotype DX® gene assay.  When comparing the tamoxifen and the sequential CAF-T 
arms in tissues from 367 patients, the RS was prognostic for DFS in the tamoxifen-alone 
arm (p=0.006).  In this study SWOG used the RS groupings defined by Paik et al. (18)  
There was no apparent CAF benefit in the low RS (0-17) group (p=0.97) or the intermediate 
RS (18-30) group (p=0.48), but a significant DFS improvement was detected for the high 
RS (31-100) subset (p=.03).  Due to failure of the proportional hazards assumption, 
separate analyses were performed for the first five years of follow-up and the period 
beyond five years. The RS-by-treatment interaction was significant in the first 5 years for 
DFS (p=0.029), with no additional prediction of CAF benefit beyond 5 years (p=0.58) but 
no loss of initial effect at 10 years. No impact of CAF was observed in the lowest RS group, 
regardless of nodal status.  Results were similar for OS. (19) 
 
In this trial, only women with RS ≤ 25 and 1-3 positive nodes will be included.  SWOG 
investigators reexamined the SWOG-8814 data using this cutoff and 10 years of survival 
using a standard Cox model. The Kaplan-Meier graph below shows little difference 
between the two groups (Figure 1) even if we restrict attention to those with RS ≥ 14 (Figure 
2).  However, the Kaplan-Meier graphs may obscure a possible difference since they do 
not use the continuous RS. If one fits a more complex model using continuous RS and its 
interaction with chemotherapy, then a pattern emerges even though there is still no 
significant interaction of RS and treatment in this patient subset with RS ≤ 25.  The Cox 
model gives an estimate of the log hazard ratio (relative failure rates) by RS with high 
hazard ratios indicating worse DFS. The hazard ratios apply at any time point (e.g. 5 or 10 
years) which is why we prefer to illustrate them here.  In the simplest case we use a Cox 
model and allow for a linear interaction of RS and treatment (Figure 3). The hazard ratios 
cross, indicating there may be a point of equivalence where a chemotherapy benefit may 
start to emerge, but of course the difference would have to be large enough to be both 
clinically and statistically significant. For nodes 1-3 this point of equivalence was about 
RS=19 in our retrospective analysis. Based on this model, the estimated hazard ratio at 
RS=22 would be 0.84 for chemotherapy versus no chemotherapy, but the 95% CI of this 

S1007 
Page 12 
Version Date 12/10/2021 
 
 
 
 
estimate is 0.28-2.49 due to the small sample size. Note that the effect in very low RS 
scores may be exaggerated due to the sparseness of data. This model is based on sparse 
data and is perhaps too simple, but does indicate that using continuous RS may provide 
more insight and power than simple categorization.  However, interaction alone is also not 
sufficient and needs to be supplemented by a clinically useful cutoff. 
Figure 1  
All patients with RS ≤ 25  
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2 
Patients with 14-25 
 
Figure 3                                                                              
 
 
 
 
 
         
 
 
 
 
 
 
0.00
0.25
0.50
0.75
1.00
0
2
4
6
8
10
Years
Without chemo
With chemo
Log-rank p-value = 0.64
RS 14-25; 1-3 Positive Nodes
DFS in S8814 by Randomized Therapy
0.00
0.25
0.50
0.75
1.00
0
2
4
6
8
10
Years
Without chemo
With chemo
Log-rank p-value = 0.82
RS 0-25; 1-3 Positive Nodes
DFS in S8814 by Randomized Therapy
0
.5
1
1.5
2
0
5
10
15
20
25
Recurrence Score
Without chemo
With chemo
RS 0-25; 1-3 Positive Nodes
Modeled Log Hazard Ratio

S1007 
Page 13 
Version Date 12/10/2021 
 
 
 
 
Based on SWOG-8814 data alone it is difficult to conclude that there is benefit of 
chemotherapy in patients with RS ≤ 25.  The sample size is small, and there are some 
trends in the data that support chemotherapy at the higher ends of the RS range. 
Furthermore, more effective chemotherapy regimens have been adopted since SWOG-
8814 was conducted. There have also been improvements in hormonal therapy, surgery, 
and radiation therapy, though these would apply equally to the two randomized groups.  
How representative of current outcomes are the SWOG-8814 data given that patients were 
randomized in the early 1990s?  SEER does not provide DFS, but does provide some 
information about overall survival (OS). Using SEER, one can examine some of this 
improvement by tumor stage. From SEER one can derive the estimated overall survival of 
52,592 women aged 55-74 diagnosed with hormone receptor-positive, node-positive 
breast cancer in the years 1996-2003.  In this group, overall survival was 83% at 5 years 
and 64% at 10 years.  Note that SWOG-8814 had an overall survival of 82% at five years 
and 64% at ten years, so the outcomes are almost identical to current population results. 
Nonetheless, randomized trials have clearly established that better chemotherapies are 
available today, including taxanes and the dose-dense concept. This would strengthen the 
importance of this trial since we would have a randomized comparison with modern 
chemotherapy, rather than observational data based on outdated chemotherapy.  
 
The high failure rate in SWOG-8814 has been criticized but, as outlined above, the overall 
survival is exactly what one would expect in a comparable population.  The recurrence 
results for SWOG-8814 have also been compared with those of TRANS-ATAC at 5 years.  
Their primary outcome is disease-free interval (DFI), which censors deaths that are not 
associated with a recurrence.  Ten deaths in SWOG-8814 occurred within 5 years and had 
no evidence of recurrence so are treated as censored in this analysis, but would be 
considered as failures for DFS.  The TRANS-ATAC investigators kindly provided 
comparison data, but collapsed over treatment group.  Recurrence rates (events/person 
years) suggest little difference between ATAC and SWOG-8814.  Adjusting for number of 
nodes and RS risk group (< 18, 18-30, > 30) showed no statistically significant difference 
in DFI between ATAC and SWOG-8814. There are not appreciable differences in the 
TRANS-ATAC and SWOG-8814 outcomes when RS groupings and number of nodes are 
considered. Thus, the SWOG-8814 data still provide an excellent reference point for the 
proposed trial. 
 
The percentage of patients in SWOG-8814 with > 3 positive nodes was 43%.  This 
proposed trial will restrict eligibility to patients with 1-3 positive nodes.  In women with 1-3 
positive nodes, RS was ≤ 25 in 67% of patients in the SWOG-8814 study. Since the 
Oncotype DX® test became available for clinical practice for node positive patients in 2008, 
it has been observed that the proportion of tested patients with RS ≤ 25 has been greater 
than 75%, consistent with the use of test more often in patients who appear lower risk by 
other prognostic factors such as patient age, tumor size, tumor grade, and/or extent of 
hormone receptor staining by IHC. Since the point of equivalence is unknown, it is 
necessary to have a wider range of RS scores to distinguish those who may need 
chemotherapy from those who do not.  
 
To summarize, SWOG-8814 provides general support for chemotherapy in patients with 
receptor-positive, node-positive disease, but no strong evidence of benefit in the subset 
with RS ≤ 25.  Looking more carefully using the actual value of RS, does reveal that 
treatment effects may start to diverge at higher values of RS, but this would need to be 
supported by data using modern endocrine and chemotherapy and many more patients.  
This study predicts that continuous RS will be directly associated with the degree of benefit. 
It also predicts there may be an equivalence point between RS 0 to 25 after which a benefit 
to chemotherapy may emerge.  When categorized, we expect no benefit below that 
cutpoint, but a clinically significant benefit above the cutpoint. 
 

S1007 
Page 14 
Version Date 12/10/2021 
 
 
 
 
Translational Medicine  
 
Comparative Effectiveness Evaluation of Oncotype DX® for Women with Node-
positive, Hormone-responsive and HER2-negative Breast Cancer 
 
While it is recognized that the majority of the acute effects of chemotherapy (e.g. nausea, 
vomiting, diarrhea, stomatitis, alopecia and neutropenia) will resolve, sub-acute effects and 
long-term sequelae may have a lasting impact on the quality of life of survivors.  Adjuvant 
chemotherapy is associated with premature menopause in some women who are less than 
40 years of age (estimates from 13%-38%) and in the vast majority of women over the age 
of 40 (estimates from 57%-96%). Weight gain has been reported in 50% or more of women 
receiving adjuvant chemotherapy. Weight gain is likely to have a profound influence on a 
woman’s physical and psychological health.  The long-term effects of chemotherapy 
associated with thrombosis, myelodysplastic syndromes, acute leukemia and cardiac 
disease may also contribute to the decreased quality of life of women.  (20,21,22,23)  With 
the increasing use of taxane based and dose-intensive regimens, previously unobserved 
sequelae such as neuropathy and myalgias are more common.  Many of these symptoms 
are slow to resolve and may have long-term consequences for women.  While the acute 
effects of chemotherapy on fatigue has long been recognized, a number of studies have 
reported problems with fatigue for lasting months or even years after adjuvant 
chemotherapy. Such fatigue was associated with a decrease in daily functioning.  (24)   
 
In addition, there has been increased awareness of cognitive dysfunction associated with 
adjuvant chemotherapy in women with breast cancer. (25)   Schagen, et al, evaluated 39 
women at approximately 2 years following 6 cycles of chemotherapy compared to 34 
women who had received local therapy only; 28% of the patients treated with CMF, 
compared to 12% of control groups, showed evidence of cognitive dysfunction 
characterized by difficulty with concentration, memory, and word finding. (26)    van Dam, 
et al, suggested that such symptoms were worse in patients treated with high-dose 
chemotherapy.  (27)  While these studies suffer from lack of good controls and poor 
association between reports of cognitive dysfunction and scores on formal testing, they 
remain concerning.  Anecdotally many breast cancer patients complain of forgetfulness, 
difficulty concentrating or "chemo brain".  These effects are likely to have significant long-
term consequences for women’s quality of life. 
 
In a single arm observational study, Ganz, et al, demonstrated the potential negative 
effects of chemotherapy on the long-term health-related quality of life (HRQOL) of breast 
cancer survivors, including decreases in sexual activity and overall well being.  (28,29) 
While earlier studies have shown some of the negative effects of adjuvant chemotherapy 
on HRQOL, changes in both regimens and supportive care practices mean that these data 
are much less relevant to modern practice.  The impact that chemotherapy has on health-
related quality of life is key and central for patients and physicians deciding whether or not 
to receive adjuvant chemotherapy in order to prevent further recurrence.  This study 
provides a unique opportunity to prospectively and quantitatively evaluate the impact of 
modern chemotherapy on the quality of life of women with early breast cancer.  It is critical 
now to take the opportunity to integrate quality of life assessment into this unique 
randomized trial.  While it is hypothesized that chemotherapy is unlikely to have an effect 
on cancer outcomes in those with an RS < 25, it is possible that a subset of patients with 
RS between 11 and 25 may achieve small benefits in reduction in recurrence.  If so, the 
impact of chemotherapy on quality of life will be particularly relevant for this group of 
patients.  Such information is also likely to be useful to all women with breast cancer and 
their physicians who are considering adjuvant chemotherapy.  This study will also provide 
an ideal opportunity to evaluate, in the context of a randomized trial, the impact of 
chemotherapy on long-term sequelae such as premature menopause and weight gain, and 
the quality of life associated with these events. 
 

S1007 
Page 15 
Version Date 12/10/2021 
 
 
 
 
Another central question is whether women will accept a recommendation not to receive 
chemotherapy based on the results of Oncotype DX®, given the findings of benefit for 
adjuvant therapy in this population. Recent studies in doctor/patient decision making 
suggest that women are likely to accept adjuvant chemotherapy for little or minimal 
benefits.  (30)  Thus, it is possible that a woman will experience anxiety about the idea of 
forgoing chemotherapy, even if the RS predicts that chemotherapy is unlikely to provide 
benefit. Such anxiety might be debilitating or lead to a decision to proceed to chemotherapy 
despite a low RS for those randomized to endocrine therapy alone. If this occurs in this 
trial, it will be important to understand the reason for this choice. 
 
Background and Significance: Cost  
 
Direct expenditures on breast cancer were estimated to be about $6 billion in 1996 (the 
last year such estimates were made), and are surely higher today. Gene expression profile 
(GEP) tests are expensive, costing approximately $4,000 per patient, yet adjuvant 
chemotherapy is much more expensive, costing $20,000 – $26,000 (upper ranges are 
closer to $50,000) (2003 dollars).  (31)  The immediate impact of GEP on breast cancer 
expenditures will depend on the degree to which the test spares women from undertaking 
costly chemotherapy.  Based on current evidence regarding test outcomes, GEP could 
reduce initial breast cancer treatment costs by hundreds of millions of dollars. The long-
term budget impact, however, will depend on the ability of the test to distinguish those who 
ultimately would experience breast cancer recurrence from those who would not. If GEP is 
a poor predictor of recurrence, the testing strategy could be more expensive than current 
practice while at the same time producing poorer outcomes. On the other hand, if GEP can 
better target women who will recur, risk profiling will substantially improve the cost-
effectiveness of adjuvant therapy. The successful use of adjuvant chemotherapy in a highly 
targeted population thus represents a paradigm shift, both clinically and from an economic 
value standpoint.  An accurate understanding of the changing economic value of adjuvant 
chemotherapy will be essential to ensure appropriate reimbursement policies. 
 
Given the proliferation of GEP tests, their potential role in clinical practice, and the national 
clinical and economic burden of breast cancer, quantitative evaluations of the economic 
outcomes associated with GEP are warranted. There have been two published cost-
effectiveness evaluations of GEP for women with localized breast cancer. Both used 
simulation modeling and available data, but came to very different conclusions. One 
analysis, basing its estimates on the performance characteristics of Oncotype DX®, found 
that risk stratification using GEP would reduce cancer care costs and increase quality-
adjusted survival.  (32)  The other based its analysis on the MammaPrint assay, and found 
that GEP increased costs and reduced quality-adjusted survival.  (33) While some might 
conclude that these analyses support the superiority of Oncotype DX® vs. MammaPrint, 
differences in the model structures and other input parameters in these studies make such 
conclusions tentative at best. Moreover, no study has evaluated costs and outcomes of 
GEP tests in the management of node-positive breast cancer. 
 
Clinical trials evaluating medicines, medical devices and procedures now commonly 
assess the economic value of these interventions. "Piggybacking" cost-effectiveness 
analyses alongside clinical trials offers many advantages over ‘pure’ modeling approaches: 
combining studies is efficient; the internal validity of both studies is maximized, and 
economic data is made available alongside clinical data in a timely fashion.  (34) A trial-
based economic analysis will provide the most accurate estimates of the cost-effectiveness 
of GEP. Decision makers in many countries now consider clinical and economic evidence 
together for formulary and insurance coverage policies, as will surely be the case for GEP.  
 
 
 
 

S1007 
Page 16 
Version Date 12/10/2021 
 
 
 
 
2.2 
Inclusion of Women and Minorities  
 
This study was designed to include women and minorities, but was not designed to 
measure differences of intervention effects. 
 
Ethnic Category 
 
Females 
Males 
Total 
Hispanic or Latino 
178 
0 
178 
Not Hispanic or Latino 
3,822 
0 
3,822 
Total Ethnic 
4,000 
0 
4,000 
Racial Category 
 
American Indian or Alaskan Native 
31 
0 
31 
Asian 
154 
0 
154 
Black or African American 
433 
0 
433 
Native Hawaiian or other Pacific Islander 
12 
0 
12 
White 
3,370 
0 
3,370 
Racial Category: Total of all Subjects 
4,000 
0 
4,000 
 
2.3 
Rationale for Additional Biomarker Analysis  
 
Gene Expression Based Prognostic and Predictive Markers in Hormone Receptor 
Positive Breast Cancer 
 
Although in S1007 the 21-gene RS was used for patient stratification, several other gene 
expression signatures are commonly used as prognostic/predictive markers including 70-
gene MammaPrint signature and PAM50 gene intrinsic subtype, SET index, Endopredict 
and Breast cancer index. Some of these expression profiles are described below.  
 
While comparison amongst genomic assays was performed in the TransATAC trial, 
generalizability concerns of these analyses include the study was limited to 
postmenopausal patients and patients did not receive chemotherapy (35, 36). There 
remains an unmet need to identify predictors of chemotherapy benefit within 
premenopausal as well as postmenopausal patients. Molecular analysis will allow for 
testing of prognostic and predictive biomarkers in patients who received chemotherapy on 
the same platform across the entire patient cohort, and will determine the underlying 
biological differences between premenopausal and postmenopausal patients. 
 
Brief description of additional assays and signatures 
 
70-gene MammaPrint signature: MammaPrint is a 70-gene signature which classifies 
tumors into groups that are associated with a good or poor prognosis on the basis of distant 
metastasis-free survival (DMFS) at 5 years and at 10 years. (37) Among the 658 women 
with HR+/HER2-, N1 breast cancers in the MINDACT (Microarray in Node-Negative and 1 
to 3 Positive Lymph Node Disease May Avoid Chemotherapy) trial who had clinical high 
but genomic low risk as determined by the 70-gene MammaPrint assay (Agendia) there 

S1007 
Page 17 
Version Date 12/10/2021 
 
 
 
 
was a 2.6% improvement in 8-year DMFS with chemotherapy. (38, 39) An exploratory 
subgroup analysis demonstrated an age-dependent effect of chemotherapy, in which the 
magnitude of chemotherapy benefit reached 5% in women age <50 and <1% benefit if age 
>50. 
 
PAM50 signature: Gene expression profiling classifies breast cancer into “intrinsic 
subtypes” based on the biology of the underlying disease pathways. (40)   This has been 
developed as Prediction Analysis of Microarray 50 (PAM50) Risk of Recurrence (ROR) 
score (Veracyte Technologies, previously Prosigna). The ROR Score was validated to 
determine the risk of recurrence of disease in HR+ breast cancer after surgery and 
treatment with 5 years of endocrine therapy. The ROR score depends on the intrinsic 
subtype, proliferation score of the tumor, and the tumor size. (41, 42, 43) 
 
SET ER/PR and SET2,3 index: Sensitivity of endocrine therapy (SET) ER/PR index was 
developed to measure gene expression microarray probe sets that associate with hormone 
receptors (ESR1 and PGR). Higher SET ER/PR index in MBC samples predicted improved 
PFS and OS when patients received endocrine therapy as next treatment, even after 
adjustment for clinical-pathologic risk factors (PFS: HR 0.534, 95% CI 0.299 to 0.955, p = 
0.035; OS: HR 0.315, 95% CI 0.157 to 0.631, p = 0.001). (44)  SET2,3 index was proposed 
as a test for sensitivity to adjuvant endocrine therapy for patients with stage II-III breast 
cancer by measuring transcription related to estrogen and progesterone  receptors (SET 
ER/PR index) adjusted for a baseline prognostic index combining clinical tumor and nodal 
stage with molecular subtype by RNA4 (ESR1, PGR, ERBB2, and AURKA). In HR+ 
patients who underwent neoadjuvant therapy, SET2,3 index was found to add independent 
prognostic information in addition to residual cancer burden in two separate cohorts. (45)  
 
EndoPredict (EP; Myriad Genetics, Cologne, Germany): EndoPredict (EP) is an RNA 
based multigene test that predicts the likelihood of distant recurrence in patients with HR+ 
breast cancer being treated with adjuvant endocrine therapy. In the GEICAM 9906 trial, EP 
was an independent prognostic parameter in node-positive, HR+ breast cancer patients 
treated with adjuvant chemotherapy followed by hormone therapy. (46, 47)  The EP assay 
is based on the quantification of eight cancer-related genes of interest and three reference 
genes. 
 
Breast Cancer Index (BCI; Biotheranostics,San Diego, CA): The Breast Cancer Index test 
analyzes the activity of seven genes to help prognosticate the risk of recurrence in patients 
with HR+ breast cancer 5 to 10 years after diagnosis. BCI can be used for prediction with 
the benefit of extended adjuvant endocrine therapy. (48, 49)  
 
Genomic Alteration in Breast Cancer as Prognostic Markers 
 
Genomic characterization of breast cancer has become standard of care for metastatic 
breast cancer (MBC) patients with HR+ cancer. There is already one therapy FDA-
approved linked to a genomic biomarker for MBC: PI3K inhibitor alpelisib in combination 
with endocrine therapy for PIK3CA mutant HR+ breast cancer. There are several other 
genomically matched therapies under investigation in MBC, with expected increase in 
clinical utility of genomic testing in MBC. 
 
Although genomic testing is not standard of care in non-metastatic breast cancer, we and 
others have already demonstrated that several key genomic alterations are associated with 
an increased risk of relapse and/or endocrine resistance in HR+ breast cancer including 
TP53 mutations, (50) and alterations in MAPK pathway such as NF1 loss. (51, 52, 53) 
Notably, ESR1 mutations have also been associated with endocrine resistance but this has 
been primarily found in metastatic tumors, as a mechanism of acquired resistance. (54)  
 

S1007 
Page 18 
Version Date 12/10/2021 
 
 
 
 
Taken together, there are several different prognostic signatures already developed for 
HR+ breast cancer and many genomic features associated with recurrence. We 
hypothesize that three established prognostic signatures (21-gene signature, breast 
cancer intrinsic subtype and 70-gene signature) based on RNAseq are associated with 
prognosis in premenopausal and postmenopausal patients with 1-3 LN+. Prognostic 
endpoints include IDFS, DDFS, LDFS, and OS.  We also hypothesize that these prognostic 
signatures alone or integrated together will predict chemotherapy benefit in premenopausal 
patients with 1-3 LN+. The prognostic and predictive value may be further enhanced with 
integration of additional gene expression sets (e.g., SET2,3, RNA4 index, MKI67 gene 
expression) and breast cancer genomics and proteomics. 
 
Baseline serum hormone levels  
 
In addition to clinical characteristics, serum hormone levels may be able to further 
discriminate menopausal status. Beyond self-reporting of menopausal status, serum levels 
can offer an objective measure. The mean age at onset of menopause is 51 years in 
Western countries, and by age 55 approximately 85% of women have undergone 
menopause, whereas less than 10% of women experience menopause at or before age 
45. (55, 56) In clinical practice, estradiol, luteinizing hormone, and follicle-stimulating 
hormone are often evaluated for determination of whether a patient is pre- or post-
menopausal. Anti-Müllerian Hormone (AMH), also called Müllerian inhibiting factor (MIF) 
is an additional indicator available as to whether a woman is approaching or is likely to 
have reached her final menstrual period. Given that there is a significant interaction 
between menopausal status, as determined by clinical characteristics, and IDFS and DDFS 
in RxPONDER, we propose evaluating hormone levels in pre-treatment baseline samples 
to assess whether menopausal status is further refined and whether an interaction term 
remains statistically significant based upon menopausal status per serum hormone levels. 
 
2.4 
Rationale for Circulating Biomarker Assessment for Late Relapse Translational Medicine 
Substudy 
 
S1007 is a trial of patients with HR+/Her2- breast cancer, with 1-3 lymph nodes involved. 
Patients with an Oncotype Recurrence Score ≤ 25 were randomized to hormone therapy 
alone vs. hormone therapy plus chemotherapy. S1007 was initiated in 2011 and completed 
accrual in October 2015 at NTCN sites. UNICANCER independently accrued ~1,000 
patients, which completed accrual October 2017. Ultimately, 5,083 patients were 
randomized to S1007. 
 
S1007 is an ideal trial to collect blood samples in patients who have not developed a 
recurrence for evaluation of blood-based biomarkers. We have baseline clinical and 
pathologic data on all randomized patients and will be following patients for several more 
years to determine recurrence rate. Identifying potential markers for late recurrence in 
patients who have taken endocrine therapy remains an important unmet need and, as 
these patients are high-risk, given their nodal involvement, this study includes the 
population for which this question should be addressed. Also, S1007 exclusively enrolled 
patients with HR+/HER2- breast cancer, a subtype with a risk of late recurrence. S1007 
initially included an optional baseline tumor and nodal tissue collection, as well as blood 
samples collection, allowing for comparison of changes over time, depending on tissue 
availability. In addition, this study and other previously completed SWOG trials collected 
samples from patients prior to initiating adjuvant therapy.  
 
The circulating biomarker assessment for late relapse will involve Streck, Cellsave®, and 
STS blood and serum sample collection (with patient consent to the substudy) for patients 
who are between 5 and 8 years following start of endocrine therapy. Previously, EDTA 
tubes were collected (with patient consent) for banking at baseline registration to S1007.  

S1007 
Page 19 
Version Date 12/10/2021 
 
 
 
 
 
This will provide a unique opportunity to compare the additional substudy samples to 
originally banked S1007 pre-treatment samples, which may, in turn, allow for identification 
of three groups of patients: 1) those who have not escaped dormancy (and may not need 
continued hormonal or other therapy), 2) those who are escaping dormancy and will 
relapse in the near future (and may need to modify treatment immediately, identifying the 
highest risk group for future clinical trial approach considerations), and 3) those who still 
are in dormancy and may experience a later relapse (and may need to switch hormonal 
therapy and/or add a new targeted treatment: again, a population for future trial selection).  
 
In summary, these findings support the design of utilizing plasma repositories from large 
adjuvant trials of endocrine therapy. A number of critical questions remain in early-stage 
breast cancer. For instance, if CTCs are identified in a patient who is still on adjuvant 
therapy without a recurrence, should we consider switching the systemic therapy to 
decrease the risk for late recurrence? Is there a role for detection of ESR1 mutations, or 
other frequent mutations such as PIK3CA mutations, during adjuvant AI therapy? Will the 
ESR1 mutation status results observed in the metastatic Bolero-2 trial (endocrine therapy 
+/- everolimus) be recapitulated in the operable setting (endocrine +/- everolimus)? If ESR1 
mutations are identified, should these patients be switched to an alternative adjuvant 
therapy, such as a selective estrogen receptor downregulator (SERD)? Perhaps switching 
strategies or combination of hormone therapy with a SERD should be utilized to overcome 
endocrine resistance in operable breast cancer? Establishing a biorepository in this node 
positive population after 5 years of endocrine therapy offers a unique opportunity to 
evaluate whether we can identify blood-based predictors of late relapse.  
 
While there are commercially available tumor-tissue based genomic tests looking at rate 
of distant relapse, including breast cancer index, these are looking at baseline, pre-
treatment samples. This substudy will be looking at real-time, on-treatment predictors, 
which may be more reflective of current tumor biology due to selective treatment pressure, 
dormancy escape, etc. In addition, other previously described blood-based markers, such 
as serum tumor markers, in patients with breast cancer can be unreliable, including in 
patients with metastatic breast cancer. CTC enumeration and the association with risk of 
late relapse was selected as the primary outcome, given that preliminary data with 
CELLSEARCH in the adjuvant setting has been previously described, allowing for 
appropriately powered calculations in this concept. It is critical to further understand the 
differences in the technologies and whether a) the rate of CTC detection vary with a 
different platform in the same population and b) there are differences in the dynamic CTC 
changes with a different platform. We hypothesize that invasive disease-free survival will 
be poorer in CTC-positive patients compared to those patients who are CTC-negative. The 
two platforms for CTC’s (Menarini and Epic Sciences) will be compared to assess positivity 
rates between these two systems at each timepoint as well as whether changes between 
timepoints are also consistent. Ultimately, the goal of this project is to identify early 
predictors of dormancy escape and late recurrence in patients with operable breast cancer, 
which can serve as the basis for future randomized, interventional trials. 
 
2.5 
Rationale for Utilization of Remote Consent Procedures for Patient Consent to the 
Circulating Biomarker Assessment for Late Relapse Translational Medicine (CBALR TM) 
Substudy 
 
The patient population being considered for inclusion in the CBALR TM substudy 
(Registration Step 3) is currently in annual follow-up. There is strong rationale for the 
allowance for participating site implementation of remote consent procedures (especially 
with consideration for the ongoing effects of the COVID-19 pandemic on the healthcare 
environment) to consent prospective participants (who meet the eligibility criteria defined 
in Section 5.3) via telehealth methods prior to the patient’s next scheduled annual follow-

S1007 
Page 20 
Version Date 12/10/2021 
 
 
 
 
up visit. Herein, an allowance for utilization of remote consent procedures has been 
requested from the NCI CIRB for U.S. sites utilizing the NCI CIRB. Please see Section 16.0 
for S1007 Remote Consent Procedures for the CBALR TM substudy. 
 
3.0 
DRUG INFORMATION 
 
(This study is being conducted under CTEP IND #) 
 
Please refer to the package insert for the drugs that the individual patient will receive for approved 
language related to information on dosing, toxicities, preparation and administration of these 
agents. 
 
 
4.0 
STAGING CRITERIA 
 
N1 
Metastasis to movable ipsilateral axillary lymph node(s) 
pN1  
Micrometastasis or Metastasis in 1 to 3 axillary lymph nodes, and/or in internal mammary 
nodes with metastasis by sentinel lymph node biopsy but not clinically detected 
pN1mi Micrometastases (greater than 0.2 mm and/or more than 200 cells, but none greater than 
2.0 mm) 
pN1a 
Metastases in 1 to 3 axillary lymph nodes, at least one metastasis greater than 2.0 mm 
pN1b 
Metastases in internal mammary nodes with micrometastases or macrometastases 
detected by sentinel lymph node dissection but not clinically detected 
pN1c 
Metastases in 1 to 3 axillary lymph nodes and in internal mammary nodes with 
micrometastases or macrometastases detected by sentinel lymph node biopsy but not 
clinically detected 
 
 
5.0 
ELIGIBILITY CRITERIA 
 
Each of the criteria in the following section must be met in order for a patient to be considered 
eligible for registration.  Use the spaces provided to confirm a patient's eligibility.  For each criterion 
requiring test results and dates, please record this information on the S1007 Prestudy Form and 
submit to the SWOG Statistics and Data Management Center in Seattle (see Section 14.0).  Any 
potential eligibility issues should be addressed to the SWOG Statistics and Data Management 
Center in Seattle at 206/652-2267 prior to registration. 
 
In calculating days of tests and measurements, the day a test or measurement is done is 
considered Day 0.  Therefore, if a test is done on a Monday, the Monday 4 weeks later would be 
considered Day 28.  This allows for efficient patient scheduling without exceeding the guidelines.  
If Day 14, 28, 42, 56 or 84 falls on a weekend or holiday, the limit may be extended to the 
next working day. 
 
5.1 
STEP 1 REGISTRATION (Oncotype DX® Screening) 
 
If patient has previously been tested by Oncotype DX®, then she still must satisfy these 
eligibility criteria to be considered for randomization 
 
a. 
Patients must have a histologically confirmed diagnosis of node positive (1-3 
nodes) invasive breast carcinoma with positive estrogen and/or progesterone 
receptor status, and negative HER-2 status.  Estrogen and progesterone receptor 
positivity must be assessed according to ASCO/CAP guidelines as either ER or 
PR ≥ 1% positive nuclear staining.  HER-2 test result negativity must be assessed 
as per ASCO/CAP 2013 guidelines using IHC, ISH or both.  HER-2 is negative if 
a single test (or all tests) performed in a tumor specimen show:  a) IHC negative 
(0 or 1+) or b) ISH negative using single probe or dual probe (average HER-2 copy 
number < 4.0 signals per cell by single probe or HER-2/CEP ration < 2.0 with an 

S1007 
Page 21 
Version Date 12/10/2021 
 
 
 
 
average copy number < 4.0 signals per cell by dual probe).  If HER-2 IHC is 2+, 
evaluation for gene amplification (ISH) must be performed and the ISH must be 
negative; ISH is not required if IHC is 0 or 1+. HER-2 equivocal is not eligible. 
b. 
Patients with multifocal, multicentric and synchronous bilateral breast cancers are 
allowed. 
 
• 
Multifocal disease is defined as more than one invasive cancer < 2 cm from 
the largest lesion within the same breast quadrant.  (NOTE:  The Oncotype 
DX® testing must be completed on the largest lesion.) 
 
• 
Multicentric disease is defined as more than one invasive cancer ≥ 2 cm from 
the largest lesion within the same breast quadrant or more than one lesion in 
different quadrants.  (NOTE:  Oncotype DX® testing should be completed on 
all tumors and the determination for eligibility should be made on the highest 
recurrence score.) 
 
• 
Synchronous bilateral disease is defined as invasive breast cancer with 
positive lymph nodes (axillary or intramammary) in at least one breast, 
diagnosed within 30 days of each other.  (NOTE:  The Oncotype DX® testing 
should be completed on both tumors and the tumor with the highest recurrence 
score should be used.) 
 
c. 
Patients will have undergone axillary staging by sentinel node biopsy or axillary 
lymph nodes dissection (ALND).  Patients must have at least one, but no more 
than three known positive lymph nodes (pN1a, pN1b or pN1c), see Section 4.0 for 
definitions.  Patients with micrometastases as the only nodal involvement (pN1mi) 
are not eligible. Patients with positive sentinel node are not required to undergo 
full axillary lymph node dissection.  This is at the discretion of the treating 
physician. 
 
Axillary node evaluation is to be performed per the standard of care at each 
insititution. 
 
d. 
Patients must not have inflammatory breast cancer and must not have metastatic 
disease.   
 
e. 
Patients with a prior diagnosis of contralateral DCIS are eligible if they underwent 
a mastectomy or lumpectomy with whole breast radiation.  Prior partial breast 
irradiation, including brachytherapy, is not allowed.  Patients with a prior diagnosis 
of ipsilateral DCIS or invasive breast cancer who received radiation to that breast 
are not eligible. 
 
f. 
Patients must have had either breast-conserving surgery with planned radiation 
therapy or total mastectomy (with or without planned postmastectomy radiation).  
Patients must have clear margins from both invasive breast cancer and DCIS (as 
per local institutional guidelines).  LCIS at the margins is allowed. 
 
g. 
Registration of patients who have not yet undergone Oncotype DX® screening 
must occur no later than 56 days after definitive surgery.  (For all patients, Step 2 
Registration must occur within 84 days after definitive surgery.)  If the Oncotype 
DX® Breast Cancer Assay has not been performed, patients must be willing to 
submit tissue samples for testing to determine the Recurrence Score value. A 
representative block or unstained sections from the representative block are sent 
directly to Genomic Health for Oncotype DX® Breast Cancer Assay which will be 
performed according to the standard commercial process (see Section 15.1). 
 
If the Oncotype DX® Recurrence Score is already known and is 25 or less, the 
patient must be registered to Step 2 immediately following Step 1 registration.  If 

S1007 
Page 22 
Version Date 12/10/2021 
 
 
 
 
the Oncotype DX® Recurrence Score is already known and is greater than 25, the 
patient is ineligible. 
 
h. 
Patients must be females ≥ 18 years of age.  As the Oncotype DX® Recurrence 
Score has not been validated in men with breast cancer, men are not eligible for 
this study. 
 
i. 
Patients must have a complete history and physical examination within 28 days 
prior to registration. 
 
j. 
Patients must have a performance status of 0-2 by Zubrod criteria (see Section 
10.7).   
 
k. 
Patients must be able to receive taxane and/or anthracycline based chemotherapy. 
 
l. 
Patients must not have begun chemotherapy or endocrine therapy for their breast 
cancer prior to registration. 
 
m. 
Patients must not require chronic treatment with systemic steroids (inhaled 
steroids are allowed) or other immunosuppressive agents. 
 
n. 
Patients must not have received an aromatase inhibitor (AI) or a selective estrogen 
receptor modulator (SERM) such as tamoxifen or raloxifene within 5 years prior to 
registration. 
 
o. 
Patients must not be pregnant or nursing due to the possibility of harm to a fetus 
or nursing infant from this treatment regimen.  Women of reproductive potential 
must have agreed to use an effective contraceptive method.  A woman is 
considered to be of "reproductive potential" if she has had menses at any time in 
the preceding 12 consecutive months.  In addition to routine contraceptive 
methods, "effective contraception" also includes heterosexual celibacy and 
surgery intended to prevent pregnancy (or with a side-effect of pregnancy 
prevention) defined as a hysterectomy, bilateral oophorectomy or bilateral tubal 
ligation.  However, if at any point a previously celibate patient chooses to become 
heterosexually active during the time period for use of contraceptive measures 
outlined in the protocol, he/she is responsible for beginning contraceptive 
measures.   
 
p. 
No other prior malignancy is allowed except for adequately treated basal cell (or 
squamous cell) skin cancer, in situ cervical cancer, or other cancer for which the 
patient has been disease-free for 5 years. 
 
q. 
The Quality of Life and Economic Substudy is permanently closed to accrual 
effective 12/1/12. Patients who consented to QOL prior to 12/1/12 should 
continue to complete QOL forms per their expectation report. Patients who 
are able to complete a questionnaire in English must be offered the opportunity to 
participate in the Quality of Life and Economic Substudy. (The Quality of Life and 
Economic Substudy is available to U.S. INSTITUTIONS ONLY.)  Patients who are 
not able to complete a questionnaire in English are registered to S1007 without 
participating in the Quality of Life and Economic Substudy.   
 
• 
Patients who consent to participate in the Quality of Life and Economic 
Substudy and who do not yet know the results of their Oncotype DX® screening 
must agree to complete the S1007 Health-Related Quality of Life 
Questionnaire:  Enrollment between 14 days prior to and 7 days after Step 1 
Registration.   
 

S1007 
Page 23 
Version Date 12/10/2021 
 
 
 
 
• 
Patients who consent to participate in the Quality of Life and Economic 
Substudy and who do already know their Oncotype DX® Recurrence Score 
(and it is 25 or less) will proceed to Step 2 Registration without completing the 
S1007 Health-Related Quality of Life Questionnaire Enrollment Form (but will 
complete the S1007 Health-Related Quality of Life Questionnaire:  
Randomized Study Form) as outlined in Section 5.2d.  
 
r. 
Patients or their legally authorized representative must be informed of the 
investigational nature of this study and must sign and give written informed consent 
in accordance with institutional and federal guidelines.  For Step 1 registration of 
patients who have not yet submitted specimens for the Oncotype DX® Breast 
Cancer Assay, the appropriate consent form is the Step 1 Consent Form.  For both 
Step 1 and Step 2 registration of patients whose Recurrence Score is already 
known and is 25 or less, the appropriate consent form is the Step 2 Consent Form. 
 
s. 
As a part of the OPEN registration process (see Section 13.4 for OPEN access 
instructions) the treating institution's identity is provided in order to ensure that the 
current (within 365 days) date of institutional review board approval for this study 
has been entered in the system. 
 
5.2 
STEP 2 REGISTRATION (Randomization) 
 
The following additional criteria must be met in order for a patient to be considered eligible 
for registration to the randomized trial.  For each criterion requiring test results and dates, 
please record this information on the S1007 Prestudy Form-Randomized Study and submit 
to the SWOG Statistics and Data Management Center in Seattle (see Section 14.0).  Any 
potential eligibility issues should be addressed to the SWOG Statistics and Data 
Management Center in Seattle at 206/652-2267 prior to registration. 
 
a. 
Recurrence score (RS) by Oncotype DX® must be ≤ 25. 
 
b. 
Step 2 Registration must take place within 84 days after definitive surgery.  
Patients must not have begun chemotherapy or endocrine therapy for their breast 
cancer prior to randomization. 
 
c. 
Patients randomized to either arm may also co-enroll in Phase III trials that 
compare local therapies, or compare systemic therapies (such as chemotherapy, 
if randomized to Arm 1 of S1007).  
 
d. 
The Quality of Life and Economic Substudy is permanently closed to accrual 
effective 12/1/12. Patients at U.S. INSTITUTIONS who consent to participate in 
the Quality of Life and Economic Substudy must agree to complete the S1007 
Health-Related Quality of Life Questionnaire:  Randomized Study Form after 
Recurrence Score results and randomized treatment status are known but before 
treatment has been initiated. 
 
e. 
Patients or their legally authorized representative must be informed of the 
investigational nature of this study and must sign and give written informed consent 
in accordance with institutional and federal guidelines.  For all patients the 
appropriate consent form for this registration is the Step 2 Consent Form. 
 
5.3 
STEP 3 REGISTRATION (U.S. Sites Only) – CBALR TM Substudy 
 
U.S. Patients who meet the following criteria at time of participating site activation of 
Revision 16 (Version Date 03/24/21) must be offered participation in sample collection and 
banking, as indicated in Section 15.3, for the Circulating Biomarker Assessment for Late 
Relapse Translational Medicine Substudy:  

S1007 
Page 24 
Version Date 12/10/2021 
 
 
 
 
 
a. 
Patients must be disease-free, with no prior invasive recurrence at time of 
registration to Step 3. 
 
b. 
Patients must be registered to Step 3 no more than 8 years after randomization 
(Step 2 Registration) and must agree to have samples drawn within 28 days after 
registration to Step 3. 
 
c. 
Patients must agree to have blood samples collected at up to 3 timepoints: 1) within 
28 days after registration to Step 3, 2) 2-3 years after time of registration to Step 
3, and 3) At time of invasive recurrence (if applicable). Patients must also agree to 
have tissue submitted at time of invasive recurrence (if applicable) from the 
invasive recurrence biopsy (where tissue is available). 
 
** NOTE: Two separate specimen collection kits must be ordered IMMEDIATELY 
after patient registration to Step 3. See Section 15.3b for kit ordering instructions. 
 
 
6.0 
STRATIFICATION FACTORS 
 
6.1 
Patients will be randomized between Arm 1 (chemotherapy and endocrine therapy) and 
Arm 2 (endocrine therapy alone) using a dynamic balancing algorithm.  (57)  Treatment 
arms will be balanced with respect to the following stratification factors: 
 
a. 
Recurrence score:  0-13 versus 14-25 
 
b. 
Menopausal status:  pre-menopausal versus postmenopausal as defined in the 
S1007 Prestudy Form. 
 
c. 
Type of nodal dissection:  axillary lymph node dissection (with or without sentinel 
node mapping) versus sentinel node biopsy without axillary lymph node dissection. 
 
 
7.0 
TREATMENT PLAN 
 
For questions regarding treatment regimen selection, please contact Dr. Kevin Kalinsky or Dr. Julie 
R. Gralow at S1007question@swog.org. For dosing principles or questions, please consult the 
SWOG 
Policy 
#38 
"Dosing 
Principles 
for 
Patients 
on 
Clinical 
Trials" 
at 
https://www.swog.org/sites/default/files/docs/2017-11/Policy38.pdf. However, individual decisions 
about patient dosing and dose modification are at the discretion of the treating investigator (see 
Section 8.3). 
 
7.1 
General Consideration/Concomitant Therapies 
 
a. 
It is recommended for patients to have adequate bone marrow function, as defined 
by peripheral granulocyte count of ≥ 1,500/mm3, and platelet count ≥ 100,000/mm3. 
 
b. 
It is recommended for patients to have adequate renal function with creatinine 
levels ≤ the institutional upper limit of normal. 
 
c. 
It is recommended for patients to have adequate liver function with a bilirubin ≤ the 
institutional upper limit of normal.  Alkaline phosphatase and transaminases (ALT 
and AST) may be up to 1.5 x the institutional upper limit of normal (ULN). 
 
d. 
If patient is clinical Stage IIIA (T3, N1, M0) a baseline chest x-ray, CT scan of the 
abdomen and pelvis, PET/CT, bone scan, or MRI is recommended. 
 

S1007 
Page 25 
Version Date 12/10/2021 
 
 
 
 
e. 
Diagnostic bilateral mammogram to obtain a baseline is recommended prior to 
surgery. 
 
f. 
MUGA or ECHO is recommended for patients who are randomized to receive 
chemotherapy and who choose to include anthracycline-based treatment in the 
regimen.  It is recommended that these patients have a normal left ventricular 
ejection fraction of ≥ 50%. 
 
g. 
In general, the use of any concomitant medication/therapy deemed necessary for 
the care of the patient is allowed, including drugs given prophylactically (e.g. 
antiemetics +/- steroids, granulocyte colony stimulating factors). 
 
h. 
Clinical Trial Conduct during COVID-19 Pandemic (and other extenuating 
circumstances) 
 
In order to provide participating sites flexibility in ongoing patient treatment in the 
current COVID-19 pandemic healthcare environment, utilization of offsite / local 
healthcare resources for conduct of participant’s annual history and physical exam 
is allowable with appropriate oversight by the Responsible Investigator. This 
utilization of local healthcare providers does not need to be documented as a 
deviation.  In addition, the following extended window for the follow-up 
assessments is allowable per protocol, where the Responsible Investigator 
determines the delayed assessment is in the best interest of the patient as 
indicated below.  
 
Extended Window for Follow-up Disease Assessment and Mammograms: 
 
The allowable best practices window for the S1007 disease assessments, 
occurring every 6 months until 5 years after time of randomization and then 
annually thereafter until 15 years after randomization, and annual mammograms 
is being extended to +/- 30 days, where the Responsible Investigator determines 
that the delayed assessments help to assure the safety of the patient, with 
consideration for the COVID-19 pandemic and related extenuating circumstances. 
 
The Responsible Investigator rationale for utilization of the extended window 
outlined above must be carefully documented in the patient chart as 
resultant from the COVID-19 pandemic and extenuating circumstance. 
Please note the allowable best practices windows for the disease assessments 
and mammograms, indicated in Section 9.0, otherwise remain applicable for all 
patients, where there is not a COVID-19 pandemic-related extenuating 
circumstance. 
 
7.2 
Oncotype DX® Assay 
 
If not already done prior to Step 1 Registration, tumor sample will be submitted to Oncotype 
DX® Assay Genomic Health for the Oncotype DX® assay, and will be evaluated for 
recurrence score (RS).  Patients with RS ≤ 25 will undergo discussion of this trial in 
consultation with their oncologist considering known RS value and number of positive 
nodes.  Patients will then be randomized to one of two arms (Step 2).   
 
Radiation is recommended per institutional and National Comprehensive Cancer Network 
(NCCN) guidelines (http://www.nccn.org) and may be given after chemotherapy and during 
endocrine therapy. 
 
 

S1007 
Page 26 
Version Date 12/10/2021 
 
 
 
 
 
7.3 
Arm 1 (chemotherapy and endocrine therapy) 
 
All Arm 1 patients will receive a protocol-approved chemotherapy regimen (see below), 
followed by a protocol-approved endocrine therapy (see below). The approved 
chemotherapy and endocrine therapy regimens are listed below, though these may be 
expanded or contracted during the course of the trial as standard of care changes occur. 
 
a. 
Chemotherapy: All patients will receive a second or third generation 
chemotherapy. Choice of chemotherapy will depend on patient/physician 
preference. 
 
1. 
Second Generation Regimens: 
 
Agents 
Schedule 
Cycle length 
Docetaxel and cyclophosphamide 
4-6 cycles 
 
5-FU, doxorubicin (or epirubicin), and 
cyclophosphamide* 
6 cycles 
 
Doxorubicin (or epirubicin) and 
cyclophosphamide (AC/EC) followed by 
paclitaxel 
4 cycles each 
q 3 weeks 
5-FU, doxorubicin (or epirubicin) and 
cyclophosphamide followed by docetaxel 
3 cycles each 
q 3 weeks 
* includes CAF/CEF with oral cyclophosphamide and FAC/FE(100)C with 
intravenous cyclophosphamide 
 
 
2. 
Third Generation Regimens: 
 
Agents 
Schedule 
Cycle length 
Doxorubicin (or epirubicin) and 
cyclophosphamide (AC/EC) followed 
by paclitaxel 
4 cycles for 
AC/EC;12 cycles 
for paclitaxel 
q 2 weeks or  
q 3 weeks for 
AC; weekly for 
paclitaxel 
5-FU, doxorubicin (or epirubicin), and 
cyclophosphamide followed by 
docetaxel 
3 cycles each 
 
All cycles q 3 
weeks 
5-FU, doxorubicin (or epirubicin), and 
cyclophosphamide followed by 
docetaxel 
3 cycles each 
 
Dose dense doxorubicin and 
cyclophosphamide  
followed by dose dense paclitaxel 
4 cycles each 
All cycles q 2 
weeks 
Docetaxel, doxorubicin, and 
cyclophosphamide 
6 cycles 
 
5-FU, doxorubicin (or epirubicin) and 
cyclophosphamide (FAC) followed by 
paclitaxel 
4 cycles for 
FAC;12 cycles 
for paclitaxel 
Weekly for 
paclitaxel 
Paclitaxel followed by  
5-FU, doxorubicin (or epirubicin) and 
cyclophosphamide (FAC) 
12 cycles for 
paclitaxel; 
4 cycles for FAC 
Weekly for 
paclitaxel 
 
 

S1007 
Page 27 
Version Date 12/10/2021 
 
 
 
 
 
b. 
Endocrine therapy: All patients will receive endocrine therapy. Choice of therapy 
will depend on menopausal status (see below) and patient/physician preference.  
Anyone not defined as postmenopausal per institutional standards should be 
treated as premenopausal.  Treatment should be at least 5 years but can be 
extended.  Switching from one therapy to another is allowed. 
 
1. 
Approved Endocrine Therapy Regimens for Premenopausal women: 
 
Treatment 
Dose 
Treatment 
duration 
Tamoxifen 
20 mg daily 
5 years 
Ovarian suppression or 
ablation 
 
5 years 
Tamoxifen combined with 
ovarian suppression or 
ablation 
20 mg daily 
5 years 
Aromatase inhibitor (AI) 
combined with ovarian 
suppression or ablation* 
Approved dose for AI 
5 years 
Tamoxifen followed by an 
aromatase inhibitor (AI)** 
20 mg daily for 
tamoxifen; approved 
dose for AI 
2-3 years each 
Tamoxifen followed by an 
aromatase inhibitor (AI)** 
20 mg daily for 
tamoxifen; approved 
dose for AI 
5 years each 
*  
if the patient cannot tolerate tamoxifen or tamoxifen is contraindicated 
**  If the patient becomes postmenopausal 
 
2. 
Approved Endocrine Therapy Regimens for Postmenopausal women: 
 
Treatment 
Dose 
Treatment 
duration 
An aromatase inhibitor 
Approved dose 
5 years 
Tamoxifen* 
20 mg daily 
5 years 
Tamoxifen followed by an 
aromatase inhibitor 
20 mg daily; 
approved dose 
2-3 years each 
An aromatase inhibitor 
followed by tamoxifen 
approved dose; 20 
mg daily 
2-3 years each 
Tamoxifen followed by an 
aromatase inhibitor 
20 mg daily; 
approved dose 
5 years each 
* 
if the patient is unsuitable for, cannot tolerate, or refuses an aromatase 
inhibitor 
 
NOTE:  All postmenopausal patients are encouraged to receive an aromatase inhibitor 
sometime during their course of adjuvant endocrine therapy. 
 
The approved regimens may be expanded or contracted if there is a shift in standard of 
care during the course of the trial. 
 
 

S1007 
Page 28 
Version Date 12/10/2021 
 
 
 
 
7.4 
Arm 2 (endocrine therapy alone) 
 
Patients will receive a protocol-approved endocrine therapy.   
 
Endocrine therapy: All patients will receive endocrine therapy.  Choice of therapy will 
depend on menopausal status (see above) and patient/physician preference. Anyone not 
defined as postmenopausal per institutional standards should be treated as 
premenopausal.  Treatment should be at least 5 years but can be extended.  Switching 
from one therapy to another is allowed.   
 
The approved endocrine therapy regimens are listed above under Arm 1, although these 
may be expanded or contracted during the course of the trial as standard of care changes 
occur. 
 
Radiation is recommended per institutional guidelines and may be given before or during 
endocrine therapy (the start date of treatment is the start date of endocrine therapy) 
 
7.5 
Criteria for Removal from Protocol Treatment (Step 2) 
 
a. 
Invasive recurrence/progression/relapse of disease (as defined in Section 10.1). 
 
b. 
Completion of 5 years from randomization.  (NOTE:  Refusal of randomized 
treatment arm assignment, completion of chemotherapy, and/or early 
discontinuation of endocrine therapy are not considered criteria for removal from 
protocol treatment for this study.) 
 
c. 
The patient may withdraw from the study at any time for any reason.  However, 
refusal of the randomized treatment arm assignment alone is not a reason to take 
the patient off study.  Randomized patients should be continued on study for 5 
years from initial registration regardless of actual treatment received. 
 
NOTE:  Patients who develop a second primary malignancy are not required to be removed 
from protocol treatment, and they are encouraged to remain on study unless it is not 
appropriate for their continued care in the opinion of the treating physician. 
 
7.6 
Discontinuation of Treatment  
 
All reasons for discontinuation of treatment must be documented in the Off Treatment 
Notice. 
 
7.7 
Follow-Up Period  
 
All patients will be followed until death or 15 years after randomization, whichever occurs 
first. 
 
 
 

S1007 
Page 29 
Version Date 12/10/2021 
 
 
 
 
 
8.0 
TOXICITIES TO BE MONITORED AND DOSAGE MODIFICATIONS 
 
8.1 
NCI Common Terminology Criteria for Adverse Events 
 
Two different versions of the NCI Common Terminology Criteria for Adverse Events 
(CTCAE) will be used on this study. 
 
a. 
Serious Adverse Event (SAE) reporting 
 
The CTCAE (NCI Common Terminology Criteria for Adverse Events) Version 5.0 
will be utilized for SAE reporting only. The CTCAE Version 5.0 can be 
downloaded from the CTEP home page (https://ctep.cancer.gov).  All appropriate 
treatment areas should have access to a copy of the CTCAE Version 5.0. 
 
b. 
Routine toxicity reporting 
 
This study will utilize the CTCAE Version 4.0 for routine toxicity reporting.  A copy 
of the CTCAE Version 4.0 can be downloaded from the CTEP home page 
(https://ctep.cancer.gov).  All appropriate treatment areas should have access to a 
copy of the CTCAE Version 4.0. 
 
8.2 
General Considerations 
 
In general, the use of any concomitant medication/therapies deemed necessary for the 
care of the patient are allowed (e.g., bisphosphonates for osteoporosis), including drugs 
given prophylactically (e.g. antiemetics +/- steroids, granulocyte colony stimulating factors),  
 
8.3 
Dose Modifications  
 
Treatment and dose modifications are at the discretion of the treating investigator.  Use of 
granulocyte growth factor support is recommended to maintain planned doses of 
chemotherapy. 
 
8.4 
Adverse Event Reporting  
 
Toxicities (including suspected reactions) that meet the expedited reporting criteria as 
outlined in Section 16.0 of the protocol must be reported to the Operations Office, Study 
Chair and NCI via CTEP-AERS, and to the IRB per local IRB requirements. 

S1007 
Page 30 
Version Date 12/10/2021 
 
 
 
9.0 
STUDY CALENDAR 
REQUIRED STUDIES 
PRE 
STUDY 
PRE 
Reg 
#2 
During 
Chemotherapy 
Treatment * 
During 
Endocrine 
Therapy 
Treatment Ω 
Clinic Visits Prior 
 to Invasive 
Recurrence/ 
Progression/ 
Relapse Ω 
At time of 
Invasive 
Recurrence 
Follow-Up Post-
Invasive Recurrence/ 
Progression/  
Relapse ^ 
  
PHYSICAL* 
  
  
  
  
  
  
 
History & physical   √  
X 
  
X 
X 
X 
X 
X 
Wt. & Performance Status 
X 
  
X 
X 
X 
X 
X 
Disease Assessment 
 X 
 
X 
X 
X 
X 
X 
Toxicity Notation  
  
  
X 
X 
  
  
  
HRQL  ¿ 
X 
X 
  
  
X 
X 
X 
LABORATORY* 
  
  
  
  
  
  
  
AST/ALT 
  
 
X 
  
  
  
  
CBC/Differential/Platelets 
  
 
X 
  
  
  
  
Serum Creatinine (POCT 
creatinine allowed) 
  
 
X 
  
  
  
  
Bilirubin 
  
  
X 
  
  
  
  
Alk Phos 
  
 
X 
  
  
  
  
HER-2 status 
X 
  
  
  
  
  
  
Hormone Receptor status 
X 
  
  
  
  
  
  
X-RAYS AND SCANS 
  
  
  
  
  
  
  
Mammogram  
  
 
  
X£ 
X£ 
X£ 
  
SPECIMENS  † 
  
  
  
  
  
  
  
Submission for Oncotype DX 
Breast Cancer Assay   # 
  
X 
  
  
  
  
  
Tissue for correlatives 
  
X§ 
  
  
  
X ∑ 
  
Blood specimens for correlatives 
  
X§ 
  
  
X ∑ 
X ∑ 
  
TREATMENT 
  
  
  
  
  
  
  
Radiation  % 
  
  
  
  
  
  
  
ARM 1 - chemotherapy followed 
by endocrine therapy 
  
  
X 
X ∫ 
X ∫ 
X ∫ 
  
ARM 2 - endocrine therapy alone 
  
  
  
X ∫ 
X ∫ 
X ∫ 
  
Calendar continued on next page. Click here for footnotes. 
Note:  Forms are found on the protocol abstract page of the SWOG website (www.swog.org).  Data submission guidelines are found in Section 14.0. 
 

S1007 
Page 31 
Version Date 12/10/2021 
 
 
 
 
 
 
NOTE: Unless indicated otherwise in the protocol, scheduled procedures and assessments (treatment administration, toxicity assessment for 
continuous treatment, disease assessment, specimen collection and follow-up activities) must follow the established SWOG guidelines as outlined 
in outlined in the SWOG Best Practices document accessible from the “Best Practices” link at: https://www.swog.org/clinical-trials/protocol-
workbench. 
 
FOOTNOTES: 
 
√  Physical exam to include breast examination. 
#  May have already been performed prestudy, see Section 5.1e. 
£  All patients with an intact breast will have an annual (± 14 days) mammogram thereafter until after time of invasive 
recurrence/progression/relapse. See also Section 7.1h for extended allowable windows for recurrence assessments in event of a COVID-19 
extenuating circumstance. 
*  
Clinic visits for labs and physical exams should be scheduled as clinically indicated based on the selected chemotherapy regimen. 
†  See Section 15.0 for specimen submission requirements and specimen processing instructions. 
% Radiation is recommended per institutional and NCCN guidelines and may be given after chemotherapy and during endocrine therapy. 
Ω  Whether or not patient is receiving endocrine therapy, patients will be followed for recurrence/progression/relapse every 3 months for the first 
year, every six months (± 7 days) from Years 2-5 and then annually (± 14 days) until 15 years after randomization or after time of invasive 
recurrence/progression/relapse. See also Section 7.1h for extended allowable windows for recurrence assessments in event of a COVID-19 
extenuating circumstance. 
∫   Treatment with endocrine therapy will continue for at least five years. 
^   After recurrence/progression/relapse, patients will be followed annually for additional recurrence endpoints, including second primary and for 
survival. 
§  Specimens for correlatives must be collected after Step 2 consent, but prior to start of treatment (see Section 14.4f). 
¿  The Health Related Quality of Life (HRQL) forms are to be completed by patients at U.S. institutions only and at the timepoints outlined in the 
HRQL schema. 
∑ 
For patients registered to Step 3, blood must be submitted within 28 days after patient registration to Step 3, then at 2-3 years after patient registration 
to Step 3 (if prior to invasive recurrence), and at time of invasive recurrence. See Section 15.3b for sample collection kit ordering instructions and allow 
sufficient time for kit shipments. Tissue must also be submitted at time of invasive recurrence. See Sections 15.3 and 15.4. 
 
 
 
 

S1007 
Page 32 
Version Date 12/10/2021 
 
 
 
10.0 
CRITERIA FOR EVALUATION AND ENDPOINT DEFINITIONS 
 
10.1 
Invasive Recurrence 
 
a. 
Appearance of any new invasive lesion(s) during or after protocol treatment.  
Whenever possible, recurrences should be documented histologically.  Invasive 
recurrence includes local, regional, or distant recurrence with an invasive 
component.  A new diagnosis of ipsilateral or contralateral DCIS without an 
invasive component is not considered to be a recurrence. 
 
10.2 
Sites of first invasive recurrence 
 
All sites of invasive disease documented within 30 days of first documentation of invasive 
recurrence. 
 
10.3 
Invasive Disease-Free Survival 
 
We use the STEEP definition (Hudis, et.al., JCO 2007) of invasive disease-free survival. 
Time from date of randomization (2nd Registration) to date of first invasive recurrence (local, 
regional or distant), second invasive primary cancer (breast or not), or death due to any 
cause.  Patients last known to be alive who have not experienced recurrence or second 
primary cancer are censored at their last contact date.  We use the acronym DFS for 
invasive disease-free survival in this protocol. 
 
10.4 
Distant Disease-Free Survival 
 
Time from date of randomization (2nd Registration) to date of invasive distant disease 
recurrence, second invasive primary cancer (breast or not) or death due to any cause.  
Patients last known to be alive who have not experienced distant recurrence, or second 
primary cancer are censored at their last contact date.  This secondary outcome requires 
continuing to follow the patient after local recurrence in order to ascertain subsequent 
distant recurrence. 
 
10.5 
Local Disease-Free Interval 
 
Time from date of randomization (2nd Registration) to date of invasive local or regional 
recurrence.  Patients last known to be alive without recurrence are censored at their last 
contact date.  Patients with distant recurrence, second primary cancer or death are 
censored at the time of that event. 
 
10.6 
Overall Survival 
 
Time from date of randomization (2nd Registration) to date of death due to any cause.  
Patients last known to be alive are censored at their last contact date. 
 
 

S1007 
Page 33 
Version Date 12/10/2021 
 
 
 
 
 
10.7 
Invasive Breast Cancer-Free Survival 
 
We use the STEEP 2.0 definition (Tolaney, et.al., JCO 2021) of invasive breast cancer-
free survival (IBCFS). Time from date of randomization (2nd Registration) to date of first 
invasive recurrence (local, regional or distant), second invasive breast cancer, or death 
due to any cause.  Patients last known to be alive who have not experienced recurrence 
or second breast cancer are censored at their last contact date. This is similar to IDFS 
except that new non-breast primary cancers are not included as events. (58)  
 
10.8 
Performance Status 
 
Patients will be graded according to the Zubrod performance status scale. 
 
POINT 
DESCRIPTION 
 
0 
Fully active, able to carry on all pre-disease performance without 
restriction. 
 
1 
Restricted in physically strenuous activity but ambulatory and able 
to carry out work of a light or sedentary nature, e.g., light 
housework, office work.   
 
2 
Ambulatory and capable of self-care but unable to carry out any 
work activities; up and about more than 50% of waking hours.   
 
3 
Capable of limited self-care, confined to bed or chair more than 
50% of waking hours.   
 
4 
Completely disabled; cannot carry on any self-care; totally 
confined to bed or chair. 
 
 
11.0 
STATISTICAL CONSIDERATIONS 
 
11.1 
Accrual Goal 
 
Women who have been diagnosed with node-positive (1-3 positive nodes), HER2-
negative, endocrine-responsive breast cancer who meet the eligibility criteria in Section 5.0 
will undergo testing by the 21-gene Recurrence Score assay (Oncotype DX®).  It is 
anticipated that 10,000 women will be tested as part of the study or will already have been 
tested.  Based on the distribution of RS scores in SWOG-8814 for women with 1-3 positive 
nodes, 7,000 women would be expected to have RS ≤ 25.  Of this group, 5,000 women are 
expected to accept randomization.  The formal sample size goal for the randomized trial is 
5,000 which will require approximately 10,000 women to be screened for inclusion. The 
5,000 randomized patients will include the original accrual goal of 4,000 NCTN patients 
plus an additional 1,000 patients accrued by UNICANCER in France and combined for a 
joint analysis. 
 
 

S1007 
Page 34 
Version Date 12/10/2021 
 
 
 
 
 
11.2 
Accrual Rate 
 
Originally we expected accrual of 4,000 randomized patients to take 6 years, giving a 
monthly accrual rate of 56 patients per month. The formal study completion date was five 
years after the last patient was enrolled to provide sufficient power for analyses.  Thus, the 
original trial duration was expected to be 11 years.  In this revised sample size calculation 
the actual monthly enrollment rates are used from study start in February 2011 to July 2014 
which showed accrual not reaching the target goal until February 2012.  Subsequently, 
accrual exceeded the goal considerably and the trial goal of 4,000 would be expected to 
be reached by August 2015 or 4.5 years of total accrual which is 1.5 years earlier than 
expected.  If the trial used the original stopping rule of 5 years after the last patient, then 
power would be reduced considerably by the shorter follow-time for events to accrue.  We 
can either extend the follow-up period and/or increase the accrual by combining with the 
UNICANCER group.  SWOG has decided to do both as explained below. 
 
Accrual from September 2014 to August 2015 is assumed to be 98 randomized patients 
per month until the NCTN accrual reaches 4,000 patients.  We assume UNICANCER will 
accrue approximately 83.3 patients per month for an additional 12 months.  This will result 
in a total sample size of 5,000 patients over a 5.5 year accrual period.  After the last patient 
is accrued, then there will be 5.5 more years of follow-up before the study will have final 
analysis. The total trial duration will be 11 years which is the original length of the trial. 
However, individual patients will be followed for a minimum of fifteen years regardless of 
the date of enrollment to assess long-term effects of treatment. 
 
11.3 
Randomization and Stratification 
 
A 1:1 parallel randomization is used with dynamic balancing on the three stratification 
factors: (1) RS 0-13 vs. RS 14-25; (2) menopausal status; and (3) axillary nodal dissection 
vs. sentinel node biopsy.   Randomization is performed separately for NCTN and 
UNICANCER patients with randomized accrual goals of 4,000 and 1,000, respectively. 
 
11.4 
Summary of Analytic Plan 
 
The complete statistical plan is presented in Appendix 18.4, but a brief summary is 
provided here.  The primary question is to test whether chemotherapy benefit (if it exists) 
depends on the Recurrence Score.  Thus the underlying hypothesis is that there is an 
interaction of chemotherapy and RS.  This interaction is tested in a Cox regression model 
of DFS.  If the interaction of chemotherapy and the linear RS term is statistically significant 
(two-sided α) and there is a point of equivalence between the two randomized treatments 
for some RS value in the range 0-25, then additional steps are undertaken.  Based on 
simulation work, power to find a significant interaction with an equivalence point is 81%.  
Assuming there is a significant predictive effect of RS on chemotherapy benefit, then a 
clinical cutpoint for recommending chemotherapy will be estimated.  This estimated 
cutpoint is the upper bound of the 95% confidence interval on the point of equivalence.  
Kaplan-Meier curves comparing randomized arms will be generated separately for RS 
values below and above this cutpoint and tested with stratified log-rank tests.  Additionally, 
Kaplan-Meier curves will be generated for specific RS values (possibly grouped due to 
sparseness), and modeled 5-year and 10-year estimates by RS and treatment will be 
provided.  If there is no statistical interaction between linear RS and chemotherapy, then 
chemotherapy will be tested in a Cox model adjusting for RS, but without an interaction 
term.  This test will be conducted at a 1-sided α=0.025 since chemotherapy would be 
expected to improve outcomes.   
 
 

S1007 
Page 35 
Version Date 12/10/2021 
 
 
 
 
 
11.5 
Compliance and Dropout 
 
Despite the required discussion between patient and physician prior to randomization, 
some patients will still be noncompliant after randomization.  The estimated sample size 
includes a 5% crossover rate and assumes that noncompliance depends on RS.  For 
patients randomized to chemotherapy, the assumption is that 5% do not receive 
chemotherapy and that a patient with RS 0-11 is twice as likely to refuse as one who has 
RS 12-25.  For patients randomized to not receive chemotherapy, the assumption is 5% 
do receive chemotherapy and that a patient with RS 18-25 is twice as likely to receive 
chemotherapy as one who has RS 0-17.  The assumption is that the noncompliant patients 
remain in the study and provide follow-up.  Thus, in the intent to treat analysis 5% of 
patients in each treatment group have a treatment opposite to their randomized 
assignment.  This crossover rate was incorporated into the simulations which used a 
sample size of 4,750.  This was increased to 5,000 to also accommodate dropout, 
ineligibility, or withdrawal of consent. 
 
11.6 
Early Termination for Futility 
 
Apart from statistical testing of outcomes, low accrual and crossovers post-randomization 
affect the viability of the trial.  It is also possible that differential acceptance of 
randomization across the range of RS from 0 to 25 may affect the statistical power of this 
study.  With respect to accrual the study will employ the usual CTEP guideline to judge 
whether accrual is within expectations and whether the protocol needs to be amended.  
After two years of accrual, a committee of five statisticians (one SWOG, two from other 
cooperative groups, and two from CTEP) will meet and discuss viability of the trial based 
on accrual, acceptance of randomization, and crossover rate. The result of this discussion 
will be presented to CTEP and the Data and Safety Monitoring Committee (DSMC) for 
action. With respect to crossover rate (randomized participants receiving the opposite 
treatment), the upper limit is set at 15% in the first year and 12% after 2 years.  The trial 
will terminate if the crossover rate exceeds this unless NCI determines that the high 
crossover rate has been corrected and that the trial remains viable.  Crossover rates 
between 5% and the upper limit can be addressed by longer follow-up without increasing 
accrual. The target crossover rate is less than 5% total. As of August 2014, the actual 
crossover rate has been just less than 5%. 
 
11.7 
Summary of Revised Analytic Plan 
 
As described in Section 11.2, accrual started slowly, but then improved dramatically so that 
now accrual of the original sample size goal is expected to finish 1.5 years early.  Since 
the original design called for a final analysis 5 years after the last patient was enrolled, the 
number of events is considerably reduced due to the shorter time window.  Using the 
observed sample size accrual, but keeping other design elements constant, then power to 
find a significant interaction would drop to 68% due to the shorter window for events.  If we 
increase the window to 6.5 years after the last patient is accrued then power can be 
restored to 82.7% without adding 1,000 new patients.  However, that provides no margin 
against some violation of the statistical assumptions of this important signature trial of the 
NCTN.  For example, if the event rate is lower than predicted we would not have power to 
address the event rate accurately (and it depends on the intervention), but we can look at 
the population in terms of prognostic risk factors compared to what was expected.  There 
has been a strong shift in the number of positive nodes compared to SWOG-8814.  The 
older trial had a distribution of positive nodes for 1-3 of 48%, 32%, and 20%, respectively 
while the current trial has a distribution of 68%, 24%, and 8%.  However, because of 
sentinel node biopsy there could have been an apparent shift downwards that does not 
reflect the true distribution of the number of positive nodes.  Furthermore, the current trial 
has a distribution of Recurrence Scores that is the same as in SWOG-8814 when restricted 
to ≤ 25 and in agreement with the expected distribution used to plan the trial.  For trial 

S1007 
Page 36 
Version Date 12/10/2021 
 
 
 
 
 
planning we used an overall 5-year DFS rate of 92.4%, but we would still like to have 
sufficient power if the event rate is less than expected. 
 
The second reason to increase the sample size is to provide a validation that the results 
apply to an external population to NCTN patients.  We are including these patients in the 
overall trial, but will conduct planned subset analyses of the two cohorts separately.  If we 
retain the same design parameters with a 5,000 patient trial of the same total duration (11 
years), then power increases to 86.3% and the expected number of events increases from 
731 to 832.  When the interaction is significant we determine the estimated cutpoint for 
using chemotherapy and its upper confidence bound.  This cutpoint can be better 
determined when there are more events.  Finally, the larger sample size allows some 
protection against lower event rates.  For example, if the actual 5-year DFS rate is 93.9%, 
then power is still 80% to detect a significant interaction. 
 
To guarantee that the trial will be well powered under the assumptions but have sufficient 
power under minor violation of the assumptions, we are increasing the sample size to 5,000 
with a 5.5 year follow-up so that the total trial duration remains the same as in the original 
protocol. 
 
11.8 
Interim Analysis 
 
Under the assumptions above, we would expect 832 events for the primary analysis of the 
interaction of RS and chemotherapy.  The first interim analysis would be after 24% of the 
events have been observed or approximately 6.6 years after initiation of the study.  This 
would correspond to the end of accrual if accrual is uniform and at the expected level. 
There would be subsequent annual interim analyses thereafter with 37%, 53%, 72%, and 
92% with the final analysis at Year 11. The analyses will use the Lan-Demets spending 
function with a truncation bound. To achieve a cumulative 0.025 1-sided significance level, 
the interim test α‘s will be 0.0005, 0.0005, 0.00149, 0.00741, 0.01673, respectively, and 
the final = 0.01871 so there is little loss of power due to the interim analyses.  All of these 
analyses are expected to be after accrual has finished so a decision to publish early would 
be based on the interim analysis.  We also want to monitor the upper RS group of 14-25 to 
avoid harming patients if there is early evidence of efficacy in this group.  An analysis will 
be conducted at 4 years to evaluate efficacy of chemotherapy in patients with RS 14-25 to 
determine if there is a potential significant benefit of chemotherapy early in the trial. If this 
comparison is statistically significant at p=0.05 (2-sided) then further randomization in 
patients with RS 14-25 would be suspended.    A similar comparison would then also be 
performed in the RS 0-13 group to determine if the trial should suspend accrual completely.  
Otherwise, all other analyses would occur after accrual is complete.   
 
11.9 
Translational Medicine 
 
The statistical considerations for the translational medicine studies, quality of life and costs 
are described in their respective sections in the appendix. 
 
11.10 
Data and Safety Monitoring Committee  
 
A Data and Safety Monitoring Committee will oversee the conduct of the study.  The 
Committee consists of four members from outside of SWOG, 3 SWOG members, 3 non-
voting representatives from the National Cancer Institute (NCI), and the Group Statistician 
(non-voting).  The members of this Committee will receive confidential reports every 6 
months from the SWOG Statistics and Data Management Center, and will meet at the 
Group's bi-annual meetings as necessary.  The Committee will be responsible for decisions 
regarding possible termination and/or early reporting of the study. 
 
 
 

S1007 
Page 37 
Version Date 12/10/2021 
 
 
 
 
 
12.0 
DISCIPLINE REVIEW 
 
This is not applicable to this study. 
 
 
13.0 
REGISTRATION GUIDELINES 
 
13.1 
Registration Timing 
 
a. 
STEP 1 - Initial Registration (Oncotype DX® Screening) 
 
Patients must meet the eligibility criteria in the Step 1 Registration criteria in 
Section 5.0.  Patients who have not yet undergone Oncotype DX® Screening must 
be registered prior to initiation of treatment no later than 56 days from the date of 
definitive surgery. 
 
Patients whose Oncotype DX® Recurrence Score is already known may undergo 
Step 1 and Step 2 registration at the same time (within 84 days after definitive 
surgery). 
 
b. 
STEP 2 - Randomization (Chemotherapy plus Endocrine Therapy vs Endocrine 
Therapy alone) 
 
Patients whose Recurrence Score is ≤ 25 and who meet the eligibility criteria as 
stated in the Step 2 Registration criteria in Section 5.0 will be registered to STEP 
2 – Randomization.  This registration must be performed within 84 days after the 
patient’s date of definitive surgery.   
 
Patients must be randomized prior to the initiation of treatment (no more than 
fourteen working days prior to the planned start of chemotherapy or endocrine 
treatment).  For patients randomized to endocrine therapy only, who would receive 
radiation therapy prior to the start of endocrine therapy, radiation therapy must be 
planned to start within fourteen working days after randomization. 
 
c. 
STEP 3 – Circulating Biomarker Assessment for Late Relapse Translational 
Medicine Substudy 
 
U.S. patients must be registered to Step 3 Registration no more than 8 years after 
randomization (Step 2 Registration) and initial CBALR TM  blood samples must be 
drawn within 28 days after registration. See also eligibility criteria indicated in 
Section 5.3. 
 
13.2 
Investigator/Site Registration 
 
This study is supported by the NCI Cancer Trials Support Unit (CTSU). 
 
Prior to the recruitment of a patient for this study, investigators must be registered members 
of a Cooperative Group.  Each investigator must have an NCI investigator number and 
must maintain an "active" investigator registration status through the annual submission of 
a complete investigator registration packet (FDA Form 1572 with original signature, current 
CV, Supplemental Investigator Data Form with signature and Financial Disclosure Form 
with original signature) to the Pharmaceutical Management Branch, CTEP, DCTD, NCI.  
These 
forms 
are 
available 
on 
the 
CTSU 
Web 
site 
(https://ctep.cancer.gov/investigatorResources/investigator_registration.htm). Questions 
should be directed to the CTEP Investigator Registration Help Desk by e-mail at 
pmbregpend@ctep.nci.gov.   
 

S1007 
Page 38 
Version Date 12/10/2021 
 
 
 
 
 
Each investigator or group of investigators at a clinic site must obtain IRB approval for this 
protocol and submit IRB approval and supporting documentation to the CTSU Regulatory 
Office before they can enroll patients. Study centers can check the status of their 
registration packets by querying the Regulatory Support System (RSS) site registration 
status page of the CTSU member web site by entering credentials at https://www.ctsu.org. 
 
Requirements for site registration: 
• 
CTSU IRB Certification 
• 
CTSU IRB/Regulatory Approval Transmittal Sheet 
 
NOTE:  Sites participating on the NCI CIRB initiative and accepting IRB approval for the 
study are not required to submit separate IRB approval documentation to the CTSU 
Regulatory Office for initial, continuing or amendment review.  This information will be 
provided to the CTSU Regulatory Office from the CIRB at the time the site’s Signatory 
Institution accepts the CIRB approval.  The Signatory site may be contacted by the CTSU 
Regulatory Office or asked to complete information verifying the participating institutions 
on the study.  Other site registration requirements (i.e., laboratory certifications, protocol-
specific training certifications, or modality credentialing) must be submitted to the CTSU 
Regulatory Office or compliance communicated per protocol instructions. 
 
13.3 
OPEN Registration Requirements 
 
The individual registering the patient must have completed the appropriate SWOG 
Registration Worksheet for each Registration Step.  The completed form must be referred 
to during the registration but should not be submitted as part of the patient data. 
 
The individual registering the patient must have completed the appropriate SWOG 
Registration Worksheet for each Registration Step.  The completed form must be referred 
to during the registration but should not be submitted as part of the patient data. 
 
OPEN will also ask additional questions that are not present on the SWOG Registration 
Worksheet.  For the Step 1 Registration, the individual registering the patient must be 
prepared to provide answers to the following questions: 
 
a. 
Institution CTEP ID 
 
b. 
Protocol Number 
 
c. 
Registration Step 
 
d. 
Treating Investigator 
 
e. 
Cooperative Group Credit  
 
f. 
Credit Investigator 
 
g. 
Patient Initials 
 
h. 
Patient’s Date of Birth 
 
i. 
Patient SSN (SSN is desired, but optional.  Do not enter invalid numbers.) 
 
j. 
Country of Residence 
 
k. 
ZIP Code 
 

S1007 
Page 39 
Version Date 12/10/2021 
 
 
 
 
 
l. 
Gender (select one): 
• 
Female Gender 
• 
Male Gender 
 
m. 
Ethnicity (select one): 
• 
Hispanic or Latino 
• 
Not Hispanic or Latino 
• 
Unknown 
 
n. 
Method of Payment (select one): 
• 
Private Insurance 
• 
Medicare 
• 
Medicare and Private Insurance 
• 
Medicaid 
• 
Medicaid and Medicare 
• 
Military or Veterans Sponsored NOS 
• 
Military Sponsored (Including Champus & Tricare) 
• 
Veterans Sponsored 
• 
Self Pay (No Insurance) 
• 
No Means of Payment (No Insurance) 
• 
Other 
• 
Unknown 
 
o. 
Race (select all that apply): 
• 
American Indian or Alaska Native 
• 
Asian 
• 
Black or African American 
• 
Native Hawaiian or other Pacific Islander 
• 
White 
• 
Unknown 
 
13.4 
Registration Procedures 
 
a. 
All site staff (SWOG and CTSU Sites) will use OPEN to enroll patients to this 
study.  OPEN is a web-based application that is integrated with the CTSU 
Enterprise System for regulatory and roster data and can be accessed at 
https://open.ctsu.org or from the OPEN tab on the CTSU members’ side of the 
website at https://www.ctsu.org, or from the OPEN Patient Registration link on the 
SWOG CRA Workbench. 
 
b. 
Prior to accessing OPEN site staff should verify the following: 
 
• 
All eligibility criteria have been met within the protocol stated timeframes (or 
each Registration Step) and the affirmation of eligibility on the Registration 
Worksheet has been signed by the registering investigator or another 
investigator designate. Site staff should refer to Section 5.0 to verify eligibility. 
 
• 
All patients have signed an appropriate consent form for each Registration 
Step and HIPAA authorization form (if applicable).  
 
• 
The study site is listed as "approved" in the CTSU RSS. 
 

S1007 
Page 40 
Version Date 12/10/2021 
 
 
 
 
 
c. 
Access requirements for OPEN: 
 
• 
Site staff will need to be registered with CTEP and have a valid and active 
CTEP-IAM account. This is the same account (user ID and password) used 
for the CTSU members' web site. Additional information about obtaining a 
CTEP-IAM account can be found at  
http://ctep.cancer.gov/branches/pmb/associate_registration.htm. 
Questions 
should be directed to the CTEP Associate Registration Help Desk by e-mail at 
ctepreghelp@ctep.nci.nih.gov. 
 
• 
To perform registrations, the site user must have been assigned the 'Registrar' 
role on the SWOG or CTSU roster:  
 
1. 
If you are a SWOG member, to perform registrations on SWOG protocols 
you must have an equivalent 'Registrar' role on the SWOG roster.  Role 
assignments are handled through SWOG.  
2. 
If you are not a SWOG member, to perform registrations on SWOG 
protocols you must have the role of Registrar on the CTSU roster. Site 
and/or Data Administrators can manage CTSU roster roles via the new 
Site Roles maintenance feature under RSS on the CTSU members' web 
site. This will allow them to assign staff the "Registrar" role.  
 
Note:  The OPEN system will provide the site with a printable confirmation of 
registration and treatment information.   Please print this confirmation for your 
records.  
 
d. 
Further instructional information is provided on the OPEN tab of the CTSU 
members’ 
side 
of 
the 
CTSU 
website 
at 
https://www.ctsu.org 
or 
at 
https://open.ctsu.org.  For any additional questions contact the CTSU Help Desk 
at 1-888-823-5923 or ctsucontact@westat.com. 
 
13.5 
Exceptions to SWOG registration policies will not be permitted. 
 
a. 
Patients must meet all eligibility requirements. 
 
b. 
Institutions must be identified as approved for registration. 
 
c. 
Registrations may not be cancelled. 
 
d. 
Late registrations (after initiation of treatment) will not be accepted. 
 
14.0 
DATA SUBMISSION SCHEDULE 
 
14.1 
Data Submission Requirement 
 
Data must be submitted according to the protocol requirements for ALL patients registered, 
whether or not assigned treatment is administered, including patients deemed to be 
ineligible.  Patients for whom documentation is inadequate to determine eligibility will 
generally be deemed ineligible. 
 
14.2 
Master Forms 
 
Master forms can be found on the protocol abstract page of the SWOG website 
(www.swog.org) and (with the exception of the sample consent form and the Registration 
Worksheet) must be submitted on-line via the Web; see Section 14.3a for details.  
Exceptions to online data submission are source documents (e.g. pathology/operative/lab 
reports). 

S1007 
Page 41 
Version Date 12/10/2021 
 
 
 
 
 
14.3 
Data Submission Procedures 
 
a. 
SWOG institutions must submit data electronically via the Web by using the SWOG 
CRA Workbench.  To access the CRA Workbench, go to the SWOG Web site 
(http://swog.org) and logon to the Members Area.  After you have logged on, click 
on the CRA Workbench link to access the home page for CRA Workbench website.  
Next, click on the Data Submission link and follow the instructions.  For new users, 
the link to a "Starter Kit" of help files may be found by clicking on the Starter Kit 
link at the Members’ logon page. 
 
To submit data via the web the following must be done (in order): 
1. 
You are entered into the SWOG Roster and issued a SWOG Roster ID 
Number, 
2. 
You are associated as an investigator or CRA/RN at the institution where 
the patient is being treated or followed, and 
3. 
Your Web User Administrator has added you as a web user and has given 
you the appropriate system permissions to submit data for that institution. 
 
For assistance with points 1 and 2 call the Operations Office at 210/614-8808.  For 
point 3, contact your local Web User Administrator (refer to the "Who is my Web 
User Administrator?" function on the swog.org Members logon page).  For other 
difficulties with the CRA Workbench, please email technicalquestion@crab.org.  
 
b. 
If you need to submit data that are not available for online data submission, the 
only alternative is via facsimile.  Should the need for this occur, institutions may 
submit data via facsimile to 800/892-4007 or 206/342-1680 locally.  Please do not 
use cover sheet for faxed data.  Please make sure that each page of all faxed data 
includes the SWOG patient number, study ID and patient initials.  
 
c. 
Data Submission Instructions for non-SWOG institutions (CTSU): 
See the CTSU participation table on Page 5. 
 
14.4 
Data Submission Overview and Timepoints  
 
a. 
WITHIN 7 DAYS AFTER INITIAL REGISTRATION (STEP 1): 
 
Submit a copy of the following: 
 
S1007 Prestudy Form  
 
All pre-registration breast cancer pathology reports. 
 
b. 
(For all patients who have not yet undergone Oncotype DX® screening) WITHIN 
7 DAYS AFTER INITIAL REGISTRATION (STEP 1): 
 
Submit specimens for the Oncotype DX® test directly to Genomic Health as 
outlined in Sections 15.1a and 15.2. 
 
c. 
(For all patients who do not continue on the randomized study and do not register 
to Step 2) WITHIN 14 DAYS AFTER DECISION NOT TO CONTINUE ON THE 
RANDOMIZED STUDY: 
 
Submit the S1007 Off Protocol Notice – Step 1. 
 
d. 
AFTER RANDOMIZATION (STEP 2), BUT PRIOR TO START OF TREATMENT: 
 
Submit blood specimens as outlined in Section 15.2b. 

S1007 
Page 42 
Version Date 12/10/2021 
 
 
 
 
 
e. 
WITHIN 7 DAYS AFTER RANDOMIZATION (STEP 2): 
 
Submit the S1007 Prestudy Form – Randomized Study. 
 
f. 
WITHIN 14 DAYS AFTER RANDOMIZATION (STEP 2) 
 
Submit tissue specimen as outlined in Section 15.2a. 
 
g. 
(For the subset of patients at U.S. INSTITUTIONS participating in the Quality of 
Life 
and 
Economic 
Analysis 
substudy) 
WITHIN 
7 
DAYS 
AFTER 
RANDOMIZATION, AT 6 MONTHS, 12 MONTHS, AND 3 YEARS AFTER 
RANDOMIZATION: 
 
Submit a copy of the following: 
 
S1007 Cover Sheet for Patient Completed Questionnaires  
 
S1007 Health-Related Quality of Life Questionnaire: Randomized Study Form. 
 
h. 
EVERY SIX MONTHS FOR THREE YEARS, AND THEN AT 4 YEARS AND 5 
YEARS AFTER RANDOMIZATION: 
 
Submit the S1007 Treatment Form  
 
i. 
AT 6 MONTHS, 12 MONTHS, 2 YEARS AND 3 YEARS AFTER 
RANDOMIZATION (if on treatment): 
 
Submit the S1007 Adverse Event Summary Form  
 
j. 
For patients who receive chemotherapy, regardless of assigned treatment arm,  
AT ONE YEAR AFTER RANDOMIZATION: 
 
Submit the S1007 Chemotherapy Form. 
 
k. 
AT ONE YEAR AFTER RANDOMIZATION: 
 
Submit the S1007 Radiation Therapy Form. 
 
l. 
WITHIN 28 DAYS AFTER STEP 3 REGISTRATION:  
 
Submit specimens as outlined in Sections 15.3 and 15.4. 
 
m. 
WITHIN 2-3 YEARS AFTER STEP 3 REGISTRATION (IF PRIOR TO INVASIVE 
RECURRENCE):  
 
Submit specimens as outlined in Sections 15.3 and 15.4. 
 
n. 
AT FIVE YEARS AFTER RANDOMIZATION (IF PRIOR TO INVASIVE 
RECURRENCE/PROGRESSION/RELAPSE): 
 
Submit the following: 
 
Final S1007 Treatment Form for current reporting period 
 
Submit the S1007 Follow Up Form 
 
Off Treatment Notice  

S1007 
Page 43 
Version Date 12/10/2021 
 
 
 
 
 
o. 
WITHIN 14 DAYS OF INVASIVE RECURRENCE/PROGRESSION/RELAPSE: 
 
Submit the following: 
 
• 
S1007 Follow Up Form documenting date, site, and method for 
determining invasive recurrence/progression/relapse. 
 
• 
If the patient was still on protocol treatment, final S1007 Treatment Form 
for current reporting period. 
 
• 
If patient was still on protocol treatment and if during the first three years 
(36 months) after randomization, final S1007 Adverse Events Summary 
Form. 
 
• 
Off Treatment Notice, if during the first five years after randomization. 
 
• 
If patient was registered to Step 3, submit specimens as outlined in 
Sections 15.3 and 15.4. 
 
p. 
AFTER OFF TREATMENT (STEP 2) – EVERY 6 MONTHS UNTIL YEAR 5, AND 
THEN ANNUALLY UNTIL YEAR 15 OR UNTIL DEATH, WHICHEVER COMES 
FIRST: 
 
Submit the S1007 Follow Up Form. 
 
 
 
Note: Follow-up data submission will be entered under Step 2 registration for all 
patients whether or not they register to Step 3 for TM substudy participation.  
 
q. 
WITHIN 4 WEEKS OF KNOWLEDGE OF SECOND MALIGNANCY (2nd Primary): 
 
Submit the S1007 Follow Up Form documenting date, site, and method of 
determining malignancy. 
 
r. 
WITHIN 4 WEEKS OF KNOWLEDGE OF DEATH: 
 
Submit the Notice of Death documenting death information. 
 
15.0 
SPECIAL INSTRUCTIONS 
 
15.1 
Oncotype DX® Testing Requirements 
 
a. 
For patients who have not had the Oncotype DX® Breast Cancer Assay performed 
at the time of Step 1 Registration, submission of materials for the Oncotype DX® 
Breast Cancer Assay is required.  Collection and submission instructions are 
outlined in Section 15.1b. 
 
b. 
The clinical investigator and the submitting pathologist have the responsibility for 
submitting materials for the purposes of genomic profiling.  Request kits and 
submit materials as outlined on the Oncotype DX® web site for "Submitting a 
Sample" 
under 
the 
"Healthcare 
Professionals" 
menu 
located 
at 
http://www.oncotypedx.com/en-
US/Breast/HealthcareProfessional/submittingsample.aspx.  
 
NOTE:  A sample Oncotype DX® requisition form with instructions for completion 
is available at www.swog.org on the S1007 abstract page. Sites that submit the 
Oncotype DX® sample via the Genomics Health website must enter "S1007" in the 
"Study Name" field.   

S1007 
Page 44 
Version Date 12/10/2021 
 
 
 
 
 
 
Sites that do not submit samples via the Genomics Health website must complete 
the Oncotype DX® Submission Form [available on the S1007 abstract page at 
www.swog.org] with the Oncotype DX® Requisition Form.  Both of these forms 
should accompany the sample to Genomic Health. 
 
15.2 
Correlative Studies and Banking 
 
a. 
Submission of tissue (for prognostic and predictive indices of breast cancer 
outcomes) is required, will be collected prior to starting treatment and will be 
shipped within 14 days after Step 2 Registration to the SWOG Biospecimen Bank 
– Solid Tissue, Myeloma, and Lymphoma Division, Lab #201. 
 
• 
Paraffin block, punch biopsy or 20 unstained slides from the primary tumor 
• 
Positive lymph node block, punch biopsy or 20 unstained slides 
• 
Negative lymph node block, punch biopsy or 20 unstained slides 
 
NOTE:  Each type of tissue should be submitted, but the patient will not be made 
ineligible if the tissue is not available.  Documentation of why incomplete 
submission took place must be noted in the patient's medical record. 
 
Specimen collection kits are not being provided for this submission; sites will use 
institutional supplies. 
 
Any leftover tissue not consumed by testing will be banked for future use according 
to the patient's selections on the "Consent Form for Use of Specimens for 
Research". 
 
b. 
Submission of blood (for pharmacogenomic studies) is required. Blood will be 
collected prior to starting treatment and will be shipped within 24 hours of collection 
to the SWOG Biospecimen Bank – Solid Tissue, Myeloma, and Lymphoma 
Division, Lab #201. 
 
• 
7.5 mL whole blood collected in lavender top, EDTA, Vacutainer® tube  
• 
10 mL whole blood collected in red-top or serum separator tube (SST), 
Vacutainer® tube 
 
Specimen collection kits are not being provided for this submission; sites will use 
institutional supplies. 
 
Any blood specimens that remain after testing is performed will be banked for 
future use according to the patient's selections on the "Consent Form for Use of 
Specimens for Research". 
 
c. 
Specimen collection and submission instructions 
 
All specimen submissions for this study must be entered and tracked using the 
SWOG online Specimen Tracking System. Complete specimen collection and 
submission instructions can be accessed on the SWOG Specimen Submission 
webpage (https://www.swog.org/member-resources/biospecimen-resources).  If 
collection/submission instructions differ from those in the protocol, the protocol 
instructions should be followed; otherwise, the website instructions should be 
followed. 
 
 

S1007 
Page 45 
Version Date 12/10/2021 
 
 
 
 
 
 
15.3 
Specimens for Circulating Biomarker Assessment for Late Relapse Translational Medicine 
(CBALR TM) Substudy (REQUIRED IF PATIENT CONSENTS): 
 
At time of distribution of Revision #16 (Version Date 03/24/21), all U.S. patients who: 
a) are disease free, with no prior invasive recurrence AND 
b) have been on protocol for up to 8 years after time of randomization to S1007 (Step 2 
registration) must be offered participation in the Circulation Biomarker Assessment for 
Late Relapse Translational Medicine (CBALR TM) substudy, as indicated in Section 
5.3.   
 
SUBMISSION SUMMARY TABLE: 
CBALR Visit #1: 
Within 28 days after  
patient registration to 
Step 3 
CBALR Visit #2:  
2-3 years  
after patient 
registration to Step 3  
CBALR Visit #3:  
At time of Invasive 
Recurrence 
Metastatic 
Tissue 
(if applicable 
and where 
available) 
FFPE block or  
20 unstained slides 
Ship to SWOG 
Biospecimen Bank 
(Lab #201) 
10 mL whole 
blood  a 
One 10 mL SST: Ship to 
SWOG Biospecimen 
Bank (Lab #201) b 
One 10 mL SST: Ship to 
SWOG Biospecimen 
Bank (Lab #201) b  
One 10 mL SST: Ship to 
SWOG Biospecimen 
Bank (Lab #201)  b  
20 mL whole 
blood a 
Two 10 mL CellSave® 
tubes: b  Ship to 
Menarini Silicon 
Biosystems Lab # 122 
Two 10 mL CellSave® 
tubes: b  Ship to 
Menarini Silicon 
Biosystems Lab # 122 
Two 10 mL CellSave® 
tubes: b  Ship to 
Menarini Silicon 
Biosystems Lab # 122 
40 mL whole 
blood a 
Four 10 mL Streck 
cfDNA tubes: 
• First 2 Streck cfDNA 
tubes collected (if 
both are collected at 
first draw attempt) b, c:  
Ship to Epic 
Sciences Lab #236  
• 2 Streck cfDNA 
tubes:  Ship to 
SWOG Biospecimen 
Bank (Lab #201) 
Four 10 mL Streck 
cfDNA tubes: 
• First 2 Streck cfDNA 
tubes collected (if both 
are collected at first 
draw attempt): b, c  
Ship to Epic Sciences 
Lab #236  
• 2 Streck cfDNA 
tubes: Ship to SWOG 
Biospecimen Bank 
(Lab #201) 
Four 10 mL Streck 
cfDNA tubes: 
• First 2 Streck cfDNA 
tubes collected (if both 
are collected at first 
draw attempt): b, c  
Ship to Epic Sciences 
Lab #236  
• 2 Streck cfDNA 
tubes: Ship to SWOG 
Biospecimen Bank 
(Lab #201) 
a  
Important: See Section 15.3c.1: Order of Sample Collection. SST should be collected under 
fasting conditions. 
b 
If the minimum blood volume for one 10 mL SST, two 10 mL CellSave® tubes, and at least two 
10 mL Streck cfDNA tubes (being shipped to Epic Sciences) cannot be collected during a visit, 
a subsequent second attempt should be scheduled for another time to collect the rest of the 
samples. The subsequent draw time can be scheduled for later the same day (if appropriate and 
site has collection tubes on hand) or for another date. See Section 15.3c.1. Due to funding 
restrictions and tube expiration dates, the SWOG Biospecimen Bank will only ship sufficient 
tubes for a single collection timepoint.  If the first draw attempt fails and the site does not have 
tubes on hand, then the site will need to: 1) reschedule the patient for a subsequent blood draw, 
allowing 5-7 days for collection kit shipment, and 2) re-order tubes for that patient. Both 
CellSave® tubes must be collected on the same day. See Sections 15.3c.3c and 15.3c.4b for 
more information.   
c 
If the second attempt at blood draw is unsuccessful in obtaining the minimum blood volume for 
two 10 mL CellSave® tubes, the patient will be deemed not evaluable for the CBALR TM 
substudy.  If the patient is deemed not evaluable for the CBALR TM substudy, do not submit any 
subsequent blood (SST, CellSave, or Streck) or tissue samples for the CBALR TM substudy. 
 

S1007 
Page 46 
Version Date 12/10/2021 
 
 
 
 
 
a. 
With the patient’s consent, the following blood, and tissue samples must be drawn 
and submitted at the following 2-3 time points:   
 
1. 
CBALR Visit # 1: Within 28 days after patient registration to Step 3: 
 
a. 
10 mL whole blood collected in one 10 mL (red top) SST, 
Vacutainer;  
 
b. 
20 mL whole blood collected in two 10 mL Cellsave® tubes; 
 
c. 
40 mL whole blood collected in four 10 mL Streck tubes. 
 
2. 
CBALR Visit #2: If no invasive recurrence at time of 2-3 years after 
patient registration to Step 3, then draw: 
 
a. 
10 mL whole blood collected in one 10 mL (red top) SST, 
Vacutainer;  
 
b. 
20 mL whole blood collected in two 10 mL Cellsave® tubes; 
 
c. 
40 mL whole blood collected in four 10 mL Streck tubes. 
 
Note: Samples should be collected at the regular patient visit 2 years after 
registration to Step 3, however they may be collected and submitted at 
any time between 2 and 3 years from registration if not drawn at the 2-year 
visit. If invasive recurrence occurs prior to the collection of the 2-year 
timepoint, the 2-year timepoint specimens are no longer required.   
 
3. 
CBALR Visit #3: At time of invasive recurrence (if applicable): 
 
a. 
FFPE tissue block, punch biopsy, or 20 unstained slides from 
metastatic site at invasive recurrence (where tissue from the 
standard of care biopsy is available); 
 
b. 
10 mL whole blood collected in one 10 mL (red top) SST, 
Vacutainer; 
 
c. 
20 mL whole blood collected in two 10 mL Cellsave® tubes; 
 
d. 
40 mL whole blood collected in four 10 mL Streck tubes. 
 
 

S1007 
Page 47 
Version Date 12/10/2021 
 
 
 
 
 
b. 
Sample Collection Kits 
 
Specimen collection kits (Streck cfDNA and CellSave tubes) must be ordered 
IMMEDIATELY after patient registration to Step 3 and prior to each collection 
timepoint.  Sites should allow 5-7 days to receive kits.  Note: Patient samples 
must be drawn within 28 days after patient registration to Step 3.  Please note 
that two separate collection kits are provided, and both must be ordered to 
obtain the blood collection tubes needed for submissions to all three labs.   
 
Streck cfDNA and CellSave® kits may be ordered by using the SWOG 
Biospecimen Bank Kit Management Application at: https://kits.bpc-apps.nchri.org.  
 
The Streck cfDNA Collection Kit provides the following for a single collection 
timepoint: 
• 
Two Streck cfDNA tubes for the collection and shipment of blood to the 
SWOG Biospeicmen Bank and includes an ambient gel pak, insulated 
shipper and packaging supplies.  
• 
A shipping label (e.g. Exempt Human Specimen) is provided in Kit 
Management for the shipment of Streck cfDNA tubes to the SWOG 
Biorepository. 
 
The Streck cfDNA and CellSave Collection Kit provides the following for a single 
collection timepoint: 
• 
Two Streck cfDNA tubes and an ambient pak for blood submitted to Epic 
Sciences Lab. 
• 
Two CellSave tubes plus an ambient pak for blood submitted to Menarini 
Silcon Biosystems.  
• 
Shipping supplies are not provided and sites must use their own shipping 
accounts for the cost of shipments to Epic and Menarini. 
 
Supplies (kits) are not being provided for tissue and SST sample collection.  Sites 
will use institutional supplies to collect and ship tissue and whole blood in SSTs. 
 
 

S1007 
Page 48 
Version Date 12/10/2021 
 
 
 
 
 
c. 
Sample Collection and Submission Instructions 
 
All sample submissions for this study must be entered and tracked using the 
SWOG online Specimen Tracking System. Complete sample collection and 
submission instructions can be accessed on the SWOG Specimen Submission 
webpage (https://www.swog.org/member-resources/biospecimen-resources).  If 
collection/submission instructions differ from those in the protocol, the protocol 
instructions should be followed; otherwise, the website instructions should be 
followed. 
 
1. 
Order of Sample Collection: 
 
Substudy samples must be collected in the following order.  If samples 
are not collected in the following order, then one (or more) of the 
samples may need to be discarded. 
 
First scheduled draw for each annual visit: 
 
Under fasting conditions:  
 
• 
First, collect: Whole blood in a Red-Top, SST, Vacutainer tube 
 
• 
Then, collect: Two 10-mL CellSave® tubes.  
 
NOTE: The 10 mL red-top tube must be obtained prior to filling 
the CellSave® tube using the same needle stick. This decreases 
the chance of contamination of the CTC sample with skin epithelial 
cells, which may occur when the needle enters the skin. 
 
Only the SST should be collected under fasting conditions. After 
collection of the SST, patients may eat or drink something. 
 
• 
Then, collect: Four 10-mL Streck cfDNA tubes. 
 
If the first scheduled draw of the two 10 mL CellSave® tubes was NOT 
successful: 
 
If the SST was collected at the first scheduled draw, and then the minimum 
blood volume for two 10 mL CellSave® tubes was not  subsequently 
collected at the same time (after the SST was collected), then for the 
subsequent attempt to draw one or both CellSave® sample(s), collect 
samples in the following order: 
 
• 
First, collect: One 10-mL Streck tube (prior to filling the CellSave® 
tube using the same needle stick). If this happens, this first Streck 
cfDNA tube sample will be shipped to the SWOG Biospecimen 
Bank (unless site is only able to collect two Streck cfDNA samples, 
in which case both Streck cfDNA samples would be shipped to 
Epic Sciences).  
 
• 
Then, collect: The remaining (one or two) 10-mL CellSave® 
tube(s). NOTE: While CellSave® tubes can be collected at 
different times throughout the day, both CellSave® tubes must be 
collected on the same day. 
 

S1007 
Page 49 
Version Date 12/10/2021 
 
 
 
 
 
• 
Then, collect: three 10-mL Streck tubes. The last 10-mL Streck 
cfDNA tube collected will also be shipped to the SWOG 
Biospecimen Bank. 
 
If there is a deviation from protocol order of collection, contact the study 
chair for guidance on which samples should still be submitted and 
document the order of collection in the “comments” section of the 
Specimen Tracking System. 
 
2. 
Whole blood (submitted to the SWOG Biospecimen Bank – Solid Tissue, 
Myeloma and Lymphoma Division, Lab #201):  
 
a.  
Seat the participant for at least five minutes prior to blood 
collection. 
 
b. 
The SST sample should be collected under fasting conditions. 
 
c. 
Collect in a 10 mL (red-top) SST, Vacutainer tube and label as 
indicated in Section 15.4. 
 
NOTES TO AVOID HEMOLYSIS (59,60,61) 
 
Do not use small-bore needles.  
Do NOT mix. Invert filled tubes gently. 
Do not keep tourniquet on too long. 
Allow the cleaned venipuncture site to dry completely before skin 
puncture.  
Do not expose to extreme heat or cold. 
 
d. 
In the event that 10 mL whole blood volume in (red-top) SST 
cannot be collected, a subsequent second attempt at 
collection should be scheduled for another time. (Note: the 
subsequent draw time can be scheduled for later the same day, if 
deemed appropriate or can be rescheduled for another date.) 
 
e. 
Place the tube in a rack at room temperature for at least one hour 
and not more than two hours. 
 
f. 
See Section 15.4 for Specimen Labelling and Shipping 
Instructions. Blood in SST tubes may be shipped with the Streck 
cfDNA tubes to the SWOG Biospecimen Bank. Samples should 
be shipped the same day as collection or if not possible, then 
sample should be shipped on the next working day to the SWOG 
Biospecimen Bank (Lab #201). 
 
g. 
Specimen collection supplies are not being provided for whole 
blood in SST samples; sites will use institutional SST, Vacutainer 
supply.  
h. 
If the patient is subsequently deemed not evaluable for the 
CBALR TM substudy, do not submit any subsequent blood 
samples for the CBALR TM substudy. 
 
 

S1007 
Page 50 
Version Date 12/10/2021 
 
 
 
 
 
3. 
CellSave® Tubes (Two Cellsave® tubes at each time point, ship directly 
to Menarini Silicon Biosystems – Lab #122 for CellSearch CTC testing) 
 
a. 
Required materials for blood collection:  
i. 
Two (2), 10 mL purple/yellow top CellSave® blood 
collection tubes,  
ii. 
Vacutainer brand adapter, and  
iii. 
Needles.  
 
b. 
See Section 15.3b for CellSave® tube collection kit ordering 
instructions. The kit does not include an adapter or needles. 
 
c. 
Collection Instructions:  
 
i. 
See Section 15.3c.1: Order of Sample Collection.  
 
Note: To prevent contamination of the CellSave® tube 
samples with epithelial cells, another tube must be collected 
prior to collection of the CellSave®  tubes, so that the 
CellSave®  tubes may be drawn from the same needle stick 
as the prior sample (either the SST at first draw attempt or 
a Streck cfDNA tube if a second attempt at drawing the 
CellSave® tube) . 
 
ii. 
Use the same needle stick as the prior tube drawn to 
collect the CellSave® sample. This decreases the chance 
of contamination of the CellSave® sample with skin 
epithelial cells, which may occur when the needle enters the 
skin. 
 
iii. 
For each patient, perform a venous puncture using a 
Vacutainer brand adapter and needle and fill each of the 
blood collection tubes (minimum blood volume of 9 mL 
for each tube). Alternatively, blood samples may be 
obtained from a port or other central venous catheter using 
appropriate access needles and techniques. Invert each 
tube a minimum of eight (8) times to ensure proper mixing 
of the additives contained in each tube.  
 
iv. 
Important Note: Both (two) 10 mL CellSave® tubes are 
required for analysis. In the event that the 18 mL minimum 
blood volume (9 mL in each) in the two 10 mL tubes 
CellSave® tubes cannot be collected, a subsequent 
second attempt at collection should be scheduled for 
another time.  
 
While CellSave® tubes can be collected at different times 
throughout the day, both CellSave® tubes must be collected 
on the same day. See Section 15.3c.1. Do not submit either 
a single CellSave® tube or two CellSave® tubes that were 
collected on different days to Menarini Silicon Biosystems 
Labs.  
 

S1007 
Page 51 
Version Date 12/10/2021 
 
 
 
 
 
Note: The subsequent draw time can be scheduled for later 
the same day, if deemed appropriate and site has additional 
collection tubes on hand, or can be rescheduled for another 
date. Due to funding restrictions and tube expiration dates, 
the SWOG Biospecimen Bank will only ship sufficient tubes 
for a single collection timepoint for each patient registered 
to Step 3.  If the first draw attempt fails, and the site does 
not have tubes on hand, then the site will need to: 1) 
reschedule the patient for another day, allowing 5-7 days for 
collection kit shipment, and 2) re-order tubes for the second 
draw attempt  
 
v. 
If at time of second attempt at blood draw, the blood 
draw is unsuccessful in obtaining the minimum 18 mL blood 
volume (9 mL in each) in the two 10 mL CellSave® tubes, 
then the patient will be deemed not evaluable for the 
CBALR TM substudy.  If this occurs and the patient is 
deemed not evaluable for the CBALR TM substudy, do not 
submit any subsequent blood or tissue samples for the 
CBALR TM substudy. 
 
vi. 
The filled CellSave® tubes must be maintained at 
ambient (15–30°C) temperature, avoiding extremes of 
heat and cold, at all times. 
 
vii. 
Label the CellSave® tubes with:  
• 
Number 1 and Number 2 (respectively, in order of 
collection).  Record the lot number and expiration date 
for each corresponding tube in the Specimen Tracking 
System.  
• 
SWOG patient number (patient ID) 
• 
Patient initials 
• 
Substudy visit number (time point) [Visit number = one, 
two, or three; i.e. one=initial blood draw on substudy, 
two= next blood draw 2-3 years later, three=invasive 
recurrence]. 
• 
Collection date and time (date and time the specimen 
was collected from the patient) 
• 
Initials of the phlebotomist  
• 
Specimen type (i.e., whole blood) 
 
 

S1007 
Page 52 
Version Date 12/10/2021 
 
 
 
 
 
 
viii. 
The following information must be entered into the SWOG 
Specimen Tracking System prior to shipment:  
• 
Site identification number;  
• 
SWOG patient number (same number as written on the 
filled blood tubes);  
• 
Site comments (i.e. phlebotomy problems; and any 
additional comments);  
• 
Collection date and time of blood draw (if all blood 
samples were not drawn at the same time; specify time 
of draw of each sample);  
• 
Order of blood sample collection (SST, CellSave® 
tubes, Streck cfDNA tubes). For CellSave® tubes, 
record the order of collection of (Number 1 or Number 
2) as well as the lot number and expiration date for each 
corresponding CellSave® tube in the Specimen 
Tracking System; 
• 
Lot number and expiration date of each corresponding 
CellSave® tube (Number 1 and Number 2).  
 
d. 
Packaging and Shipping Instructions: Ship directly to Menarini 
Silicon Biosystems (Lab #122) 
 
i. 
Cellsave® tubes must be shipped ambient (with an ambient 
gel pack) the same day as collected, via overnight delivery 
to: Menarini Silicon Biosystems (Lab # 122). If possible, 
collect and ship samples Monday-Thursday. Packages 
shipped on a Friday, must be sent via Fed-Ex Saturday 
Delivery, with no signature required. Do not collect 
samples the day prior to a holiday. 
 
ii. 
Wrap the CellSave® tubes in the shipping blanket. This 
gives added thermal protection during shipment. Place 
ambient gel packs in the box to stabilize the 
temperature at 15-30ºC. Place the Styrofoam lid, and seal 
the Styrofoam box. 
 
iii. 
All shipments must include a requisition form (Packing 
list) generated by the SWOG Specimen Tracking 
System. See Section 15.4c. Place the completed Packing 
List generated from the SWOG Specimen Tracking System 
into the shipper box. 
 
e. 
Questions pertaining to Cellsave® collection or shipping should 
be directed to: 
 
Menarini Silicon Biosystems Labs (Lab #122) 
msb-labservicesus@siliconbiosystems.com   
Phone: 215/346-8499 
Fax: 215/560-3730 
Customer Service Hours of Operation: M-F, 8:00am - 5:00pm ET 

S1007 
Page 53 
Version Date 12/10/2021 
 
 
 
 
 
4. 
Streck Cell-Free DNA Collection Tubes (2 Streck cfDNA Tubes will be 
submitted to the SWOG Biospecimen Bank – Solid Tissue, Myeloma and 
Lymphoma Division, Lab #201 and 2 Streck cfDNA Tubes will be 
submitted to Epic Sciences (Lab #236)):  
 
a. 
Prior to Collection 
 
• 
Patients are not required to fast prior to Streck cfDNA blood 
draw. Patients may eat or drink something prior to blood draw 
into Streck cfDNA tubes. 
• 
See Section 15.3b for ordering instructions for Streck cfDNA 
tube collection kits. 
• 
Confirm blood tubes are not expired. Expired tubes should not 
be used for blood collection.  
• 
Schedule courier for same-day sample pick-up prior to 
collection.  
 
b. 
Instructions for handling Streck cfDNA tubes: 
 
Prevention of Backflow: Since Streck Cell-Free DNA BCT tubes 
contain chemical additives, it is important to avoid possible 
backflow from the tube. To guard against backflow, observe the 
following precautions:  
 
• 
Keep patient’s arm in the downward position during the 
collection procedure.  
• 
Hold the tube with the stopper uppermost.  
• 
Release tourniquet once the blood starts to flow into the tube, 
or within 2 minutes of application.  
• 
Tube contents should not touch stopper or the end of the 
needle during the collection procedure.  
 
c. 
Additional Blood Collection Instructions: 
• 
Draw whole blood samples into four (4), 10 mL Streck Cell-
Free DNA BCT tubes. Fill tube until blood flow stops.  
• 
IMPORTANT NOTE: Fill each tube completely (10 mL), when 
possible.  
• 
For the 2 tubes being shipped to the Epic Sciences (Lab # 
236), a minimum of 4 mL blood per tube is required (at least 
8 mL total volume collected in two 10 mL Streck tubes – 
subsequent to SST and CellSave® draws). In the event that 
8 mL blood volume cannot be collected, do not submit Streck 
cfDNA tube samples to Epic Sciences. (The SST and 
CellSave® Tubes must still be submitted as indicated in 
Sections 15.3c.2 and 15.3c.3.) For the two Streck Tube 
samples being sent to the Epic Sciences (Lab # 236), a 
subsequent second attempt at collection should be 
scheduled for another time. (Note: the subsequent draw 
time can be scheduled for later the same day, if deemed 
appropriate and site has tubes on hand, or can be 
rescheduled for another date.)    

S1007 
Page 54 
Version Date 12/10/2021 
 
 
 
 
 
• 
If the patient is subsequently deemed not evaluable for the 
CBALR TM substudy, do not submit any subsequent blood 
samples for the CBALR TM substudy. 
• 
Approximate volumes are illustrated below. Each red arrow 
indicates the level to which the blood collection tube should 
be filled to achieve the corresponding volume in red, yellow, 
or blue. As a reference, a volume of 6-mL would fill the Streck 
tube to just below the first “7” in the blood tube lot number 
“72750315” on the blood tube label. 
 
 
 
 
 
 
• 
Remove tube from adapter and immediately mix by gentle 
inversion 8 to 10 times. Tube inversion prevents clotting. 
Inadequate or delayed mixing may result in inaccurate test 
results.  
• 
After collection, blood in Streck cfDNA tubes should 
never be refrigerated or frozen, as this will compromise the 
specimen. Blood collected in Streck cfDNA tubes is stable at 
room temperature.  
 
d. 
Labelling and Shipping Instructions 
 
i. Two (2) Streck cfDNA tubes (preferably first and second 
Streck cfDNA tubes drawn – if first draw attempt is 
successful) will be shipped to Epic Sciences (Lab # 236) 
per the following instructions: 
 
a. Specimens must be shipped with an ambient pack 
(provided in the Streck tube kit). 
 
b. See Section 15.4 for Specimen Labelling Instructions and 
Section 15.4c for requirements for specimen entry, 
tracking, and generation of a Packing List via the SWOG 
Specimen Tracking System.  
 
c. All shipments must include requisition form (Packing list) 
generated by the SWOG Specimen Tracking System. 
Print a copy of the Packing List in the online SWOG 
Specimen Tracking System. Place the Packing List in the 
pocket of the specimen bag if it has one, or in a separate 
resealable bag.  
 
d. IMPORTANT NOTE: If a collection time is not provided, 
Epic Sciences will default to sample collection at 8:00 am 
(local time) on the date of collection. 
 

S1007 
Page 55 
Version Date 12/10/2021 
 
 
 
 
 
e. Do not place “Infectious Substance” sticker on shipper, as 
this can result in a delay of shipment. If possible, include 
a scanned copy of the completed sample requisition form.  
 
f. 
For questions pertaining to the two Streck cfDNA tubes 
being shipped to Epic Sciences Lab, contact:  
Lab #236:  Epic Sciences  
Email: partners@epicsciences.com / Attn: S1007 
Phone: 858/356-6610 
 
ii. Two (2) Streck cfDNA tubes will be shipped to the SWOG 
Biospecimen Bank (Lab #201).  
 
a. If blood in Streck cfDNA tube cannot be shipped the day 
of collection, then it must be kept at room temperature 
and shipped on the next working day to the SWOG 
Biospecimen Bank (Lab #201). Do not process.  
 
b. See Section 15.4 for Specimen Labelling and Shipping 
Instructions.  
 
c. For questions pertaining to the the two Streck cfDNA 
tubes being shipped to the SWOG Biospecimen Bank, 
contact: 
Lab #201:  SWOG Biospecimen Bank – Solid 
Tissue, Myeloma and Lymphoma Division, Lab #201 
Phone: 614/722-2865 
E-mail:  bpcbank@nationwidechildrens.org  
 
5. 
Metastatic Tumor tissue (SWOG Biospecimen Bank – Solid Tissue, 
Myeloma and Lymphoma Division, Lab #201) 
 
a. At time of invasive recurrence (where tissue is available), 
submit FFPE tissue block, punch biopsy, or 20 unstained slides 
from standard of care biopsy of metastatic site at invasive 
recurrence. 
 
b. See Section 15.4 for Specimen Labelling and Shipping 
Instructions. It is preferred that samples are shipped within 48 
hours of collection, where possible. Samples must be shipped 
within 28 days after collection. 
 
c. Specimen collection kits are not being provided for tissue 
submission; sites will use institutional supplies.   
 
d. 
NOTE: Correlative biomarker testing of specimens banked for planned future 
research (not otherwise specified in Sections 18.6, 18.7, or 18.8) will not occur until 
an amendment to this protocol (or separate correlative science protocol) is 
reviewed and approved in accordance with National Clinical Trials Network 
(NCTN) policies. 
 
 

S1007 
Page 56 
Version Date 12/10/2021 
 
 
 
 
 
15.4 
SPECIMEN LABELING AND SHIPPING  
a. 
Label blood tubes with the following: 
 
• 
SWOG patient number (patient ID) 
• 
Patient initials 
• 
Substudy visit number (time point) [Visit number = one, two, or three; i.e. 
one=within 28 days after patient registration to Step 3, two= 2-3 years after 
patient registration to Step  3, three=invasive recurrence]. 
• 
Collection date and time (date and time the specimen was collected from 
the patient) 
• 
Initials of the phlebotomist (Epic Sciences Streck cfDNA and Menarini 
Silicone Biosystems CellSave® blood tubes only) 
• 
Specimen type (i.e., whole blood) 
 
b. 
Include the following on FFPE tissue labels: 
 
• 
SWOG patient number 
• 
Patient initials 
• 
Collection date (date the specimen was collected from the patient) 
• 
The Surgical Pathology ID # (Accession#) and block number (e.g., A2, 3E, 
2-1, B, etc.) that corresponds with the pathology report  
 
Note: if submitting slides, then also include the thickness (in µm). 
 
c. 
SHIPPING SAMPLES 
 
1. 
SWOG Specimen Tracking System (STS) 
 
All specimen submissions for this study must be entered and tracked using 
the SWOG online Specimen Tracking System. SWOG members may log 
on the online system via the CRA Workbench. To access the CRA 
Workbench, go to the SWOG Web site (http://swog.org) Non- SWOG 
users may log into SpecTrack using their CTSU UserID and password on 
the SpecTrack login page located at  
https://spectrack.crab.org (select the option “SWOG – SWOG – CTSU”).  
SpecTrack start-up instructions (both written and demo) are available after 
signing in to SpecTrack.  
 
A copy of the Shipment Packing List produced by the online Specimen 
Tracking System should be printed and placed in the pocket of the 
specimen bag if it has one, or in a separate resealable bag. The Specimen 
Submission Form is NOT required when the online system is used. 
 
ALL SPECIMENS MUST BE LOGGED VIA THIS SYSTEM; THERE ARE 
NO EXCEPTIONS. 
 
To report technical problems with Specimen Tracking, such as database 
errors 
or 
connectivity 
issues, 
please 
send 
an 
email 
to 
technicalquestion@crab.org. For procedural help with logging and 
shipping specimens, there is an introduction to the system on the 
Specimen Tracking main page (https://spectrack.crab.org/Instructions); or 
contact the SWOG Statistics and Data Management Center at 206/652-
2267 to be routed to the Data Coordinator for further assistance. 
 
 
 

S1007 
Page 57 
Version Date 12/10/2021 
 
 
 
 
 
In the online Specimen Tracking System, the appropriate SWOG 
laboratory for submission of diagnostic tissue samples for SWOG 
Biospecimen Submission and Pathology review is identified for each 
specimen type and timepoint.  
 
For questions pertaining to the the SST, two Streck cfDNA tubes, or 
FFPE tissue being shipped to the SWOG Biospecimen Bank, contact: 
 
Lab #201:  
SWOG Biospecimen Bank – Solid Tissue, Myeloma and 
Lymphoma Division, Lab #201 
Phone: 614/722-2865 
E-mail:  bpcbank@nationwidechildrens.org  
For questions pertaining to the two Cellsave® tubes being shipped to 
Menarini Silicon Biosystems contact: 
 
Lab #122:  
Menarini Silicon Biosystems Labs (Lab #122) 
msb-labservicesus@siliconbiosystems.com   
Phone: 215/346-8499 
Fax: 215/560-3730 
Customer Service Hours of Operation: M-F, 8:00am - 
5:00pm ET 
 
For questions pertaining to the two Streck cfDNA tubes being shipped 
to Epic Sciences Lab contact: 
 
Lab #236:  
Epic Sciences  
Email: partners@epicsciences.com / Attn: S1007  
Phone: 858/356-6610 
 
2. 
Complete instructions for packaging and shipping specimens are located 
on the SWOG Specimen submission webpage  
(https://www.swog.org/clinical-trials/biospecimen-
resources/biospecimen-processing-and-submission-procedures). 
 
 
 

S1007 
Page 58 
Version Date 12/10/2021 
 
 
 
 
 
16.0 
ETHICAL AND REGULATORY CONSIDERATIONS 
 
The following must be observed to comply with Food and Drug Administration regulations for the 
conduct and monitoring of clinical investigations; they also represent sound research practice: 
 
Informed Consent 
 
The principles of informed consent are described by Federal Regulatory Guidelines (Federal 
Register Vol. 46, No. 17, January 27, 1981, part 50) and the Office for Protection from Research 
Risks Reports:  Protection of Human Subjects (Code of Federal Regulations 45 CFR 46).  They 
must be followed to comply with FDA regulations for the conduct and monitoring of clinical 
investigations. 
 
S1007 Remote Consent Procedures for the CBALR TM substudy: 
  
For U.S. sites utilizing a local IRB of record, the Study Chair has determined that the CBALR TM 
substudy presents no more than minimal risk to participants, and that an alteration of the informed 
consent process to allow for remote consent to be obtained in accordance with the following NCI 
CIRB requirements for remote consent would not adversely affect the rights and welfare of 
participants.  
 
Procedures that must be utilized for the S1007 Remote Consent Process for the CBALR TM 
substudy (for sites utilizing the NCI CIRB as the IRB of record) are as follow:  
 
a. 
The participant or their legally-authorized representative (LAR) must receive a copy of the 
NCI CIRB-approved informed consent document (e.g., via mail, fax or email) in advance 
of discussion regarding the study.  
• 
If mailed, two copies must be mailed so the participant or LAR is able to retain a copy 
for reference when their signed document is returned to the site and they are waiting 
to receive the final copy with all necessary signatures back from the site. 
 
b. 
The investigator or designee must discuss the study with the potential participant either via 
telephone or video conferencing.  
• 
The investigator/designee must have the same consent discussion via telephone/video 
conferencing that they would have had with the participant or LAR during an in-person 
meeting.  
• 
Important: The investigator/designee must also implement a method to ensure the 
identity of the participant or LAR (such as: verification of state identification or other 
identifying documents or use of personal questions or visual methods). 
 
c. 
A witness must be present during the telephone/videoconferencing consent process.  
• 
There are no restrictions on who can serve as a witness and the witness does not need 
to be impartial. The witness must be able to hear both sides of the conversation (e.g., 
speaker phone, conference line).  
• 
Requirements for social distancing may dictate that the witness is in a different location 
than both the potential participant and/or the investigator/designee obtaining consent. 
Any arrangement is acceptable if the witness can listen to both parties in the informed 
consent discussion.  
 
 

S1007 
Page 59 
Version Date 12/10/2021 
 
 
 
 
 
d. 
If the potential participant or LAR agrees to participation, they sign the consent form and 
return it to the investigator (e.g., via mail, fax or email). If postal mail is used, a pre-paid, 
self-addressed envelope should be provided to the participant or LAR to mail the signed 
consent form back to the investigator.   
 
e. 
Once the research team receives the signed informed consent document from the 
participant or LAR, the investigator/designee who conducted the consent process must 
sign and date the document using the current date.  
• 
Under the signature line, the investigator/designee must document whether consent 
was obtained over the telephone or video conferencing, the date of the telephone/video 
conference, and the date the signed consent was received. For example, “Discussed 
with [participant or LAR name] via [telephone or videoconferencing] on [insert date] 
and received signed consent form on [insert date].” Include a brief reason for 
performing the informed consent discussion over the telephone/videoconferencing. 
 
f. 
If the participating site has an informed consent policy that requires the witness to sign the 
consent document, the witness signs the informed consent. If the participating site does 
not have an informed consent policy that requires the signature of the witness on the 
consent document, then the name of the witness along with the date of the original 
consenting phone call is recorded in the research records to document the participation of 
the witness.   
 
g. 
The date the investigator/designee signs the informed consent document, not the date the 
consent discussion with the participant or LAR took place, is the official date of informed 
consent for the participant on the trial.   
 
h. 
The final informed consent document must be filed in the designated investigator/site 
regulatory file location. A copy of the final informed consent document, signed by the 
participant or LAR, the investigator, and the witness (if applicable), must be sent back to 
the participant via email/scan, fax, or postal mail. 
 
i. 
No research activities related to the study can begin until all steps of the informed consent 
process are complete. 
 
j. 
Participating site utilization of an e-signature with  the remote consent process: For sites 
utilizing the NCI CIRB as the IRB of record, eSignatures, may be permitted to be 
implemented on a site-by-site basis. Sites must submit the required information on Study 
Specific Worksheets (SSW) or the Signatory Institution Worksheet (SIW) worksheets 
before using an e-signature with the remote consent process. For sites utilizing the NCI 
CIRB as the IRB of record, questions regarding NCI CIRB approval process for 
participating site utilization of e-signatures are to be directed to the NCI CIRB. 
• 
An e-signature is defined as: an electronic sound, symbol, or process, attached to or 
logically associated with a contract or other record and executed or adopted by a 
person with the intent to sign the record.   
 
Institutional Review 
 
This study must be approved by an appropriate institutional review committee as defined by Federal 
Regulatory Guidelines (Ref. Federal Register Vol. 46, No. 17, January 27, 1981, part 56) and the 
Office for Protection from Research Risks Reports:  Protection of Human Subjects (Code of Federal 
Regulations 45 CFR 46). 
 
 

S1007 
Page 60 
Version Date 12/10/2021 
 
 
 
 
 
Monitoring 
 
This study will be monitored by the Clinical Data Update System (CDUS) Version 3.0.  Cumulative 
CDUS data will be submitted quarterly to CTEP by electronic means.  Reports are due January 31, 
April 30, July 31 and October 31. 
 
GEICAM is responsible for auditing their own institutions according to SWOG and NCI-CTMB 
Guidelines.  Audit data will be provided in English to the SWOG QA Department who will enter the 
audit data into the NCI database. 
 
Confidentiality 
 
Please note that the information contained in this protocol is considered confidential and should 
not be used or shared beyond the purposes of completing protocol requirements until or unless 
additional permission is obtained. 
 
16.1 
Adverse Event Reporting Requirements 
 
a. 
Purpose 
 
Adverse event data collection and reporting, which are required as part of every 
clinical trial, are done to ensure the safety of patients enrolled in the studies as well 
as those who will enroll in future studies using similar agents. Adverse events are 
reported in a routine manner at scheduled times during a trial. (Directions for 
routine reporting are provided in Section 14.0.) Additionally, certain adverse events 
must be reported in an expedited manner to allow for more timely monitoring of 
patient safety and care. The following guidelines prescribe expedited adverse 
event reporting for this protocol. See also Appendix 18.4 for general and 
background information about expedited reporting. 
 
b. 
Reporting method 
 
This study requires that expedited adverse events be reported using the CTEP 
Adverse Event Reporting System (CTEP-AERS). The NCI’s guidelines for CTEP-
AERS can be found at http://ctep.cancer.gov. A CTEP-AERS report must be 
submitted to the SWOG Operations Office electronically via the CTEP-AERS web-
based application located at 
http://ctep.cancer.gov/protocoldevelopment/electronic_applications/adverse_eve
nts.htm.  
 
In the rare event when internet connectivity is disrupted an electronic report MUST 
be submitted immediately upon re-establishment of internet connection.   
 
c. 
When to report an event in an expedited manner 
 
When the adverse event requires expedited reporting, submit the report within 10 
calendar days of learning of the event. 
 
d. 
Other recipients of adverse event reports 
 
The SWOG Operations Office will forward reports and documentation to the 
appropriate regulatory agencies and drug companies as required. 
 
Adverse events determined to be reportable to the Institutional Review Board 
responsible for oversight of the patient must be reported according to local policy 
and procedures. 
 

S1007 
Page 61 
Version Date 12/10/2021 
 
 
 
 
 
e. 
Expedited reporting for commercial agents 
 
Commercial reporting requirements are provided in Table 16.1. If there is any 
question about the reportability of an adverse event or if on-line CTEP-AERS 
cannot be used, please telephone or email the SAE Program at the Operations 
Office, 210/614-8808 or adr@swog.org, before preparing the report. 
 
Table 16.1 Expedited reporting requirements for adverse events experienced 
by patients within 30 days of the last administration of the commercial agent.  
 
ATTRIBUTION 
 
Grade 4 
 
Grade 5
a 
Unexpected 
Expected 
Unexpected 
Expected 
Unrelated or 
Unlikely 
 
 
CTEP-AERS 
CTEP-AERS 
Possible, 
Probable, Definite 
CTEP-AERS 
 
CTEP-AERS 
CTEP-AERS 
CTEP-AERS:  Indicates an expedited report is to be submitted via CTEP-AERS within 
10 calendar days of learning of the event. b 
 
a This includes all deaths within 30 days of the last dose of treatment with a commercial 
agent(s), regardless of attribution. Any death that occurs more than 30 days after the 
last dose of treatment with a commercial agent(s) and is attributed (possibly, probably, 
or definitely) to the agent(s) and is not due to cancer recurrence must be reported 
according to the instructions above. 
 
b Submission of the on-line CTEP-AERS report plus any necessary amendments 
generally completes the reporting requirements. You may, however, be asked to 
submit supporting clinical data to the Operations Office in order to complete the 
evaluation of the event. If requested, the specified data should be sent within 5 
calendar days by fax to 210-614-0006. 
 
 
f. 
Reporting Pregnancy, Fetal Death, and Death Neonatal 
 
1. 
Pregnancy Study participants who become pregnant while on study; that 
pregnancy should be reported in an expedited manner via CTEP-AERS 
as Grade 3 “Pregnancy, puerperium and perinatal conditions – Other 
(pregnancy)” under the Pregnancy, puerperium and perinatal 
conditions SOC.   
 
Additionally, the pregnancy outcome for patients on study should be 
reported via CTEP-AERS at the time the outcome becomes known, 
accompanied by the same Pregnancy Report Form used for the initial 
report. 
 
2. 
Pregnancy Loss Pregnancy loss is defined in CTCAE as “Death in utero.” 
Pregnancy loss should be reported expeditiously as Grade 4 “Pregnancy 
loss” under the Pregnancy, puerperium and perinatal conditions 
SOC. 
 
A Pregnancy loss should NOT be reported as a Grade 5 event under the 
Pregnancy, puerperium and perinatal conditions SOC, as currently CTEP-
AERS recognizes this event as a patient death. 
 

S1007 
Page 62 
Version Date 12/10/2021 
 
 
 
 
 
3. 
Death Neonatal Death neonatal is defined in CTCAE as “Newborn death 
occurring during the first 28 days after birth. A neonatal death should be 
reported expeditiously as Grade 4 “Death neonatal” under the General 
disorders and administration SOC.   
 
Neonatal death should NOT be reported as a Grade 5 event under the 
General disorders and administration SOC as currently CTEP-AERS 
recognizes this event as a patient death 
 
NOTE:  When submitting CTEP-AERS reports for “Pregnancy, 
“Pregnancy loss”, or “Neonatal loss”, the Pregnancy Information Form 
should also be completed and faxed with any additional medical 
information to 301-897-7404.  The potential risk of exposure of the fetus 
to the investigational agent(s) or chemotherapy agent(s) should be 
documented in the “Description of Event” section of the CTEP-AERS 
report. 
 
The Pregnancy Information Form is available at:  
http://ctep.cancer.gov/protocolDevelopment/adverse_effects.htm. 
 
g. 
COVID-19 Adverse Event Reporting Requirements:  
 
Per the NCI “Guidance for Collection of Adverse Events Related to COVID-19 
Infection,” accessible from: 
https://ctep.cancer.gov/content/docs/Adverse_Event_Guidance_COVID-
19_Final_3-25-20.pdf, any known COVID-19 infection should be reported as an 
adverse event (and if applicable via CTEP-AERS). 
 
 

S1007 
Page 63 
Version Date 12/10/2021 
 
 
 
 
 
 
17.0 
BIBLIOGRAPHY 
 
1  
Early Breast Cancer Trialists' Collaborative Group (EBCTCG).  Effects of chemotherapy and hormonal 
therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomized 
trials.  Lancet 365:1687-717. PMID: 15894097, 2005. 
 
2  
Early Breast Cancer Trialists' Collaborative Group (EBCTCG).  Effects of chemotherapy and hormonal 
therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomized 
trials.  Lancet 365:1687-717. PMID: 15894097, 2005. 
 
3  
Fisher B, Jeong JH, Bryant J, et al. Treatment of lymph-node-negative, oestrogen-receptor-positive 
breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project 
randomized clinical trials.  Lancet 364:858-68.  PMID: 15351193, 2004. 
 
4  
Berry DA, Cirrincione C, Henderson IC, et al.  Estrogen-receptor status and outcomes of modern 
chemotherapy for patients with node-positive breast cancer.  JAMA 295:1658-67.  PMID: 16609087, 
2006. 
 
5  
Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-
negative breast cancer. N Engl J Med. 351:2817-26.  PMID: 15591335, 2004. 
 
6  
Paik S, Tang G, Shak S, et al.  Gene expression and benefit of chemotherapy in women with node-
negative, estrogen receptor–positive breast cancer.  J Clin Oncol 24:3726-34.  PMID: 16720680, 
2006. 
 
7  
Berry DA, Cirrincione C, Henderson IC, et al.  Estrogen-receptor status and outcomes of modern 
chemotherapy for patients with node-positive breast cancer.  JAMA 295:1658-67.  PMID: 16609087, 
2006. 
 
8  
Albain KS, Barlow WE, Shak S, Hortobagyi GN, et al. Prognostic and predictive value of the 21-
gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-
positive breast cancer on chemotherapy: a retrospective analysis of a randomized trial, Lancet 
Oncology 11:55-65, PMID: 20005174, 2010. 
 
9  
Albain KS, Barlow WE, Shak S, Hortobagyi GN, et al. Prognostic and predictive value of the 21-
gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-
positive breast cancer on chemotherapy: a retrospective analysis of a randomized trial, Lancet 
Oncology 11:55-65, PMID: 20005174, 2010. 
 
10  
Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-
negative breast cancer. N Engl J Med. 351:2817-26.  PMID: 15591335, 2004. 
 
11  
Paik S, Tang G, Shak S, et al.  Gene expression and benefit of chemotherapy in women with node-
negative, estrogen receptor–positive breast cancer.  J Clin Oncol 24:3726-34.  PMID: 16720680, 
2006. 
 
12  
Cronin M, Sangli C, Liu M-L, et al.  Analytical validation of the Oncotype DX genomic diagnostic 
test for recurrence, prognosis and therapeutic response prediction in node-negative, estrogen 
receptor positive breast cancer. Clinical Chemistry 53:1084-91, 2007. 
 
13  
Oratz R, Paul D, Cohn AL, Sedlacek SM.  Impact of a commercial reference laboratory test recurrence 
score on decision making in early-stage breast cancer.  J Oncol Practice 3:182-6, 2007. 
 
 

S1007 
Page 64 
Version Date 12/10/2021 
 
 
 
 
 
 
14  
Lo SS, Mumby PB, Norton J, et al. Prospective multicenter study of the impact of the 21-gene 
recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment 
selection. J Clin Oncol 28:1671-76, 2010. 
 
15  
Albain KS, Barlow WE, Shak S, Hortobagyi GN, et al. Prognostic and predictive value of the 21-
gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-
positive breast cancer on chemotherapy: a retrospective analysis of a randomized trial, Lancet 
Oncology 11:55-65, PMID: 20005174, 2010. 
 
16  
Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic 
subtypes. J Clin Oncol 27:1160-7. PMID: 19204204, 2009. 
 
17  
Albain KS, Barlow WE, Shak S, Hortobagyi GN, et al. Prognostic and predictive value of the 21-
gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-
positive breast cancer on chemotherapy: a retrospective analysis of a randomized trial, Lancet 
Oncology 11:55-65, PMID: 20005174, 2010. 
 
18  
Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-
negative breast cancer. N Engl J Med. 351:2817-26.  PMID: 15591335, 2004. 
 
19  
Albain KS, Barlow WE, Shak S, Hortobagyi GN, et al. Prognostic and predictive value of the 21-
gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-
positive breast cancer on chemotherapy: a retrospective analysis of a randomized trial, Lancet 
Oncology 11:55-65, PMID: 20005174, 2010. 
 
20  
Levine MN, Gent M, Hirsh J, et al. The thrombogenic effect of anticancer drug therapy in women 
with stage II breast cancer. N Engl J Med 318:404-7, 1988. 
 
21  
Pritchard KI, Paterson AH, Paul NA, et al. Increased thromboembolic complications with concurrent 
tamoxifen and chemotherapy in a randomized trial of adjuvant therapy for women with breast 
cancer. National Cancer Institute of Canada Clinical Trials Group Breast Cancer Site Group. J Clin 
Oncol 14: 2731-37, 1996. 
 
22  
Valagussa M, Zambetti S, Biasi A, et al. Cardiac effects following adjuvant chemotherapy and 
breast irradiation in operable breast cancer. Ann Oncol 5:209-16, 1994. 
 
23  
Shapiro CL, Hardenbergh PH, Gelman R, et al. Cardiac effects of adjuvant doxorubicin and 
radiation therapy in breast cancer patients. J Clin Oncol 16: 3493-501, 1998. 
 
24  
Mar Fan HG, Houede-Tchen N, Qi-Long Y, et al. Fatigue, menopausal symptoms, and cognitive 
function in women after adjuvant chemotherapy for breast cancer: 1- and 2-year follow up of a 
prospective controlled study. J Clin Oncol 23:8025-32), 2005. 
 
25  
Bower JE, Ganz PA, Desmond KA, et al. Fatigue in breast cancer survivors: occurrence, correlates, 
and impact on quality of life. J Clin Oncol 18:743-53, 2000. 
 
26  
Schagen S, van Dam F, Muller M, et al. Cognitive defects after postoperative adjuvant 
chemotherapy of breast carcinoma. Cancer 85:640-50, 1999. 
 
27  
van Dam FS, Schagen SB, Muller MJ, et al. Impairment of cognitive function in women receiving 
adjuvant treatment for high-risk breast cancer: high-dose versus standard dose chemotherapy. J 
Natl Cancer Inst 90:210-8, 1988. 
 
28  
Ganz PA, Desmond KA, Leedham B, et al. Quality of life in long-term, disease-free survivors of 
breast cancer: a follow-up study. J Natl Cancer Inst 94:39-49, 2002. 
 

S1007 
Page 65 
Version Date 12/10/2021 
 
 
 
 
 
 
 
29  
Ganz PA, Kwan L, Stanton AL, et al. Quality of life at the end of primary treatment of breast cancer: 
first results from the moving beyond cancer randomized trial. J Natl Cancer Inst 96:376-87, 2004. 
 
30  
Duric V, Stockler M. Patients’ preference for adjuvant chemotherapy in early breast cancer: a 
review of what makes it worthwhile? Lancet Oncol 2:691-697, 2001. 
 
31  
Oestreicher N, Ramsey SD, McCune JS, et al. The cost of adjuvant chemotherapy in patients with 
early-stage breast carcinoma. Cancer 104:2054-62, 2005. 
 
32  
Hornberger J, Cosler LE, Lyman GH. Economic analysis of targeting chemotherapy using a 21-
gene RT-PRC assay in lymph-node negative, estrogen-receptor positive, early-stage breast 
cancer. Am J Manag Care 11:313-324, 2005. 
 
33  
Oestreicher N, Ramsey SD, Linden HM, et al. Gene expression profiling and breast cancer care: 
what are the potential benefits and policy implications? Genet Med 7:380-9, 2005. 
 
34  
Ramsey SD, Willke R, Briggs A, et al. Good research practices for cost-effectiveness analysis 
alongside clinical trials: the ISPOR RCT-CEA task force report. Value Health 8:521-33, 2005. 
 
35  
Buus R, Sestak I, Kronenwett R, et al. Molecular Drivers of Oncotype DX, Prosigna, EndoPredict, 
and the Breast Cancer Index: A TransATAC Study. J Clin Oncol 2021; 39(2): 126-35. 
 
36  
Sestak I, Buus R, Cuzick J, et al. Comparison of the Performance of 6 Prognostic Signatures for 
Estrogen Receptor-Positive Breast Cancer: A Secondary Analysis of a Randomized Clinical Trial. 
JAMA Oncol 2018; 4(4): 545-53. 
 
37  
van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival 
in breast cancer. N Engl J Med 2002; 347(25): 1999-2009. 
 
38  
Cardoso F, van't Veer LJ, Bogaerts J, et al. 70-Gene Signature as an Aid to Treatment Decisions 
in Early-Stage Breast Cancer. N Engl J Med 2016; 375(8): 717-29. 
 
39  
Piccart M, van 't Veer LJ, Poncet C, et al. 70-gene signature as an aid for treatment decisions in 
early breast cancer: updated results of the phase 3 randomised MINDACT trial with an exploratory 
analysis by age. Lancet Oncol 2021; 22(4): 476-88. 
 
40  
Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish 
tumor subclasses with clinical implications. Proceedings of the National Academy of Sciences 
2001; 98(19): 10869-74. 
 
41  
Lænkholm AV, Jensen MB, Eriksen JO, et al. PAM50 Risk of Recurrence Score Predicts 10-Year 
Distant Recurrence in a Comprehensive Danish Cohort of Postmenopausal Women Allocated to 5 
Years of Endocrine Therapy for Hormone Receptor-Positive Early Breast Cancer. J Clin Oncol 
2018; 36(8): 735-40. 
 
42  
Gnant M, Sestak I, Filipits M, et al. Identifying clinically relevant prognostic subgroups of 
postmenopausal women with node-positive hormone receptor-positive early-stage breast cancer 
treated with endocrine therapy: a combined analysis of ABCSG-8 and ATAC using the PAM50 risk 
of recurrence score and intrinsic subtype. Ann Oncol 2015; 26(8): 1685-91. 
 
43  
Wallden B, Storhoff J, Nielsen T, et al. Development and verification of the PAM50-based Prosigna 
breast cancer gene signature assay. BMC Med Genomics 2015; 8: 54. 
 
 

S1007 
Page 66 
Version Date 12/10/2021 
 
 
 
 
 
 
44  
Sinn BV, Fu C, Lau R, et al. SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine 
therapy for metastatic breast cancer. NPJ Breast Cancer 2019; 5: 16. 
 
45  
Du L, Yau C, Brown-Swigart L, et al. Predicted sensitivity to endocrine therapy for stage II-III 
hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancer before chemo-
endocrine therapy. Ann Oncol 2021; 32(5): 642-51. 
 
46  
Filipits M, Rudas M, Jakesz R, et al. A new molecular predictor of distant recurrence in ER-positive, 
HER2-negative breast cancer adds independent information to conventional clinical risk factors. 
Clin Cancer Res 2011; 17(18): 6012-20. 
 
47  
Martin M, Brase JC, Calvo L, et al. Clinical validation of the EndoPredict test in node-positive, 
chemotherapy-treated ER+/HER2− breast cancer patients: results from the GEICAM 9906 trial. 
Breast Cancer Research 2014; 16(2): R38. 
 
48  
Bartlett JMS, Sgroi DC, Treuner K, et al. Breast Cancer Index and prediction of benefit from 
extended endocrine therapy in breast cancer patients treated in the Adjuvant Tamoxifen-To Offer 
More? (aTTom) trial. Ann Oncol 2019; 30(11): 1776-83. 
 
49  
Noordhoek I, Treuner K, Putter H, et al. Breast Cancer Index Predicts Extended Endocrine Benefit 
to Individualize Selection of Patients with HR(+) Early-stage Breast Cancer for 10 Years of 
Endocrine Therapy. Clin Cancer Res 2021; 27(1): 311-9. 
 
50  
Meric-Bernstam F, Zheng X, Shariati M, et al. Survival Outcomes by TP53 Mutation Status in 
Metastatic Breast Cancer. JCO Precis Oncol 2018; 2018. 
 
51  
Akcakanat A, Zheng X, Cruz Pico CX, et al. Genomic, Transcriptomic, and Proteomic Profiling of 
Metastatic Breast Cancer. Clin Cancer Res 2021. 
 
52  
Keene KS, King T, Hwang ES, et al. Molecular determinants of post-mastectomy breast cancer 
recurrence. NPJ Breast Cancer 2018; 4: 34. 
 
53  
Zheng ZY, Anurag M, Lei JT, et al. Neurofibromin Is an Estrogen Receptor-α Transcriptional Co-
repressor in Breast Cancer. Cancer Cell 2020; 37(3): 387-402.e7. 
 
54  
Jeselsohn R, Yelensky R, Buchwalter G, et al. Emergence of constitutively active estrogen 
receptor-α mutations in pretreated advanced estrogen receptor-positive breast cancer. Clin Cancer 
Res 2014; 20(7): 1757-67. 
 
55  
Broekmans FJ, Knauff EA, te Velde ER, Macklon NS, Fauser BC. Female reproductive ageing: 
current knowledge and future trends. Trends Endocrinol Metab. 2007;18(2):58-65. 
 
56  
Krailo MD, Pike MC. Estimation of the distribution of age at natural menopause from prevalence 
data. Am J Epidemiol. 1983;117(3):356-361. 
 
57  
Pocock SJ, Simon R.  Sequential treatment assignment with balancing for prognostic factors in 
controlled clinical trials.  Biometrics 31:103-115, 1975. 
 
58  
Tolaney SM, Garrett-Mayer E, White J, et al. Updated Standardized Definitions for Efficacy End 
Points (STEEP) in Adjuvant Breast Cancer Clinical Trials: STEEP Version 2.0. J Clin Oncol. 2021 
Aug 20;39(24):2720-2731. doi: 10.1200/JCO.20.03613. Epub 2021 May 18. PMID: 34003702. 
 
59  
CAP, So you are going to collect a blood specimen.  An Introduction to Phlebotomy, 6th Ed., 1994. 
 
 

S1007 
Page 67 
Version Date 12/10/2021 
 
 
 
 
 
 
60  
Ernst, DJ, Calan, R.NCCLS simplifies order of draw: a brief history, MLO, 2004. 
 
61  
Ernst, DJ, Calan, R.NCCLS simplifies order of draw: a brief history, MLO, 2004. 
 
 
 

S1007 
Page 68 
Version Date 12/10/2021 
 
 
 
 
 
18.0 
APPENDIX 
 
18.1 
Comparative Effectiveness and Health Related Quality of Life 
 
18.2 
Prospective Validation of Other Prognostic/Predictive Indices of Breast Cancer Outcomes 
and Evaluation of Pre-treatment Hormone Levels  
 
18.3 
Statistical Analysis Plan 
 
18.4 
Determination of Expedited Adverse Event Reporting Requirements 
 
18.5 
Participation Procedures for the International Collaborating Institutions 
 
18.6 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, 
Hormone-Receptor Positive, Her2 Negative, Operable Breast Cancer Translational 
Medicine Substudy (U.S. INSTITUTIONS ONLY) - CELLSEARCH ANALYSES (Menarini 
Silicon Biosystems) 
 
18.7 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, 
Hormone-Receptor Positive, Her2 Negative, Operable Breast Cancer Translational 
Medicine Substudy (U.S. INSTITUTIONS ONLY) - EPIC SCIENCES CTC DETECTION 
PLATFORM 
 
18.8 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, 
Hormone-Receptor Positive, Her2 Negative, Operable Breast Cancer Translational 
Medicine Substudy (U.S. INSTITUTIONS ONLY) - NON-CTC ANALYSES  
 
18.9 
Instructions for the SWOG Biospecimen Bank – Lab #201, Solid Tissue, Myeloma and 
Lymphoma Division 
 
 
 

S1007 
Page 69 
Version Date 12/10/2021 
 
 
 
 
 
18.1 
Comparative Effectiveness and Health Related Quality of Life (U.S. INSTITUTIONS ONLY) 
(Permanently closed to accrual effective 12/1/12.) 
 
A. 
Health-Related Quality of Life 
 
Background and Significance: HRQOL& Oncotype DX® Testing/Effects of 
Chemotherapy 
 
While it is recognized that the majority of the acute effects of chemotherapy (e.g. 
nausea, vomiting, diarrhea, stomatitis, alopecia and neutropenia) will resolve, sub-
acute effects and long-term sequelae may have a lasting impact on the quality of 
life of survivors.  Other symptoms such as fatigue, depression, and pain are slow 
to resolve and may have long-term consequences for women. (1) 
 
Anxiety associated with the breast cancer diagnosis, anticipatory distress prior to 
treatment, and fear of recurrence has been documented for women with breast 
cancer. (2,3,4) A central question is whether women will accept a recommendation 
not to receive chemotherapy based on the results of Oncotype DX®, given the 
findings of benefit for adjuvant therapy in this population. 
 
Recent studies in doctor/patient decision making suggest that women are likely to 
accept adjuvant chemotherapy for little or minimal benefits.  (5) Thus, it is possible 
that a woman will experience anxiety about the idea of forgoing chemotherapy, 
even if the RS predicts that chemotherapy is unlikely to provide benefit. Such 
anxiety might be debilitating or lead to a decision to proceed to chemotherapy 
despite a low RS for those randomized to no treatment. Lo et al reported a 
significant decrease in anxiety for women receiving adjuvant treatment for breast 
cancer but there was only 1 patient who received observation only and one who 
received observation and then endocrine treatment. (6) Patients were not 
randomized to chemotherapy versus no chemotherapy as in this trial. This study 
will include one general measure of anxiety for cancer patients (primary measure) 
plus a measure of concerns about cancer recurrence and diagnostic testing. 
 
We will measure anxiety with the Patient-Reported Outcomes Measurement 
Information System (PROMIS) short form Emotional Distress-Anxiety scale. (7) 
The 8-item anxiety measure was developed and received preliminary validation in 
a cancer population (Personal Communications, Sofia Garcia and David Cella, 
January 2010). 
 
We expect that the "reach" of the various treatment-related side effects discussed 
above will be generally captured by the ratings of health status provided by the 
EQ-5D along with the utilities associated with these ratings. (8) The EQ-5D 
descriptive ratings for different health states and the single utility index value will 
be compared for women with RS ≤ 25 who receive chemotherapy versus those 
who do not. However, given that the quality of life study will be conducted with the 
randomized sample where one arm receives chemotherapy and the other arm 
does not, this study offers an opportunity to examine a placebo-controlled 
chemotherapy effect over a three-year period on patient report of both fatigue and 
cognitive dysfunction. Therefore, we decided to include two single-item measures 
of these important symptom problems. 
 
However, two symptoms are of particular interest because of their prevalence and 
association with cancer therapy: fatigue and cognitive dysfunction. While the acute 
effects of chemotherapy on fatigue has long been recognized, a number of studies 
have reported problems with fatigue for lasting months or even years after adjuvant 
chemotherapy.  (9)  Such fatigue was associated with a decrease in daily 
functioning. (10) We will measure fatigue with the 7 item PROMIS Fatigue Short 
Form. (Personal Communication, S. Garcia, January 2007; 2) In addition there has 
been an increased awareness of cognitive dysfunction associated with adjuvant 

S1007 
Page 70 
Version Date 12/10/2021 
 
 
 
 
 
chemotherapy in women with breast cancer. (11)  Schagen et al evaluated 39 
women at approximately 2 years following 6 cycles of chemotherapy compared to 
34 women who had received local therapy only; 28% of the patients treated by 
CMF compared to 12% of control groups showed evidence of cognitive dysfunction 
characterized by difficulty with concentration, memory, and word finding. (12) van 
Dam et al suggested that such symptoms were worse in patients with high dose 
chemo-therapy. (13) While these studies suffer from lack of good controls and poor 
association between reports of cognitive dysfunction and scores on formal testing, 
they remain concerning.  Studies conducted by Jacobsen and colleagues have 
failed to document the association between adjuvant chemotherapy and cognitive 
dysfunction. (14) Vardy et al. summarized the evidence for the association based 
on the second international workshop on cognitive function in terms of effects of 
the cancer and its treatment and conclude that "the characterization of cognitive 
impairment in terms of its nature, course over time, underlying mechanisms and 
impact on subject’s lives is still limited". (15) Anecdotally many breast cancer 
patients complain of forgetfulness, difficulty concentrating or "chemo brain". These 
effects are likely to have significant long-term consequences for women’s quality 
of life. The current study with its randomized design offers an opportunity to 
contribute to the understanding chemotherapy’s impact on cognitive function. We 
will use the PROMIS Perceived Cognitive Function Concerns Short Form (8 items) 
to measure cognitive function. 
 
The impact that chemotherapy has on HRQL is key and central for patients 
deciding whether or not to receive adjuvant chemotherapy in order to prevent 
further recurrence. S1007 provides a unique opportunity to prospectively and 
quantitatively evaluate the impact of modern chemotherapy on the HRQL of 
women with early breast cancer. It is critical now to take the opportunity to integrate 
HRQL assessment into this unique randomized trial. While it is hypothesized that 
chemotherapy is unlikely to have an effect on cancer outcomes in those with an 
RS ≤ 25, it is possible that a subset of patients with RS between 11 and 25 may 
achieve small benefits in reduction in recurrence. If so, the impact of chemotherapy 
on HRQL will be particularly relevant for this group of patients. Such information is 
also likely to be useful to all women with breast cancer and their physicians who 
are considering adjuvant chemotherapy.  
 
HRQL Study Design 
This protocol addresses the impact of two treatment issues on patient HRQL: the 
impact of testing and receiving information about risk of recurrence (Phase I); and 
the impact on HRQL of being randomized to chemotherapy vs. no chemotherapy 
(Phase II). 
 

S1007 
Page 71 
Version Date 12/10/2021 
 
 
 
 
 
SCHEMA: HRQL Sample (U.S. INSTITUTIONS ONLY) 
 
The following Schema describes the process for administering Health-Related Quality of Life 
(HRQL) forms to patients participating in the two HRQL Studies for S1007. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
RS > 25 
RS ≤ 25 
 
 
 
  Accept 
 
 
 
 
 
        
 
 
 
Refuse 
 
 
 
 
 
 
 
 
 
 
 
 
Node-positive (1-3 nodes) HR-positive and HER2-negative breast cancer 
RS already available and ≤ 25. 
Physician and patient discuss 
randomization knowing the RS 
10% of Full Sample = 60 
Recurrence 
Score 
Discuss 
alternative 
trials for high 
risk patients 
40% of 
1000=400 
Physician and 
patient discuss 
randomization 
knowing the RS 
N=600 
Step 2 Registration/ 
Randomization stratified 
by: 
1.  RS 0-13 vs. 14-25 
2.  Menopausal  
     Status 
3.  Axillary node  
     Dissection vs.  
     Sentinel node  
     Biopsy 
 
HRQL sample=440+60 
                    =500 
Chemotherapy; 
endocrine 
therapy 
No 
Chemotherapy; 
endocrine 
therapy 
Patients consent to Recurrence Score (RS) testing, 
discussion of potential randomization on this trial. 
2nd HRQL Time point 
Observational Study Form 
No further follow-up 
Step 1 Registration and tumor tissue submission 
for RS testing 1000 of 8800 approached for HRQL 
Study  
1st HRQL Time point: Enrollment Form 
2nd HRQL Time Point/1st for women who enter 
with Recurrence Score: Randomized Study Form 
HRQL Follow-up: Months 6, 12, 36 
Step 1 
Registration 
Step 1  
Step 1 
Step 2 

S1007 
Page 72 
Version Date 12/10/2021 
 
 
 
 
 
Step 1 Study: Impact of Oncotype DX® Testing on Patient HRQL   
 
A. 
Step 1 data collection for assessments will be supported with NIH funding:  
Comparative Effectiveness Evaluation of Oncotype DX® for Women with 
Node-positive, Hormone-responsive and HER2-negative Breast Cancer. 
NIH RC2CA148570-01 (Scott Ramsey, MD, PhD, Principal Investigator) 
 
B. 
At Enrollment (prior to Oncotype DX® testing), 1000 women (of the 8800 
tested) will be asked to complete the S1007 Health-Related Quality of Life 
Questionnaire: Enrollment that includes the following scales:  
 
1. 
Patient Pre-Oncotype (RS Assay) Questionnaire [10 items] (Lo 
et al., 2010); 
 
2. 
Decisional Conflict Scale [16 items] (O’Connor, 1995; O’Connor, 
1993/1999/2005); 
 
3. 
EQ-5D [6 items], a measure of patient health state preference 
(Krabbe et al., 2004; Pickard, Wilke, et al., 2007; Pickard, Neary, 
et al., 2007); 
 
4. 
a measure of anxiety (Patient-Reported Outcomes Measurement 
Information System [PROMIS] short form, Emotional Distress-
Anxiety [9 items]) (Cella, 2009; Yost et al., submitted);  
 
5. 
Assessment of Survivor Concerns [3 items] that addresses 
concern about cancer recurrence (Gotay, 2007).   
 
Anxiety is the primary outcome measure for Step 1 enrollment 
assessment.   
 
C. 
The same scales will be completed a second time by different subsets of 
the 1,000 women in Step 1 above (Recurrence Score Known/Treatment 
Decision Made Assessment), all of whom will have their Recurrence Score 
(RS) results and will have made a treatment decision.  The S1007 Health-
Related Quality of Life Questionnaire: Observational Study will be 
administered to women with RS value > 25 (estimated % of 1,000 = 40%; 
n = 400) and to those women whose RS was ≤ 25 but who refused 
randomization (estimated refusal rate of 27%, n = 160).  Thus, the total 
number of women in the observational QOL study is estimated to be 560.  
Women in these two groups will not receive any additional follow-up 
assessments.  These women will answer the items after the recurrence 
results have been received (week to 10 days after enrollment) and after a 
discussion regarding treatment options has resulted in a treatment 
decision.  The scales at this second-time point will be the same as those 
in the Enrollment Questionnaire with the exception of the RS Assay items.  
These Post-Oncotype RS questions [13 items] address the patient’s 
evaluation of the RS result.  Those who refuse to be randomized will also 
be asked to indicate reasons for their refusal to accept a treatment based 
on randomization and to rate the importance of the reasons deemed true 
for that patient.  Anxiety is the primary outcome for women who receive a 
second assessment but will not be participating in the randomized study. 
 
 

S1007 
Page 73 
Version Date 12/10/2021 
 
 
 
 
 
Step 2 Randomized Trial: Impact of Chemotherapy on HRQL   
 
A. 
Women whose RS is ≤ 25 and consent to participate in the randomized 
trial will complete the S1007 Health-Related Quality of Life Questionnaire: 
Randomized Study.  A subsample (n=440) of the women hemotherapy 
and who were enrolled in Step 1 will be asked to complete additional forms 
as part of Step 2 of the HRQL study.  In addition, women who already have 
RS results (i.e., did not participate in Step 1 of the HRQL study) will enter 
the randomized phase of the study at this point.  We estimate that 6% of 
the 1000 patients assessed in Step 1 or 60 patients will enter Step 2 with 
their RS from another source.  These women will answer the items after 
the recurrence results have been received and after a discussion 
regarding treatment options has resulted in a consent to randomization 
and a treatment assignment.  For the patients who consent to the 
randomized trial after Enrollment, the time from Oncotype DX® testing to 
receipt of RS results will be approximately 3 weeks after Enrollment; we 
estimate that discussion of treatment options and the randomized trial will 
require another 3 weeks.  Assessment 2 (baseline assessment for the 
randomized trial) will occur prior to randomized treatment initiation.  
Women who have an RS not obtained through Step 1 will complete the 
randomized trial baseline assessment after discussion with a physician 
about the RS score, the consent to being randomized, and the knowledge 
about the treatment assignment but prior to initiation of the randomized 
treatment.  
 
B. 
The randomized trial has two primary HRQL outcomes: anxiety (PROMIS 
short form Emotional Distress-Anxiety); and a utility or health state 
preference score (EQ-5D).  Additional HRQL outcomes include the 
following: PROMIS short form measures of Fatigue (7 items) and 
Perceived Cognitive Function-Cognitive Impairments (8 items).  The 
following scales will be administered at the baseline assessment for the 
randomized trial:  
 
1. 
Post-Oncotype (RS Assay) baseline items [13 items];    
 
2. 
Post-Oncotype (RS Assay) follow-up items months 6, 12, & 36 [2 
items] 
 
3. 
Decisional Conflict Scale [16 items];  
 
4. 
EQ-5D [6 items];  
 
5. 
PROMIS Emotional Distress-Anxiety Short Form [9 items];  
 
6. 
Assessment of Survivor Concerns [3 items] that addresses 
concern about cancer recurrence (Gotay, 2007.   
 
7. 
PROMIS Fatigue Short Form [7 items] (Garcia et al., 2007; Yost 
et al., submitted; Personal Communications, D Cella, S Garcia, 
Jin-Shei Lai, 2010 and draft project summaries for the Cancer 
PROMIS Supplement) 
 
8. 
PROMIS Cognitive Function Concerns [8 items] (Personal 
Communications, D Cella, S Garcia, Jin-Shei Lai, 2010 and draft 
project summaries for the Cancer PROMIS Supplement and the 
Development of PROMIS-cancer Perceived Cognitive Function 
(PCF) Item Bank) 
 
 

S1007 
Page 74 
Version Date 12/10/2021 
 
 
 
 
 
In addition, three follow-up HRQL post-randomization assessments will 
occur at six months, one year, and three years.   
 
 
 
Outcome Measures 
 
Primary Outcomes:  Two primary HRQL outcomes will be used to compare 
patients receiving chemotherapy versus those not receiving chemotherapy: 
anxiety and a utility value for the patient’s selfreport of health status.  
 
PROMIS Anxiety Short Form:  Anxiety will be assessed by one short form measure 
of Emotional Distress-Anxiety. This 9-item scale was developed as part of the NIH-
sponsored Patient-Reported Outcomes Measurement Information System 
(PROMIS) initiative.  (16,17) We will use the anxiety measure validated for cancer 
patients (Personal Communication, Sofia Garcia, January 2010).  Higher scores 
reflect more anxiety.   
 
EQ-5D:  Patients will rate their health status with the EuroQol-5D [EQ-5D], which 
includes population adjustments for health state preferences or utilities for different 
health states as well as a visual analogue scale (VAS) measure of perceived value 
for that status (degree of good versus bad) for those patients who receive 
chemotherapy versus those who do not. (18,19,20) The utility index weighting the 
health state descriptions with values that were obtained from other samples of 
individuals with the VAS or time trade-off techniques.  The index can be used to 
adjust years of life. (21) Higher scores reflect the person’s perceived health state 
as a better/more preferred state of health.  We will use the EQ-5D Index scores 
 
Secondary Outcomes:  In addition, we will assess the degree to which patients 
worry about their cancer using the Assessment of Survivor Concerns (ASC) as a 
secondary, exploratory HRQL outcome. (22) The psychometric properties of this 
measure have been documented.  We will use the 3-item Cancer Worry subscale 
(coefficient alpha reliability for this subscale is 0.93), which the authors suggest 
can be used alone if the research context is cancer.  Two prevalent symptom 
measures, cognitive dysfunction and fatigue, will be assessed at the four-time 
points with PROMIS short forms developed as part of the PROMIS item bank 
project.  The fatigue short form was developed as part of the PROMIS item bank 
initiative and was further tested in cancer patients. (23,24,25,26) The cognitive 
disabilities or concerns short form was also part of the PROMIS item bank initiative 
 
HRQL Study Calendar 
 
 
 
 
 
 
 
 
REQUIRED 
STUDIES 
PRE 
POST 
RANDOMIZED STUDY 
Oncotype 
DX® 
Oncotype 
DX® 
Pre Tx 
6 
months 
1 
year 
3 
years 
STEP 1 
 
 
 
 
 
 
Enrollment 
Form 
X 
 
 
 
 
 
Observational 
Study Form 
 
X 
 
 
 
 
 
 
 
 
 
 
 
STEP 2 
 
 
 
 
 
 
Randomized 
Study Form 
 
 
X 
X 
X 
X 
 
 
 
 
 
 
 

S1007 
Page 75 
Version Date 12/10/2021 
 
 
 
 
 
(Unpublished project summaries: Development of PROMIS-Cancer Perceived 
Cognitive function (PCF) Item Bank; The Cancer PROMIS Supplement (CaPS).  
 
Decision making issues regarding recurrence risk testing and selection of 
treatment were measured with two sets of items.  The Decisional Conflict Scale 
(DCS) (O’Connor, 1995; O’Connor, 1993/1999/2005) has 16 items addressing 
uncertainty associated with choosing a health care option, factors contributing to 
this uncertainty, and the evaluation of the decision.  We are using the Traditional 
Decisional Conflict Scale that has items in the form of statements (versus 
questions); reliability has been estimated at ≥ 0.78 for the various versions of the 
scale.   
 
A second set of decision making items specifically addresses the Oncotype DX® 
testing context. (27; Personal Communication: S Lo, P Mumby). These items were 
developed to report as single items with no overall scaled score.  S1007 uses items 
that were slightly revised from those reported by Lo et al. based on the 
investigators’ experience with the items in the published study. (28, Personal 
Communication, Lo SS, Mumby P, August 2010) Some of these single items have 
been further revised to reflect specific research questions in S1007.  The Phase I 
Enrollment form items address current choice of treatment [1 item], perceived risk 
for recurrence [1 item], factors affecting a treatment decision [4 items], and 
perceptions about the Oncotype DX® test [4 items].  The Phase I Observational 
Study form addresses current choice of treatment [1 item], perceived risk of 
recurrence [1 item], factors affecting a treatment decision [4 items], yes/no 
question regarding the influence of the test on a treatment decision, and evaluation 
of the Oncotype DX® test and the patient’s treatment decision [6 items].   
 
For patients who do not consent to be randomized, the Observational study 
questionnaire contains a list of 8 possible reasons (plus an Other option with space 
to provide a specific reason) for not agreeing to participate in a randomized trial 
for cancer treatment. Items used in S0316, Barriers to Accrual to Clinical Trials in 
older (≥ 65 years) Cancer Patients, were selected for S1007 based on frequency 
of endorsement in that study.  (Javid SH, Unger JM, Gralow JR, et. al. manuscript 
in preparation).  The Phase II Randomized Study form at baseline has the same 
Oncotype DX® testing and treatment decision making items as the Phase I 
Observational Study but the three follow-up forms for the randomized trial include 
two additional questions (satisfaction with treatment decision; if not satisfied, 
reasons for non-satisfaction). 
 
Statistical design 
 
Step 1.  The primary comparison for Step 1 testing will be the change in the 
PROMIS anxiety short form scores between the Enrollment and second 
assessments (as obtained for patients who do not participate in the randomize trial 
as well as those who do consent to the trial).  We will select the first 1000 patients 
enrolled in S1007 at either Community Clinical Oncology Program (CCOP) or non-
CCOP sites participating in the trial.  This provides a sufficient sample size for the 
HRQL component of the randomized trial (see support for randomized n=500 
below).   
 
 

S1007 
Page 76 
Version Date 12/10/2021 
 
 
 
 
 
Hypothesis: 
 
Comparisons based on the full sample. 
 
H1: Women who receive an RS that is > 25 will have greater anxiety than those 
whose RS is ≤ 25 when compared at the second assessment when RS results and 
treatment decisions are known.   
 
H2: Women whose RS is ≤ 25 but do not consent to randomization will have lower 
anxiety scores than those who do agree to be randomized when compared at the 
second assessment when  
 
H3: EQ-5D Index scores will be worse for women whose RS is > 25 compared to 
women whose RS is ≤ 25 at the second assessment when RS and treatment 
decisions are known. 
 
Comparisons based on the randomized group. 
 
H4: Anxiety for women who are randomized to no chemotherapy will be greater 
than for those who are randomized to receive chemotherapy when compared at 
the second assessment and at all follow-up assessments. 
 
H5: Patients receiving adjuvant chemotherapy will report worse EQ-5D utility or 
Index scores than will patients receiving no chemotherapy. 
 
Step 1 Analyses:  The primary analyses for the QOL follow-up measures adjust for 
baseline if one exists.  In general, analysis of covariance of the follow-up measured 
on a continuous scale will benefit from adjustment from baseline by taking 
advantage of internal consistency within an individual.  Analysis of covariance 
includes "change score" as a special case where the coefficient of the baseline 
variable is -1. If baseline and follow-up are weakly correlated, then simple analyses 
at follow-up are more powerful.  For ordinal or binomial outcomes, adjustment for 
baseline is rarely helpful.  For some outcomes measured at time of the second 
registration (choice to enter the randomized trial or not), there is not an appropriate 
baseline from the initial battery.  Standard regression (linear and logistic) will be 
used for these analyses.    Note that even for a binomial outcome from 1,000 
patients (600 RS ≤ 25 versus 400 RS>25) we can detect a 10% difference with 
power 85% or greater.   
 
Step 2 Analyses:  The primary randomized trial HRQL treatment arm comparisons 
for anxiety and health utility will occur at 6 months but additional analyses of the 
HRQL measures will use longitudinal methods that can address loss-to-follow-up 
which may be associated with survival. The proposed sample size for the HRQL 
randomized trials analyses is 500 women randomized to receive chemotherapy or 
not. Projected accrual for the trial is 56 patients per month. CCOP sites account 
for approximately 25% of patient registrations to SWOG trials (Report of Studies, 
April 2010). In addition, we will also accrue from non-CCOP sites.     
 
The PROMIS Emotional Distress-Anxiety standard deviation (SD) for 101 cancer 
patients was 7.5 for the first assessment and 7.7 for the second assessment; the 
longitudinal SD was 4.6. As an index of a clinically significant difference between 
the two study groups (chemotherapy versus no chemotherapy), we would be 
interested in SD differences between 1/3 (1/3 SD’s were 2.5 and 2.6 were reported 
for two sequential assessments) to ½ (1/2 SD’s were 3.7 and 3.9 for 2 sequential 
assessments2): longitudinal SD’s were smaller (1/3 SD=1.5; ½ SD=2.3). [Personal 
Communication, Kathleen Yost, January, 2010). HRQL score differences of 1/3 
SD have previously been shown to be clinically meaningful in terms of their 
association with change in other important clinical indicators such as performance 
status, pain levels, and patient self-perceived change. (29) With a sample size of 

S1007 
Page 77 
Version Date 12/10/2021 
 
 
 
 
 
500, α = 0.025 (two primary HRQL outcomes: anxiety and utility scores) and a two-
sided test, power is .93 for detecting a 0.33 SD difference in anxiety and utility 
scores between the two arms. 
 
Sample size calculations for the EQ-5D are based on published identification of 
minimally important differences for its utility scores.  (30) Pickard et al. estimated 
that a minimally important difference for a EQ-5D utility score was .06 (US cancer 
patients, mixed cancer sites); the SD for the U.S. sample (mixed cancer sites 
including breast cancer) was 0.15. Therefore the 0.33 effect we are basing our 
sample size on is consistent with the minimally important difference identified for 
the ED-5D utility scores.   
 
The primary HRQL comparisons will occur at 6 months to evaluate the difference 
in anxiety and utility scores for patients receiving versus not receiving adjuvant 
chemotherapy. However, we will also use linear mixed model analysis to estimate 
change in anxiety and EQ-5D scores, but will monitor the influence of non-random 
missing data. (31) Should cohort plots and other diagnostic techniques suggest 
the presence of non-random missing data, we will use more appropriate analysis 
techniques such as pattern mixture models. (32)  Secondary, exploratory analyses 
will address the relationship between patient anxiety scores and several other 
outcomes: relationships with continuous measures such as the Decisional Conflict 
Scale scores and the Survivorship Concerns scores will be examined with 
correlations; relationships between a dichotomous form of the anxiety outcome 
and single items from the Oncotype DX® testing questions and items addressing 
barriers to randomization will be examined with chi-square tests. 
 
C. 
Comparative Effectiveness Analysis:  Backgound and Analysis Plan 
 
Background and Significance: Cost 
Direct expenditures on breast cancer were estimated to be about $6 billion in 1996 
(the last year such estimates were made), and are surely higher today. Gene 
expression profile (GEP) tests are expensive, costing approximately $4,000 per 
patient, yet adjuvant chemotherapy is much more expensive, costing $20,000 – 
$26,000 (upper ranges are closer to $50,000) (2003 dollars) (Oestreicher et al. 
Cancer 2005;104:2054-62). The immediate impact of GEP on breast cancer 
expenditures will depend on the degree to which the test spares women from 
undertaking costly chemotherapy. Based on current evidence regarding test 
outcomes, GEP could reduce initial breast cancer treatment costs by hundreds of 
millions of dollars. The long-term budget impact, however, will depend on the ability 
of the test to distinguish those who ultimately would experience breast cancer 
recurrence from those who would not. If GEP is a poor predictor of recurrence, the 
testing strategy could be more expensive than current practice while at the same 
time producing poorer outcomes. On the other hand, if GEP can better target 
women who will recur, risk profiling will substantially improve the cost-effectiveness 
of adjuvant therapy. The successful use of adjuvant chemotherapy in a highly 
targeted population thus represents a paradigm shift, both clinically and from an 
economic value standpoint. An accurate understanding of the changing economic 
value of adjuvant chemotherapy will be essential to ensure appropriate 
reimbursement policies. 
 
Given the proliferation of GEP tests, their potential role in clinical practice, and the 
national clinical and economic burden of breast cancer, quantitative evaluations of 
the economic outcomes associated with GEP are warranted. 
 
There have been two published cost-effectiveness evaluations of GEP for women 
with localized breast cancer. Both used simulation modeling and available data, 
but came to very different conclusions. One analysis, basing its estimates on the 
performance characteristics of Oncotype DX®, found that risk stratification using 

S1007 
Page 78 
Version Date 12/10/2021 
 
 
 
 
 
GEP would reduce cancer care costs and increase quality adjusted survival 
(Hornberger et al. Am J Manag Care 2005;11:476). The other based its analysis 
on the MammaPrint assay, and found that GEP increased costs and reduced 
quality-adjusted survival (Oestreicher et al. Genet Med 20057:380-9). While some 
might conclude that these analyses support the superiority of Oncotype DX® vs. 
MammaPrint, differences in the model structures and other input parameters in 
these studies make such conclusions tentative at best. Moreover, no study has 
evaluated costs and outcomes of GEP tests in the management of node positive 
breast cancer. 
 
Clinical trials evaluating medicines, medical devices and procedures now 
commonly assess economic value of these interventions. "Piggybacking" cost-
effectiveness analyses alongside clinical trials offers many advantages over ‘pure’ 
modeling approaches: combining studies is efficient; the internal validity of both 
studies is maximized, and; economic data is made available alongside clinical data 
in a timely fashion (Ramsey et al. Value Health 2005;8:521-33). A trial-based 
economic analysis will provide the most accurate estimates of the cost-
effectiveness of GEP. Decision makers in many countries now consider clinical 
and economic evidence together for formulary and insurance coverage policies, 
as will surely be the case for GEP. 
 
1.  
OBJECTIVES 
 
The primary objectives of the comparative effectiveness analyses are as follows: 
  
1)   
Determine short term (1 year) and longer term (3 years) direct medical 
care costs for women with 1-3 positive nodes, HR-positive HER2, negative 
breast cancer with low Oncotype Recurrence Scores  
a)  
managed with chemotherapy 
b)  
managed without chemotherapy 
2)  
Determine health state utilities for three health states related to the study 
(see Quality of Life section for details): 
a)  
Breast cancer, Recurrence Score unknown (one time point) 
b)  
Breast cancer, Recurrence Score known, no chemotherapy 
(multiple time points) 
c) 
Breast cancer, Recurrence Score known, chemotherapy (multiple 
time points) 
Using data from 1) and 2) and overall survival estimates from 
the trial, estimate the lifetime cost-effectiveness of Oncotype 
DX®-directed management vs. best alternative care (NIH 
guidelines) for women with 1-3 positive nodes, HR-positive 
HER2, negative breast cancer. Cost-effectiveness will be 
measured as cost per life-year gained and cost per quality-
adjusted life year (QALY) over a time horizon of 3 years (within-
trial analysis) and a lifetime (projections of cost and outcome 
modeled from the observed trial. 
 
A planned subgroup analysis is to estimate costs, QALYs and 
cost-effectiveness for two subgroups: (1) women for whom 
Medicare is their primary insurer (2) Women under age 65 with 
commercial insurance. 

S1007 
Page 79 
Version Date 12/10/2021 
 
 
 
 
 
 
2.   
RESEARCH DESIGN AND METHODS 
Conceptual framework and primary research hypothesis. The study will be 
conducted as cost-effectiveness analysis using life years gained (LYG) and 
quality-adjusted life years (QALYs) as measures of effectiveness. QALYs are an 
appropriate measure of outcome for this study because they capture most 
important health dimensions of the effects of an intervention, reflect preferences 
for health states under uncertainty, and facilitate comparison with other health care 
interventions whose effects have been evaluated using QALYs. (33,34) The Public 
Health Service’s Panel on Cost-Effectiveness in Health and Medicine recommends 
using QALYs as the measure of outcome for cost-effectiveness analysis. (35) The 
methods that will be used to estimate QALYs are described below. 
 
Costs and outcomes will be estimated using the health insurer perspective 
(secondary). Health insurers, who make the bulk of health care resource allocation 
decisions in the United States, generally consider only costs that they are directly 
accountable for when making resource allocation decisions for their insured 
populations.  To address a primary objective of the study, the cost-effectiveness 
of OncotypeDX versus Usual Care will be calculated as follows: 
(CODx – CUC)/(QALYODx –QALYUC) 
 
Here, C denotes the direct health care costs, and QALY denotes quality-adjusted 
life years for Oncotype DX® (ODx) and Usual Care (UC), respectively. Costs and 
QALYs will be calculated for a 3-year time horizon (the maximum observation 
period possible for S1007).  Future costs and QALYs will be discounted to their 
present value on the date of the intervention.  
 
Cost-effectiveness alongside clinical trials.  Prospective measurement of 
economic and health outcome data alongside randomized clinical trials (RCTs) to 
support has become increasingly common in recent years.  There are two main 
advantages.  First, this procedure is an efficient and timely way to obtain clinical, 
economic, and health-related quality of life, health state preference data 
simultaneously.  Timely economic data will be particularly useful to those who are 
responsible for health care budgets, since as mentioned above, rapid and 
extensive growth in the use of Oncotype DX® can be expected if the results are 
positive.  Second, a randomized, controlled trial has high internal validity and low 
potential for bias. On the other hand, RCTs have disadvantages for cost-
effectiveness analysis.  First, RCTs tend to have low external validity due to their 
restrictive inclusion/exclusion criteria and carefully selected settings. Second, 
artificially close monitoring and many protocol-induced procedures are part of the 
study. These factors may distort the economic and health outcome data relative to 
what one may expect under real-world conditions. Finally, limited follow-up periods 
that are common in a clinical trial may not be sufficient to directly estimate 
outcomes that are important for the cost-effectiveness analysis (e.g., a lifetime). 
Because of these issues, the estimates of cost-effectiveness obtained from the 
S1007, will represent a best-case scenario.   
 
 

S1007 
Page 80 
Version Date 12/10/2021 
 
 
 
 
 
Estimating direct medical care costs.  Direct health care costs include the value of all 
health care resources, non-health care resources, informal caregiver time, and the value 
of patient treatment time utilized over the time horizon of interest.  The cost of care is 
determined as the product of the number of units of each item consumed and the unit value 
assigned to that product or service.  Detailed elements of each cost category are described 
below.  Note that these equations do not include the cost of working time lost to treatment. 
Cost of working time will be excluded from the primary analysis. 
 
Total Medical Care Costs.  The elements included in this category include all hospital, 
physician, laboratory, durable medical equipment, medications, home health and skilled 
nursing facility (SNF) care. Services will be valued using based on nationally standardized 
Medicare reimbursement rates. Sources and methods for collecting these costs are 
detailed in this section.  
 
Medicare enrollees: The Medicare files will be the main source of data on the utilization of 
health care resources for trial enrollees ages 65 and higher.  Medicare files provide data 
on hospital, physician, laboratory, and home health care services, durable medical 
equipment, infused or injected pharmaceuticals, outpatient medications and some skilled 
nursing facility (SNF) care.  The Medicare Claims History Files contain patient identifying 
information, date of service, and complete utilization information for every Medicare-
covered service submitted for payment by providers or patients under the Medicare 
traditional fee-for-service program.  CMS’s Bureau of Data Management and Strategy has 
established methods for creating analytic files on individual beneficiaries.  Files will be 
created annually covering all enrollees and Medicare registrants in the trial from the day of 
registration. 
 
Hospital Inpatient:  Expenditures for hospitalizations will be valued according to DRG codes 
assigned 
on 
the 
patient’s 
discharge 
abstract. 
Site-specific 
urban/rural, 
and 
teaching/nonteaching multipliers for the year 2011 will be applied, as defined by the CMS. 
 
Outpatient Technical Services: Each service provided (coded by revenue center on the 
UB-92) will be mapped into a Medicare cost-reporting department.  The Medicare Hospital 
Cost Reporting Information System (HCRIS) files for each year will be used to convert 
charges into costs using department-level cost-to-charge ratios reported annually by every 
Medicare-participating hospital.  The Medicare cost-reporting data are available in public 
use tapes approximately 2 years after the cost-reporting period ends.  Therefore, to avoid 
delay in publication after the final study year, department-level cost-to-charge ratios will be 
estimated from the historical average over the first 3 years of the study. 
 
Physician Services:  The Resource-Based Relative Value System (RBRVS) Medicare fee 
schedule value in the year 2011 for each CPT-4 code under which physician’s bill will be 
the basis for unit cost of each specific billed physician service. 
 
Laboratory and Other Part B Services:  National 2011 Medicare average allowed amounts 
recorded for each Medicare-covered service (HCPCS Level I and Level II coding system) 
in the Medicare Part B file will be used to estimate the cost of all Medicare Part B services 
except physicians. 
 
Skilled Nursing Facilities:  National 2011 average allowed daily rate for payment of nursing 
home care will be used to assign SNF unit costs. 
Home Health and Hospice Services:  National 2011 Medicare fee schedules for payment 
of home health visits will be used to estimate these costs. 
 
Outpatient Prescription Drugs:  National average Medicare Part D 2011 reimbursements 
for outpatient medicines will be used for this analysis. 
 
Long-Term Institutional Nursing Home Care:  Medicare covers skilled nursing facilities for 
a limited period post-hospitalization, but long-term residence in a nursing home is not 

S1007 
Page 81 
Version Date 12/10/2021 
 
 
 
 
 
covered.  The history and physical form administered to trial enrollees during the follow-up 
period will contain a checklist item for current residence as follows: private home; 
retirement home; nursing home; hospital.  If the patient was a nursing home resident at the 
previous follow-up visit, it will be assumed that he or she was a nursing home resident for 
the entire period.  If not, then it will be assumed that the patient entered the nursing home 
at the midpoint of the follow-up period.  Medicare SNF claims will be compared with patient 
responses to avoid double counting of costs.  The unit (daily) cost of nursing home care 
will be valued at the Medicare SNF daily rate. 
 
Commercially Insured Patients 
Due to the large number of commercial insurance plans in the United States and the 
national scope of this study, it is not feasible to obtain health insurance records for all 
commercially insured patients. Rather, we will identify the most common commercial 
insurance carriers for trial enrollees and obtain claims records directly from those plans. 
Four health insurance groups—Blue Cross/Blue Shield Association Plans, Aetna, 
UnitedHealth, and CIGNA—insure more than 70% of all working age individuals and their 
families in the United States. We expect that approximately the same proportion of trial 
enrollees will have one of these plans as their primary insurer.  
 
Obtaining Health Insurance Records: 
Medicare and commercial enrollees will be asked to provide their Medicare identification 
(HIC) or commercial plan identification information as part of study enrollment and consent. 
Identifiers for those who provide consent will be used to obtain insurance claims for a period 
from 1 year prior to study enrollment through death or end of the follow-up period. We will 
exclude patients enrolled in Medicare Advantage (capitation) or commercial HMO plans 
because individual-level service claims will not be available for these individuals. 
 
Measurement of quality-adjusted life years (QALYs).  The S1007 clinical protocol calls 
for measurement of health-related quality of life using the EQ-5D questionnaire.  The EQ-
5D is a validated measure with several domains of health status. (36,37) Population-based 
preference weights have been derived for each EQ-5D domain that permit translation of 
functional status scores to utility weights that may be used to derive QALYs. (38,39) 
 
Survival estimates for patients in each trial arm will be combined with utility weights to 
determine QALYs for the arms of the study.  To create uniform periods of utility and 
survival, S1007 trial patient survival rates will be computed for each observation period 
covered the EQ-5D.  The method for estimating QALYs from survival and utility data is 
discussed below. 
 
Statistical Methods and Data Analysis.   
Estimating Mean Costs for OncotypeDX+nochemotherapy and OncotypeDX+ 
chemotherapy.  In order to minimize bias in the cost estimates, two important issues must 
be addressed: (1) the problem of censoring; and (2) that a number of patients will incur 
extremely high costs of care, resulting in skewed data.  Ideally, one would measure lifetime 
costs for patients in each study arm, but the finite observation period and continuous 
enrollment throughout the study will result in the cost histories being truncated (censored) 
for many patients.  Censoring and skewedness can be addressed by using the Kaplan-
Meier sample average estimation (KMSA) technique described by Etzioni and colleagues. 
Using monthly cost histories from the patients in each study arm, the KMSA technique 
determines the mean cost over the time period of interest as: 
 
 
 
where Si denotes the probability of the event occurring in the time period i and ci is the 
average cost among patients experiencing the event in time period i.  The probability of the 
event occurring is a function of the probability of surviving to the start of the time period i, 

S1007 
Page 82 
Version Date 12/10/2021 
 
 
 
 
 
as determined by Kaplan-Meier survival analysis.  Lin et al demonstrate that the KMSA 
estimator is unbiased and consistent so long as (1) censoring is independent in time and 
(2) the time intervals for the cost analysis are sufficiently narrow. The design of the 
treatment trial is consistent with independent censoring.  Monthly cost records are available 
from Medicare, thus providing appropriately narrow time intervals.  Lin et al also show that 
the KMSA estimator is asymptotically normal with easily estimated variances, permitting 
standard two-sample parametric testing.  Thus, the KMSA estimator also has the 
advantage of overcoming the problems of statistical testing of skewed data. 
  
 
Using KMSA, 1-year and 3-year average cumulative costs with confidence intervals for 
each treatment arm will be computed.  Future costs will be adjusted for inflation to constant 
dollars and discounted to net present value using a discount rate of 3 percent prior to 
calculating M.  Cumulative costs will be plotted for 1- and 3-year time intervals for each 
study arm, with standard error bars for each interval. The Bonferroni method will be used 
to adjust for multiple comparisons among the treatment arms.  Confidence intervals for 
incremental costs (i.e., absolute differences in the mean 3-year cost) will also be reported. 
 
Estimating QALYs.   
Quality-adjusted life years can be estimated in a manner similar to that which is used to 
described costs (see above).  To estimate QALYs (), utility weights are combined with 
survival at each point of measurement across the period of interest using the following 
formula, as described in Ramsey et al. 
 
 
 
Where i is the width of the interval i, xi and xi+1 and the sample average utility weights, 
and Si and S i+1 are the estimated survival probabilities at i and i+1, respectively.  As with 
costs, future QALYs will be discounted to their present value at a rate of 3% per annum. 
 
Estimating Incremental Costs Per QALY.  
Using the 3-year estimates for cumulative costs and QALYs in each treatment arm derived 
as described above, we will compute the incremental cost per QALY for the all study 
participants and the specified subgroups 
 
Uncertainty Analysis.   
One-way uncertainty analyses will be conducted to identify model parameters that have 
the greatest impact on the results presented as a tornado diagram. Multi-way uncertainty 
analysis will be conducted to represent overall uncertainty around the estimates of clinical 
and economic effectiveness using probabilistic sensitivity analysis (PSA). The PSA will be 
completed using a second-order Monte Carlo simulation with 50,000 runs and appropriate 
parameter distributions. ICER results will be presented on the cost-effectiveness plane and 
as acceptability curves with willingness-to-pay (WTP) thresholds of $25,000, $50,000, 
$75,000 and $100,000 marked for reference.  The uncertainty of cost per unit of outcome 
results for other endpoints (e.g. lives saved) will be presented as 95% confidence intervals. 
Again, threshold sensitivity analyses will also be completed to identify specific conditions 
under which the overall cost-effectiveness result would change.  
 
Missing Data.   
As with all clinical trials, missing data can be expected for S1007 trial participants.  Although 
Medicare claims records are expected to be complete for all participants, it is likely that 
some patient records will have incomplete health care utilization data (for services not 
covered by Medicare) and quality of life estimates.  Imputation methods used for the 
primary clinical endpoints will be used to generate inputs for missing data elements. The 
method of imputation will vary depending on whether or not the missing data are believed 
to occur at random.  This is difficult to know ex ante. It seems likely, however, that the 

S1007 
Page 83 
Version Date 12/10/2021 
 
 
 
 
 
likelihood of missing quality of life data may be a function of the patients health status (i.e., 
sicker patients will be less likely to complete the questionnaires). Logistic regression will 
be used to test the correlation between missing parameters and patient characteristics 
[dependent variable: missing response (Y/N)].  
 
Mid-study Analysis 
To ensure that the complex task of analyzing the cost-effectiveness data runs smoothly 
and quickly at the end of the study, a mid-study "mock analysis" will be conducted where 
claims, EQ-5D, and survival data are merged and analyzed to produce an incremental 
analysis. To protect from revealing the results of the study at this point, SWOG analysts 
will remove actual patient assignment information and randomly assign enrollees to 
treatment and control arms prior to analysis. 
 
REFERENCES 
 
1  
Cella D, Yount S, Rothrock N, Gershon R, Cook K, Reeve B, Ader D, Fries JF, 
Bruce B, Rose, M, on behalf of the PROMIS Cooperative Group.  The Patient-
Reported Outcomes Measurement Information System (PROMIS).  Progress of an 
NIH roadmap Cooperative Group during its first two years.  Med Care 
2007;45(5(Suppl1): S3-S11. 
 
2  
Leedham B, Ganz PA.  Psychosocial concerns and quality of life in breast cancer 
survivors.  Cancer Investigation 1999;17(5):342-348. 
 
3  
Vickberg SMJ.  The concerns about Recurrence Scale(CARS): A systematic 
measure of women’s fears about the possibility of breast cancer recurrence.  Ann 
Behav Med 2003;25(1):16-24; Lee-Jones C, Humphris G, Dixon R, Hatcher MB.  
Fear of cancer recurrence—A literature review and proposed cognitive foumulation 
to explain exacerbation of recurrence fears.  Psychooncology 1997;6:95-105. 
 
4  
Lee-Jones C, Humphris G, Dixon R, Hatcher MB.  Fear of cancer recurrence—A 
literature review and proposed cognitive formulation to explain exacerbation of 
recurrence fears.  Psychooncology 1997;6:95-105. 
 
5  
Duric V, Stockler M.  Patients’ preferences for adjuvant chemotherapy in early 
breast cancer: A review of what makes it worthwhile.  Lancet Oncol 
2001;2(11):691-697. 
 
6  
Lo SS, Mumby PB, Norton J, Rychlik K, Smerage J, Kash J, Chew HK, Gaynor 
ER, Hayes DF, Epstein A, Albain KS.  Prospective multicenter study of the impact 
of the 21-Gene Recurrence Score assay on medical oncologist and patient 
adjuvant breast cancer treatment selection.  J Clin Oncol 2010;28(10):1671-1676. 
 
7  
Cella D, Yount S, Rothrock N, Gershon R, Cook K, Reeve B, Ader D, Fries JF, 
Bruce B, Rose, M, on behalf of the PROMIS Cooperative Group.  The Patient-
Reported Outcomes Measurement Information System (PROMIS).  Progress of an 
NIH roadmap Cooperative Group during its first two years.  Med Care 
2007;45(5(Suppl1): S3-S11. 
 
8  
Pickard AS, Wilke CT, Lin H-W, Lloyd A.  Health utilities using the EQ-5D in studies 
of cancer.  Pharmacoeconomics 2007;25(5):365-384. 
 
9  
Panel State of the Science Panel.  National Institutes of Health State-of-the-
Science Conference Statement: Symptom management in cancer: Pain, 
depression, and fatigue, July 15-17, 2002.  J Natl Cancer Inst 2003;95(15):1110-
1117. 
 

S1007 
Page 84 
Version Date 12/10/2021 
 
 
 
 
 
 
 
10  
Mar Fan HG, Houédé-Tchen N, Qi-Long Y, Chemerynsky I, Downie FP, Sabate K, 
Tannock IF.  Fatigue, menopausal symptoms, and cognitive function in women 
after adjuvant chemotherapy for breast cancer: 1- and2-uear follow-up of a 
prospective controlled study.  J Clin Oncol 2005;23(31):8025-8032. 
 
11  
Bower JE, Ganz PA, Desmond KA, Rowland JH, Meyerowitz B, Belin TR.  Fatigue 
in breast cancer survivors: occurrence, correlates, and impact on quality of life.  J 
Clin Oncol 2000;18(4):743-753. 
 
12  
Schagen SB, van Dam F S, Muller M J, Boogerd W, Lindeboom J, Bruning PF.  
Cognitive deficits after postoperative adjuvant chemotherapy for breast carcinoma.  
Cancer 1999:85:640-50. 
 
13  
Van Dam FS, Schagen SB, Muller MJ, Boogerd W, van der Wall E, Droogleever 
Fortuyn ME, Rodenhuis S.  Impairment of cognitive function in women receiving 
adjuvant treatment for high-risk breast cancer: high-dose versus standard-dose 
chemotherapy.  J Natl Cancer Inst.  1998;90:210-218. 
 
14  
Donovan KA, Small BJ, Andrykowski MA, Schmitt FA, Munster P, Jacobsen PB.  
Cognitive functioning after adjuvant chemotherapy and/or radiotherapy for early-
stage breast carcinoma.  Cancer 2005;104(11):2499-2507. 
 
15  
Vardy J, Wefel JS, Ahles T, Tannock IF, Schagen SB.  Cancer and cancer-therapy 
related cognitive dysfunction: an international perspective from the Venice 
cognitive workshop.  Ann Oncol 2008;19(4):623-629, p. 624. 
 
16  
Cella D, Yount S, Rothrock N, Gershon R, Cook K, Reeve B, Ader D, Fries JF, 
Bruce B, Rose, M, on behalf of the PROMIS Cooperative Group.  The Patient-
Reported Outcomes Measurement Information System (PROMIS).  Progress of an 
NIH roadmap Cooperative Group during its first two years.  Med Care 
2007;45(5(Suppl1): S3-S11. 
 
17  
Garcia DG, Vrlls F, Vlsudrt DN, Glynn KR, Lad T, Lai J-S, Reeve BB, Wilder Smith 
A, Stone AA, Weinfurt K.  Standardizing patient-reported outcomes assessment in 
cancer clinical trials: A Patient-Reported Outcomes Measurement Information 
System initiative.  J Clin Oncol 2007;25(32):5106-12. 
 
18  
Cheung K, Oemar M, Oppe M, Rabin R, on behalf of the EuroQol Group  EQ-5D.  
User Guide.  Basic information on how to use EQ-5D.  Euroqol Group, 2009. 
 
19  
Krabbe PF, Peerenboom L, Langenhoff BS, Ruers TJM.  Responsiveness of the 
generic EQ-5D summary measure compared to the disease-specific EORTC QLQ 
C-30.  Qual Life Res.  2004;13:1247-1253. 
 
20  
Pickard AS, Wilke CT, Lin H-W, Lloyd A.  Health utilities using the EQ-5D in studies 
of cancer.  Pharmacoeconomics 2007;25(5):365-384. 
 
21  
Cheung K, Oemar M, Oppe M, Rabin R, on behalf of the EuroQol Group  EQ-5D.  
User Guide.  Basic information on how to use EQ-5D.  Euroqol Group, 2009. 
 
22  
Gotay CC, Pagano IS.  Assessment of survivor concerns (ASC): A newly proposed 
brief 
questionnaire. 
 
Health 
Qual 
Life 
Outcomes. 
 
2007;5:15 
[http://www.hqlo.com/content/5/1/15]. 
 
 

S1007 
Page 85 
Version Date 12/10/2021 
 
 
 
 
 
 
23  
Cella D, Yount S, Rothrock N, Gershon R, Cook K, Reeve B, Ader D, Fries JF, 
Bruce B, Rose, M, on behalf of the PROMIS Cooperative Group.  The Patient-
Reported Outcomes Measurement Information System (PROMIS).  Progress of an 
NIH roadmap Cooperative Group during its first two years.  Med Care 
2007;45(5(Suppl1): S3-S11. 
 
24  
Garcia DG, Vrlls F, Vlsudrt DN, Glynn KR, Lad T, Lai J-S, Reeve BB, Wilder Smith 
A, Stone AA, Weinfurt K.  Standardizing patient-reported outcomes assessment in 
cancer clinical trials: A Patient-Reported Outcomes Measurement Information 
System initiative.  J Clin Oncol 2007;25(32):5106-12. 
 
25  
Yost KJ, Eton DT.  Combining distribution-and anchor-based approaches to 
determine minimally important differences.  The FACIT experience.  Eval Health 
Prof 2005;28(2):172-191. 
 
26  
Christodoulou C, Junghaenel DU, DeWalt DA, Rothrock N, Stone AA.  Cognitive 
interviewing in the evaluation of fatigue items: Results from the patient-reported 
outcomes measurement information system (PROMIS).  Qual Life Res 
2008;17(10):1239-46. 
 
27  
Lo SS, Mumby PB, Norton J, Rychlik K, Smerage J, Kash J, Chew HK, Gaynor 
ER, Hayes DF, Epstein A, Albain KS.  Prospective multicenter study of the impact 
of the 21-Gene Recurrence Score assay on medical oncologist and patient 
adjuvant breast cancer treatment selection.  J Clin Oncol 2010;28(10):1671-1676. 
 
28  
Lo SS, Mumby PB, Norton J, Rychlik K, Smerage J, Kash J, Chew HK, Gaynor 
ER, Hayes DF, Epstein A, Albain KS.  Prospective multicenter study of the impact 
of the 21-Gene Recurrence Score assay on medical oncologist and patient 
adjuvant breast cancer treatment selection.  J Clin Oncol 2010;28(10):1671-1676. 
 
29  
Yost KJ, Eton DT.  Combining distribution-and anchor-based approaches to 
determine minimally important differences.  The FACIT experience.  Eval Health 
Prof 2005;28(2):172-191. 
 
30  
Pickard AS, Wilke CT, Lin H-W, Lloyd A.  Health utilities using the EQ-5D in studies 
of cancer.  Pharmacoeconomics 2007;25(5):365-384. 
 
31  
Laird NM, Ware JH.  Random-effects models for longitudinal data.  Biometrics 
1982;38:963-974. 
 
32  
Hogan JW, Laird NM.  Mixture models for the joint distribution of repeated 
measures and event times.  Stat Med 1997;16:239-257. 
 
33  
Patrick DL, Erickson P. Health Status and Health Policy: Quality of Life in Health 
Care Evaluation and Resource Allocation. New York: Oxford University Press, 
1993. 
 
34  
Garber AM, Phelps CE. Economic Foundations of cost-effectiveness analysis. J of 
Health Economics 1997;16:1-31. 
 
35  
Gold MR, Russell LB, Siegel JE, Weinstein MC. Cost-Effectiveness in Health and 
Medicine. 1996 :425. 
 
 

S1007 
Page 86 
Version Date 12/10/2021 
 
 
 
 
 
 
36  
Ries AL, Kaplan RM, Limberg TM, Prewitt LM. Effects of pulmonary rehabilitation 
on physiologic and psychosocial outcomes in patients with chronic obstructive 
pulmonary disease. Ann-Intern-Med 1995;122(11):823-32. 
 
37  
Squier HC, Ries AL, Kaplan RM, Prewitt LM, Smith CM, Kriett JM, Jamieson SW. 
Quality of well-being predicts survival in lung transplantation candidates. Am-J-
Respir-Crit-Care-Med 1995;152(6 Pt 1):2032-6. 
 
38  
Kaplan R, Anderson J. The quality of well-being scale: rationale for a single quality 
of life index. In: Walker S, Rosser R, eds.  Quality of life: assessment and 
application.  (Vol. I). London: MTP Press, 1988, pp.51-77. 
 
39  
Kaplan R, Anderson J.   Quality of life assessment: key issues in the 1990s.  (Vol. 
I). London: Kluver Academic Publishers, 1993, pp.65-94. 
 

S1007 
Page 87 
Version Date 12/10/2021 
 
 
 
18.2 
Prospective Validation of Other Prognostic/Predictive Indices of Breast Cancer Outcomes 
and Evaluation of Pre-treatment Hormone Levels 
 
a. Objectives 
 
1. To perform other molecular assays or test other signatures that measure prognosis 
and potential benefit of chemotherapy and compare them to Oncotype DX®. 
 
2. To determine the role of other assays as predictors of DFS, DDFS and LDFI for 
patients randomized to chemotherapy versus no chemotherapy. 
 
3. To compare clinically reported menopausal status with status categorized by 
serum hormone levels determined from baseline serum in women under age 55 
years and to assess subsequent association with outcomes. 
 
b. Background and Rationale for Additional Biomarker Analysis  
 
Gene Expression Based Prognostic and Predictive Markers in Hormone 
Receptor Positive Breast Cancer 
 
Although in S1007 the 21-gene RS was used for patient stratification, several other 
gene expression signatures are commonly used as prognostic/predictive markers 
including 70-gene MammaPrint signature and PAM50 gene intrinsic subtype, SET 
index, Endopredict and Breast cancer index. Some of these expression profiles are 
described below.  
 
While comparison amongst genomic assays was performed in the TransATAC trial, 
generalizability concerns of these analyses include the study was limited to 
postmenopausal patients and patients did not receive chemotherapy (1, 2). There 
remains an unmet need to identify predictors of chemotherapy benefit within 
premenopausal as well as postmenopausal patients. Molecular analysis will allow for 
testing of prognostic and predictive biomarkers in patients who received chemotherapy 
on the same platform across the entire patient cohort, and will determine the underlying 
biological differences between premenopausal and postmenopausal patients.  
 
Brief description of additional assays and signatures 
 
70-gene MammaPrint signature: MammaPrint is a 70-gene signature which 
classifies tumors into groups that are associated with a good or poor prognosis on the 
basis of distant metastasis-free survival (DMFS) at 5 years and at 10 years. (3) Among 
the 658 women with HR+/HER2-, N1 breast cancers in the MINDACT (Microarray in 
Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy) 
trial who had clinical high but genomic low risk as determined by the 70-gene 
MammaPrint assay (Agendia) there was a 2.6% improvement in 8-year DMFS with 
chemotherapy. (4, 5) An exploratory subgroup analysis demonstrated an age-
dependent effect of chemotherapy, in which the magnitude of chemotherapy benefit 
reached 5% in women age <50 and <1% benefit if age >50. 
 
PAM50 signature: Gene expression profiling classifies breast cancer into “intrinsic 
subtypes” based on the biology of the underlying disease pathways. (6)   This has been 
developed as Prediction Analysis of Microarray 50 (PAM50) Risk of Recurrence (ROR) 
score (Veracyte Technologies, previously Prosigna). The ROR Score was validated to 
determine the risk of recurrence of disease in HR+ breast cancer after surgery and 
treatment with 5 years of endocrine therapy. The ROR score depends on the intrinsic 
subtype, proliferation score of the tumor, and the tumor size. (7, 8, 9) 

S1007 
Page 88 
Version Date 12/10/2021 
 
 
 
 
 
 
SET ER/PR and SET2,3 index: Sensitivity of endocrine therapy (SET) ER/PR index 
was developed to measure gene expression microarray probe sets that associate with 
hormone receptors (ESR1 and PGR). Higher SET ER/PR index in MBC samples 
predicted improved PFS and OS when patients received endocrine therapy as next 
treatment, even after adjustment for clinical-pathologic risk factors (PFS: HR 0.534, 
95% CI 0.299 to 0.955, p = 0.035; OS: HR 0.315, 95% CI 0.157 to 0.631, p = 0.001). 
(10)  SET2,3 index was proposed as a test for sensitivity to adjuvant endocrine therapy 
for patients with stage II-III breast cancer by measuring transcription related to 
estrogen and progesterone  receptors (SET ER/PR index) adjusted for a baseline 
prognostic index combining clinical tumor and nodal stage with molecular subtype by 
RNA4 (ESR1, PGR, ERBB2, and AURKA). In HR+ patients who underwent 
neoadjuvant therapy, SET2,3 index was found to add independent prognostic 
information in addition to residual cancer burden in two separate cohorts (11).  
 
EndoPredict (EP; Myriad Genetics, Cologne, Germany): EndoPredict (EP) is an RNA 
based multigene test that predicts the likelihood of distant recurrence in patients with 
HR+ breast cancer being treated with adjuvant endocrine therapy. In the GEICAM 
9906 trial, EP was an independent prognostic parameter in node-positive, HR+ breast 
cancer patients treated with adjuvant chemotherapy followed by hormone therapy (12, 
13). The EP assay is based on the quantification of eight cancer-related genes of 
interest and three reference genes. 
 
Breast Cancer Index (BCI; Biotheranostics,San Diego, CA): The Breast Cancer Index 
test analyzes the activity of seven genes to help prognosticate the risk of recurrence 
in patients with HR+ breast cancer 5 to 10 years after diagnosis. BCI can be used for 
prediction with the benefit of extended adjuvant endocrine therapy (14, 15).  
 
Genomic Alteration in Breast Cancer as Prognostic Markers 
 
Genomic characterization of breast cancer has become standard of care for metastatic 
breast cancer (MBC) patients with HR+ cancer. There is already one therapy FDA-
approved linked to a genomic biomarker for MBC: PI3K inhibitor alpelisib in 
combination with endocrine therapy for PIK3CA mutant HR+ breast cancer. There are 
several other genomically matched therapies under investigation in MBC, with 
expected increase in clinical utility of genomic testing in MBC. 
 
Although genomic testing is not standard of care in non-metastatic breast cancer, we 
and others have already demonstrated that several key genomic alterations are 
associated with an increased risk of relapse and/or endocrine resistance in HR+ breast 
cancer including TP53 mutations, (16) and alterations in MAPK pathway such as NF1 
loss (17, 18, 19). Notably, ESR1 mutations have also been associated with endocrine 
resistance but this has been primarily found in metastatic tumors, as a mechanism of 
acquired resistance (20).  
 
Taken together, there are several different prognostic signatures already developed 
for HR+ breast cancer and many genomic features associated with recurrence. We 
hypothesize that three established prognostic signatures (21-gene signature, breast 
cancer intrinsic subtype and 70-gene signature) based on RNAseq are associated with 
prognosis in premenopausal and postmenopausal patients with 1-3 LN+. Prognostic 
endpoints include IDFS, DDFS, LDFS, and OS. We also hypothesize that these 
prognostic signatures alone or integrated together will predict chemotherapy benefit in 
premenopausal patients with 1-3 LN+. The prognostic and predictive value may be 
further enhanced with integration of additional gene expression sets (e.g., SET2,3, 
RNA4 index, MKI67 gene expression) and breast cancer genomics and proteomics. 

S1007 
Page 89 
Version Date 12/10/2021 
 
 
 
 
 
Baseline serum hormone levels  
 
In addition to clinical characteristics, serum hormone levels may be able to further 
discriminate menopausal status. Beyond self-reporting of menopausal status, serum 
levels can offer an objective measure. The mean age at onset of menopause is 51 
years in Western countries, and by age 55 approximately 85% of women have 
undergone menopause, whereas less than 10% of women experience menopause at 
or before age 45 (21, 22). In clinical practice, estradiol, luteinizing hormone, and follicle-
stimulating hormone are often evaluated for determination of whether a patient is pre- 
or post-menopausal. Anti-Müllerian Hormone (AMH), also called Müllerian inhibiting 
factor (MIF) is an additional indicator available as to whether a woman is approaching 
or is likely to have reached her final menstrual period. Given that there is a significant 
interaction between menopausal status, as determined by clinical characteristics, and 
IDFS and DDFS in RxPONDER, we propose evaluating hormone levels in pre-
treatment baseline samples to assess whether menopausal status is further refined 
and whether an interaction term remains statistically significant based upon 
menopausal status per serum hormone levels. 
 
c. Tumor Tissue 
 
For all of the translational medicine studies specified below, specimens will be 
collected and banked at the SWOG Biospecimen Bank – Lab #201, Solid Tissue, 
Myeloma and Lymphoma Division. Integrated DNA/RNA will be performed for available 
tissue samples. Matching blood or normal tissue will be analyzed to facilitate identifying 
somatic vs germline variants on whole exome sequencing.     
 
1. Prospective validation of other prognostic/predictive indices of breast cancer 
outcomes 
 
We will collect one paraffin block of the primary tumor, one positive lymph node 
block, and one negative lymph node block in all patients. Slides will be obtained 
when blocks are not available or feasible to obtain. 
 
A prospective clinical trial of these characteristics is the perfect setting to validate 
other available molecular signatures that have been previously associated with 
prognosis or therapy benefit. Although performing different assays has some 
advantages, it is tissue intensive and will limit the number of different signatures 
that can be tested. Therefore, we will perform integrated analysis with RNAseq and 
whole exome sequencing, and will test different signatures and their 
prognostic/predictive role.  
 
a. Prognostic and predictive role of three established breast cancer prognostic 
signatures  
 
Prognostic and predictive role of three established breast cancer prognostic 
signatures (21-gene signature, breast cancer intrinsic subtype, and 70-gene 
signature) based on RNAseq are associated with prognosis and 
chemotherapy benefit. Though assessment of alternate gene expression 
signatures is a pre-planned secondary objective, tissue limitations will not 
allow us to perform each individual assay, thus we will perform transcriptional 
profiling on archival primary tumor tissue using RNAseq (GEM Extra assay). 
We will estimate the 21-gene recurrence score (RS), 70-gene MammaPrint 
signatures, and the PAM50 subtype using data from the RNAseq and assess 
whether these signatures are associated with invasive breast cancer–free 
survival (IBCFS) and DDFS. We will also compare the 21-gene signature 
estimated through RNAseq with that of Oncotype DX® RS score. 
 

S1007 
Page 90 
Version Date 12/10/2021 
 
 
 
 
 
We use the STEEP 2.0 definition (Tolaney, et.al., JCO 2021) of invasive breast 
cancer-free survival (IBCFS). Time from date of randomization (2nd 
Registration) to date of first invasive recurrence (local, regional or distant), 
second invasive breast cancer, or death due to any cause.  Patients last known 
to be alive who have not experienced recurrence or second breast cancer are 
censored at their last contact date. This is similar to IDFS except that new non-
breast primary cancers are not included as events (23). 
 
b. Prognostic/predictive value of other available signatures  
 
We will assess whether other established models and signatures are 
prognostic and predictive of chemotherapy benefit. The following signatures 
will be evaluated: SET2,3, RNA4 index, MKI67 gene expression, the hypoxia 
signature, 12-gene EndoPredict signature, and 7-gene breast cancer index. 
The prognostic and predictive role of these signatures will be assessed alone 
and in combination with the intrinsic subtype. In addition, we will assess the 
association of genomic alterations (TP53 mutations, PIK3CA mutations, 
MAPK pathway alterations) with IBCSF and DDFS in order to determine the 
role of integrated DNA/RNA analysis. 
 
Notably, we will assess the prognostic and predictive role of different gene sets 
rather than derive formal scores corresponding to different commercial assays.  
Please see below for description of use of principal component analysis to 
derive “pseudoscores” with different gene sets.  
 
c. Description of assay  
 
We will perform RNAseq and whole exome sequencing with the Exact 
Sciences Corporation’s GEM ExTra assay. The GEM ExTra assay 
interrogates exonic sequences from 19,396 genes and 169 introns known to 
harbor cancer-related translocations. Using KAPA Hyper library construction 
and an IDT bait-capture solution, these sequences (collectively referred to as 
the exome, herein) are selected, amplified and prepared for sequencing on an 
Illumina NovaSeq 6000 instrument. Importantly, both DNA from the tumor 
tissue and an accompanying germline sample (saliva or blood) are sequenced, 
enabling the discovery of polymorphisms that are somatic in nature. In parallel, 
KAPA RNA libraries are constructed from the cancer’s total RNA and 
sequenced on the same Illumina platform. To preserve tissue, DNA and RNA 
are co-extracted from the same material, using Covaris’ truXTRAC kits, which 
we have found to improve our ability to extract high quality RNA from FFPE 
specimens. 
 
GEM ExTra is validated for use with FFPE or freshly frozen tissue specimens. 
We anticipate using FFPE tissue sections that will be assessed by a board-
certified anatomic pathologist and marked for manual microdissection if there 
is less than 50% tumor compared to metabolically active tissues per the 
Genomic Health, Inc SOP used to handle all RxPONDER samples used for 
Recurrence Score testing.  
 
 
 

S1007 
Page 91 
Version Date 12/10/2021 
 
 
 
 
 
d. Statistical Plan  
 
1. Clinical Endpoints and the biomarker measurements involved in the 
analysis. 
 
The primary outcome of the trial was invasive disease-free survival (IDFS) 
with distant disease-free survival (DDFS) as secondary. We propose to 
use invasive breast cancer–free survival (IBCFS) as described in STEEP 
2.0 which excludes non-breast new primaries as events, but includes all 
other IDFS event types. This sharpens the evaluation of chemotherapy 
benefit. Each biomarker is constructed from the sequencing analysis. 
 
2. Case selection method if only a subset of patients will be included in the 
biomarker evaluation. 
 
Patients from UNICANCER (n=1014) are excluded since tissue samples 
were not submitted to the Nationwide repository. Tissues from GEICAM 
patients (n=762) have been submitted to Nationwide recently, but have not 
yet been integrated into the inventory so we cannot specify yet how many 
patients are included. Of the remaining 3,071 eligible patients, 2,959 
(96.4%) have available tissue.  
 
3. Numbers of patients to be studied and biomarker assays/tests to be 
performed. 
 
All patients with tissue are included. Case-cohort approaches could 
reduce the number of assays, but events continue to occur so it is wiser 
to include all from the start. Only the GEM ExTra assay is performed and 
all signatures are computed across that common platform. 
 
4. Statistical analysis methodology and underlying assumptions. 
 
For this restricted sample the number of IBCFS events are currently 96 
and 222 for premenopausal and postmenopausal women, respectively. (In 
contrast, for IDFS there are 106 and 274 events, showing that many IDFS 
events in postmenopausal women were other cancers and equally 
distributed by treatment group.) Median follow-up time is approximately 
6.1 years in this cohort. IBCSF hazard ratios (HRs) in favor of 
chemotherapy are 0.69 (95% CI 0.46-1.04) and 0.99 (95% 0.76-1.29), for 
premenopausal and postmenopausal patients respectively. 
 
All analyses use IBCSF or DDFS measured from randomization in ITT Cox 
regression analyses adjusting for tumor size, tumor grade, and number of 
positive nodes. All analyses maintain the expected overall HRs given 
above. Prognostic analyses include the biomarker with and without the 
original Recurrence Score (RS) based on expression, to test whether the 
marker can add prognostic value beyond commercial RS, and conversely 
whether the original RS adds prognostic power given the new marker. 
Prediction analyses include an interaction term between continuous 
marker and randomized treatment assignment. If the interaction is 
statistically significant then a cutpoint for chemotherapy benefit is 
estimated using the methods established in the original protocol for the 
expected interaction of RS and treatment assignment. For dichotomous 
markers an interaction test will be conducted as well as separate analyses 
by marker positive and negative subgroups to test qualitative interactions. 
 

S1007 
Page 92 
Version Date 12/10/2021 
 
 
 
 
 
In terms of prediction for premenopausal women there may be a small 
fraction of patients who do not benefit from chemotherapy despite the 
strong results in S1007. Similarly, for postmenopausal women there may 
be an even smaller fraction who do benefit from chemotherapy and the 
goal of this research is to identify those groups. Ultimately, we may 
determine an optimal signature though any signature would need 
validation (internal or external with the GEICAM/UNICANCER patients). 
 
Continuous RS based on gene expression is a highly significant prognostic 
factor for both premenopausal and postmenopausal women in this 
sample. The Interquartile Range (IQR) of 7 points (RS 11-18) has a HR of 
1.53 (p<0.003) for premenopausal women and 1.42 (p<0.001) for 
postmenopausal women. It is likely that replacing RS with values based 
on sequencing will improve prognostic ability. For 1-sided α=0.05 and 80% 
power, the magnitude of the HR for the IQR must exceed 1.43 and 1.30 
for 
premenopausal 
and 
postmenopausal 
women, 
respectively. 
Consequently, there is sufficient power for testing prognosis. 
 
Testing prediction will be with limited power. We will use a continuous 
marker by treatment interaction to signify a potential predictive marker. 
However, using a dichotomous marker has more limited power. For 
example, for premenopausal women a 50% negative marker with HR of 
1.00 and 50% positive with a computed HR maintaining the overall hazard 
ratio at 0.69 would have only 54% power at 1-sided α=0.05 and 68% power 
at 1-sided α=0.10 (commonly used for interactions). This decreases to 
33% and 47% power, respectively, if the negative marker has 30% 
prevalence. Since the postmenopausal HR is 0.985 there is room only to 
identify a small subset who may benefit. For example, if 5% benefit 
considerably but the remainder have HR=1.00 then there is only 21% 
power at 1-sided α=0.05 and 33% power at 1-sided α=0.10, respectively, 
to find a significant interaction. Consequently, while an interaction of a 
continuous marker and treatment may suggest prediction it may be difficult 
to demonstrate with a dichotomized marker. 
 
5. Additional Bioinformatics Considerations 
 
The bioinformatics analyses will guide selection of the gene expression 
signatures (21-gene signature, PAM50 and 70-gene signature) that are 
predictive of prognosis and chemotherapy (CT) benefit. The median 
normalized mRNA expression data will be analyzed with both supervised 
and 
unsupervised 
techniques 
to 
identify 
the 
molecular 
correlates/predictors of CT responses. We will also implement user-
friendly scripts and tools for rapid data access and visualization using the 
Next-Generation clustered heatmaps and Oncoprint suites (24, 25). The 
tools will enable automated selection of patient groups carrying aberrant 
expression or mutations in genes of interest. 
 
a. Unsupervised detection of genes signatures. The analysis will 
inform on which gene signatures and subsets of genes within the 
signatures are most informative of CT benefit. With a multi-step 
unsupervised approach on mRNA expression data, we will detect the 
gene signatures (and gene subsets within) that can best classify 
patients as responders and non-responders. First, through a two-way 
unsupervised hierarchical clustering, we will map the distribution of 
gene expressions across the patient groups. The patient clusters will 
be selected with the dynamictree-cutting algorithm applied on the 
hierarchical patient trees. (26) To test whether distinct clusters 

S1007 
Page 93 
Version Date 12/10/2021 
 
 
 
 
 
correlate with CT benefit, we will compare the IDFS, IBCFS, and 
DDFS differences between the clusters with Kaplan-Meier curves 
and log-ranked tests. Next, to detect the most predictive subsets of 
genes within the signatures, we will quantify the median gene 
expression differences between the clusters. With a Wilcoxon rank-
sum test, the genes with significant differential expression between 
responder and non-responder cohorts will be selected. The analysis 
will be applied to each gene signature of interest (21-gene, PAM50, 
70-gene signature). The signatures will be ranked for their predictive 
power of patient-classification for CT-benefit based on the survival 
differences between clusters. Through Fisher’s exact test, we will 
also determine the mutations that are significantly enriched in 
responder or non-responder groups. All statistical analyses will be 
corrected for multiple hypothesis testing using Benjamini-Hochberg 
procedure. 
 
b. Supervised detection of gene signatures. To go beyond the 
correlative analysis and select most predictive gene-sets, we will 
perform a Cox regression with elastic-net penalty (R-package: 
Regularized Cox Regression). The regression analysis will be 
applied to each signature and mRNA expression data. The survival 
data will serve as the dependent variables and mRNA expression 
values for signature genes are the independent variables. The 
predictive power of each signature will be quantified with a 10-fold 
cross validation. The models will be built using a training set (90% of 
patients selected with boot-strapping). Resulting models will be used 
to predict the CT-response of remaining patients that were hidden in 
the model building. The gene signatures will be ranked for their 
predictive power based on the cross-validation errors. The subsets 
of the most predictive gene subsets from most predictive signatures 
will be determined based on regression-predicted weights. 
 
c. Improvement of gene signatures through differential analysis of 
responder and non-responder groups. We will perform a 
differential analysis of genomic alterations across whole genome to 
identify other genes (not-sampled in the signatures) that are enriched 
in patients with CT-benefit. First, we will stratify the patients to 
responders vs. non-responders based on the survival distributions. 
Next, we will perform a differential RNA expression analysis using the 
Deseq2 R package. The differentially expressed genes in responder 
or non-responder groups will be included to the pre-defined gene 
signatures. The supervised and unsupervised analyses will be 
iterated using the expanded gene list. The improvements in 
predictive powers will be quantified and improved gene-signatures 
for CT-benefit will be reported. This iterative approach will prevent 
loss of predictive power due to pre-existing bias in selection of gene 
signatures. 
 
d. Test of prediction for derived signatures. To actually determine 
whether we have significant predictive abilities with the derived 
signatures we intend to use the following methods.  
 
 

S1007 
Page 94 
Version Date 12/10/2021 
 
 
 
 
 
6. Discovery Analysis Methods 
 
Genes considered will be all the constituent genes (except reference 
genes, where present) from the MammaPrint, PAM50, SET Index, 
Endopredict, Breast Cancer Index and Recurrence Score tests. For each 
set of genes examined, a score will be constructed using the first principal 
component of the gene set.  
 
For assessment of chemotherapy effect prediction, a Cox proportional 
hazards regression model will be fit with endpoint iDFS and terms for the 
gene set score, treatment and the interaction of the gene set score with 
treatment. The log standardized hazard ratio for interaction (27) and its 
variance will be computed for each gene set score. 
 
For assessment of prognosis, a Cox model will be fit with a single term for 
the gene score using the patients who were randomized to endocrine 
therapy alone. For assessment of residual risk, the same procedure will 
be used for patients randomized to chemo-endocrine therapy.  
 
False discovery rates (28) and log standardized hazard ratios with 
correction for regression to the mean (29, 30) will be calculated using 
model space sampling considering the universe of gene set scores 
selected from all genes under consideration and gene sets from 1 to 40 
genes.  
 
If prognostic gene sets are discovered at FDR 10%, their prognostic 
efficacy will be described using predictiveness curves (31) corrected for 
regression to the mean.  
 
If predictive gene sets are discovered at FDR 10%, their predictive efficacy 
will be described using treatment effect predictiveness curves, that is, 
predictiveness curves applied to the distribution of estimated treatment 
hazard ratio with correction for regression to the mean. Potential gene set 
score cut-points for identifying patients with substantial treatment benefit 
versus no substantial benefit will be assessed based on these curves. 
 
These discovery analyses will be conducted separately for pre-
menopausal patients and post-menopausal patients. 
 
Pseudoscores were previously constructed using RNASeq of the SWOG 
8814 study and the constituent genes of the MammaPrint®, Prosigna®, 
EndoPredict®, Genomic Grade Index, Breast Cancer Index® and 
Sensitivity Endocrine Treatment (SET) scores as well as the Oncotype DX 
Recurrence Score®. Each pseudoscore was constructed using the 
coefficients of the first principal component of the constituent genes. 
These pseudoscores will be evaluated and compared as continuous 
numeric biomarkers for prognosis of iDFS and prediction of the effect of 
chemotherapy using the RxPONDER data set and standardized hazard 
ratios. Categorical analyses for both prognosis and prediction will use 
equivalent cut-points using population quantiles. Since SWOG 8814 
included only post-menopausal women, the pseudoscores will be re-
derived separately using pre-menopausal and post-menopausal women 
in RxPONDER and the scores compared between pre- and post-
menopausal women. If it is concluded that the premenopausal 
pseudoscores are sufficiently different from the postmenopausal 
pseudoscores, then it may require regeneration of the first principal 
component weights using five-fold cross-validation. Overall, it is 

S1007 
Page 95 
Version Date 12/10/2021 
 
 
 
 
 
recognized that the pseudoscores are not an exact match for the actual 
gene signatures, as they use different coefficients and analytical platforms, 
so that the performance of the actual signatures might be different.  This 
analysis seeks to generally evaluate the information content of the 
constituent genes in each gene list.      
 
Because of the restriction of the S1007 study population to patients with 
Recurrence Score result 0 – 25, it is recognized that the estimated 
prediction of effects of genes from the Recurrence Score and other genes 
substantially correlated with these genes will be biased downward. 
 
2. Additional Molecular characterization of node-positive, HR-positive and HER2-
negative breast cancer and association with patient outcome 
 
We will collect one paraffin block of the primary tumor, one positive lymph node 
block, and one negative lymph node block (if available) in all patients. Blocks will 
be stored at the SWOG Biospecimen Bank – Solid Tissue, Myeloma, and 
Lymphoma Division, Lab #201. We plan to use the samples for evaluations at the 
protein levels and immune profile. By evaluating the tumors of patients in this trial 
we will be able to discover potential markers of response to commonly used and 
novel therapies as well as new potential targets for future therapies in this 
population. 
 
Samples will not be used until the proposed research platforms to be used at the 
time of analyses have been validated.  
 
3. Pharmacogenomic studies of the effects of inherited, germline polymorphisms on 
toxicity and efficacy of aromatase inhibitors and chemotherapy. 
 
By evaluating germ-line DNA we will be able to discover potential 
pharmacogenomic markers of outcome and toxicity to commonly used and novel 
therapies. 
 
Samples will not be used until the proposed research platforms to be used at the 
time of analyses have been validated (32, 33, 34, 35, 36, 37, 38, 39, 40, 41). 
 
d. Baseline Serum 
 
1. Serum Hormone Level 
 
Given that there is a significant interaction between menopausal status, as 
determined by clinical characteristics, and IDFS and DDFS in RxPONDER, we 
propose evaluating hormone levels in pre-treatment baseline samples to assess 
whether menopausal status is further refined and whether an interaction term 
remains statistically significant based upon menopausal status per serum hormone 
levels. 
 
2. Description of Assay 
 
We will analyze baseline serum estradiol, luteinizing hormone (LH), follicle-
stimulating hormone (FSH), and anti-müllerian hormone (AMH)/Müllerian inhibiting 
factor (MIF). These analyses will be performed at the University of Kansas Medical 
Center through the Kansas Institute for Precision Medicine (KIPM) COBRE (P20 
GM130423, PI: Godwin, A.K.) Biobanking and Biomarker Validation Core (BBV).  
We will use fluorescent bead-based immunoassays (Luminex assays) to measure 
circulating levels of all 4 markers. These will be performed via standard laboratory 
procedures following manufacturer’s protocol. 

S1007 
Page 96 
Version Date 12/10/2021 
 
 
 
 
 
 
3. Statistical Plan 
 
a. Clinical Endpoints and the biomarker measurements involved in the analysis. 
 
The primary outcome of the trial was IDFS, with secondary outcomes including 
DDFS and now IBCFS.  
 
b. Case selection method if only a subset of patients will be included in the 
biomarker evaluation. 
 
Patients from UNICANCER (n=1,014) are excluded since samples were not 
submitted to the Nationwide repository. At this time, there 3,255 patients with 
baseline samples available. Of these, 1,039 were reported as premenopausal. 
Of the 3,255 patients, 1,364 were age < 55.  
 
c. Numbers of patients to be studied and biomarker assays/tests to be 
performed. 
 
We will focus on the premenopausal patient population with available baseline 
serum samples – and analyze patients age < 55, as these are most likely to 
be premenopausal. 
 
d. Statistical analysis methodology and underlying assumptions. 
 
For this restricted sample the number of IBCFS events are currently 96 and 
222 for premenopausal and postmenopausal women, respectively. (In 
contrast, for IDFS there are 106 and 274 events, showing that many IDFS 
events in postmenopausal women were other cancers and equally distributed 
by treatment group.) Median follow-up time is approximately 6.1 years in this 
cohort. IBCFS hazard ratios in favor of chemotherapy are 0.69 (95% CI 0.46-
1.04) and 0.99 (95% 0.76-1.29), for premenopausal and post-menopausal 
patients respectively. In Section 18.3, the statistical analysis plan is defined. 
In this biomarker analysis, we will evaluate whether an interaction term with 
menopausal status and clinical outcome remains when menopausal status, as 
defined by serum hormone levels.  
 
e. Funding 
 
The Biobanking and Biomarker Validation Core (part of the Kansas Institute 
for Precision Medicine COBRE) will analyze baseline serum samples from pre-
menopausal patients under age 55 for estradiol, luteinizing hormone, follicle-
stimulating hormone, and anti-mullerian hormone/Mullerian inhibiting factor, 
with labor and equipment fee provided in-kind (at no cost to the study). The 
reagent costs will be offset via Hematology and Medical Oncology-associated 
funds provided by the Winship Cancer Institute of Emory University in support 
of biomarker analyses to further inform whether invasive disease-free survival 
benefit remains in premenopausal patients. 
4. References  
 
1.  Buus R, Sestak I, Kronenwett R, et al. Molecular Drivers of Oncotype DX, 
Prosigna, EndoPredict, and the Breast Cancer Index: A TransATAC Study. J 
Clin Oncol 2021; 39(2): 126-35. 
 
 

S1007 
Page 97 
Version Date 12/10/2021 
 
 
 
 
 
 
2.  Sestak I, Buus R, Cuzick J, et al. Comparison of the Performance of 6 
Prognostic Signatures for Estrogen Receptor-Positive Breast Cancer: A 
Secondary Analysis of a Randomized Clinical Trial. JAMA Oncol 2018; 4(4): 
545-53. 
 
3.  van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as 
a predictor of survival in breast cancer. N Engl J Med 2002; 347(25): 1999-
2009. 
 
4.  Cardoso F, van't Veer LJ, Bogaerts J, et al. 70-Gene Signature as an Aid to 
Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 2016; 
375(8): 717-29. 
 
5.  Piccart M, van 't Veer LJ, Poncet C, et al. 70-gene signature as an aid for 
treatment decisions in early breast cancer: updated results of the phase 3 
randomised MINDACT trial with an exploratory analysis by age. Lancet Oncol 
2021; 22(4): 476-88. 
 
6.  Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast 
carcinomas 
distinguish 
tumor 
subclasses 
with 
clinical 
implications. 
Proceedings of the National Academy of Sciences 2001; 98(19): 10869-74. 
 
7.  Lænkholm AV, Jensen MB, Eriksen JO, et al. PAM50 Risk of Recurrence 
Score Predicts 10-Year Distant Recurrence in a Comprehensive Danish 
Cohort of Postmenopausal Women Allocated to 5 Years of Endocrine Therapy 
for Hormone Receptor-Positive Early Breast Cancer. J Clin Oncol 2018; 36(8): 
735-40. 
 
8.  Gnant M, Sestak I, Filipits M, et al. Identifying clinically relevant prognostic 
subgroups of postmenopausal women with node-positive hormone receptor-
positive early-stage breast cancer treated with endocrine therapy: a combined 
analysis of ABCSG-8 and ATAC using the PAM50 risk of recurrence score and 
intrinsic subtype. Ann Oncol 2015; 26(8): 1685-91. 
 
9.  Wallden B, Storhoff J, Nielsen T, et al. Development and verification of the 
PAM50-based Prosigna breast cancer gene signature assay. BMC Med 
Genomics 2015; 8: 54. 
 
10.  Sinn BV, Fu C, Lau R, et al. SET(ER/PR): a robust 18-gene predictor for 
sensitivity to endocrine therapy for metastatic breast cancer. NPJ Breast 
Cancer 2019; 5: 16. 
 
11.  Du L, Yau C, Brown-Swigart L, et al. Predicted sensitivity to endocrine therapy 
for stage II-III hormone receptor-positive and HER2-negative (HR+/HER2-) 
breast cancer before chemo-endocrine therapy. Ann Oncol 2021; 32(5): 642-
51. 
 
12.  Filipits M, Rudas M, Jakesz R, et al. A new molecular predictor of distant 
recurrence in ER-positive, HER2-negative breast cancer adds independent 
information to conventional clinical risk factors. Clin Cancer Res 2011; 17(18): 
6012-20. 
 
13.  Martin M, Brase JC, Calvo L, et al. Clinical validation of the EndoPredict test 
in node-positive, chemotherapy-treated ER+/HER2− breast cancer patients: 
 

S1007 
Page 98 
Version Date 12/10/2021 
 
 
 
 
 
 
results from the GEICAM 9906 trial. Breast Cancer Research 2014; 16(2): 
R38. 
 
14.  Bartlett JMS, Sgroi DC, Treuner K, et al. Breast Cancer Index and prediction 
of benefit from extended endocrine therapy in breast cancer patients treated 
in the Adjuvant Tamoxifen-To Offer More? (aTTom) trial. Ann Oncol 2019; 
30(11): 1776-83. 
 
15.  Noordhoek I, Treuner K, Putter H, et al. Breast Cancer Index Predicts 
Extended Endocrine Benefit to Individualize Selection of Patients with HR(+) 
Early-stage Breast Cancer for 10 Years of Endocrine Therapy. Clin Cancer 
Res 2021; 27(1): 311-9. 
 
16.  Meric-Bernstam F, Zheng X, Shariati M, et al. Survival Outcomes by TP53 
Mutation Status in Metastatic Breast Cancer. JCO Precis Oncol 2018; 2018. 
 
17.  Akcakanat A, Zheng X, Cruz Pico CX, et al. Genomic, Transcriptomic, and 
Proteomic Profiling of Metastatic Breast Cancer. Clin Cancer Res 2021. 
 
18.  Keene KS, King T, Hwang ES, et al. Molecular determinants of post-
mastectomy breast cancer recurrence. NPJ Breast Cancer 2018; 4: 34. 
 
19.  Zheng ZY, Anurag M, Lei JT, et al. Neurofibromin Is an Estrogen Receptor-α 
Transcriptional Co-repressor in Breast Cancer. Cancer Cell 2020; 37(3): 387-
402.e7. 
 
20.  Jeselsohn R, Yelensky R, Buchwalter G, et al. Emergence of constitutively 
active estrogen receptor-α mutations in pretreated advanced estrogen 
receptor-positive breast cancer. Clin Cancer Res 2014; 20(7): 1757-67. 
 
21.  Broekmans FJ, Knauff EA, te Velde ER, Macklon NS, Fauser BC. Female 
reproductive ageing: current knowledge and future trends. Trends Endocrinol 
Metab. 2007;18(2):58-65. 
 
22.  Krailo MD, Pike MC. Estimation of the distribution of age at natural menopause 
from prevalence data. Am J Epidemiol. 1983;117(3):356-361. 
 
23.  Tolaney SM, Garrett-Mayer E, White J, et al. Updated Standardized Definitions 
for Efficacy End Points (STEEP) in Adjuvant Breast Cancer Clinical Trials: 
STEEP Version 2.0. J Clin Oncol. 2021 Aug 20;39(24):2720-2731. doi: 
10.1200/JCO.20.03613. Epub 2021 May 18. PMID: 34003702. 
 
24.  Cerami E, Gao J, Dogrusoz U, et al. The cBio cancer genomics portal: an open 
platform for exploring multidimensional cancer genomics data. Cancer Discov 
2012; 2(5): 401-4. 
 
25. Ryan MC, Stucky M, Wakefield C, et al. Interactive Clustered Heat Map 
Builder: An easy web-based tool for creating sophisticated clustered heat 
maps. F1000Res 2019; 8. 
 
26.  Langfelder P, Zhang B, Horvath S. Defining clusters from a hierarchical cluster 
tree: the Dynamic Tree Cut package for R. Bioinformatics 2008; 24(5): 719-
20. 
 
 

S1007 
Page 99 
Version Date 12/10/2021 
 
 
 
 
 
 
27.  Crager MR (2020).  Extensions of the absolute standardized hazard ratio and 
connections with measures of explained variation and variable importance.  
Lifetime Data Analysis 26:872-892. 
 
28.  Storey JD (2002).  A direct approach to false discovery rates.  Journal of the 
Royal Statistical Society Series B. 64:479–498. 
 
29.  Crager MR (2010).  Gene identification using true discovery rate degree of 
association sets and estimates.  Statistics in Medicine 29:33-45. 
 
30.  Crager MR (2012).  Generalizing the standardized hazard ratio to multivariate 
proportional hazards regression, with an application to clinical-genomic 
studies.  Journal of Applied Statistics 39:399-417. 
 
31.  Huang Y, Pepe MS, Feng Z.  Evaluating the predictiveness of a continuous 
marker.  Biometrics 63:1181-1188. 
 
32.  Ma CX, Araba AA, Oreste ES, et al. Experimental therapeutics, molecular 
targets, and chemical biology human aromatase: gene resequencing and 
functional genomics. Cancer Res 2005;65:11071-82. 
 
33.  Marsh S, Somlo G, Li X, et al. Pharmacogenetic analysis of Paclitaxel transport 
and metabolism genes in breast cancer. Pharmacogenomics J 2007;7:362-65. 
 
34.  Petros WP, Hopkins PJ, Spruill S, et al. Associations between drug 
metabolism genotype, chemotherapy pharmacokinetics, and overall survival 
in patients with breast cancer. J Clin Oncol 2005;23:6117-25. 
 
35.  Shrubsole MJ, Shu XO, Ruan ZX, et al. MTHFR genotypes and breast cancer 
survival after surgery and chemotherapy: a report from the Shanghai Breast 
Cancer Study. Breast Cancer Res Treat 2005;91:73-79. 
 
36.  Pare L, Altes A, Cajal TR, et al. Influence of thymidylate synthase and 
metylenetetrahydrofolate reductase gene polymorphisms and the diesease-
free 
survival 
of 
breast 
cancer 
patients 
receiving 
adjuvant 
5-
fluorouracil/methotrexate-based therapy. Anticancer Drugs 2007:18:821-25. 
 
37.  Fan L, Goh B, Wong C, et al. Genotype of human carbonyl reductase CBR3 
correlates with doxorubicin disposition and toxicity. Pharmacogenet genomics 
2008;18:623-31. 
 
38.  Lal S, Wong ZW, Sandanaraj E, et al. Influence of ABCB1 and ABCG2 
polymorphisms on doxorubicin disposition in Asian breast cancer patients. 
Cancer Sci 2008;99:816-23. 
 
39.  Engen RM, Marsh S, van Booven DJ, et al. Ethnic differences in 
pharmacogenetically relevant genes. Curr Drug Targets 2006;1641-48 
 
40.  Innocenti F, Iyer L, Ramirez J, et al. Epirubicin glucuronidation is catalyzed by 
human UDP-glucuronosyltransferase 2B7. Drug Metab Dispos 2001; 29:686-
92. 
 
41.  Fagerholm R, Hofstetter B, Tommiska J, et al. NAD(P):quinine oxidoreductase 
1 NQO1*2 genotype (P187S) is a stro0ng prognostic and predictive factor in 
breast cancer. Nat Genet 2008; 40:884-53. 
 
 

S1007 
Page 100 
Version Date 12/10/2021 
 
 
 
 
 
18.3 
Statistical Analysis Plan 
 
1.0 
SCIENTIFIC OVERVIEW AND SUMMARY OF THE STATISTICAL PLAN 
 
1.1 
SPECIFIC HYPOTHESES 
 
a. 
We hypothesize that the 21-gene recurrence score (RS) will 
predict the benefit of chemotherapy in node positive (1-3 nodes), 
hormone receptor (HR)-receptor positive breast cancer patients 
with RS ≤ 25 treated with state-of-the-art endocrine therapy.  
Chemotherapy benefit (if it exists) will increase as the RS 
increases.  
 
b. 
We hypothesize that chemotherapy is not beneficial for some 
patients in the range of RS 0-25 and that the point of equivalence 
between chemotherapy and no chemotherapy can be identified in 
this range. Above this point, patients begin to benefit from the 
addition of chemotherapy.  We will identify a RS cutpoint for which 
there is clinically significant benefit of chemotherapy for all RS 
values above this cutpoint.   
 
1.2  
PRIMARY OBJECTIVE 
 
To determine the effect of chemotherapy in patients with node positive 
breast cancer who do not have high Recurrence Scores; In patients with 
1-3 positive nodes, and HR-positive, HER2-negative breast cancer with 
RS ≤ 25 treated with state-of-the-art endocrine therapy we will test whether 
the difference in disease-free survival for patients treated with optimal 
chemotherapy compared to no chemotherapy depends directly on the 
magnitude of RS.  If benefit depends on the RS score, the trial will 
determine the optimal cutpoint for recommending chemotherapy or not.  
 
1.3 
OVERVIEW OF ANALYSIS FOR THE PRIMARY OBJECTIVE 
 
The primary analysis will be a test of interaction of Recurrence Score with 
randomized treatment assignment.  If this test is statistically significant, 
then it will be determined whether there is a point of equivalence between 
the two treatments within the range of RS from 0 to 25.  The upper limit of 
the 95% confidence interval on this equivalence point determines the 
cutpoint for determining that chemotherapy is effective for all values at that 
cutpoint or above. If there is no significant interaction, then the overall 
effect of chemotherapy will be tested adjusting for a common prognostic 
effect of RS on both treatment groups.   
 
 

S1007 
Page 101 
Version Date 12/10/2021 
 
 
 
 
 
1.4 
SECONDARY OBJECTIVES 
 
• 
To compare overall survival (OS), distant disease-free survival 
(DDFS) and local disease-free interval (LDFI) by receipt of 
chemotherapy or not and its interaction with RS. 
• 
To compare the toxicity across the treatment arms 
• 
To perform other molecular assays or test other signatures that 
measure prognosis and potential benefit of chemotherapy and 
compare them to Oncotype DX®.  
• 
To determine the impact of management with Oncotype DX® on 
patient-reported anxiety (co-primary Health-Related Quality of Life 
[HRQL] outcome) prior to screening, after disclosure of test results, 
and during the randomized trial. 
• 
To determine the impact of Oncotype DX® on the initial management 
cost of node-positive, HR-positive, HER2-negative breast cancer. 
• 
To compare patient-reported utilities (e.g., QOL) outcomes for those 
randomized to chemotherapy versus no chemotherapy. 
• 
Using modeling and DFS information from the trial, to estimate the 
cost-effectiveness of management with Oncotype DX® vs. usual care. 
• 
To determine the role of other assays as predictors of DFS, DDFS and 
LDFI for patients randomized to chemotherapy versus no 
chemotherapy. 
• 
To determine the impact of treatment with chemotherapy versus no 
chemotherapy on patient-reported fatigue and cognitive concerns 
(secondary HRQL outcomes). 
• 
To determine the impact of management with Oncotype DX® on 
patient-reported decision conflict, perceptions regarding Oncotype 
DX® testing, and survivor concerns prior to screening, after disclosure 
of test results, and during the randomized trial (secondary HRQL 
outcomes). 
• 
The presence of circulating tumor cells (CTC+) using two CTC 
platforms will be assessed at up to two time points to assess late 
recurrence in those still at risk for the primary outcome. Invasive 
disease-free survival (IDFS) will be compared between CTC+ versus 
CTC-, incorporating use of endocrine therapy. 
• 
To compare clinically reported menopausal status with status 
categorized by serum hormone levels determined from baseline 
serum in women under age 55 years and to assess subsequent 
association with outcomes. 
 
2.0 
BACKGROUND 
 
2.1 
Results of the S8814 trial 
 
Until recently, there was no information on the potential value of the RS assay in 
patients with positive axillary nodes and HR-positive disease from a study that 
contains a similar tamoxifen-alone control arm since today these patients are 
routinely treated with chemotherapy as well as endocrine adjuvant therapy. 
SWOG-8814 was a practice-changing phase III trial for postmenopausal women 
with node-positive, ER-positive breast cancer that demonstrated that CAF 
chemotherapy added survival benefit to tamoxifen, especially in the sequential 
setting, with CAF preceding the initiation of tamoxifen therapy. The study had 
optional specimen banking which yielded tumor specimens for RS determination 
by the Oncotype DX® gene assay.  When comparing the tamoxifen and the 
sequential CAF-T arms in tissues from 367 patients, the RS was prognostic for 
DFS in the tamoxifen-alone arm (p=0.006).  In this study we used the RS grouping 
defined by Paik et al. (1,2) There was no apparent CAF benefit in the low RS (0-

S1007 
Page 102 
Version Date 12/10/2021 
 
 
 
 
 
17) group (p=0.97) or the intermediate RS (18-30) group (p=0.48), but a significant 
DFS improvement was detected for the high RS (31-100) subset (p=.03).  Due to 
failure of the proportional hazards assumption, separate analyses were performed 
for the first five years of follow-up and the period beyond five years. The RS-by-
treatment interaction was significant in the first 5 years for DFS (p=0.029), with no 
additional prediction of CAF benefit beyond 5 years (p=0.58).  No impact of CAF 
was observed in the lowest RS, regardless of nodal status.  Results were similar 
for OS. (3) 
 
In the proposed trial, only women with RS ≤ 25 and 1-3 positive nodes would be 
included.  We reexamined the S8814 data using this cutoff and 10 years of survival 
using a standard Cox model. The Kaplan-Meier graph below shows little difference 
between the two groups (Figure 1) even if we restrict attention to those with RS ≥ 
14 (Figure 2).  However, the Kaplan-Meier graphs may obscure a possible 
difference since they do not use the continuous RS. If one fits a more complex 
model using continuous RS and its interaction with chemotherapy, then a pattern 
emerges even though there is still no significant interaction of RS and treatment in 
this subset with RS ≤ 25.  The Cox model gives an estimate of the log hazard ratio 
(relative failure rates) by RS with high hazard ratios indicating worse DFS. The 
hazard ratios apply at any time point (e.g. 5 or 10 years) which is why we prefer to 
illustrate them here.  In the simplest case we use a Cox model and allow for a 
linear interaction of RS and treatment (Figure 3). The hazard ratios cross indicating 
there may be a point of equivalence where a chemotherapy benefit may emerge, 
but of course the difference would have to be large enough to be both clinically 
and statistically significant. For nodes 1-3 this point of equivalence was about RS 
= 19. Based on this model the estimated hazard ratio at RS=22 would be 0.84 for 
chemotherapy versus no chemotherapy, but the 95% CI is 0.28-2.49 due to the 
small sample size. Note that the effect in very low RS scores may be exaggerated 
due to the sparseness of data. Pepe et al. recommends using quantiles in the 
regression so that scores are distributed equally along the x-axis. (4) We used a 
linear quantile model in (Figure 4), but then graphed it on the original RS axis.  This 
mutes the effect of sparse scores, but the pattern is similar.  These models are 
based on sparse data and are perhaps too simple, but they do indicate that using 
continuous RS may provide more insight and power than simple categorization.  
However, interaction alone is also not sufficient and needs to be supplemented by 
a clinically useful cutoff. 

S1007 
Page 103 
Version Date 12/10/2021 
 
 
 
 
 

S1007 
Page 104 
Version Date 12/10/2021 
 
 
 
 
 
Based on S8814 data alone it is difficult to conclude that there is benefit of 
chemotherapy in patients with RS ≤ 25.  We recognize that the sample size is 
small, there are some trends in the data that support chemotherapy at the higher 
ends of the RS range, and that chemotherapy has improved since S8814. There 
have also been improvements in hormonal therapy, surgery, and radiation therapy, 
though these would apply equally to the two randomized groups.  How 
representative of current outcomes are the S8814 data given that patients were 
randomized in the early 1990’s?  SEER does not provide DFS, but does provide 
some information about overall survival (OS). Using SEER, one can examine some 
of this improvement by tumor stage. For Stage II/III disease there have been 
improvements in OS (Figure 5), while in Stage I disease (Figure 6) there has been 
little improvement in OS. From SEER one can derive the estimated overall survival 
of 52,592 women aged 55-74 diagnosed with receptor positive, node positive 
breast cancer in the years 1996-2003.  In this group overall survival was 83% at 5 
years and 64% at 10 years.  Note that S8814 had an overall survival of 82% at five 
years and 64% at ten years, so the outcomes are almost identical to current 
population results. Nonetheless, it seems likely that better chemotherapies are 
available. This would strengthen the importance of this trial since we would have 
a randomized comparison with modern chemotherapy, rather than observational 
data based on outdated chemotherapy.  
 
While the failure rate in S8814 seems high, we show that the overall survival is 
exactly what one would expect in a comparable population.  We have also 
compared S8814 recurrence results with those of TRANS-ATAC at 5 years.  Their 
primary outcome is disease-free interval (DFI) which censors deaths that are not 
associated with a recurrence.  Ten deaths in S8814 occurred within 5 years and 
had no evidence of recurrence so are treated as censored in this analysis, but 
would be considered as failures for DFS.  The TRANS-ATAC investigators kindly 
provided comparison data, but collapsed over treatment group.  Recurrence rates 
(events/person years) suggest little difference between ATAC and S8814.  
Adjusting for number of nodes and RS risk group (< 18, 18-30, > 30) showed no 
statistically significant difference in DFI between ATAC and S8814. There are not 
appreciable differences in the TRANS-ATAC and S8814 outcomes when RS 
groupings and number of nodes are considered. Thus, the S8814 data still provide 
an excellent reference point for the proposed trial. 
  
Figure 5                                                                           Figure 6 
   
 
 
0.00
0.25
0.50
0.75
1.00
0
5
10
15
Years
1992-1995  (5-year survival 73%)
1996-1999  (5-year survival 77%)
2000-2003  (5-year survival 79%)
Year of diagnosis
67,746 women aged 55-74
Overall Survival of Stage II/III Disease by SEER
0.00
0.25
0.50
0.75
1.00
0
5
10
15
Years
1992-1995  (5-year survival 90%)
1996-1999  (5-year survival 91%)
2000-2003  (5-year survival 91%)
Year of diagnosis
85,937 Women Aged 55-74
Overall Survival of Stage I Disease by SEER

S1007 
Page 105 
Version Date 12/10/2021 
 
 
 
 
 
The percentage of patients in S8814 with > 3 positive nodes was 43%.  This 
proposed trial will restrict eligibility to patients with 1-3 positive nodes.  In women 
with 1-3 positive nodes, RS was ≤ 25 in 67%.  The overall distribution is shown 
below.  Since the point of equivalence is unknown it is necessary to have a wider 
range of RS scores to distinguish who may need chemotherapy from those who 
do not.  
 
Figure 7 
 
 
 
 
 
 
 
 
 
 
 
 
To summarize, S8814 provides general support for chemotherapy in patients with 
receptor-positive, node-positive disease, but no strong evidence of benefit in the 
subset with RS ≤ 25.  Looking more carefully using the actual value of RS, does 
reveal that treatment effects may start to diverge at higher values of RS, but this 
would need to be supported by data using modern chemotherapy and many more 
patients.  We predict that continuous RS will be directly associated with the degree 
of benefit. We also predict there may be an equivalence point between RS 0 to 25 
after which a benefit to chemotherapy may emerge.  When categorized we expect 
no benefit below that cutpoint, but a clinically significant benefit above the cutpoint.  
 
3.0 
TRIAL OVERVIEW 
 
3.1  
TRIAL DESIGN SCHEMATIC 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
10
20
30
0
5
10
15
20
25
Recurrence Score
Restricted to 1-3 Positive Nodes and RS <= 25
RS DIstribution in S8814

S1007 
Page 106 
Version Date 12/10/2021 
 
 
 
 
 
NUMBER OF PATIENTS SCREENED AND NUMBER RANDOMIZED 
 
The schema shows the patient flow from screening to randomization.  Most 
patients who meet eligibility (1-3 positive nodes; HR-positive and HER2-negative 
disease) will need to be screened.  We expect to perform the 21-gene assay on 
approximately, 10,000 patients but the number could vary to achieve the target 
accrual in the randomized trial. A small number of eligible patients (~800) will 
already have RS scores available from having ordered the test commercially. 
Among those with an obtained RS score (~10,000), patients with RS ≤ 25 
(N~7,000) will be eligible for the randomized trial while those with RS>25 
(N~3,000) will be ineligible.  Upon receipt of the RS, patients with RS > 25 will be 
informed of their RS score, its interpretation, and other available trials. Patients 
with RS ≤ 25 will undergo discussion of this trial in consultation with their oncologist 
considering known RS value. We expect about 29% (~2,000) will not accept 
randomization.  Thus, the target accrual goal is 5,000 patients randomized equally 
to chemotherapy or no chemotherapy with stratification by Recurrence Score (0-
13 vs. 14-25), menopausal status, and complete nodal dissection versus sentinel 
node biopsy.  NCTN will be limited to 4,000 randomized patients and UNICANCER 
to 1,000 patients. The randomized accrual targets are fixed, but all other stated 
sample sizes are approximate and depend on the distribution of RS scores and 
the number accepting randomization. 
 
3.2  
STRATIFICATION FACTORS 
 
Patients are randomized separately for NCTN and UNICANCER.  Patients are also 
stratified at time of randomization on three factors: 
 
1. 
RS value 0-13 versus RS value 14-25 
 
2. 
Pre-menopausal versus post-menopausal 
 
3. 
Type of nodal dissection:  axillary lymph node dissection (with or without 
sentinel node mapping) versus sentinel node biopsy without axillary lymph 
node dissection. 
 
A dynamic balancing scheme is used to assure that randomization is balanced 
across all stratification factors. 
 
3.3 
ENDPOINTS 
 
PRIMARY ENDPOINT 
DFS:  Invasive disease-free survival (DFS) - time from the second registration 
(randomization) to local, regional, or distant recurrence, new invasive primary, or 
death due to any cause.  The STEEP definition of invasive disease-free survival 
(IDFS) is used, although it is referred to here by the more common acronym DFS.  
Survival times are censored at time of last follow-up for individuals who did not 
have any event meeting the above definition. 
 
SECONDARY ENDPOINTS 
OS:  Overall survival (OS) - time from the second registration (randomization) to 
death due to any cause.  Survival times are censored at time of last follow-up for 
individuals who are not known to have died. 
 
 
 

S1007 
Page 107 
Version Date 12/10/2021 
 
 
 
 
 
DDFS: Distant disease-free survival (DDFS) - time from second registration to 
distant recurrence, new invasive primary, or death due to any cause. Patients who 
have local or regional recurrence are continued to be followed for a distant event 
or death. Survival times are censored at time of last follow-up for individuals who 
are not known to have died and have not had a distant recurrence or new primary. 
 
LDFI: Local-regional disease-free interval (LDFI) - time from second registration to 
local/regional recurrence. 3 Patients who have distant recurrence or a new primary 
or who die without recurrence are censored at time of this event. The analysis of 
this endpoint must account for informative censoring using a competing risk 
framework. Survival times are also censored at time of last follow-up for individuals 
who are not known to have died and have had a recurrence or new primary.  
 
Toxicity:  Toxicities using standard NCI-CTCAE criteria (CTCAE Version 4.0). 
 
Other endpoints including QOL, costs, and correlative outcomes are described 
elsewhere. 
 
4.0  
SAMPLE SIZE AND POWER 
 
4.1  
ASSUMPTIONS 
 
We propose to randomize 5,000 patients over a 5.5-year accrual period with 5.5 
additional years of follow-up after the last randomized patient.  Since the accrual 
target has changed, we are using actual enrollment per month through July 2014 
and the estimated enrollment thereafter until August 2016.  All statistical tests use 
an overall 2-sided  = 0.05 except where specified. 
 
Estimated survival is based on disease-free survival in S8814.  In this study, only 
patients with RS ≤ 25 and 1-3 positive nodes are included. In that subgroup in 
S8814 the overall 5 year DFS rate was 91% and was 70% at 10 years. In this case 
the overall 5-year DFS rate is 92.4% reflecting improvement in modern rates. 
 
Compliance is discussed in detail below, but in order to accommodate random 
dropout we increased the sample size by 5%.  Simulations used a sample size of 
4,750 which is increased by 5.3% to 5,000 for the overall accrual goal.  Power was 
obtained by simulating a population (n=4,750; 2,375 per group) that had relative 
results similar to S8814. A Weibull model provided a reasonable fit to the S8814 
data and gave hazard ratios comparable to those of the Cox model.  Since the 
model data were sparse, we assumed that the observed interaction in S8814 ( = 
-0.052) may be an overestimate. We used a more conservative value of -0.042 
(20% reduction) as the primary simulation model.  The interaction parameter was 
fixed at that value and the other parameters re-estimated from S8814 so that the 
estimated model would be consistent with observed data. The primary simulation 
model used an equivalence point of 19 and a hazard ratio of 0.78 in favor of 
chemotherapy at RS=25.  Alternatives are considered below. Ten thousand 
simulations were performed to determine power. The simulation was performed in 
SAS. 
 
 

S1007 
Page 108 
Version Date 12/10/2021 
 
 
 
 
 
4.2  
OVERVIEW OF POWER CALCULATIONS 
 
Power is based on a stepped analytic plan. It seeks to establish the following: 
 
1) 
There is a statistically significant interaction (2-sided p ≤ 0.05) of treatment 
and RS.  That leads to three subsequent steps: 
a) 
There is a point of equivalence in the range 0-25 for a model that 
incorporates a linear interaction of continuous RS and treatment 
randomization. 
b) 
If (a) is true, the upper limit of a one-sided 95% confidence interval 
for the point of equivalence marks the RS for which there is a 
significant benefit of chemotherapy. If this upper limit ≤ 25 then we 
can establish a clinically meaningful cutoff for recommending 
chemotherapy.  If the upper limit exceeds 25, then we can only 
suggest chemotherapy for RS > 25. 
 
c) 
If (b) gives a cutoff in the range 0-25, then the trial population will 
be divided at this cutoff.  At the cutoff or above, we expect to see 
a clinically and possibly statistically significant effect of 
chemotherapy.  Below the cutoff, we will find no statistically 
significant benefit of chemotherapy.    
 
2) 
If there is no statistically significant interaction of treatment and RS, then 
the overall effect of chemotherapy will be tested adjusting for RS as a 
prognostic factor.   
a) 
If a significant benefit of chemotherapy is observed, then it will 
suggest all patients in the range RS 0 to 25 should receive 
chemotherapy. 
b) 
If no significant effect of chemotherapy is observed, then power is 
sufficiently high to conclude that it is unlikely a benefit exists and 
no patients with RS 0-25 and 1-3 positive nodes would be 
recommended for chemotherapy.  
 
PREDICTION OF CHEMOTHERAPY BENEFIT 
 
The first hypothesis to be tested is whether continuous RS predicts chemotherapy 
benefit.  In this case we are predicting an interaction of randomized treatment with 
the linear RS score.  Even if the log hazard ratios are not perfectly linearly related 
to RS, the test of interaction will measure divergence in chemotherapy benefit. We 
tested the significance of the interaction in the Cox model:   
 
 
 
Using an ITT analysis, the power for the primary simulation was 86.3% to detect a 
significant interaction (predictive ability of the RS score).  The interaction was 
marginal (0.05 < p ≤ 0.20) in another 10% of the cases, but these are not included 
as a significant interaction.  For the 14% of simulations which showed no significant 
interaction, we fit a model without the interaction term.  In the simulations without 
a significant interaction, not one simulation showed a statistically significant benefit 
of chemotherapy.  Furthermore, 88% of these simulations showed that the lower 
95% CI for the hazard ratio (chemo versus no chemo) exceeded 0.90, thus ruling 
out a protective effect of chemotherapy. 
 
However, a significant interaction alone is not sufficient for prediction. One also 
needs to demonstrate a qualitative interaction as well, i.e. there is a group who 
benefits from chemotherapy and a group who does not. 
 
 
 
(
)
0
1
2
3
(t; chemo, RS )
(t) exp
chemo+ 
 + 
*
RS
chemo RS





=

S1007 
Page 109 
Version Date 12/10/2021 
 
 
 
 
 
PREDICTION OF THE POINT OF EQUIVALENCE AND ITS CONFIDENCE 
INTERVAL 
 
When the interaction is statistically significant, the second hypothesis to be tested 
is whether a specific range of RS values can be specified as showing equivalent 
results for chemotherapy versus no chemotherapy.  Estimation of this value can 
be done by several methods. One method is to test all possible RS integer values 
between 0-25 to determine maximum discrimination after accounting for multiple 
comparisons.  However, this method may not guarantee a single consistent 
answer.  Instead, we consider the point of intersection of the two therapies based 
on the model in (1).  The interaction model yields estimates that allow estimation 
of an estimated equivalence point  = (- 1 /  3) with a standard error for the 
estimate of  determined by the delta method. If  is not within the range (0, 25) 
then one treatment dominates the other and would always be preferred.  If  is in 
the range 0 to 25, then a 95% one-sided CI would be obtained on the upper bound.  
The upper limit of this confidence interval ("c") would indicate that chemotherapy 
can be assumed to be more efficacious above this point.  This is illustrated below. 
In the example, we identify that the two treatments are estimated to be equivalent 
at RS=19.3, but that the upper limit of the 95% CI extends to 24.0.  At this value, 
the estimated benefit of chemotherapy would be about a 18% relative reduction in 
the failure rate, which would be in the range of clinical benefit.  The actual hazard 
ratio at the upper limit would vary, but the power calculations assumed that the 
hazard ratio is 0.78 at RS=25.  The expected 5 year DFS survival rates under the 
simulation model are the following: 
 
Recurrence 
Score 
No 
Chemotherapy 
 
Chemotherapy 
Difference in favor of 
chemotherapy  
15 
93.2% 
92.0% 
-1.2% 
20 
90.5% 
90.8% 
0.3% 
25 
86.7% 
89.4% 
2.7% 
 
 
 
 
 
Equivalence
Chemotherapy
superior
HR = 0.82
0
.5
1
1.5
2
0
5
10
15
20
25
30
Recurrence Score
No chemotherapy
Chemotherapy

S1007 
Page 110 
Version Date 12/10/2021 
 
 
 
 
 
With the current sample size the estimated  would have a standard deviation of 
approximately 2.44.  In the simulations finding a statistically significant interaction, 
the point of equivalence () was in the range of 0-25 in 99.34% so the crossover 
point almost certainly will be found in the range of the data.  In 81.6% of the 
simulations, the upper bound of the confidence interval for the estimate of  (c) 
was in the range of 0-25.  So we have sufficient power to declare a value at which 
chemotherapy is clinically superior if the underlying model is correct. In the 
remaining simulations the upper limit exceeded 25 so the clinical recommendation 
would be to use chemotherapy when RS > 25.  Therefore, there is strong evidence 
that the linear interaction model will provide evidence for a clinically useful cutpoint. 
 
If there is a significant interaction and the point of equivalence is in the range 0-
25, then we expect there could be a slight difference in DFS at the cutpoint.  The 
following table shows the results of the simulations and the expected DFS and 
difference at 5 and 10 years at the cutpoint:  
 
5-year and 10-year DFS at the upper limit of the equivalence region 
 
Conditional on a significant interaction and estimable equivalence point 
 
 
 
 
Percentile 
Outcome 
Mean 
SD 
5 
25 
50 
75 
95 
5-yr Chemo  DFS 
90.0% 
2.01% 
86.3% 
88.8% 
90.3% 
91.4% 
92.9% 
5-yr No Chemo DFS 
88.7% 
2.27% 
84.6% 
87.3% 
89.0% 
90.3% 
91.9% 
5-yr Difference 
1.31% 
0.36% 
0.81% 
1.08% 
1.28% 
1.51% 
1.92% 
10-yr Chemo  DFS 
66.1% 
5.72% 
55.9% 
62.5% 
66.6% 
70.2% 
74.6% 
10-yr No Chemo DFS 
62.4% 
6.17% 
51.6% 
58.5% 
63.0% 
66.8% 
71.7% 
10-yr Difference 
    3.67% 
0.81% 
2.41% 
3.23% 
3.68% 
4.17% 
4.91% 
 
The expected difference in 5-year DFS at the cutpoint is shown below: 
 
 
 
 
 
0
2
4
6
8
10
0
1
2
3
Estimated percent difference in 5-year DFS
Limited to Simulations with a Significant Interaction
Difference in Five-year DFS at Cutpoint

S1007 
Page 111 
Version Date 12/10/2021 
 
 
 
 
 
PREDICTION OF CHEMOTHERAPY BENEFIT IN PATIENTS ABOVE AND 
BELOW THE CUTPOINT 
 
Having established this upper cutpoint (c) inside the range 0-25, we would then 
like to show that for observations above c, that there is a significant benefit to 
chemotherapy collapsing across RS above this cutpoint.  However, because this 
cutoff is likely to be very close to 25 if it exists then there may not be sufficient data 
to show a statistically significant benefit. Power for this analysis is likely to be low 
(estimated to be 23%), but we will also show the Kaplan-Meier graph for this group 
which should indicate an advantage to chemotherapy. Similarly, one would want 
to show no significant benefit of chemotherapy below the cutpoint c.  When there 
was a significant statistical interaction, the estimated lower bound for the HR of 
chemo versus no chemotherapy for RS values below the cutpoint exceeded 0.90 
in 97% of the simulations. Thus, there is sufficient power for data below the cutpoint 
to show no clinical benefit of chemotherapy.  
 
The analysis of the overall chemotherapy effect (collapsed over RS) and then 
separately by groups below and above the cutpoint will provide further supportive 
evidence of the approach since it does not directly require that RS be linearly 
related to outcome. Patients above the cutpoint will have clear evidence in favor 
of chemotherapy while patients below the cutpoint might want to balance the risks 
against the benefits.  As discussed above the cutpoint should divide the population 
into two groups. One might expect a qualitative interaction, i.e. that there would 
not be a benefit in the lower group, but there would be a significant benefit in the 
upper group. The size of these two groups would depend on the location of the 
cutpoint. Kaplan-Meier survival curves will be used to illustrate the comparison of 
chemotherapy versus no chemotherapy for the group below the cutoff and the 
group above the cutoff.  
 
EFFECT OF COMPLIANCE ON POWER 
 
Our proposed trial enrollment is a two-step method intended to minimize non-
compliance.  We hope to eliminate most potentially non-compliant patients from 
the randomized trial prior to randomization and thus improve the power of the ITT 
analysis. For patients with a higher RS score, the patient may be unwilling to be 
randomized to no chemotherapy.  Therefore, we intend to provide the RS value 
prior to randomization.  Similarly, patients with a very low RS may not want to 
receive chemotherapy so these patients may elect not to be randomized.  All 
patients will be fully informed prior to randomization and will provide informed 
consent after knowledge of the RS value.  
 
While we hope that the above procedures eliminate likely noncompliant patients 
prior to randomization, we know that some will still be noncompliant after 
randomization.  Dr. Gray, statistician for the TAILORx trial, has suggested that 
among patients with known RS value prior to enrollment, about 10% in each group 
were noncompliant with randomized assignment and this may depend on the RS 
values.  We believe the procedures instituted above can reduce this to about 5% 
in each group.  Consequently, the estimated sample size above includes this 5% 
noncompliance rate and assumes that noncompliance depends on RS.  For 
patients randomized to chemotherapy, we assume 5% do not receive 
chemotherapy and that a patient with RS 0-11 is twice as likely to refuse as one 
who has RS 12-25.  For patients randomized to not receive chemotherapy, we 
assume 5% do receive chemotherapy and that a patient with RS 18-25 is twice as 
likely to receive chemotherapy as one who has RS 0-17.  We further assume that 
the noncompliant patients remain in the study and provide follow-up.  Thus, in the 
ITT analysis 5% of patients in each treatment group have a treatment opposite to 
their randomized assignment.  This results in a huge increase in the necessary 

S1007 
Page 112 
Version Date 12/10/2021 
 
 
 
 
 
sample size. Based on the original design if all patients were compliant, then the 
necessary sample size would be 3,200.  With just 5% of patients expected to be 
noncompliant, then the sample size increases by 800 patients.  Clearly, eliminating 
potentially noncompliant patients may result in more screens, but ultimately 
provides a much smaller randomized group. 
 
The 5% noncompliance rate was incorporated into the simulations.  However, we 
also added an additional 5% to the simulation sample size (n=4,750) to allow for 
dropout and ineligible patients so the final accrual goal is 5,000. 
 
5.0 
STATISTICAL ANALYSIS PLAN 
 
5.1 
STATISTICAL MODEL 
 
All analyses will use Cox regression models for DFS. The model will be stratified 
by group (NCTN or UNICANCER) so that the baseline hazard rate will reflect the 
different populations.  The primary hypothesis about interaction of RS and 
treatment will be tested using the model: 
 
  
where menopause is an indicator for the stratification factor of menopausal status.  
The power calculations assume no interaction of prediction by RS and menopausal 
status or number of nodes, but those assumptions will be tested.  If the interaction 
of treatment and RS is statistically significant then the second step is to estimate 
the equivalence point.   The two log hazard ratios will intersect at 
 
 
indicating the point of equivalence. Variance for the estimate of  is derived from 
the delta method as 
 
 
where V indicates the covariance matrix. Then the 95% CI for the estimate of  
can be derived assuming normality. In this case we are interested only in a 1-sided 
95% CI for the upper limit.  We assume that this estimate of  is in the range 0-25, 
otherwise either chemotherapy is universally better or worse for all RS values in 
the range.  To establish the cutpoint for efficacy we use the upper limit 
 
If c > 25, then we need to recommend chemotherapy for all RS>25.  If c ≤ 25, then 
we can determine the cutpoint where chemotherapy is superior to no 
chemotherapy.   
 
Power was computed first on the probability of finding a significant interaction and 
secondly on the upper confidence interval of the cutpoint being less than 25.  
 
These methods assume that there is at least a monotonic increase in benefit of 
chemotherapy as RS increases. This will be further established with secondary 
analyses including tests of departure from linearity and dependence of the cutpoint 
on other factors such as menopausal status or number of positive nodes. 
Simulations using a misspecified model that was nonlinear showed that the liner 
model provided a reasonable fit to the data and gave an accurate representation 
of the cutpoint.  Furthermore, the trial data will be dichotomized at the cutpoint in 
order to perform a stratified (by menopausal status) log-rank test of chemotherapy 
in the lower RS group and the upper RS group as determined by the cutpoint. The 
(
)
0
1
2
3
4
(t; chemo, rs, menopause)
(t) exp
chemo+ 
RS + 
chemo*RS+ 
menopause






=
1
3
ˆ
ˆ
ˆ
/



= −
( )
2
11
13
33
2
3
1
ˆ
ˆ
ˆ
2
ˆ
Var
V
V
V






=
+
+


( )
ˆ
ˆ
1.645*
c
Var




=
+





S1007 
Page 113 
Version Date 12/10/2021 
 
 
 
 
 
expectation is that the lower group will not show a significant benefit of 
chemotherapy while the upper group may show a statistically significant benefit 
after collapsing RS values within the subgroup. This will further confirm that there 
is an optimal RS value to consider chemotherapy. 
 
The assumption of proportional hazards in all models will be tested.  If the 
proportional hazards assumption is not satisfied (p<0.05) we will split the time axis 
at 5 years and perform separate analyses.   
 
Should a significant interaction not be found, the next step is to assume that the 
underlying model is the following:  
 
 
 
The main effect of chemotherapy will be tested against the reduced (null) model: 
 
 
 
The null model assumes that RS is prognostic, and that menopause is included as 
a stratification variable. 
 
Planned secondary analyses include adjustment for sentinel node biopsy and 
group NCTN/UNICANCER.  Test of the interactions of these stratification variables 
with treatment will also be conducted.  If there is a significant interaction, separate 
models will be fit for that stratum to determine if it is a quantitative or qualitative 
interaction.  
 
5.2 
INTERIM ANALYSIS 
 
Under the assumptions above, we would expect 832 events for the primary 
analysis of the interaction of RS and chemotherapy.  The first interim analysis 
would be after 24% of the events have been observed or approximately 6.6 years 
after initiation of the study.  This would correspond to the end of accrual if accrual 
is uniform and at the expected level.  There would be subsequent annual interim 
analyses thereafter with 37%, 53%, 72%, and 92% with the final analysis at Year 
11.  The analyses will use the Lan-Demets spending function with a truncation 
bound.  To achieve a cumulative 0.025 1-sided significance level, the interim test 
‘s will be 0.0005, 0.0005, 0.00149, 0.00741, 0.01673, respectively, and the final 
=0.01871 so there is little loss of power due to the interim analyses. All of these 
analyses are expected to be after accrual has finished so a decision to publish 
early would be based on the interim analysis. 
 
5.3 
SAFETY ANALYSIS 
 
We also want to monitor the upper RS group of 14-25 to avoid harming patients if 
there is early evidence of efficacy in this group.  An analysis will be conducted at 
4 years to evaluate efficacy of chemotherapy in patients with RS 14-25 to 
determine if there is a potential significant benefit of chemotherapy early in the trial. 
If this comparison is statistically significant at p=0.05 (2-sided) then further 
randomization in patients with RS 14-25 would be suspended.    A similar 
comparison would then also be performed in the RS 0-13 group to determine if the 
trial should suspend accrual completely.  Otherwise, all other analyses would occur 
after accrual is complete.   
 
 
(
)
0
1
2
3
(t; chemo, rs, menopause)
(t) exp
chemo+ 
RS + 
menopause





=
(
)
0
1
2
(t; chemo, rs, menopause)
(t) exp
RS
menopause




=
+

S1007 
Page 114 
Version Date 12/10/2021 
 
 
 
 
 
5.4 
SECONDARY OUTCOMES ANALYSIS 
 
Analyses for secondary survival outcomes (OS and DDFS) will be analyzed in a 
similar manner to DFS, though power will be lower than DFS, due to fewer events.  
Local disease-free interval will use a competing risk framework to accommodate 
informative censoring due to distant recurrence or death.  Analysis of toxicity will 
be compared between the two arms using logistic regression.   
 
5.5 
OVERALL TYPE 1 ERROR 
 
Power is based on the alternative hypothesis being true.  We have a two-step 
testing procedure. The first step is a test of the interaction.  If that interaction is not 
statistically significant, then we test for a main effect of chemotherapy adjusting for 
RS as a linear variable.  Thus, we consider the following model as the null 
hypothesis for the simulations: 
 
 
 
As expected the first stage had a Type 1 error rate of 5.08%.  If there was not a 
significant interaction, then the effect of chemotherapy was tested.  This added 
2.46% to the error rate so the Type 1 error rate overall is about 7.5% for the two-
stage testing. 
 
5.6 
ACCRUAL RATE (ORIGINAL) 
 
Years 1-6, 48 patients per month for the randomized trial. 
 
 
6.0A 
ACCRUAL (ORIGINAL SECTION) 
 
We intend to accrue 4,000 randomized patients over 6 years. The power calculations 
assume uniform accrual over the six years. In practice, however, accrual in the first year is 
typically slower due to IRB approvals and lack of familiarity with the trial. We allow for 5 
additional years of follow-up after the last patient has been entered.  TAILORx has accrued 
well, but targets node-negative women which comprises a greater percentage of women 
with breast cancer. Using SEER incidence rates from 2004 we computed the expected 
number of incident breast cancer cases for women aged 35-74 using age-specific 
incidence to be 148,686 invasive cases in the U.S. Of this number 38,671 would have 
stage II/IIIA and would be ER positive. Based on the S8814 distribution of RS, 23,589 per 
year would have RS ≤ 5.  To reach our goal of 667 per year (56/month) we would have to 
enroll about 2.8% of patients in the U.S.  We believe this trial will be attractive to insurers 
and HMO’s since there is the possibility of costs reduction with the expected outcome.  
With the support of advocacy groups and the assistance of NCIC and other international 
partners the monthly accrual goal seems feasible.   
 
Another issue concerns the number needed to screen to identify a population of 1-3 node-
positive patients with RS ≤ 25.  We have estimated the number of 8,800 screenees to yield 
5,600 possibly eligible patients based on the S8814 distribution.  The Oncotype DX® test 
has been used in clinical practice for node positive disease since 2008, and there is 
experience in reporting Recurrence Score results in more than 5,000 patients. For both the 
node negative and node positive cases submitted in clinical practice, there has had a 
somewhat smaller proportion of very high and very low Recurrence Scores compared to 
the distribution in the clinical trials. Approximately 80% of the tested cases in the Genomic 
Health clinical laboratory have had RS ≤ 25 (32% with RS 0 – 13 and 48% with RS 14-25) 
(Dr. Shak, personal communication). Based on these numbers, it is estimated that 
randomization of 4,000 patients with RS ≤ 25 would require screening with Oncotype DX® 
(
)
0
1
(t; RS)
(t) exp
RS 



=

S1007 
Page 115 
Version Date 12/10/2021 
 
 
 
 
 
approximately 7,200 patients. To allow some protection we have specified this as 8,800, 
but believe this to be an overestimate.  One area of concern with our proposed recruitment 
strategy is that patients eligible for the trial may not enroll after receiving their RS value.  
We have estimated that the proportion accepting randomization will be 69%.   
 
To reach our goal of 667 per year (56/month) we would have to enroll about 2.8% of 
patients in the U.S. With the support of advocacy groups and the assistance of NCIC and 
other international partners the monthly accrual goal seems feasible.   
 
6.0B 
ACCRUAL (REVISED) 
 
Originally we expected accrual of 4,000 randomized patients to take 6 years, giving a 
monthly accrual rate of 56 patients per month. The formal study completion date was five 
years after the last patient was enrolled to provide sufficient power for analyses.  Thus, the 
original trial duration was expected to be 11 years.  In this revised sample size calculation 
we use the actual monthly enrollment rates from study start in February 2011 to July 2014 
which showed accrual not reaching the target goal until February 2012.  Subsequently, 
accrual exceeded the goal considerably and the trial goal of 4,000 would be expected to 
be reached by August 2015 or 4.5 years of total accrual which is 1.5 years earlier than 
expected.  If the trial used the original stopping rule of 5 years after the last patient, then 
power would be reduced considerably by the shorter follow-time for events to accrue.  We 
can either extend the follow-up period and/or increase the accrual by combining with the 
UNICANCER group.  We have elected to do both as explained below. 
 
Accrual from Sept 2014 to August 2015 is assumed to be 98 randomized patients per 
month until the NCTN accrual reaches 4,000 patients.  We assume UNICANCER will 
accrue approximately 83.3 per month for 12 additional months.  This will result in a total 
sample size of 5,000 patients over a 5.5 year accrual period.  After the last patient is 
accrued, then there will be 5.5 more years of follow-up before the study will have final 
analysis.  The total trial duration will be 11 years which is the original length of the 
trial.  However, individual patients will be followed for a minimum of fifteen years regardless 
of the date of enrollment to assess long-term effects of treatment.   
 
Through July 2014, we have found 50% of patients who enroll in the trial are subsequently 
randomized.  Originally, we expected that to be only 43%.  Therefore, to achieve 5,000 
randomized patients we expect to screen 10,000 possible candidates. 
 
7.0 
INCREASE IN SAMPLE SIZE FROM 4,000 TO 5,000 
 
In September 2014, we amended the sample size from 4,000 to 5,000.  This was in part 
due to accrual that was more rapid than expected.  Since the analysis was to be performed 
at 5 years after the last accrual, then total follow-up time would be shortened and there 
would not be enough events.  While one could lengthen the follow-up time without 
increasing accrual, this increased power back to the original level but would provide no 
protection against lower than expected event rates or violation of the statistical 
assumption.  Instead we had an opportunity to partner with UNICANCER in France and 
increase the sample size by 1,000 randomized patients. The combined data will be the 
basis of the analysis with planned subset analyses in each of the populations intended to 
show similar results.  Below we explain the implications in changing the accrual target. 
 
As described in Section 11.2 accrual started slowly, but then improved dramatically so that 
now accrual of the original sample size goal is expected to finish 1.5 years early. Since the 
original design called for a final analysis 5 years after the last patient was enrolled, the 
number of events is considerably reduced.  Using the observed sample size accrual, but 
keeping other design elements constant then power to find a significant interaction would 
drop to 68% due to the shorter window for events.  If we increase the window to 6.5 years 
after the last patient is accrued then power can be restored to 82.7% without adding 1,000 

S1007 
Page 116 
Version Date 12/10/2021 
 
 
 
 
 
new patients.  However, that provides no margin against some violation of the statistical 
assumptions of this important signature trial of the NCTN.  For example, if the event rate 
is lower than predicted we would not have power to address this important question.  It is 
too early in the trial to assess the event rate accurately (and it depends on the intervention), 
but we can look at the population in terms of prognostic risk factors compared to what was 
expected.  There has been a strong shift in the number of positive nodes compared to 
SWOG-8814.  The older trial had a distribution of positive nodes for 1-3 of 48%, 32%, and 
20%, respectively while the current trial has a distribution of 68%, 24%, and 8%.  However, 
because of sentinel node biopsy there could have been an apparent shift downwards that 
does not reflect the true distribution of number of positive nodes.  Furthermore, the current 
trial has a distribution of Oncotype DX® scores that is the same as in SWOG-8814 when 
restricted to ≤ 25 and in agreement with the expected distribution used to plan the trial.  For 
trial planning we used an overall 5-year DFS rate of 92.4%, but we would still like to have 
sufficient power if the event rate is less than expected.   
 
The second reason to increase the sample size is to provide a validation that the results 
apply to an external population to NCTN patients.  We are including these patients in the 
overall trial but will conduct planned subset analyses of the two cohorts separately.  If we 
retain the same design parameters with a 5,000 patient trial of the same total duration (11 
years), then power increases to 86.7% and the expected number of events increases from 
731 to 832.  When the interaction is significant we determine the estimated cutpoint for 
using chemotherapy and its upper confidence bound. This cutpoint can be better 
determined when there are more events.  Finally, the larger sample size allows some 
protection against lower event rates.  For example, if the actual 5-year DFS rate is 93.9%, 
then power is still 80% to detect a significant interaction. 
 
To guarantee that the trial will be well powered under the assumptions but have sufficient 
power under minor violation of the assumptions, we are increasing the sample size to 
5,000 with a 5.5 year accrual and a 5.5 year follow-up so that the total trial duration 
remains the same as in the original protocol. 
 
8.0 
MONITORING TRIAL ACCRUAL AND COMPLIANCE 
 
Accrual will always be a potential concern in every trial and it is often difficult to assess 
how successful a trial will be.  CTEP has an existing rule at one year that mandates an 
assessment of accrual.  Even after passing this test, the success of such a trial will depend 
on accrual projections, percentage eligible, percentage accepting randomization, and 
compliance. We propose that a committee of five statisticians (1 SWOG, 2 NCI, and 2 
others from the cooperative groups) jointly review the data (excluding outcomes) after two 
full years of accrual to determine viability of the trial and/or changes to be made in accrual 
projections.  
 
Compliance is a threat to statistical power since the intention-to-treat analysis classifies 
patients by treatment assignment regardless whether they received the assigned 
treatment.  This trial has been powered with an expectation that 5% of patients are 
noncompliant, i.e. receive the alternative treatment, but remain in the analysis and are 
classified by treatment assigned, not by treatment received. Accordingly, if compliance 
among randomized patients exceeds 15% in the first year of accrual, consideration will be 
given to stopping the trial unless the problem has been corrected.  After two years, the 
cumulative crossover rate cannot exceed 12%.   
 
 
 

S1007 
Page 117 
Version Date 12/10/2021 
 
 
 
 
 
As long as the crossover rate is 12% or less, we can maintain power by keeping the sample 
size constant, but increase the follow-up period to ensure sufficient power to find a 
significant interaction.  For the standard model we assumed a 5% crossover rate and had 
81% power.  If crossover is lower, than power increases.  If crossover is 6-7%, then we 
increase follow-up by 6 months to regain 80% or greater power. If crossover is 8-9%, then 
we increase follow-up by 12 months to regain 80% or greater power. If crossover is 10-
12%, then increasing follow-up to 18 months provides sufficient power as shown in the 
graph below. 
 
 
 
9.0  
REFERENCES 
 
1.  
Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-
treated, node-negative breast cancer. N Engl J Med. 2004; 351:2817-26.  PMID: 
15591335. 
 
2.  
Paik S, Tang G, Shak S, et al.  Gene expression and benefit of chemotherapy in 
women with node-negative, estrogen receptor–positive breast cancer.  J Clin 
Oncol 2006; 24:3726-34.  PMID: 16720680. 
 
3. 
Albain KS, Barlow WE, Shak S, Hortobagyi GN, et al. Prognostic and predictive 
value of the 21-gene recurrence score assay in postmenopausal women with 
node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a 
retrospective analysis of a randomized trial, Lancet Oncology, 11:55-65, 2010.  
PMID: 20005174. 
 
4.  
Pepe MS, Feng Z, Huang Y, Longton G, Prentice R, Thompson IM, Zheng Y. 
Integrating the predictiveness of a marker with its performance as a classifier. Am J 
Epidemiol. 2008;167(3):362-8. 
 
 
 
 
60
70
80
90
100
0
.01
.02
.03
.04
.05
.06
.07
.08
.09
.1
.11
.12
Crossover rate
5 years follow-up
5.5 years folow-up
6 years follow-up
6.5 years follow-up
Keep n fixed; increase follow-up
Power by Crossover Rate

S1007 
Page 118 
Version Date 12/10/2021 
 
 
 
 
 
18.4 
Determination of Expedited Adverse Event Reporting Requirements 
 
Adverse event data collection and reporting, which are required as part of every clinical 
trial, are done to ensure the safety of patients enrolled in the studies as well as those who 
will enroll in future studies using similar agents. Adverse events are reported in a routine 
manner at scheduled times during a trial. (Directions for routine reporting are provided in 
Section 14.0.) Additionally, certain adverse events must be reported in an expedited 
manner to allow for more timely monitoring of patient safety and care. Expedited adverse 
event reporting principles and general guidelines follow; specific guidelines for expedited 
adverse event reporting on this protocol are found in Section 16.1. 
 
All serious adverse events determined to be reportable to the Institutional Review Board 
responsible for the oversight of the patient must be reported according to local policy and 
procedures.  Documentation of this reporting should be maintained for possible inspection 
during quality assurance audits. 
 
Steps to determine if an adverse event is to be reported in an expedited manner (This 
includes all events that occur while on treatment or within 30 days of the last dose of 
protocol treatment.) 
 
Step 1: Determine whether the patient has received an investigational agent, commercial 
agent, or a combination of investigational and commercial agents. 
 
An investigational agent is a protocol drug administered under an Investigational New 
Drug Submission (IND). In some instances, the investigational agent may be available 
commercially, but is actually being tested for indications not included in the approved 
package label.  
 
Commercial agents are those agents not provided under an IND but obtained instead 
from a commercial source. The NCI, rather than a commercial distributor, may on some 
occasions distribute commercial agents for a trial. 
When a study includes both investigational and commercial agents, the following rules 
apply.   
• 
Concurrent administration: When an investigational agent(s) is used in 
combination with a commercial agent(s), the combination is considered to be 
investigational and expedited reporting of adverse events would follow the 
guidelines for investigational agents. 
• 
Sequential administration:   When a study includes an investigational agent(s) 
and a commercial agent(s) on the same study arm with sequential administration 
all expedited reporting of adverse events should follow the guidelines for the type 
of agent being given.  For example, if the patient begins the study on the 
investigational agent(s), then all expedited reporting of adverse events should 
follow guidelines for the investigational agent(s).  Once the patient begins receiving 
the commercial agent(s) then all expedited reporting of adverse events should 
follow the guidelines for commercial agent(s).   
 
Step 2: Identify the type of event using the NCI Common Terminology Criteria for Adverse 
Events (CTCAE). The CTCAE provides descriptive terminology and a grading scale for 
each adverse event listed. A copy of the CTCAE can be downloaded from the CTEP home 
page (http://ctep.cancer.gov). Additionally, if assistance is needed, the NCI has an Index 
to the CTCAE that provides help for classifying and locating terms.  
 
Step 3:  Grade the event using the NCI CTCAE version specified in the protocol for 
reporting serious adverse events. 
 

S1007 
Page 119 
Version Date 12/10/2021 
 
 
 
 
 
Step 4: Determine if the adverse event is Expected or an Exception to Expedited 
Reporting.  Expected events are those that have been previously identified as resulting 
from administration of the agent and are listed in one of the following:   
 
• 
The current NCI SPEER (Specific Protocol Exceptions to Expedited Reporting) for 
treatments using agents provided under an NCI-held IND, or an equivalent listing 
for treatments using agents provided under a Non-CTEP-held IND; located in 
Section 3.0 of the protocol. 
• 
For treatments using commercial agents, the current CAEPR (Comprehensive 
Adverse Event and Potential Risks), ASAEL (Agent Specific Adverse Event List), 
or other list of expected toxicities located in Section 3.0 of the protocol, or the drug 
package insert.   
• 
Exception to Expedited reporting located in Section 16.1f of the protocol. 
 
An adverse event is considered unexpected, for expedited reporting purposes only, when 
either the type of event or the severity of the event is not listed in one of the areas outlined 
above. 
 
Step 5:  Determine whether the adverse event involved hospitalization or a 
prolongation of hospitalization (≥ 24 hours). 
 
Step 6:  Additionally, for commercial drugs, determine whether the adverse event 
is related to the protocol therapy. Attribution categories are as follows: 
Unrelated, Unlikely, Possible, Probable, and Definite.  Consult the 
appropriate table for expedited reporting criteria for commercial agent(s). 
 
NOTE:   Any event that occurs more than 30 days after the last dose of study agent 
and is attributed (possible, probable, or definite) to the study agent(s) must be 
reported according to the instructions above and as outlined in the appropriate 
table in Section 16.1. 
 

S1007 
Page 120 
Version Date 12/10/2021 
 
 
 
 
 
18.5 
Participation Procedures for the International Collaborating Institutions  
 
SWOG 
 
A PHASE III, RANDOMIZED CLINICAL TRIAL OF STANDARD ADJUVANT 
ENDOCRINE THERAPY +/- CHEMOTHERAPY IN PATIENTS  
WITH 1-3 POSITIVE NODES, HORMONE RECEPTOR-POSITIVE AND HER2-
NEGATIVE BREAST CANCER WITH RECURRENCE SCORE (RS) OF 25 OR LESS. 
RXPONDER:  A CLINICAL TRIAL RX FOR POSITIVE NODE, ENDOCRINE 
RESPONSIVE BREAST CANCER 
 
 
EudraCT 2012-000174-37 
 
 
 
GEICAM CHAIR: 
 
Emilio Alba Conejo, M.D. 
Hospital Clinico Univérsitario Virgen de la Victoria 
Medical Oncology Department 
Colonia Santa Ines s/n 
Campus Univérsitario Teatinos 
Malaga, 29010 ES 
Phone: +34 951 032000  
E-mail:  oncologia98@yahoo.com 
 
UNICANCER CHAIR: 
 
Suzette Delaloge, M.D., M.Sc. 
Chef du Comite de Pathologie Mammaire 
Head, Breast Cancer Group 
Gustave Roussy 
Phone:  01 42 11 42 11  
FAX:  01 42 11 52 74 
E-mail:  suzette.delaloge@gustaveroussy.Fr 
 
CTEP – IND –– NOTE:  The CTEP IND is crossfiled against the docetaxel IND.  However, 
the investigational aspect of the study is in regard to the use of the Oncotype DX® testing. 

S1007 
Page 121 
Version Date 12/10/2021 
 
 
 
 
 
Appendix Overview 
 
International sites should follow the main protocol except as detailed below. 
 
Subject 
Protocol Section 
Appendix Section 
Study Monitoring 
16.0 
1.0 
Data Submission 
13.0 and 14.0 
2.0 
Handling of Samples 
15.0 
3.0 
Independent Ethics 
Committee 
16.0 
4.0 
Archiving 
Not mentioned in protocol 
5.0 
Compliance with National 
Cancer Institute (NCI) 
Guidelines for International 
Collaborations 
Not mentioned in protocol 
6.0 
 
Treatment questions from Spanish sites should be directed to Emilio Alba Conejo, M.D., 
(oncologia98@yahoo.com, 34 951 032000).  Non-treatment questions from Spanish sites 
should be directed to Ruth Campo (rcampo@geicam.org). 
 
Treatment questions from French sites should be directed to Suzette Delaloge M.D., M. 
Sc., (suzette.delaloge@gustaveroussy.fr, 01 42 11 42 11).  Non-treatment questions from 
French sites should be directed to Jerome Lemonnier (j-lemonnier@unicancer.fr). 
 
1.0 
STUDY MONITORING 
 
Prior to the first patient registration, an Initiation Visit will be conducted onsite or 
via teleconference and the local approved consent form will be submitted to SWOG 
for approval. 
 
International Collaborating Institutions are responsible for auditing their own 
institutions according to SWOG and NCI-CTMB Guidelines.  Audit data will be 
provided in English to the SWOG QA Department who will enter the audit data into 
the NCI database. 
 
2.0 
REGISTRATION AND DATA SUBMISSION 
 
Sites will follow instructions in Sections 13.0 and 14.0 of the main protocol with the 
following exceptions: 
 
Sites must submit original pathology reports along with the English Translation 
Summary which is located on the S1007 abstract page (www.swog.org). 
 
Eligibility data are due within7 days after randomization.  Subsequent treatment, 
adverse event and follow-up data submission vary; adherence to protocol 
requirements is expected. 
SWOG Policies apply to GEICAM and UNICANCER’s participation in S1007. 
Policy 33 describes Institutional Performance Review metrics and expectations.  
Failure to submit data as specified in the protocol may result in corrective action 
as described in the policy, 
(https://swog.org/visitors/Download/Policies/Policy33.pdf). 
 
 

S1007 
Page 122 
Version Date 12/10/2021 
 
 
 
 
 
3.0 
HANDLING OF SAMPLES 
 
Institutions are required to collect specimens as outlined in Section 15.0 of the 
protocol.   
 
Institutions will submit tissue directly to Genomics Health for the Oncotype testing 
as outlined in Section 15.1 of the protocol.   
 
Spanish institutions will submit tissue and blood to the GEICAM repository 
(Fundation Jimenez Diaz located in Madrid, Spain) for correlative studies and 
banking as per Section 15.2 of the protocol.  French institutions will submit tissue 
and blood to the Centre de Ressource Biologique (located in Lyon, France) for 
correlative studies and banking per Section 15.2 of the protocol. 
 
The GEICAM and UNICANCER repositories will batch ship the specimens every 
6 months to the SWOG Repository at the following address: 
 
SWOG Biospecimen Bank 
Solid Tissue, Myeloma and Lymphoma Division 
Nationwide Children’s Hospital 
700 Children’s Drive, WA 1340 
Columbus, OH  43205 
 
4.0 
INDEPENDENT ETHICS COMMITTEE 
 
The study will be performed in accordance with the protocol, lCH-GCP, Competent 
Authorities regulations and the national laws applicable for conduct of clinical trials.  
The Coordinating Investigator has the responsibility to apply and receive 
acceptance and applications for the study from the Regional Ethics Committee and 
the Competent Authority, and to forward such acceptance to these parties.   
 
5.0 
ARCHIVING 
 
In accordance with the U.S. regulations, essential documents must be maintained 
for at least 3 years after completion of the research (see SWOG Record Retention 
Guidance available at www.swog.org).  
 
6.0 
COMPLIANCE WITH NATIONAL CANCER INSTITUTE (NCI) GUIDELINES FOR 
INTERNATIONAL COLLABORATIONS 
 
Participation in this study will take place in compliance with the National Cancer 
Institute’s “Cooperative Group Guidelines for the Development, Conduct and 
Analysis of Clinical Trials with International Collaborating Institutions, Version 2.0”. 
The guidelines have been satisfied as detailed below. 
 
Monitoring the trial: 
 
The study is monitored by the SWOG Data and Safety Monitoring Committee 
(DSMC) as described in Section 11.9 of the main protocol. Sites will be notified of 
DSMC recommendations and actions through postings on the SWOG website. The 
NCI CTEP guidelines applied to Phase III studies regarding rate of accrual will be 
followed.  
 

S1007 
Page 123 
Version Date 12/10/2021 
 
 
 
 
 
Clinical study data analysis: 
 
Data will be transmitted directly from each site to the SWOG Statistics and Data 
Management Center in Seattle. Each site transmitting data has an FWA or other 
OHRP-approved assurance.  
 
Auditing of participating institutions: 
 
The Clinical Trials Monitoring Branch (CTMB) Cooperative Group Audit Guidelines 
will be followed; all scheduling, preliminary reports and final reports will be reported 
to the SWOG QA Department which will enter audit findings into the CTMB Audit 
Information System (AIS). Each single participating site will have a separate report 
submitted through the CTMB-AIS. SWOG will be responsible for obtaining follow-
up information and monitoring/reporting any disciplinary action, if required. 
 
Logistical issues related to international collaborative clinical trials: 
 
 
GEICAM has established the following Federal-Wide Assurance (FWA) with the 
Office for Human Research Protections (OHRR):    
 
Foundation for GEICAM FWA00018352 
 
UNICANCER has established the following Federal-Wide Assurance (FWA) with 
the office of for Human Research Protections (OHRP): 
 
UNICANCER FWA00020555 
 
Each registering institution will need to provide a link to an active FWA. The 
following pages of this section include all of the approved institutions and 
registering investigators for GEICAM and UNICANCER. 
 
Notification of international involvement in group trials (Department of State 
clearance): SWOG and the CTEP Program Specialist received State Department 
approval of GEICAM’s participation effective 6/5/12. 
 
1572 Registrations: All registering investigators have submitted 1572s. Please 
note that the FDA 1572 document must be submitted to the National Cancer 
Institute's Pharmaceutical Management Branch for final approval before 
registration privileges can be finalized for investigators.  
 
Adverse event reporting: Adverse events will be transmitted to AdEERS by the 
sites as designated in Section 16.1 of the main protocol. SWOG will notify sites of 
adverse events via postings on the SWOG website. CTEP will receive a copy of 
all MedWatch Forms submitted to the FDA or international drug agencies for 
adverse events related to commercial drugs. 
 
Biological specimens: The procedures for biological specimen collection and 
shipment meet local regulations for the international collaborative group. 
 
Protocol and informed consent translation: The collaborative groups version of the 
protocol and the translated version of the informed consent form are accepted by 
the Regional Ethics Committee and Competent Authority (CA). 
 
Logistical issues specific to international collaborative clinical trials performed with 
European Union member states: 
 

S1007 
Page 124 
Version Date 12/10/2021 
 
 
 
 
 
Ethics committee: A lead ethics committee has been designated, and it has 
reviewed and approved the conduct of the trial within the country of the 
international collaborative group.  This has been submitted to the CTSU-RSS. 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
 
Institut Bergonie 
229 cours de l’Argonne 
Bordeaux, FR 33076 
Phone: 33 5 56 33 33 33 
 
FWA: 00004444 
CTEP Code:  28118 
Dr. Herve Bonnefoi (E-mail: 
h.bonnefoi@bordeaux.unicancer.fr) 
Institut de Cancerologie de 
l’Ouest Site Paul Papin 
2 rue Moll 
Angers Cedex 9, FR 49933 
Phone: 33 2 40 67 99 77 
 
FWA: 00021775 
CTEP Code:  28060 
Dr. Mario Campone  
(E-mail: Mario.campone@ico.unicancer.fr) 
Dr. Sophie Abadie LaCourtoisie  
(E-mail: sophie.abadie@ico.unicancer.fr)  
Dr. Paule Augereau  
(E-mail: paule.augereau@ico.unicancer.fr)  
Dr. Elouen Boughalen  
(Email: elouen.boughalen@ico.unicancer.fr)  
Dr. Caroline Fosegrive   
(E-mail: 
caroline.fosegrive@ico.unicancer.fr)  
Dr. Anne Patsouris  
(E-mail: anne.patsouris@ico.unicancer.fr)  
Dr. Patrick Soulie  
(E-mail: patrick.soulie@ico.unicancer.fr)  
 
Institut de Cancerologie de 
l’ouest Site Rene Gauducheau 
Boulevard Jacques Monod 
Saint-Herblain, FR 44805 
Phone: 33 2 40 67 99 77 
 
FWA: 0021775 
CTEP Code:  28124 
Dr. Mario Campone  
(E-mail: Mario.campone@ico.unicancer.fr)  
Dr. Dominique Berton Rigaud 
(E-mail: dominique.berton-
rigaud@ico.unicancer.fr)  
Dr. Emmanuelle Bourbouloux  
(E-mail: 
emmanuelle.bourbouloux@ico.unicancer.fr)  
Dr. Mathilde Cabart  
(E-mail: mathilde.cabart@ico.unicancer.fr)  
Dr. Jean-Sebastien Frenel  
(E-mail: jean-
sebastien.frenel@ico.unicancer.fr)  
Dr. Carole Gourmelon  
(E-mail: carole.gourmelon@ico.unicancer.fr)  
 
Gustave Roussy 
114 rue Edouard Vaillant 
Villejuif Cedex, FR 94805 
Phone: 33 1 42 11 51 27 
 
FWA: 00007889 
CTEP Code:  28011 
Dr. Suzette Delaloge  
(E-mail: 
suzette.delaloge@gustaveroussy.fr)  
Dr. Mahasti Saghatchian  
(E-mail:  
mahasti.saghatchian@gustaveroussy.fr)  
Dr. Fabrice Andre  
(E-mail: fabrice.andre@ gustaveroussy.fr)  
 

S1007 
Page 125 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Centre Francois  Baclesse 
3 avenue du Général Harris-
BP5026 
Caen, FR 14076 
Phone 33 2 31 45 50 15 
 
FWA: 00022417 
CTEP Code: 28070 
Dr. Christelle Levy  
(E-mail:  c.levy@baclesse.unicancer.fr)  
Dr. Djelila Allouache  
(E-mail: dallouache@baclesse.unicancer.fr)  
Dr. Corinne Delcambre-Lair ( 
E-mail: 
c.delcambre@baclesse.unicancer.fr)  
Dr. Jean-Michel Ollivier  
(E-mail: jmollivier@baclesse.unicancer.fr)  
Dr. Carine Segura-Djezzar  
(E-mail: c.segura@baclesse.unicancer.fr)  
Dr. Julien Geffrelot  
(E-mail: j.geffrelot@baclesse.unicancer.fr)  
Dr. Sabine Noal 
(E-mail:  s.noal@baclesse.unicancer.fr)  
Dr. Ioana Hrab  
(E-mail: i.hrab@baclesse.unicancer.fr)  
Dr. Sandrine Vivier  
(E-mail: s.vivier@baclesse.unicancer.fr)  
Dr. Elodie Coquan  
(E-mail: e.coquan@baclesse.unicancer.fr)  
Centre Antoine Lacassagne 
33 avenue de Valombrose 
Nice Cedex 2, FR 06189 
Phone: 04 92 03 10 00 
 
FWA: 00021829 
CTEP Code: 28036 
Dr. Jean-Marc Ferrero  
(E-mail: jean-
marc.ferrero@nice.unicancer.fr)  
Dr. Philippe Follana  
(E-mail: philippe.follana@nice.unicancer.fr)  
Dr. Veronique Mari  
(E-mail: veronique.mari@nice.unicancer.fr)  
Dr. Jerome Barriere   
(E-mail: jerome.barriere@nice.unicancer.fr)  
Dr. Delphone Borchiellini  
(E-mail: 
delphine.borchiellini@nice.unicancer.fr)  
Centre Hopitalier Prive Saint 
Gregoire 
6 boulevard de la Boutière  
Saint Gregoire, FR 35760 
Phone: 02 99 23 33 33 
 
FWA: 00021797 
CTEP Code: 28130 
Dr. Anne Mercier-Blas  
(E-mail: amercierblas@vivalto-sante.com)  
Dr. Xavier Artignan  
(E-mail: xartigana@vivalto-sante.com)  
Dr. Romuald Le Scodan  
(E-mail: rlescodan@vivalto-sante.com)  
Dr. Laurent Miglianico  
(E-mail: lmiglianico@vivalto-sante.com)  
Dr. Jerome Chamois  
(E-mail: jchamois@vivalto-sante.com)  
Hopital Regional Orleans  
La Source 
14 avenue de l’Hôpital – BP 
6709 
Orleans, FR 45000 
Phone: 02 38 51 44 44 
 
FWA: 00021772 
CTEP Code: 28071 
 
 
Dr. Jerome Meunier  
(E-mail: jerome.meunier@chr-orleans.fr)  
Dr. Corina Cornila-Preda  
(E-mail: corina.cornila@chr.orleans.fr)  
 

S1007 
Page 126 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Centre Catherine de Sienne 
2 rue Eric Tabarly – BP 20215 
Nantes, FR 44202 
Phone: 02 28 27 20 00 
 
FWA: 00021798 
CTEP Code: 28129 
Dr. Alain Lortholary  
(E-mail: 
sec.lortholary@catherinedesienne.fr)  
Dr. Claude El Kouri  
(E-mail: 
elkouri.claude@catherinedesienne.fr)  
Dr. Christele Le Gouill  
(E-mail: 
legouill.christele@catherinedesienne.fr)  
Polyclinique Bordeaux Nord 
Aquitaine 
15-33 rue Claude Boucher 
Bordeaux, FR 33077 
Phone:05 56 43 71 11 
 
FWA: 00021822 
CTEP Code: 28135 
Dr. Nadine Dohollou  
(E-mail: n.dohollou@bordeauxnord.com)  
Dr. Caroline Bureau  
(E-mail: dr.bureau@bordeauxnord.com)  
 
Hopital Pitie Salpetriere 
47-83 Boulevard de l'Hôpital 
Paris, FR 75013 
Phone: 01 42 16 00 00 
 
FWA: 00008088 
CTEP Code: 28002 
Dr. Rosa Conforti  
(E-mail: Rosa.conforti@psl.aphp.fr)  
Dr. Jean-Philippe Spano  
(E-mail:  
jean-philippe.spano@psl.aphp.fr)  
Dr. Marian Gil Delgado  
(E-mail: 
 Marian.gil-delgado@psl.aphp.fr)  
Dr. Marie Ange Rocher  
(E-mail: 
 Marie-ange.rocher@psl.aphp.fr)  
Dr. Johanna Wassermann ( 
E-mail: johanna.wassermann@psl.aphp.fr)  
Clinique Hartmann 
4 rue Kléber 
Levallois Perret, FR 92300 
Phone: 01 46 39 89 89 
 
FWA: 00021935 
CTEP Code: 28106 
Dr. Jean-Michel Vannetzel  
(E-mail: jmvannetzel@i-o-h.org)  
Dr. Jean-Francois Llory  
(E-mail: jfllory@i-o-h.org)  
 
Hopital Prive de Villeneuve 
D’Asq 
20 avenue de la 
Reconnaissance 
Villeneuve D’Asq, FR 59657 
Phone: 0826 666 900 
 
FWA: 00021803 
CTEP Code: 28126 
Dr. Frederic Caquant  
(E-mail: frederic.caquant@mac.com)  
Dr. Olivier Romano  
(E-mail: romanoolivier@yahoo.fr)  
Dr. Sebastien Rault  
(E-mail: sebrault@hotmail.com)  
Centre Oscar Lambret 
3 rue F. Combemale 
Lille, Fr  59000 
Phone:  03 20 29 59 43 
 
FWA: 00015571 
CTEP Code: 28026 
 
Dr. Laurence Vanlemmens 
(E-mail:  l-vanlemmens@o-lambret.fr)  

S1007 
Page 127 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Institut Claudius Regaud 
20-24 Rue Du Pont Saint-Piere 
Toulouse, FR 31059 
Phone:  011 1 48 95 51 31 
 
FWA: 00018273 
CTEP Code: 28103 
Dr. Carlos Alberto Gomez-Roca  
(E-mail: 
Gomez-roca.carlos@iuct-oncopole.fr)  
Dr.Florence Dalenc  
(E-mail: Dalec.florence@iuct-oncolole.fr)  
Dr. Laurence Gladieff  
(E-mail: Gladieff.laurence@iuct-oncopole.fr)  
Dr. Henri Roche  
(E-mail: Roche.henri@iuct-oncopole.fr)  
Institut Jean Godinot 
1 Avenue du General Koenig 
Reims, FR 51056 
Phone: 03 26 50 43 83 
 
FWA: 00021821 
CTEP Code: 28141 
Dr. Christelle Jouannaud  
(E-mail: 
christelle.jouannaud@reims.unicancer.fr)  
Dr. Brigitte Costa  
(E-mail: brigitte.costa@reims.unicancer.fr)  
Dr. Gabriel Yazbek  
(E-mail: gabriel.yazbek@reims.unicancer.fr)  
 
Institut Sainte Catherine 
250 Chemin de Baigne-Pieds – 
CS 80005 
Avignon, FR 84918 
Phone: 04 90 27 63 97 
 
FWA: 00021943 
CTEP Code: 28143 
Dr. Julien Grenier  
(E-mail: j.grenier@isc84.org)  
Dr. Gaetan De Rauglaudre  
(E-mail: g.derauglaudre@isc84.org)  
Dr. Yvelise Goubely Brewer  
(E-mail: y.goubely@isc84.org)  
Dr. Sylvie Kirscher  
(E-mail: s.kirscher@isc84.org)  
Dr. Antoine Arnaud  
(E-mail: a.arnaud@ isc84.org)  
Dr. Gaetan De Rauglaudre  
(E-mail:  g.derauglaudre@ isc84.org )  
Dr. Alice Mege  
(E-mail: a.mege@ isc84.org)  
Hopitaux Du Leman – Site 
Georges Pianta 
3 Avenue de la Dame 
Thonon Les Bains, FR 74203 
Phone: 03 87 50 69 79 
 
FWA: 00021792 
CTEP Code: 28140 
Dr. Francesco Del Piano  
(E-mail: f-delpiano@ch-hopitauxduleman.fr)  
Dr. Khoutir Mahour Bacha  
(E-mail: k-mahour@ch-hopitauxduleman.fr)  
 
Centre Hospitalier De 
Perpignan – Hopital Saint Jean 
20 Avenue du Languedoc – BP 
4052 
Perpignan, FR 66046 
Phone:  33 04 68 61 89 07 
 
FWA: 00022762 
CTEP Code: 28147 
 
 
 
 
 
Dr. Fawzi Kara Slimane  
(E-mail: kara.slimane@ch-perpignan.fr)  
Dr. Christina Rosca  
(E-mail: cristina.rosca@ch-perpignan.fr)  
 

S1007 
Page 128 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Clinique Mutualiste De 
L’Estuaire 
11 boulevard Georges Charpak 
Saint-Nazaire Cedex, FR 44606 
Phone: 02 72 27 54 02 
 
FWA: 00022862 
CTEP Code: 28133 
Dr. Valerie Delecroix  
(E-mail: valerie.delecroix@mla.fr)  
Dr. Phiippe Deguiral  
(E-mail: philippe.deguiral@mla.fr)  
Dr. Catherine Ligeza Poisson  
(E-mail: catherine.ligeza@mla.fr)  
Dr. Thierry Chatellier  
(E-mail: thierry.chatellier@mla.fr)  
Clinique Tivoli Ducos 
220 rue Mandron 
Bordeaux, FR 33000 
Phone: 011 33 5 56 11 60 87 
 
FWA: 00022879 
CTEP Code: 28127 
Dr. Nathalie Bonichon Lamichhane  
(E-mail: bonichon-lamichhane@wanadoo.fr)  
Dr. Hortense Laharie Mineur  
(E-mail: h.laharie@orange.fr)  
Dr. Christophe Debelleix  
(E-mail: christophedebelleix@yahoo.fr)  
Centre Hospitalier Rene Dubos 
Pontoise 
6 avenue de I’lle de France 
Cergy-Pontoise, FR 95301 
Phone: 01 30 75 54 05 
 
FWA: 00021887 
CTEP Code: 28150 
Dr. Francois Morvan ( 
E-mail: francois.morvan@ch-pontoise.fr)  
Dr. Helene Berseneff  
(E-mail: helene.berseneff@ch-pontoise.fr)  
Dr. Sophie Vautier Rit  
(E-mail: sophie.vautier-rit@ch-pontoise.fr)  
Dr. Faiza Atmani  
(E-mail: faiza.atmani@ch-pontoise.fr)  
Centre Leon Berard 
28 rue Laennec 
Lyon, FR 69373 
Phone: 04 78 78 26 54 
 
FWA: 00021946 
CTEP Code: 28006 
Dr. Thomas Bachelot  
(E-mail: 
thomas.bachelot@lyon.unicancer.fr)  
Dr. Paul Rebattu ( 
E-mail: paul.rebattu@lyon.unicancer.fr)  
 
Centre Hospitalier de Douai 
Leonard De Vinci Centre 
Route de Cambrai 
Dechy, FR 59187 
Phone: 03 27 08 60 64 
 
FWA: 00021791 
CTEP Code: 28155 
Dr. Virginie Pottier  
(E-mail: vpottier@clinique-psv.fr)  
Dr. Claire Giraud  
(E-mail: cgiraud@clinique-psv.fr)  
Dr. Franck Darloy  
(E-mail: fdarloy@clinique-psv.fr)  
Clinique Pasteur  
45 Avenue de Lombez 
Toulouse, FR 31076 
Phone: 011 33 5 62 21 16 43 
 
FWA: 00010067 
CTEP Code: 28137 
Dr. Raymond Despax  
(E-mail: r.despax@clinique-pasteur.com)  
Dr. Alain Gratet  
(E-mail: a.gratet@clinique-pasteur.com)  
 
Centre Hospitalier De 
Montelimar 
Quartier Beausseret 
Montelimar, FR 26200 
Phone:  011 33 04 75 53 43 89 
 
FWA: 00022943 
CTEP Code: 28144 
Dr. Bernard Duvert  
(E-mail: bernard.duvert@ch-montelimar.fr)  
 

S1007 
Page 129 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Hopital Prive Drome Ardeche – 
Clinique Pasteur 
294 Boulevard Charles de 
Gaulle 
Guilherand-Granges, FR 07500 
Phone: 04 75 82 31 83 
 
FWA: 00022145 
CTEP Code: 28139 
Dr. Hugues Barletta   
(E-mail: dr.barletta@wanadoo.fr)  
Dr. Mathieu Bosset  
(E-mail: mathieu.bosset@wanadoo.fr)  
Dr. Stephane Lantheaume  
(E-mail: dr.lantheaume@orange.fr)  
Dr. Francois Sensenbrenner  
(E-mail: f.sensenbrenner@orange.fr)  
Hopital Bretonneau 
2 Boulevard Tonnelle 
Tours, FR 37044 
Phone: 011 33 2 47 47 82 61 
 
FWA: 00022750 
CTEP Code: 28078 
Dr. Nawale Hajjaji  
(E-mail: n.hajjaji@chu-tours.fr)  
Dr. Catherine Barbe 
(E-mail: c.barbe@chu-tours.fr)  
Dr. Dorothee Chocteau-Bouju 
(E-mail: d.chocteau-bouju@chu-tours.fr)  
Centre Alexis Vautrin 
6 avenue de Bourgogne 
Vandoeuvre-Les-Nancy Cedex, 
FR 54511 
Phone: 03 83 59 84 19 
 
FWA: 00022450 
CTEP Code: 28014 
Dr. Anne Lesur  
(E-mail: a.lesur@nancy.unicancer.fr)  
Dr. Mathilde Deblock  
(E-mail: m.deblock@nancy.unicancer.fr)  
Dr. Elisabeth Luporsi  
(E-mail: e.luporsi@nancy.unicancer.fr)  
Dr. Maria Rios  
(E-mail: m.rios@nancy.unicancer.fr)    
Dr. Lionel Uwer  
(E-mail: l.uwer@nancy.unicancer.fr)  
 
 
Hopital Prive Clairval 
317 Boulevard du Redon 
Marseille, FR 13009 
Phone: 04 91 17 16 39 
 
FWA: 00022616 
CTEP Code: 28023 
Dr. Cyril Foa  
(E-mail: foacyril@club-internet.fr)  
Dr. Jean-Baptiste Paoli  
(E-mail: jb.paoli@free.fr)  
Dr. Robert Herve  
(E-mail: bob.herve@wanadoo.fr)  
Polyclinique Francheville 
38 boulevard de Vesone - BP 
4063 
Periguex, FR 24000 
Phone: 011 33 0 55 302 1332 
 
FWA: 00022545 
CTEP Code: 28161 
Dr. Charles Briac Levache  
(E-mail:  levache@oncoradio24.com)  
Dr. Laurent Cany  
(E-mail: l.cany@oncoradio24.com)  
Clinique Chenieux 
18 Rue Du General Catroux 
Limoges, FR 87039 
Phone: 011 33 05 55 45 4800 
 
FWA: 00022634 
CTEP Code: 28160 
Dr. Dominique Genet 
(E-mail:  dominique.genet!chu-limoges.fr )   

S1007 
Page 130 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Centre Henri Becquerel 
Rue D'Amiens 
CS 11516 
Rouen, FR 76038 
Phone: 011 33 2 32 08 22 42 
 
FWA: 00022923 
CTEP Code: 28123 
Dr. Marianne Leheurteur  
(E-mail:  
marianne.leheurteur@chb.unicancer.fr)  
Dr. Sophie Gouerant 
(E-mail:  
sophie.gouerant@chb.unicancer.fr)  
Dr. Jean Christophe Thery  
(E-mail:  jean-
christophe.thery@chb.unicancer.fr)  
Dr. Corinne Veyret  
(E-mail:  corinne.veyret@chb.unicancer.fr)  
Polyclinique De L’ormeau 
28 Boulevard Du 8 Mai 1945 
Tarbes, FR 65000 
Phone: 011 33 05 62 44 33 08 
 
FWA: 00022735 
CTEP Code: 28162 
Dr. Virginie Fichet  
(E-mail:  v.fichet@yahoo.fr)  
Dr. Philippe Ayela  
(E-mail:  nathalie.monteiro@wanadoo.fr)  
 
Centre Hospitalier De Pau 
4 boulevard Hauterive 
Pau, FR 64046 
Phone: 011 33 05 62 56 45 09 
 
FWA: 00022631 
CTEP Code: 28041 
Dr. Suzanne Nguyen  
(E-mail: suzanne.nguyen@ch-pau.fr)  
Dr. Corinne Dagada ( 
E-mail:  corinne.dagada@ch-pau.fr)  
 
Centre Hospitalier d’Auch 
Alee Marie Clarac 
Auch, FR 32008 
Phone: 011 33 05 62 61 32 49 
 
FWA: 00022790 
CTEP Code: 28163 
Dr. Karine Salignon  
(E-mail: k.salignon@ch-auch.fr)  
Clinique Saint Jean Languedoc 
20 route de Revel 
Toulouse, FR 31077 
Phone:  05 67 20 44 00 
 
FWA: 00022689 
CTEP Code:  28142 
Dr. Etienne Suc  
(E-mail: esucsjl@club-internet.fr)  
Centre Hospitalier de la Cote 
Basque 
13 avenue de l'interne Jacques 
Loeb 
Bayonne, FR 64109 
Phone: 011 33 05 59 44 37 62 
 
FWA: 00022880 
CTEP Code: 28059 
Dr. Dominique Larregain-Fournier  
(E-mail: dlarregainfou1@chicb.com)  
Dr. Jean-Philippe Dutin  
(E-mail: jean-philippe@3c-bayonne.org)  

S1007 
Page 131 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
CHU de Brest - Hôpital Morvan 
5 avenue Foch 
Brest, FR 29609 
Phone: 011 33 02 98 22 33 95 
 
FWA: 00018296 
CTEP Code: 28122 
Dr. Helene Simon  
(E-mail:  helene.simon@chu-brest.fr)  
Dr. Caroline Cheneau  
(E-mail: caroline.cheneau@chu-brest.fr)  
Dr. Jerome Martin-Babau  
(E-mail: jerome.martin-babau@chu-brest.fr)  
Dr. Fanny Trouboul  
(E-mail: fanny.trouboul@chu-brest.fr)  
Hopital Prive Jean Mermoz 
55 Avenue Jean Mermoz 
Lyon, FR 69008 
Phone: 011 33 0 4 3753 8725 
 
FWA: 00021793 
CTEP Code: 28152 
Dr. Dominique Beal-Ardisson  
(E-mail: dbealardisson@aol.fr)  
 
Centre Georges Francois 
Leclerc 
1 rue Professeur Marion 
Dijon, FR 21079 
Phone: 03 80 73 75 00 
 
FWA: 00021826 
CTEP Code: 28105  
Dr. Nicolas Isambert  
(E-mail: nisambert@cgfl.fr)  
Institut Curie Paris 
26 rue d’Ulm 
Paris, FR 75005 
Phone: 01 44 32 43 32 
 
FWA: 00016034 
CTEP Code:  28107 
Dr. Jean-Yves Pierga  
(E-mail: jean-yves.pierga@curie.fr)  
 
 
Departemental Hospitalier 
Roche-sur-Yon  
(Les Oudairies) 
Boulevard Stephane Moreau 
La Roche-Sur-Yon, FR 85925 
Phone: 02 51 44 61 61 
 
FWA: 00021871 
CTEP Code:  28145 
Dr. Tifenn L Haridon  
(E-mail: tifenn.lharidon@chd-vendee.fr)  
Dr. Veronique Girre  
(E-mail: veronique.girre@chd-vendee.fr)  
Dr. Herve Maisonneuve  
(E-mail: herve.maisonneuve@chd-
vendee.fr)  
Dr.Frank Priou  
(E-mail: Frank.priou@chd-vendee.fr)  
Dr. Mourad Tiab  
(E-mail: mourad.tiab@chd-vendee.fr)  
Dr. Bruno Villemagne  
(E-mail: bruno.villemagne@chd-vendee.fr)  

S1007 
Page 132 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
 
Centre Jean Perrin 
58 rue Montalembert 
Clermont Ferrnad, FR 63011 
Phone: 04 73 27 81 37 
 
FWA: 00021771 
CTEP Code:  28154 
Dr. Marie-Ange Mouret-Reynier  
(E-mail: marie-ange.mouret-reynier@cjp.fr)  
Dr. Pascale Dubray-Longeras  
(E-mail: pascale.dubray-longeras@cjp.fr)  
Dr. Isabelle Van Praagh-Doreau 
 (E-mail: isabelle.vanpraagh@cjp.fr)  
Dr. Anne-Francois Dillies  
(E-mail: anne-francoise.dillies@cjp.fr)  
Dr. Pierre Dalloz  
(E-mail: dalloz.pierre@cjp.fr)  
Dr. Xavier Durando  
(E-mail: Xavier.durando@cjp.fr)  
Clinique Victor Hugo – Centre 
Jean Bernard 
18 rue Victor Hugo 
Le Mans, FR 72000 
Phone: 02 43 47 94 94 
 
FWA: 00021876 
CTEP Code: 28153 
Dr. Hugues Bourgeois  
(E-mail: h.bourgeois@cjb72.org)  
Dr. Olivier Dupuis  
(E-mail: o.dupuis@cjb72.org)  
 
Centre De Cancerologie Paris 
Nord 
6 avenue Charles Peguy 
Sarcelles, FR 95200 
Phone: 01 39 90 49 55 
 
FWA: 00021854 
CTEP Code: 28149 
Dr. Catherine Boaziz  
(E-mail: Catherine.boaziz@wanadoo.fr)  
Dr. Cyril Laporte  
(E-mail: Cyril.laporte@free.fr)  
Dr. Anne Larrouy  
(E-mail: alarrouy@free.fr)  
 
Centre Hospitalier 
Intercommunal De Creteil 
40 Avenue de Verdun 
Creteil, FR 94000 
Phone: 01 45 17 52 10 
 
FWA:  00022960 
CTEP Code: 28136 
Dr. Domnita Burcoveanu  
(E-mail:  domnita.burcoveanu@chicreteil.fr)  
Dr. Stephane Henault  
(E-mail: stephane.henault@chicreteil.fr)  
Dr. Emmanuelle Malaurie 
(E-mail: Emmanuelle.malaurie@chicreteil.fr)  
Dr. Michel Martin  
(E-mail:  Michel.martin@chicreteil.fr)  
Dr. Zineb Sellam-Chorfi  
(Email: zineb.sellam-chorfi@chicreteil.fr)  
Centre Hospitalier De Blois 
Mail Pierre Charlot 
Blois, FR 41016 
Phone: 02 54 56 64 05 
 
FWA: 00023179 
CTEP Code: 28159 
Dr. Olivier Arsene  
(E-mail: areseneo@ch-blois.fr)  
Dr. Abdelouhab Mazari  
(E-mail: mazaria@ch-blois.fr)  
 
Clinical Saint-Pierre/ 
Centre Catalan d’Oncologie 
80 rue Pascal-Marie Agasse 
Perpignan, FR 66000 
Phone: 04 68 55 74 96 
 
FWA: 00022959 
CTEP Code: 28164 
Dr. Stephanie Catala  
(E-mail: catalacco.stephanie@gmail.com)  
Dr. Stephen Ellis  
(E-mail: ellisteve@yahoo.fr)  
Dr.Sabine Vieillot 
(E-mail: sabinevieillot@gmail.fr)  

S1007 
Page 133 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Centre D’Oncologie et de 
Radiotherapie du Pays Basque 
14 Allees Paulmy 
Bayonne, FR 64100 
Phone: 05 59 59 38 71 
 
 
FWA: 00022747 
CTEP Code:  28168 
Dr. Aurelien Blouet 
(E-mail: aurelien.blouet@oncologie-pays-
basque.org)  
Dr. Stephane Remy  
(E-mail: stephane.remy@oncologie-pays-
basque.org)  
Dr. Maciej Rotarski  
(E-mail: maciej.rotarski@oncologie-pays-
basque.org)  
Centre Hospitalier De Beauvais 
40 avenue Leon Blum 
Beauvais, FR 60021 
Phone: 03 44 11 21 21  
 
FWA: 00023029 
CTEP Code: 28146 
Dr. Hanifa Ammarguellat  
(E-mail: h.ammarguellat@ch-beauvais.fr)  
 
CHRU 
Strasbourg – Hopital Civil 
1 place de l’Hopital 
Strasbourg, Fr 67091 
Phone:  03 88 11 67 28 
 
FWA: 00006432 
CTEP Code: 28074 
Dr. Brigitte Duclos  
(E-mail: Brigitte.duclos@chru-strasbourg.fr)  
Dr. Philippe Barthelemy  
(E-mail:  
philippe.barthelemy@chru-strasbourg.fr)  
Groupe Hospitalier Public  
     du Sud de L’Oise 
14 Avenue Paul Rough 
Senlis, FR 60309 
Phone:  03 44 21 70 02 
 
FWA: 00023130 
CTEP Code: 28165 
Dr. Stephanie Trager  
(E-mail: Stephanie.trager-maury@ch-
senlis.fr)  
Dr. Elisabeth Carola  
(E-mail: Elisabeth.carola@ch-senlis.fr)  
 
Hopital Privee De L’Estuaire 
505 rue Irene Joliot-Curie 
Le Havre, FR 76620 
Phone: 02 32 55 69 10 
 
FWA: 00023024 
CTEP Code: 28156 
Dr. Angel Moran  
(E-mail: amoran2@wanadoo.fr)  
 
Clinique Pasteur Oncorad 
1 rue de la Petite Vitesse 
Toulouse, FR 
Phone: 05 62 21 16 67  
 
FWA: 00010067 
CTEP Code: 28137 
Dr. Chantal Bernard-Marty  
(E-mail: cbernardm@clinique-pasteur.com)  
Dr. Mathilde Martinez  
(E-mail: m.martinez@clinique-pasteur.com)  
 
Instit Curie-Centre Rene 
Huguenin Saint Cloud  
35 rue dailly 
Saint Cloud, FR 92210 
Phone: 01 47 11 15 15 
 
FWA: 00016034 
CTEP Code: 28027 
Dr. Etienne Brain  
(E-mail: etienne.brain@curie.fr)  
 

S1007 
Page 134 
Version Date 12/10/2021 
 
 
 
 
 
Approved UNICANCER Sites and Participating Investigators 
SITES 
Investigators 
Centre Paul Strauss 
3 rue de la porte de l’hopital 
Strasbourg, FR 67000 
Phone:  03 88 25 24 56 
 
FWA: 00023151 
CTEP Code: 28169  
Dr. Thierry Petit  
(E-mail: tpetit@strasbourg.unicancer.fr)  
Dr. Christine Belletier  
(E-mail: cbelletier@strasbourg.unicancer.fr)  
 
 
 
 
CHU Limoges – Hopital 
Dupuytren 
2 avenue Martin Luther King 
Limoges, FR 87042 
Phone: 05 55 05 63 96 
 
FWA: 00022535 
CTEP Code: 28063 
Dr. Sandrine Lavau-Denes  
(E-mail: sandrine.lavau-denes@chu-
limoges.fr)  
Dr. Nicole Tubiana-Mathieu  
(E-mail: nicole.tubiana-mathieu@chu-
limoges.fr)  
Dr. Laurence Venat  
(E-mail: laurence.venat@chu-limoges.fr)  
 
Hopital Saint Louis 
1 Claude Vellefaux Avenue 
Paris, FR 75010 
Phone:  01 42 49 49 49 
 
FWA: 00013985 
CTEP Code: 28003 
 
Dr. Marc Espie  
(E-mail: marc.espie@aphp.fr)  
 
Hopital Prive de Peupliers 
8 place De L’ Abbe Georges 
Henocque 
Paris, FR 75013 
Phone: 01 44 16 53 33 
 
FWA: 00022930 
CTEP Code: 28170  
Dr. Mustapha Zoubir  
(E-mail:m. zoubir@gsante.fr)  
 
 
 
Approved GEICAM Sites and Participating Investigators 
SITES 
Investigators 
Hospital Clinic i Provincial 
170 Calle Villarroel 
Barcelona,  08036 ES 
Phone: +34 932275400 Ext: 4368 and 
Ext: 3456 
 
FWA: 00020830 
CTEP Code:  65003 
 
Dr. Monterrat Munoz Mateu  
(E-mail: mmunoz@clinic.ub.es)  
Dr. Lydia Gaba Garcia  
(E-mail: lgaba@clinic.ub.es)  
Dr. Ana Arance Fernandez  
(E-mail: anarance@clinic.ub.es)  
Hospital Nuestra Senora de Aranzazu 
Paseo Doctor Beguiristain 
San Sebastian,  20014 ES 
Phone: +34 943 006002 
 
FWA: 00006055 
CTEP Code:  65013 
Dr. Isabel Alvarez Lopez  
(E-mail: 
isabelmanuela.alvarez@osakidetza.net)  
Dr. Cristina Curruca Galaz (E-mail: 
cristinamaria.currucagalaz@osakidetza.net)  
 

S1007 
Page 135 
Version Date 12/10/2021 
 
 
 
 
 
Approved GEICAM Sites and Participating Investigators 
SITES 
Investigators 
 
Hospital Clinico Universitario Virgen de 
la Victoria 
Campus Universitario De Teatinos 
Malaga,  29010 ES 
Phone: +34 609250477 
 
FWA: 00017537 
CTEP Code:  650409 
Dr. Emilio Alba Conejo  
(E-mail: emilioalbac@gmail.com)  
Dr. Nuria Ribelles Entrena  
(E-mail: nuriaribelles@gmail.com)  
Dr.Alfonso Sanchez Munoz  
(E-mail: asmoncomed@yahoo.es  
Dr. Antonia Marquez Aragones  
(E-mail: antoniamararagones@gmail.com)  
Dr. Bella Isabel Pajares Hachero  
(E-mail: oncologia98@yahoo.com)  
 
Instituto Valenciano de Oncologia 
Beltran Baguena 19 
Valencia,  46009 ES 
Phone: +34 961104606 
 
FWA: 00015116 
CTEP Code:  65016 
Dr. Angel L. Guerrero Zotano  
(E-mail: angelgz@comv.es)  
Dr. Amparo Ruiz Simon  
(E-mail: aruiz@fivo.org)  
 
 
Hospital Clinico Universitario Lozano 
Blesa 
Avenida San Juan Bosco 15 
Zaragoza,  50009 ES 
Phone: +34 976765746 
FWA: 00021913 
CTEP Code:  65040 
 
Dr. Alejandro Tres  
(E-mail: atres@salud.aragon.es)  
Dr. Raquel Andres  
(E-mail: andresraquel@hotmail.com)  
Dr. Laura Murillo  
(E-mail: lmjaso@yahoo.es)  
 
Hospital Universitario Ramon y Cajal 
Calle De Colmenar Viejo 9 
Madrid,  28034 ES 
Phone: +34 913368263 
 
FWA: 00001735 
CTEP Code:  65041 
Dr. Noelia Martinez Janez  
(E-mail: mjnoelia@hotmail.com)  
Dr. Alfredo Carrato Mena 
 (E-mail: acarrato@telefonica.net)  
Dr. Eva Maria Guerra Alia  
(E-mail: eva_m_guerra@hotmail.com)  
 
Hospital De La Santa Creu I Sant Pau 
Avenida San Antonio M Claret 167 
Barcelona,  08025 ES 
Phone: +34 935537118 
 
FWA: 00008876 
CTEP Code:  65017 
 
Dr. Agustin Barnadas Molins  
(E-mail: abarnadasm@santpau.cat)  
Dr. Teresa Ramon y Cajal Asensio  
(E-mail: tramon@santpau.cat)  
 
 
Complejo Hospitalario Universitario de 
Albacete 
Hermanos Palco 37 
Albacete,  02006 ES 
Phone: +34 967597480 
 
FWA: 00014411 
CTEP Code:  65021 
 
Dr. Encarna Adrover Cebrian  
(E-mail: eadroverc@seom.org)  
Dr. Veronica Gonzalez Orozco  
(E-mail: vrnkj@hotmail.com)  
Dr. Antonio Fernandez Aramburo  
(E-mail: afernandeza@jccm.sescam.es)  

S1007 
Page 136 
Version Date 12/10/2021 
 
 
 
 
 
Approved GEICAM Sites and Participating Investigators 
SITES 
Investigators 
 
Hospital Universitario Gregorio 
Maranon 
Doctor Esquerdo 46 
Madrid,  28007 ES 
Phone: +34 91.426.90.70 
FWA: 00010143 
CTEP Code:  65027 
Dr. Ricardo Gonzalez del Val Subirats  
(E-mail: rimagm@telefonica.net)  
Dr. Yolanda Jerez Gilarranz  
(E-mail: itacayoli@hotmail.com)  
Dr. Ivan Marquez Rodas  
(E-mail: ivanpantic@hotmail.com)  
Dr. Miguel Martin Jimenez ( 
E-mail: mmartin@geicam.org)  
 
Hospital San Pedro de Alcantara 
Avenida Pablo Naranjo S/N 
Caceres,  10003 ES 
Phone: +34 927256234 / 
 +34 625548963 
 
FWA: 00021890 
CTEP Code:  65034 
Dr. Santiago Gonzalez Santiago  
(E-mail: sgonzalezs@seom.org)  
Dr. Mª Helena Lopez de Ceballos  
(E-mail: mariahelenalc@gmail.com)  
 
Hospital Clinico Universitario de 
Valencia 
Avenida Blasco Ibanez 17 
Valencia,  46010 ES 
Phone: +34 630506888 
 
FWA: 00021120 
CTEP Code:  65035 
Dr. Ana Lluch Hernandez  
(E-mail: lluch_ana@gva.es) 
Dr. Begona Bermejo de las Heras  
(E-mail:begobermejo@gmail.com) 
Dr. Vanessa Pons Sanz  
(E-mail: v.pons@hotmail.com 
Dr. Jose Alejandro Perez Fidalgo  
(E-mail: japfidalgo@msn.com) 
 
Centro Oncologico de Galicia 
Avenida De Montserrat 
Coruna,  15009 ES 
Phone: 34 981 287 499 Ext: 174 
 
FWA: 00021453 
CTEP Code:  65036 
 
Dr. Manuel Ramos Vazquez  
(E-mail: mramos@cog.es)  
Dr. Margarita Amenedo Gancedo  
(E-mail: margarita.amenedo@cog.es)  
Dr. Jose Carlos Mendez Mendez  
(E-mail: carlos.mendez@cog.es)  
Dr. Ana Medina Colmenero  
(E-mail: ana.medina@cog.es)  
 
 
 
Hospital Provincial de Castellon 
Avenida Doctor Clara 19 
Castellon,  12002 ES 
Phone: +34 655241146 
 
FWA: 00021470 
CTEP Code:  65037 
Dr. Eduardo Martinez de Duenas  
(E-mail: Eduardo.martinez@hospital2000.net)  
Dr. Angeles Lopez Rodriguez  
(E-mail: angelalopez@comcas.es)  
Dr. Javier Munarriz Ferrandis  
(E-mail: jmunarriz@comcas.es)  
Dr. Santiago Olmos Anton  
(E-mail: olmos_san@gva.es)  
 
Hospital Universitari Germans Trias i 
Pujol 
Carretera De Canyet S/n 
Barcelona,  08916 ES 
Phone: +34 934978729 
 
FWA: 00001930 
CTEP Code:  65042 
Dr. Mireia Margeli Vila  
(E-mail: mmargeli@iconcologia.net)  
Dr. Beatriz Cirauqui Cirauqui  
(E-mail: bcirauqui@iconcologia.net)  
 

S1007 
Page 137 
Version Date 12/10/2021 
 
 
 
 
 
Approved GEICAM Sites and Participating Investigators 
SITES 
Investigators 
 
Hospital Infanta Cristina de Parla 
Avenida Nueve De Junio 2 
Madrid,  28981 ES 
Phone: +34 687938291 
 
FWA: 00021941 
CTEP Code:  65045 
 
Dr. Coralia Bueno Muino  
(E-mail: corabumu@hotmail.com)  
Dr. Alejandro Riquelme Oliveira  
(E-mail: ariquelme.hrc@salud.madrid.org)  
 
Hospital Universitario Virgen del Rocio 
Avenida Manuel Siurot 
Sevilla,  41013 ES 
Phone: +34 671533372 
 
 
 
FWA: 00006226 
CTEP Code:  65046 
Dr. Manuel Ruiz Borrego  
(E-mail: ruizsabates@gmail.com)  
Dr. Maria Luisa Limon Miron  
(E-mail: mllimon02@hotmail.com)  
Dr. Maria Reina Atienza Amores  
(E-mail: mratienza@gamil.com)  
Dr. Rosario Gonzalez Mancha  
(E-mail: 
Rosario.gonzalez.mancha.sspa@juntadeandalu
cia.es)  
 
Hospital Virgen de la Salud 
Avenida Barber 30 
Toledo,  45004 ES 
Phone: +34 925269200 Ext: 48632 
 
 
 
 
 
 
 
 
 
FWA: 00021751 
CTEP Code:  65043 
Dr. Jose Ignacio Chacon Lopez-Muniz  
(E-mail: jignaciochacon@gmail.com)  
Dr. Miguel Angel De la Cruz Mora  
(E-mail: mcruz@sescam.jccm.es)  
Dr. Luis Lopez Gomez (E-mail: 
luisl@sescam.jccm.es)  
Dr. Jesus Andrade Santiago  
(E-mail: jandrades@sescam.jccm.es)  
Dr. Iciar Garcia Carbonero  
(E-mail: igcarbonero@yahoo.es)  
Dr. Carmen Esteban Esteban  
(E-mail: cesteban@sescam.jccm.es)  
Dr. Ruth Alvarez Cabellos  
(E-mail: ruthalvarez21@gmail.com)  
 
Dr. Antonio Irigoyen Medina  
(E-mail: antonioirigoyen@yahoo.com)  
Dr. Javier Medina Martinez  
(E-mail: boladiez39@yahoo.es)  
 
Hospital Universitari de Girona Doctor 
Josep Trueta 
Avda De Franca 
Girona,  17007 ES 
Phone: +34 972225827 
 
FWA: 00010143 
CTEP Code:  65032 
Dr. Joan Dorca Ribugent  
(E-mail: jdorca@iconcologia.net)  
Dr. Sonia Del Barco Berron  
(E-mail: sdel@iconcologia.net)  
Dr. Gemma Vinas Villaro  
(E-mail: bmartin@iconcologia.net)  
 
Onkologikoa 
Paseo Doctor Begiristain 121 
San Sebastian,  20014 ES 
Phone: +34943328000 
 
FWA: 00021483 
Dr. Arrate Plazaola Alcibar 
(E-mail: aplazaola@onkolgikoa.org)  
Dr. Jesus Alfaro Lizaso 
(E-mail: jalfaro@onkolgikoa.org)  
Dr. Ainhara Lahuerta Martinez  
(E-mail: alahuerta@onkolgikoa.org)  
Dr. Ander Urruticoechea Ribate 

S1007 
Page 138 
Version Date 12/10/2021 
 
 
 
 
 
Approved GEICAM Sites and Participating Investigators 
SITES 
Investigators 
CTEP Code:  65044 
(E-mail: anderu@iconcologia.net)  
 
Institut Catalad'Oncologia 
Avenue Gran Via 
Girona,  08907 ES 
Phone: +34 932607333 
 
FWA: 00010235 
CTEP Code:  65031 
Dr. Miguel Gil Gil  
(E-mail: mgilgil@iconcologia.net)  
Dr. Idoia Morilla  
(E-mail: imorilla@iconcologia.net)  
 
 
Hospital Universitario Miguel Servet 
Paseo Isabel La Catolica 1-3 
Zaragoza, 50009 ES 
Phone: +34 976765500 ext 3825  
 
 
 
 
 
FWA: 00021746 
CTEP Code:  65038 
Dr. Antonio Anton Torres  
(E-mail: aantont@gmail.com)  
Dr. Teresa de Jesus Puertolas Hernandez 
(Email: tjpuertolasa@wanadoo.es)  
Dr. Juan Lao Romera  
(E-mail: juanlaoromera@msn.com)  
Dr. Maria Esther Millastre Bocos 
 (E-mail: emib7@hotmail.com)  
Dr. Julia Madani Perez  
(Email: julimuna@hotmail.com)  
Dr. Ana Cebollero  
(E-mail: mtarazona.miguelservet@gmail.com)  
 
 
 
 
 

S1007 
Page 139 
Version Date 12/10/2021 
 
 
 
 
 
18.6 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, 
Hormone-Receptor Positive, Her2 Negative, Operable Breast Cancer Translational 
Medicine Substudy (U.S. INSTITUTIONS ONLY) – CELLSEARCH ANALYSES (Menarini 
Silicon Biosystems) 
 
Although endocrine therapy remains standard of care for patients with operable hormone 
receptor-positive (HR+) breast cancers (BCs), pts with HR+ BC may have a recurrence as 
a result of acquired resistance. Recurrences that occur 5 or more years after diagnosis 
(i.e., late relapse) account for approximately 50% of all BC recurrences. For instance, in a 
meta-analysis of 62,923 women with HR+ BC who were disease-free after 5 years of 
endocrine therapy, distant recurrence risk associated with tumor size and lymph node 
status, ranging from 10-40% up to 20 years from diagnosis. (1) Identifying markers that 
can predict late recurrence, such as blood-based biomarkers, remains an unmet need in 
this population. 
 
a. 
Objectives 
 
1. 
Primary 
The presence of circulating tumor cells (CTC+) using CELLSEARCH will 
be assessed at up to 8 years after randomization in those still at risk for 
the primary outcome. Invasive disease-free survival (IDFS) will be 
compared between CTC+ versus CTC-, incorporating endocrine therapy 
use prior to and during follow-up after the CTC evaluation.   
 
2. 
Secondary 
To evaluate changes in CTC over time, i.e. a) baseline at up to 8 years 
after randomization and b) 2-3 years later after the initial blood draw on 
the substudy in those who have not yet had a recurrence. We will explore 
whether those patients for whom CTC status becomes CTC+, or who have 
additional mutations develop over time, develop a late recurrence at a rate 
that is different from those who do not. 
 
3. 
Exploratory 
We will explore the degree of heterogeneity of the CTC population. 
 
b. 
Background 
 
1. 
Late Recurrence 
 
Hormone receptor positive (HR+)/HER2- breast cancers account for 
approximately 2/3 of breast cancers. Although endocrine therapy, such as 
selective estrogen receptor modulators (e.g., tamoxifen) and aromatase 
inhibitors, remain standard of care in the operable setting for patients with 
HR+ breast cancers, these patients may have a recurrence of their cancer, 
as a result of acquired resistance to endocrine therapies. Recurrences that 
occur 5 or more years after diagnosis (i.e., late relapse) account for 
approximately 50% of all breast cancer recurrences. In a meta-analysis 
involving 62,923 women with ER+ breast cancer who were disease-free 
after 5 years of endocrine therapy, the risk of distant recurrence strongly 
correlated with original tumor size and lymph node status, ranging from 
10-40% up to 20 years (1). We propose creating a biospecimen repository, 
including plasma and serum, for those who have not recurred, and to 
evaluate for blood-based markers that associate with a risk of late 
recurrence. 
 
 

S1007 
Page 140 
Version Date 12/10/2021 
 
 
 
 
 
2. 
Circulating Tumor Cells (CTCs) 
 
The presence of CTCs may have prognostic significance in this setting. 
Sparano et al. have reported the prognostic implications of CTCs in 
patients with HER2 negative breast cancer enrolled to E5103 (2). CTCs 
were enumerated using CELLSEARCH. Of the nearly 5000 patients 
enrolled to E5103, 547 patients agreed to have blood collected who were 
disease free at 4.5-7.5 years from initial diagnosis. While the CTC+ rate 
was low in the HR+ population (23/353 pts: 5.1%), a positive CTC assay 
was associated with a 10.8-fold higher risk of recurrence (p<0.001). In the 
multivariate analysis adjusted for important clinical and pathologic 
features, including age, tumor size, node status, and grade, a positive CTC 
assay was associated with a 13.1-fold increased risk of recurrence in HR+ 
breast cancer. The median time to recurrence was 2.8 years (0.1-2.8 
years) among the CTC-positive patients. These data are intriguing and 
worth assessing in a high-risk, node positive cohort, such as S1007. 
 
CellSearch 
 
The CellSearch System employs immunomagnetic separation technology 
in which the blood specimen is incubated with magnetic beads coated with 
antibodies directed against the epithelial cell adhesion molecule (EpCAM) 
(3). A magnet is used to isolate the immunomagnetically labeled epithelial 
cells. 
After immunomagnetic isolation, the cells are stained with 
fluorescently labeled anti-cytokeratin antibodies and the fluorescent 
nuclear stain DAPI. A fluorescently labeled pan-leukocyte monoclonal 
antibody is included as a counter-stain to discriminate contaminating 
white blood cells. Sample processing is fully automated. After isolation 
and staining, the CTCs are placed in a proprietary chamber for viewing 
on a semi-automated fluorescence microscope. Image analysis software 
pre-selects specific objects based on fluorescence staining patterns and 
intensities. The outcome/report is a quantitative analysis of the CTC 
contained in the blood specimen.  
 
The CellSearch System has been shown to be accurate and reproducible 
(4). Blood samples spiked with standardized numbers of cultured human 
breast cancer cells demonstrate a linear recovery over a range of 5 to 
1,142 cells (correlation coefficient R2=0.99), with an average recovery of 
> 85% at each level. There is also strong agreement between duplicate 
samples (correlation coefficient R2=0.975) and between independent 
operators reviewing the same digital images (correlation coefficient 
R2=0.994). 
 
c. 
Rationale and Hypothesis 
 
The above findings support the design of utilizing plasma repositories from large 
adjuvant trials of endocrine therapy. A number of critical questions remain in early-
stage breast cancer. For instance, if CTCs are identified in a patient who is still on 
adjuvant therapy without a recurrence, should we consider switching the systemic 
therapy to decrease the risk for late recurrence? Establishing a biorepository in 
this node positive population after 5 years of endocrine therapy offers a unique 
opportunity to evaluate whether we can identify blood-based predictors of late 
relapse.  
 
While there are commercially available tumor-tissue based genomic tests looking 
at rate of distant relapse, including breast cancer index, these are looking at 

S1007 
Page 141 
Version Date 12/10/2021 
 
 
 
 
 
baseline, pre-treatment samples. This substudy will look at real-time, on-treatment 
predictors, which may be more reflective of current tumor biology due to selective 
treatment pressure, dormancy escape, etc.  
 
In addition, other previously described blood-based markers, such as serum tumor 
markers, in patients with breast cancer can be unreliable, including in patients with 
metastatic breast cancer. CTC enumeration and the association with risk of late 
relapse was selected as the primary outcome, given that preliminary data with 
CELLSEARCH in the adjuvant setting has been previously described, allowing for 
appropriately power calculations in this concept2. Ultimately, the goal of this project 
is to identify early predictors of dormancy escape and late recurrence in patients 
with operable breast cancer, which can serve as the basis for future, randomized, 
interventional trials.  
 
We may be able to identify 3 groups of patients: 1) those who have not escaped 
dormancy (and may not need continued hormonal or other therapy), 2) those who 
are escaping dormancy and will relapse in the near future (and may need to modify 
treatment immediately, identifying the highest risk group for future clinical trial 
approach considerations), and 3) those who still are in dormancy and may 
experience a later relapse (and may need to switch hormonal therapy and/or add 
a new targeted treatment: again a population for future trial selection).  
 
We hypothesize that invasive disease-free survival will be poorer in CTC-positive 
patients compared to those patients who are CTC-negative.  
 
d. 
Experimental Approach and Assays 
 
1. 
Sample Collection and Timepoints 
 
At time of distribution of Revision #16 (Version Date: 03/24/21), all U.S. 
patients who a) are disease free, with no prior invasive recurrence AND b) 
have been on protocol for up to 8 years after time of randomization to 
S1007 (Step 2 registration) must be offered participation in the Circulation 
Biomarker Assessment for Late Relapse Translational Medicine (CBALR 
TM) substudy.   
 

S1007 
Page 142 
Version Date 12/10/2021 
 
 
 
 
 
SUBMISSION SUMMARY TABLE: 
CBALR Visit #1: 
Within 28 days 
after patient 
registration to 
Step 3  
CBALR Visit #2:  
2-3 years   
after patient 
registration to 
Step 3  
CBALR Visit #3:  
At time of Invasive 
Recurrence 
20 mL 
whole 
blood a 
Two 10 mL 
CellSave® tubes b, c 
 
Ship to Menarini 
Silicon Biosystems 
(Lab # 122) 
Two 10 mL 
CellSave® tubes b, c 
 
Ship to Menarini 
Silicon Biosystems 
(Lab # 122) 
Two 10 mL 
CellSave® tubes b, c 
 
Ship to Menarini 
Silicon Biosystems 
(Lab # 122) 
a  Important: See Section 18.6d.4: Order of Sample Collection.  
b  If the minimum blood volume for two 10 mL CellSave® tubes cannot be 
collected during a visit, a subsequent second attempt at collection should be 
scheduled for another time. The subsequent draw time can be scheduled for 
later the same day (if appropriate and site has collection tubes on hand) or for 
another date. See Section 18.6d.4. Due to funding restrictions and tube 
expiration dates, the SWOG Biospecimen Bank will only ship sufficient tubes 
for a single collection timepoint.  If the first draw attempt fails and the site does 
not have tubes on hand, then the site will need to: 1) reschedule the patient for 
a subsequent blood draw, allowing 5-7 days for collection kit shipment, and 2) 
re-order tubes for that patient. Both CellSave® tubes must be collected on the 
same day. See Section 18.6d.5 for more information.  
c 
If the second attempt at blood draw is unsuccessful in obtaining the minimum 
blood volume for two 10mL CellSave® tubes, the patient will be deemed not 
evaluable for the CBALR TM substudy.  If the patient is deemed not evaluable 
for the CBALR TM substudy, do not submit any subsequent blood samples for 
the CBALR TM substudy. 
 
2. 
Sample Collection Kits 
 
Specimen collection kits (CellSave® tubes and ambient gel pack) 
must be ordered IMMEDIATELY after patient registration to Step 3 
and prior to each collection timepoint.  Sites should allow 5-7 days 
to receive kits.  Note: Patient samples must be drawn within 28 days 
after patient registration to Step 3. 
 
CellSave® kits may be ordered by using the SWOG Biospecimen Bank 
Kit Management Application at: https://kits.bpc-apps.nchri.org.   
 
The kit provides: Two CellSave® tubes and an ambient pak for blood 
submitted to Menarini Silcon Biosystems for a single collection timepoint. 
 
3. 
Sample Collection and Submission Instructions 
 
All sample submissions for this study must be entered and tracked using 
the SWOG online Specimen Tracking System. Complete sample 
collection and submission instructions can be accessed on the SWOG 
Specimen 
Submission 
webpage 
(https://www.swog.org/member-
resources/biospecimen-resources).  If collection/submission instructions 
differ from those in the protocol, the protocol instructions should be 
followed; otherwise, the website instructions should be followed. 
 
 

S1007 
Page 143 
Version Date 12/10/2021 
 
 
 
 
 
4. 
Order of Sample Collection: 
 
Substudy samples must be collected in the following order. If samples are 
not collected in the following order, then one (or more) of the 
samples may need to be discarded. 
 
First scheduled draw for each annual visit: 
 
Under fasting conditions:  
 
• 
First, collect: Whole blood in a Red-Top, SST, Vacutainer tube 
 
• 
Then, collect: Two 10-mL CellSave® tubes.  
 
NOTE: The 10 mL red-top tube must be obtained prior to filling 
the CellSave® tube using the same needle stick. This decreases 
the chance of contamination of the CellSave® sample with skin 
epithelial cells, which may occur when the needle enters the skin. 
 
Only the SST should be collected under fasting conditions. After 
collection of the SST, patients may eat or drink something. 
 
• 
Then, collect: Four 10-mL Streck cfDNA tubes for future analysis, 
such as cfDNA assessment. 
 
If the SST was collected at the first scheduled draw, and then the minimum 
blood volume for two 10 mL CellSave® tubes was not  subsequently 
collected at the same time (after the SST was collected), then for the 
subsequent attempt to draw one or both CellSave® sample(s), collect 
samples in the following order: 
 
• 
First, collect: One 10-mL Streck cfDNA tube (prior to filling the 
CellSave® tube using the same needle stick). If this happens, ship 
the first Streck cfDNA tube sample to the SWOG Biospecimen 
Bank.  
 
• 
Then, collect: The remaining (one or two) 10-mL CellSave® 
tube(s). NOTE: While CellSave® tubes can be collected at 
different times throughout the day, both CellSave® tubes must be 
collected on the same day. 
 
• 
Then, collect: three 10-mL Streck cfDNA tubes. 
 
• 
Streck cfDNA tubes will be collected for future analyses, such as 
cfDNA assessment. 
 
If there is a deviation from protocol order of collection, contact the study 
chair for guidance on which samples should still be submitted and 
document the order of collection in the “comments” section of the 
Specimen Tracking System. 
 
5. 
CellSave® Tubes (Two Cellsave® tubes at each time point, ship directly 
to Menarini Silicon Biosystems – Lab #122 for CellSearch CTC testing) 
 

S1007 
Page 144 
Version Date 12/10/2021 
 
 
 
 
 
a. 
Required materials for blood collection:  
i. 
Two (2), 10 mL purple/yellow top CellSave® blood 
collection tubes,  
ii. 
Vacutainer brand adapter, and  
iii. 
Needles.  
b. 
See Section 18.6d.2 for CellSave® tube collection kit ordering 
instructions. The kit does not include an adapter or needles. 
c. 
Collection Instructions: 
  
i. 
See Section 18.6d.4: Order of Sample Collection. 
Note: To prevent contamination of the CellSave® tube 
samples with epithelial cells, another tube must be collected 
prior to collection of the CellSave®  tubes, so that the 
CellSave®  tubes may be drawn from the same needle stick 
as the prior sample (either the SST at first draw attempt or 
a Streck cfDNA tube if a second attempt at drawing the 
CellSave® tube). 
ii. 
Use the same needle stick as the prior tube drawn to 
collect the CellSave® samples. This decreases the 
chance of contamination of the CellSave® sample with skin 
epithelial cells, which may occur when the needle enters the 
skin. 
iii. 
For each patient, perform a venous puncture using a 
Vacutainer brand adapter and needle and fill each of the 
blood collection tubes (minimum blood volume of 9 mL for 
each tube). Alternatively, blood samples may be obtained 
from a port or other central venous catheter using 
appropriate access needles and techniques. Invert each 
tube a minimum of eight (8) times to ensure proper mixing 
of the additives contained in each tube.  
iv. 
Important Note: Both (two) 10 mL CellSave® tubes are 
required for analysis. In the event that the 18 mL minimum 
blood volume (9 mL in each) in the two 10 mL tubes 
CellSave® tubes cannot be collected, a subsequent 
second attempt at collection should be scheduled for 
another time.  
While CellSave® tubes can be collected at different times 
throughout the day, both CellSave® tubes must be collected 
on the same day. See Section 18.6d.4. Do not submit either 
a single CellSave® tube or two CellSave® tubes collected 
on different days to Menarini Silicon Biosystems Labs.  
Note: The subsequent draw time can be scheduled for later 
the same day, if deemed appropriate and site has additional 
collection tubes on hand or can be rescheduled for another 
date. Due to funding restrictions and tube expiration dates, 
the SWOG Biospecimen Bank will only ship sufficient tubes 
for a single collection timepoint for each patient registered 
to Step 3.  If the first draw attempt fails, and the site does 

S1007 
Page 145 
Version Date 12/10/2021 
 
 
 
 
 
not have tubes on hand, then the site will need to 1) 
reschedule the patient for another day, allowing 5-7 days for 
collection kit shipment, and 2) re-order tubes for the second 
draw attempt.  
v. 
If at time of second attempt at blood draw, the blood 
draw is unsuccessful in obtaining the minimum 18 mL blood 
volume (9 mL in each) in the two 10 mL CellSave® tubes, 
then the patient will be deemed not evaluable for the 
CBALR TM substudy.  If this occurs and the patient is 
deemed not evaluable for the CBALR TM substudy, do not 
submit any subsequent blood or tissue samples for the 
CBALR TM substudy. 
vi. 
The filled CellSave® tubes must be maintained at 
ambient (15–30°C) temperature, avoiding extremes of 
heat and cold, at all times.  
vii. 
Label the CellSave® tubes with:  
• 
Number 1 and Number 2 (respectively, in order of 
collection).  Record the lot number and expiration date 
for each corresponding tube in the Specimen Tracking 
System.  
• 
SWOG patient number (patient ID) 
• 
Patient initials 
• 
Substudy visit number (time point) [Visit number = one, 
two, or three; i.e. one=initial blood draw on substudy, 
two= next blood draw 2-3 years later, three=invasive 
recurrence]. 
• 
Collection date and time (date and time the specimen 
was collected from the patient) 
• 
Initials of the phlebotomist  
• 
Specimen type (i.e., whole blood) 
 
viii. 
The following information must be entered into the SWOG 
Specimen Tracking System prior to shipment:  
• 
Site identification number;  
• 
SWOG patient number (same number as written on the 
filled blood tubes);  
• 
Site comments (i.e. phlebotomy problems; and any 
additional comments);  
• 
Collection date and time of blood draw (if all blood 
samples were not drawn at the same time; specify time 
of draw of each sample);  
• 
Order of blood sample collection; For CellSave® tubes, 
record the order of collection of (Number 1 or Number 
2) as well as the lot number and expiration date for each 
corresponding CellSave® tube in the Specimen 
Tracking System; 
• 
Lot number and expiration date of each corresponding 
CellSave® tube (Number 1 and Number 2).  
 
d. 
Packaging and Shipping Instructions: Ship directly to Menarini 
Silicon Biosystems (Lab #122) 
 

S1007 
Page 146 
Version Date 12/10/2021 
 
 
 
 
 
i. 
Cellsave® tubes must be shipped ambient (with an ambient 
gel pack) the same day as collected, via overnight delivery 
to: Menarini Silicon Biosystems (Lab # 122). If possible, 
collect and ship samples Monday-Thursday. Packages 
shipped on a Friday, must be sent via Fed-Ex Saturday 
Delivery, with no signature required. Do not collect 
samples the day prior to a holiday. 
ii. 
Wrap the CellSave® tubes in the shipping blanket. This 
gives added thermal protection during shipment. Place the 
ambient gel packs in the box to stabilize the 
temperature at 15-30ºC. Place the Styrofoam lid, and seal 
the Styrofoam box. 
iii. 
All shipments must include a requisition form (Packing 
list) generated by the SWOG Specimen Tracking 
System. Place the completed Packing List (generated from 
the SWOG Specimen Tracking System) into the shipper 
box. 
e. 
Questions pertaining to Cellsave® collection or shipping should 
be directed to: 
Menarini Silicon Biosystems Labs (Lab #122) 
msb-labservicesus@siliconbiosystems.com   
Phone: 215/346-8499 
Fax: 215/560-3730 
Customer Service Hours of Operation: M-F, 8:00am – 5:00pm ET 
 
6. 
CTC methods 
 
a. 
CellSearch Systems 
 
i. 
Operator Training:   System Operators will be training at 
Menarini Silicon Biosystems. Follow-up examinations will be 
given to document operator proficiency. Training manuals 
and documentation of training will be maintained at Menarini 
Silicon Biosystems. 
ii. 
Image 
interpretation 
and 
enumeration 
of 
CTCs: 
Determination of CTC counts will be made by trained 
operators. Circulating tumor cells are identified based on 
analysis of results from the CellTracks Analyzer II. Tumor 
cells will be identified by the instrument software, and objects 
will be confirmed visually by the operator. 
iii. 
Quality Control of the AutoPrep and CTC analysis systems 
is maintained via Operator Training procedures, daily, 
weekly and monthly maintenance of systems, use of a two-
level control cell sample for AutoPrep according to standard 
protocols as described in the Operator Manuals. 
iv. 
Assay Procedures 
a. 
Upon specimen arrival at the laboratory, the 
laboratory personnel will ensure that one of the 

S1007 
Page 147 
Version Date 12/10/2021 
 
 
 
 
 
two tubes of blood collected will be tested and the 
other stored in case it is required due to any 
circumstances leading to the inability to test the 
first tube. This will mitigate the potential of being 
unable to perform a CTC count at each blood 
draw. 
 
b. 
The sample will be processed within 96 hours of 
collection using the CellSearch® System. 
 
c. 
All patient specimens are to be assayed using the 
CellSearch Assay as per the manufacturer’s 
instructions. CTCs will be isolated using the 
CellTracks AutoPrep sample processor. A 
volume of 7.5 mL from the sample will be diluted 
with buffer and centrifuged for processing on the 
AutoPrep system. Plasma is withdrawn and 
additional buffer added. Epithelial cell-specific 
immunomagnetic particles (EpCAM-ferrofluid) is 
added and incubated for 30 minutes at room 
temperature. Unbound sample is then aspirated 
while the sample is in a magnetic field. Buffer is 
added and the sample is mixed and separated in 
a magnetic field. Supernatant is removed and a 
permeabilizing agent added, followed by a 
nucleic acid dye, anti-cytokeratin (a marker of 
epithelial cells), and anti- CD45. The specimen is 
mixed and incubated for 15 minutes. The sample 
is washed with buffer, magnetically separated, 
and labeled cells are fixed. Multiple lots of 
CellSearch® Reagents and Control materials will 
be used in the performance of this clinical trial. 
 
e. 
Statistical Design 
 
We anticipate that 8.9% of patients without a recurrence at substudy enrollment 
will develop a late recurrence in the follow-up period1. We will be collecting and 
analyzing blood samples on all patients, as we will otherwise not be able to 
prospectively predict who will develop a late recurrence. Furthermore, CTC 
evaluation by CELLSEARCH must be done in real time rather than use stored 
specimens once case/control status is known.  Among the 1,951 U.S. patients still 
being followed and who do not have a recurrence, we assume that we may recruit 
890 patients for at least a single blood submission. Allowing for a CTC assay failure 
of 10%, then 800 patients would have assay results.  We anticipate conservatively 
that 3% of the 800 patients will be CTC+ (n=24) and 97% will be CTC- (n=776) 
post-endocrine therapy initiation2. The estimated number of invasive disease-free 
survival events after an additional median 4 years of follow-up (from time of blood 
collection) in 800 patients is 71 using an overall hazard rate of 0.231.  With a two-
sided alpha of 0.05, power is 80% to detect a hazard ratio of 3.3 for CTC-positive 
versus CTC-negative.  This is a conservative estimate given that E5103 had a 
5.1% positivity rate and a 13.1 hazard rate in HR+ breast cancer. This will still allow 
sufficient power for a lower positivity rate than 3% or greater difficulty in patient 
recruitment as long as the hazard ratio is high.  
 
The actual analysis planned is a Cox regression on IDFS starting at the time of 
blood collection. We believe it is important to control for time since initial 

S1007 
Page 148 
Version Date 12/10/2021 
 
 
 
 
 
randomization and initial treatment assignment. It is also important to include use 
of endocrine therapy as a time-dependent covariate, as there will some variability 
in terms of whether patients extend beyond 5 years of endocrine therapy. The 
ultimate goal is to determine who may have benefited from extended endocrine 
therapy given CTC determination, but power will be lower for making this 
assessment. 
 
f. 
Data Analysis 
 
The data will be analyzed by the SWOG Statistics and Data Management Center 
along with the investigators of S1007. The S1007 primary endpoint must be 
published prior to reporting results of the Circulating Biomarker Assessment for 
Late Relapse TM substudy.  
 
g. 
References 
 
1. 
Pan H, Gray R, Braybrooke J, et al: 20-Year Risks of Breast-Cancer 
Recurrence after Stopping Endocrine Therapy at 5 Years. N Engl J Med 
377:1836-1846, 2017. 
2. 
Sparano J, O'Neill A, Alpaugh K, et al: Association of Circulating Tumor 
Cells With Late Recurrence of Estrogen Receptor-Positive Breast Cancer: 
A Secondary Analysis of a Randomized Clinical Trial. JAMA Oncol. 2018 
Jul 26.  doi: 10.1001/jamaoncol.2018.2574.  
3. 
Zhang QX, Borg A, Wolf DM, et al: An estrogen receptor mutant with 
strong hormone-independent activity from a metastatic breast cancer. 
Cancer Res 57:1244-9, 1997. 
4. 
Segal CV, Dowsett M: Estrogen receptor mutations in breast cancer--new 
focus on an old target. Clin Cancer Res 20:1724-6, 2014. 
5. 
Takeshita T, Yamamoto Y, Yamamoto-Ibusuki M, et al: Prognostic role of 
PIK3CA mutations of cell-free DNA in early-stage triple negative breast 
cancer. Cancer Sci 106:1582-9, 2015. 
 
 
 

S1007 
Page 149 
Version Date 12/10/2021 
 
 
 
 
 
18.7 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, 
Hormone-Receptor Positive, Her2 Negative, Operable Breast Cancer Translational 
Medicine Substudy (U.S. INSTITUTIONS ONLY) – EPIC SCIENCES CTC DETECTION 
PLATFORM 
 
Although endocrine therapy remains standard of care for patients with operable hormone 
receptor-positive (HR+) breast cancers (BCs), pts with HR+ BC may have a recurrence as 
a result of acquired resistance. Recurrences that occur 5 or more years after diagnosis 
(i.e., late relapse) account for approximately 50% of all BC recurrences. For instance, in a 
meta-analysis of 62,923 women with HR+ BC who were disease-free after 5 years of 
endocrine therapy, distant recurrence risk associated with tumor size and lymph node 
status, ranging from 10-40% up to 20 years from diagnosis. (1) Identifying markers that 
can predict late recurrence, such as blood-based biomarkers, remains an unmet need in 
this population. 
 
a. 
Objectives 
 
1. 
Primary 
 
The presence of circulating tumor cells (CTC+) will be assessed at up to 
8 years after randomization in those still at risk for the primary outcome. 
Invasive disease-free survival (IDFS) will be compared between CTC+ 
versus CTC-, incorporating endocrine therapy use prior to and during 
follow-up after the CTC evaluation.   
 
2. 
Secondary 
 
To evaluate changes in CTC over time, i.e. a) baseline at up to 8 years 
after randomization and b) 2-3 years later after the initial blood draw on 
the substudy in those who have not yet had a recurrence. We will explore 
whether those patients for whom CTC status becomes CTC+, or who have 
additional mutations develop over time, develop a late recurrence at a rate 
that is different from those who do not. 
 
3. 
Exploratory  
 
In addition, we will explore the degree of heterogeneity of the CTC 
population. 
 

S1007 
Page 150 
Version Date 12/10/2021 
 
 
 
 
 
b. 
Background 
 
1. 
Late Recurrence 
 
Hormone receptor positive (HR+)/HER2- breast cancers account for 
approximately 2/3 of breast cancers. Although endocrine therapy, such as 
selective estrogen receptor modulators (e.g., tamoxifen) and aromatase 
inhibitors, remain standard of care in the operable setting for patients with 
HR+ breast cancers, these patients may have a recurrence of their cancer, 
as a result of acquired resistance to endocrine therapies. Recurrences that 
occur 5 or more years after diagnosis (i.e., late relapse) account for 
approximately 50% of all breast cancer recurrences. In a meta-analysis 
involving 62,923 women with ER+ breast cancer who were disease-free 
after 5 years of endocrine therapy, the risk of distant recurrence strongly 
correlated with original tumor size and lymph node status, ranging from 
10-40% up to 20 years (1). We propose creating a biospecimen repository, 
including plasma, for those who have not recurred, and to evaluate for 
blood-based markers that associate with a risk of late recurrence.  
 
2. 
Circulating Tumor Cells (CTCs) 
 
The presence of CTCs may have prognostic significance in this setting. 
Sparano et al. have reported the prognostic implications of CTCs in 
patients with HER2 negative breast cancer enrolled to E5103 (2). CTCs 
were enumerated using CELLSEARCH. Of the nearly 5000 patients 
enrolled to E5103, 547 patients agreed to have blood collected who were 
disease free at 4.5-7.5 years from initial diagnosis. While the CTC+ rate 
was low in the HR+ population (23/353 pts: 5.1%), a positive CTC assay 
was associated with a 10.8-fold higher risk of recurrence (p<0.001). In the 
multivariate analysis adjusted for important clinical and pathologic 
features, including age, tumor size, node status, and grade, a positive CTC 
assay was associated with a 13.1-fold increased risk of recurrence in HR+ 
breast cancer. The median time to recurrence was 2.8 years (0.1-2.8 
years) among the CTC-positive patients. These data are intriguing and 
worth assessing in a high-risk, node positive cohort, such as S1007. 
 
Epic Sciences 
The Epic Sciences CTC detection platform has been analytically validated 
(3) and has the ability to assess clonality and cell morphology, to 
determine the degree of heterogeneity of the CTC population, and to apply 
downstream assays such as copy number variation (CNV), similar to gene 
status reporting via fluorescence in-situ hybridization (FISH) and 
biomarker assessment (ex. PD-L1 expression) at the single cell level (4). 
The technology falls under the selection free immunofluorescence-based 
assay category, in which the entire buffy coat containing peripheral blood 
WBCs and CTCs is spread onto slides, and all cells undergo 
immunofluorescence staining for the markers of interest. CTCs are 
identified based on staining patterns as well as morphology. CTC-based 
biomarker assays have subsequently been utilized in research trials. 
Additionally, the AR-V7 Nucleus Detect assay has been validated and is 
clinically accessible through Epic Sciences’ commercial access partner, 
Exact Sciences. Using the Epic platform, Scher et al. recently showed that 
the degree of CTC phenotype heterogeneity can inform treatment 
decisions for metastatic castrate resistant prostate cancer patients, with 
differential responses in the low and high heterogeneity groups to taxane 
versus androgen receptor signaling inhibitor therapy (5). 
 

S1007 
Page 151 
Version Date 12/10/2021 
 
 
 
 
 
c. 
Rationale and Hypothesis 
 
The above findings support the design of utilizing liquid biopsy repositories from 
large adjuvant trials of endocrine therapy. A number of critical questions remain in 
early-stage breast cancer. For instance, if CTCs are identified in a patient who is 
still on adjuvant therapy without a recurrence, should we consider switching the 
systemic therapy to decrease the risk for late recurrence? Establishing a 
biorepository in this node positive population after 5 years of endocrine therapy 
offers a unique opportunity to evaluate whether we can identify blood-based 
predictors of late relapse.  
 
While there are commercially available tumor-tissue based genomic tests looking 
at rate of distant relapse, including breast cancer index, these are looking at 
baseline, pre-treatment samples. This substudy will look at real-time, on-treatment 
predictors, which may be more reflective of current tumor biology due to selective 
treatment pressure, dormancy escape, etc.  
 
In addition, other previously described blood-based markers, such as serum tumor 
markers, in patients with breast cancer can be unreliable, including in patients with 
metastatic breast cancer. Ultimately, the goal of this project is to identify early 
predictors of dormancy escape and late recurrence in patients with operable breast 
cancer, which can serve as the basis for future, randomized, interventional trials.  
 
We may be able to identify 3 groups of patients: 1) those who have not escaped 
dormancy (and may not need continued hormonal or other therapy), 2) those who 
are escaping dormancy and will relapse in the near future (and may need to modify 
treatment immediately, identifying the highest risk group for future clinical trial 
approach considerations), and 3) those who still are in dormancy and may 
experience a later relapse (and may need to switch hormonal therapy and/or add 
a new targeted treatment: again a population for future trial selection).  
 
We hypothesize that invasive disease-free survival will be poorer in CTC-positive 
patients compared to those patients who are CTC-negative.  
 
d. 
Experimental Approach and Assays 
 
1. 
Sample Collection and Timepoints 
 
At time of distribution of Revision #16 (Version Date 03/24/21), all U.S. 
patients who a) are disease free, with no prior invasive recurrence AND b) 
have been on protocol for up to 8 years after time of randomization to 
S1007 (Step 2 registration) must be offered participation in the Circulation 
Biomarker Assessment for Late Relapse Translational Medicine (CBALR 
TM) substudy.   
 

S1007 
Page 152 
Version Date 12/10/2021 
 
 
 
 
 
SUBMISSION SUMMARY TABLE: 
CBALR Visit #1:  
Within 28 days after 
patient registration 
to Step 3  
CBALR Visit #2:  
2-3 years after 
patient registration 
to Step 3  
CBALR Visit #3: 
At time of 
Invasive 
Recurrence 
20 mL 
whole 
blood 
a 
Two 10 mL  
Streck cfDNA tubes 
Ship 2 tubes to  
Epic Sciences Lab 
#236 b, c 
Two 10 mL  
Streck cfDNA tubes 
Ship 2 tubes to  
Epic Sciences Lab 
#236 b, c 
Two 10 mL  
Streck cfDNA tubes 
Ship 2 tubes to  
Epic Sciences 
Lab #236 b 
a  See Section 18.7d.4a. Patients may eat or drink something prior to 
blood draw for the Streck cfDNA tubes. 
b If the minimum blood volume for two 10 mL Streck cfDNA tubes (being 
shipped to Epic Sciences) cannot be collected during a visit, a 
subsequent second attempt at collection should be scheduled for 
another time. The subsequent draw time can be scheduled for later 
the same day (if appropriate and site has collection tubes on hand) or 
for another date. Due to funding restrictions and tube expiration dates, 
the SWOG Biospecimen Bank will only ship sufficient tubes for a 
single collection timepoint.  If the first draw attempt fails and the site 
does not have tubes on hand, then the site will need to: 1) reschedule 
the patient for a subsequent blood draw, allowing 5-7 days for 
collection kit shipment, and 2) re-order tubes for that patient.  See 
Section 18.7d.4c for more information.   
c If the patient is subsequently deemed not evaluable for the CBALR 
TM substudy, do not submit any subsequent blood samples for the 
CBALR TM substudy. 
 
Streck tubes will be collected for future analyses, such as cfDNA 
assessment. 
 
2. 
Sample Collection Kits 
 
Specimen collection kits (Streck cfDNA tubes and ambient gel packs) 
must be ordered IMMEDIATELY after patient registration to Step 3 
and prior to each collection timepoint.   
 
Sites should allow 5-7 days to receive kits.  Note: Patient samples 
must be drawn within 28 days after patient registration to Step 3. 
 
Streck cfDNA kits may be ordered by using the SWOG Biospecimen Bank 
Kit Management Application at: https://kits.bpc-apps.nchri.org.    
 
The kit provides: Two Streck cfDNA tubes and an ambient  pak for blood 
submitted to Epic Sciences Lab for a single collection timepoint.  
 
 

S1007 
Page 153 
Version Date 12/10/2021 
 
 
 
 
 
3. 
Sample Collection and Submission Instructions 
 
All sample submissions for this study must be entered and tracked using 
the SWOG online Specimen Tracking System. Complete sample 
collection and submission instructions can be accessed on the SWOG 
Specimen 
Submission 
webpage 
(https://www.swog.org/member-
resources/biospecimen-resources).  If collection/submission instructions 
differ from those in the protocol, the protocol instructions should be 
followed; otherwise, the website instructions should be followed. 
 
4. 
Streck Cell-Free DNA Collection Tubes (2 Streck cfDNA Tubes will be 
submitted to Epic Sciences (Lab #236)):  
 
a. 
Prior to Collection 
 
• 
Patients are not required to fast prior to Streck cfDNA blood 
draw. Patients may eat or drink something prior to blood draw 
into Streck cfDNA tubes. 
• 
See Section 18.7d.2 for ordering instructions for Streck cfDNA 
tube collection kits. 
• 
Confirm blood tubes are not expired. Expired tubes should not 
be used for blood collection.  
• 
Schedule courier for same-day sample pick-up prior to 
collection.  
 
b. 
Instructions for handling Streck cfDNA tubes during collection: 
Prevention of Backflow: Since Streck Cell-Free DNA BCT tubes 
contain chemical additives, it is important to avoid possible 
backflow from the tube.  
 
To guard against backflow, observe the following precautions:  
• 
Keep patient’s arm in the downward position during the 
collection procedure.  
• 
Hold the tube with the stopper uppermost.  
• 
Release tourniquet once the blood starts to flow into the tube, 
or within 2 minutes of application.  
• 
Tube contents should not touch stopper or the end of the 
needle during the collection procedure.  
 
 

S1007 
Page 154 
Version Date 12/10/2021 
 
 
 
 
 
c. 
Additional Blood Collection Instructions: 
 
• 
Draw whole blood sample into four (4), 10 mL Streck Cell-Free 
DNA BCT tubes. Fill tube until blood flow stops.  
 
• 
IMPORTANT: Fill each tube completely (10 mL), when 
possible.  
 
• 
For the 2 tubes being shipped to Epic Sciences (Lab # 236), 
a minimum of 4 mL blood per tube is required (at least 8 mL 
total volume collected in two 10 mL Streck cfDNA tubes). In 
the event that 8 mL blood volume (4 mL blood per tube) 
cannot be collected, do not submit Streck cfDNA tube 
samples to Epic Sciences. A subsequent second attempt at 
collection should be scheduled for another time. 
 
• 
Note: The subsequent draw time can be scheduled for later 
the same day, if deemed appropriate and site has additional 
collection tubes on hand or can be rescheduled for another 
date. Due to funding restrictions and tube expiration dates, the 
SWOG Biospecimen Bank will only ship sufficient tubes for a 
single collection timepoint for each patient registered to Step 
3.  If the first draw attempt fails, and the site does not have 
tubes on hand, then the site will need to 1) reschedule the 
patient for another day, allowing 5-7 days for collection kit 
shipment, and 2) re-order tubes for the second draw attempt.   
• 
If the patient is subsequently deemed not evaluable for the 
CBALR TM substudy, do not submit any subsequent blood 
samples for the CBALR TM substudy. 
 
• 
Approximate volumes are illustrated below. Each red arrow 
indicates the level to which the blood collection tube should 
be filled to achieve the corresponding volume in red, yellow, 
or blue. As a reference, a volume of 6-mL would fill the Streck 
cfDNA tube to just below the first “7” in the blood tube lot 
number “72750315” on the blood tube label. 
 
• 
 
 
• 
 
• 
Remove tube from adapter and immediately mix by gentle 
inversion 8 to 10 times. Tube inversion prevents clotting. 
Inadequate or delayed mixing may result in inaccurate 
test results.  
 
• 
After collection, do not refrigerate or freeze blood in 
Streck cfDNA tubes, as this will compromise the specimen. 
Blood collected in Streck cfDNA tubes is stable at room 
temperature.  
 
 

S1007 
Page 155 
Version Date 12/10/2021 
 
 
 
 
 
d. 
Labelling and Shipping Instructions 
 
1. Label blood tubes with the following: 
 
• 
SWOG patient number (patient ID) 
• 
Patient initials 
• 
Substudy visit number (time point) [Visit number = 
one, two, or three; i.e. one=within 28 days after 
patient registration to Step 3, two= 2-3 years after 
patient registration to Step  3, three=invasive 
recurrence]. 
• 
Collection date and time (date and time the specimen 
was collected from the patient) 
• 
Initials of the phlebotomist (Epic Sciences tubes only) 
• 
Specimen type (i.e., whole blood) 
 
2. Two (2) Streck cfDNA tubes will be shipped to Epic Sciences 
(Lab # 236) per the following instructions: 
 
• 
Specimens must be shipped with an ambient pack 
(provided in the Streck cfDNA tube kit). 
• 
All shipments must include a requisition form 
(Packing list) generated by the SWOG Specimen 
Tracking System. Print a copy of the Packing List in 
the online SWOG Specimen Tracking System. Place 
the Packing List in the pocket of the specimen bag if 
it has one, or in a separate resealable bag. 
• 
IMPORTANT NOTE: If a collection time is not 
provided, Epic Sciences will default to sample 
collection at 8:00 am (local time) on the date of 
collection. 
• 
Do not place “Infectious Substance” sticker on 
shipper, as this can result in a delay of shipment. If 
possible, include a scanned copy of the completed 
sample requisition form.  
 
e. 
For questions pertaining to the two Streck cfDNA tubes being 
shipped to Epic Sciences Lab contact:  
 
Lab #236:  Epic Sciences  
Email: partners@epicsciences.com / Attn: S1007   
 
 

S1007 
Page 156 
Version Date 12/10/2021 
 
 
 
 
 
5. 
CTC methods 
 
Epic Systems 
 
a. 
The Epic Sciences CTC platform is a multi-component system 
utilizing 
automated 
staining 
and 
fluorescent 
scanning 
instrumentation to detect and characterize nucleated cells isolated 
from patient blood samples. Peripheral blood samples are 
collected via standard butterfly needle into Streck Cell-Free DNA 
blood collection tubes containing protein fixatives. Upon sample 
receipt, plasma is isolated and nucleated cells are isolated from 
whole blood via red blood cell lysis and subsequently deposited 
onto functionalized glass slides. Plasma and slides can be either 
immediately stained or banked in -80 C for future testing. 
 
b. 
Immunofluorescent staining of deposited cells utilizes a primary 
antibody cocktail enabling the detection of all nucleated cells with 
DAPI staining, the detection and distinction of cytokeratin (CK)-
positive CTCs from CD45-positive white blood cells, and the 
identification of a fourth protein biomarker as specified by project 
(e.g., ER, PR, HER2). Appropriate anti-species secondary 
antibodies conjugated to fluorescent dyes allow for multiplexed 
visualization of DAPI, CK, CD45 and an additional biomarker. 
 
c. 
All cells on a slide are imaged by automated fluorescent scanners, 
and the images are subsequently fed into proprietary software 
algorithms that quantify fluorescence intensities and morphologic 
features to distinguish and characterize rare cells from normal 
WBCs. WBCs are categorized by CD45 positivity and associated 
morphologic features, while rare cells and CTCs are categorized 
by cytokeratin positivity and/or fourth channel biomarker positivity 
and CD45 negativity. Trained operators review the algorithmic 
classifications to produce a final report that includes total cell 
counts, CTC count, fluorescent staining intensities and various 
morphologic features including nuclear and cytoplasmic areas. If 
desired, each cell of interest can be relocated and individually 
recovered via a micromanipulator for single-cell genomic analysis. 
 

S1007 
Page 157 
Version Date 12/10/2021 
 
 
 
 
 
Overview of Epic Sciences Process for CTC Identification 
 
 
e. 
Statistical Design 
 
We anticipate that 8.9% of patients without a recurrence at substudy enrollment 
will develop a late recurrence in the follow-up period1. We will be collecting and 
analyzing blood samples on all patients, as we will otherwise not be able to 
prospectively predict who will develop a late recurrence. Among the 1,951 U.S. 
patients still being followed and who do not have a recurrence, we assume that we 
may recruit 890 patients for at least a single blood submission. Allowing for a CTC 
assay failure of 10%, then 800 patients would have assay results.  We anticipate 
conservatively that 3% of the 800 patients will be CTC+ (n=24) and 97% will be 
CTC- (n=776) post-endocrine therapy initiation2. The estimated number of invasive 
disease-free survival events after an additional median 4 years of follow-up (from 
time of blood collection) in 800 patients is 71 using an overall hazard rate of 0.231.  
With a two-sided alpha of 0.05, power is 80% to detect a hazard ratio of 3.3 for 
CTC-positive versus CTC-negative.  This is a conservative estimate given that 
E5103 had a 5.1% positivity rate and a 13.1 hazard rate in HR+ breast cancer. 
This will still allow sufficient power for a lower positivity rate than 3% or greater 
difficulty in patient recruitment as long as the hazard ratio is high.  
 
The actual analysis planned is a Cox regression on IDFS starting at the time of 
blood collection. We believe it is important to control for time since initial 
randomization and initial treatment assignment. It is also important to include use 
of endocrine therapy as a time-dependent covariate, as there will some variability 
in terms of whether patients extend beyond 5 years of endocrine therapy. The 
ultimate goal is to determine who may have benefited from extended endocrine 
therapy given CTC determination, but power will be lower for making this 
assessment. 
 
The kappa statistic will be used to assess agreement between the two systems 
when dichotomized into positive and negative.  
 
f. 
Data Analysis 
 
The data will be analyzed by the SWOG Statistics and Data Management Center 
along with the investigators of S1007. The S1007 primary endpoint must be 
published prior to reporting results of the Circulating Biomarker Assessment for 
Late Relapse TM substudy.  
 
 

S1007 
Page 158 
Version Date 12/10/2021 
 
 
 
 
 
g. 
References 
 
1. 
Pan H, Gray R, Braybrooke J, et al: 20-Year Risks of Breast-Cancer 
Recurrence after Stopping Endocrine Therapy at 5 Years. N Engl J Med 
377:1836-1846, 2017. 
2. 
Sparano J, O'Neill A, Alpaugh K, et al: Association of Circulating Tumor 
Cells With Late Recurrence of Estrogen Receptor-Positive Breast Cancer: 
A Secondary Analysis of a Randomized Clinical Trial. JAMA Oncol. 2018 
Jul 26.  doi: 10.1001/jamaoncol.2018.2574.  
3. 
Segal CV, Dowsett M: Estrogen receptor mutations in breast cancer--new 
focus on an old target. Clin Cancer Res 20:1724-6, 2014. 
4. 
Takeshita T, Yamamoto Y, Yamamoto-Ibusuki M, et al: Prognostic role of 
PIK3CA mutations of cell-free DNA in early-stage triple negative breast 
cancer. Cancer Sci 106:1582-9, 2015. 
5. 
Diehn M, Alizadeh AA, Adams H-P, et al: Early prediction of clinical 
outcomes in resected stage II and III colorectal cancer (CRC) through 
deep sequencing of circulating tumor DNA (ctDNA). Journal of Clinical 
Oncology 35:3591-3591, 2017. 
 
 

S1007 
Page 159 
Version Date 12/10/2021 
 
 
 
 
 
18.8 
Circulating Biomarker Assessment for Late Relapse in Patients with Node-Positive, 
Hormone-Receptor Positive, Her2 Negative, Operable Breast Cancer Translational 
Medicine Substudy (U.S. INSTITUTIONS ONLY) – NON-CTC ANALYSES – FUTURE 
ANALYSES 
 
Although endocrine therapy remains standard of care for patients with operable hormone 
receptor-positive (HR+) breast cancers (BCs), pts with HR+ BC may have a recurrence as 
a result of acquired resistance. Recurrences that occur 5 or more years after diagnosis 
(i.e., late relapse) account for approximately 50% of all BC recurrences. For instance, in a 
meta-analysis of 62,923 women with HR+ BC who were disease-free after 5 years of 
endocrine therapy, distant recurrence risk associated with tumor size and lymph node 
status, ranging from 10-40% up to 20 years from diagnosis. (1) Identifying markers that 
can predict late recurrence, such as blood-based biomarkers, remains an unmet need in 
this population.  Blood specimens for future cfDNA analyses will be collected at the same 
time as CTC specimens.  The analytic plan for these specimens has not yet been 
developed and will be submitted to CTEP for approval in the future. Below we outline the 
steps needed for future analysis. 
 
a. 
Primary Objective 
 
To collect and store blood specimens so that we can assess whether subsequent 
invasive disease-free survival depends on cfDNA status. The primary objective is 
to bank blood specimens from the blood draw at a baseline that is up to 8 years 
post-randomization and then 2-3 years later to be used in future TM proposals. 
 
b. 
Future objectives to be submitted to CTEP (Secondary to analyses, specified 
above and CTC analyses in Sections 18.6 and 18.7) 
 
1. 
To determine the frequency of serial cell free DNA (cfDNA) mutation when 
assessed at the same time as CTC and whether it is associated with 
subsequent IDFS. 
 
2. 
To determine the frequency of mutations, including ESR1, PIK3CA, AKT1 
(E17K), and p53, and other alterations as measured by cfDNA and 
subsequent association with IDFS. 
 
3. 
To assess the molecular evolution of mutation status by comparing the 
mutations identified with the following: a) primary tumor, b) cfDNA at the 
time of recurrence, and c) recurrence tumor tissue.  
 
4. 
To assess for associations between serum-based markers of the insulin 
growth factor pathway and subsequent IDFS. Other markers, such as 
inflammatory markers (c-reactive protein), will be explored. We note that 
pre-randomization blood specimens are available as well.   
 
c. 
Background 
 
1. 
Late Recurrence 
 
Hormone receptor positive (HR+)/HER2- breast cancers account for 
approximately 2/3 of breast cancers. Although endocrine therapy, such as 
selective estrogen receptor modulators (e.g., tamoxifen) and aromatase 
inhibitors, remain standard of care in the operable setting for patients with 
HR+ breast cancers, these patients may have a recurrence of their cancer, 
as a result of acquired resistance to endocrine therapies. Recurrences that 
occur 5 or more years after diagnosis (i.e., late relapse) account for 

S1007 
Page 160 
Version Date 12/10/2021 
 
 
 
 
 
approximately 50% of all breast cancer recurrences. In a meta-analysis 
involving 62,923 women with ER+ breast cancer who were disease-free 
after 5 years of endocrine therapy, the risk of distant recurrence strongly 
correlated with original tumor size and lymph node status, ranging from 
10-40% up to 20 years (1). We propose creating a biospecimen repository, 
including plasma and serum, for those who have not recurred, and to 
evaluate for blood-based markers that associate with a risk of late 
recurrence. 
 
2. 
Cell-free DNA (cfDNA)  
 
Several other assays are available that may detect occult tumor burden. 
These include collecting plasma and assessing for cfDNA. The majority of 
mutation detection work with cfDNA has been in the metastatic setting. As 
an example, mutations in the ESR1 gene, first reported in 1997 (2), have 
been reported in ~ 20% of recurrent breast cancer patients previously 
treated with endocrine therapy. These mutations are infrequently detected 
in the primary breast tumor (~ 2%) (3). Four hot-spot mutations contribute 
to ~ ¾ of ESR1 acquired mutations identified in the recurrent setting 
(D538G, Y537S/N/C)4.  In a small study in early-stage triple negative 
breast cancer, the rate of PIK3CA mutations in cfDNA was 24.4% (4). In 
other cancer types, including colorectal cancer, the identification of cfDNA 
in Stage II (5% prevalence) and stage III (16% prevalence) colorectal 
cancer has prognostic implications6. In fact, there is a proposed NRG 
adjuvant colorectal study (CR1643), randomizing patients with Stage II 
colorectal cancer to chemotherapy (Folfox) vs. observation based upon 
cfDNA status. 
 
Numerous recent reports have demonstrated the detection of mutant DNA 
alleles as tumor-specific markers in cfDNA, including a number of 
prospective-retrospective analyses of ESR1 mutations in randomized-
controlled trials. Bolero-2 was a double-blind, placebo-controlled 
metastatic trial in patients who previously progressed on a non-steroidal 
aromatase inhibitor (NSAI) who were randomized to the steroidal AI 
exemestane with or without everolimus. The presence of ESR1 D537S 
and D538G mutations had a significantly worse prognosis (20 months) 
compared to ESR1 wild type tumors (32 months) (5). Patients with D538G 
ESR1 mutations experienced clinical benefit from everolimus, while 
Y537S mutation did not. While the overall rate of ESR1 mutation detection 
at the time of study entry was ~ 30%, the rate was higher in those who had 
previously received AI for treatment in the metastatic setting (33%) 
compared to those who went onto study after receiving AI therapy only in 
the adjuvant setting (11%). In the SoFEA trial, women whose cancer had 
progressed after a period of sensitivity to an NSAI, defined as recurrence 
after at least 12 months of adjuvant NSAI or disease progression after at 
least 6 months of first-line metastatic treatment with an NSAI, were 
randomly assigned to be administered exemestane, fulvestrant 250 mg, 
or the combination of anastrozole and fulvestrant. Patients with ESR1 
mutations (~40% of those evaluated) had an improved progression free 
survival (PFS) receiving fulvestrant compared to exemestane (p=0.02). 
ESR1 wild type did just as well on either arm5. These data demonstrate 
the potential advantage of evaluating liquid biopsies. 
 
 

S1007 
Page 161 
Version Date 12/10/2021 
 
 
 
 
 
3. 
Rationale and Hypothesis 
 
The above findings support the design of utilizing plasma repositories from 
large adjuvant trials of endocrine therapy. A number of critical questions 
remain in early-stage breast cancer. Is there a role for detection of ESR1 
mutations, or other frequent mutations such as PIK3CA mutations, during 
adjuvant AI therapy? Will the ESR1 mutation status results observed in 
the metastatic Bolero-2 trial (endocrine therapy +/- everolimus) be 
recapitulated in the operable setting (endocrine +/- everolimus)? If ESR1 
mutations are identified, should these patients be switched to an 
alternative adjuvant therapy, such as a selective estrogen receptor 
downregulator (SERD)? Perhaps, switching strategies or combination of 
hormone therapy with a SERD should be utilized to overcome endocrine 
resistance in operable breast cancer? Establishing a biorepository in this 
node positive population after 5 years of endocrine therapy offers a unique 
opportunity to evaluate whether we can identify blood-based predictors of 
late relapse.  
 
While there are commercially available tumor-tissue based genomic tests 
looking at rate of distant relapse, including breast cancer index, these are 
looking at baseline, pre-treatment samples. This substudy will look at real-
time, on-treatment predictors, which may be more reflective of current 
tumor biology due to selective treatment pressure, dormancy escape, etc.  
 
In addition, other previously described blood-based markers, such as 
serum tumor markers, in patients with breast cancer can be unreliable, 
including in patients with metastatic breast cancer. Ultimately, the goal of 
this project is to identify early predictors of dormancy escape and late 
recurrence in patients with operable breast cancer, which can serve as the 
basis for future, randomized, interventional trials.  
 
We may be able to identify 3 groups of patients: 1) those who have not 
escaped dormancy (and may not need continued hormonal or other 
therapy), 2) those who are escaping dormancy and will relapse in the near 
future (and may need to modify treatment immediately, identifying the 
highest risk group for future clinical trial approach considerations), and 3) 
those who still are in dormancy and may experience a later relapse (and 
may need to switch hormonal therapy and/or add a new targeted 
treatment: again a population for future trial selection).  
 
 

S1007 
Page 162 
Version Date 12/10/2021 
 
 
 
 
 
d. 
Experimental Approach and Assays 
 
1. 
Sample Collection Timepoints 
SUBMISSION SUMMARY TABLE: 
CBALR Visit #1: 
Within 28 days 
after patient 
registration  
to Step 3 
CBALR Visit #2:  
2-3 years  
after patient 
registration  
to Step 3  
CBALR Visit #3:  
At time of 
Invasive 
Recurrence 
Metastatic 
Tissue 
(if 
applicable 
and where 
available) 
FFPE block or  
20 unstained 
slides 
 
Ship to SWOG 
Biospecimen 
Bank 
10 mL 
whole 
blood  a 
One 10 mL SST 
 
Ship to SWOG 
Biospecimen Bank 
One 10 mL SST 
 
Ship to SWOG 
Biospecimen 
Bank 
One 10 mL SST 
 
Ship to SWOG 
Biospecimen 
Bank 
20 mL 
whole 
blood a 
Two 10 mL Streck 
cfDNA tubes:  
Ship 2 Streck 
cfDNA tubes to 
SWOG 
Biospecimen Bank 
(Lab #201) b, c 
Two 10 mL Streck 
cfDNA tubes:  
Ship 2 Streck 
cfDNA tubes to 
SWOG 
Biospecimen 
Bank (Lab #201) 
b, c  
Two 10 mL 
Streck cfDNA 
tubes:  
Ship 2 Streck 
cfDNA tubes to 
SWOG 
Biospecimen 
Bank (Lab 
#201) b, c  
a  
Important: See Section 15.3c.1: Order of Sample Collection. Samples should 
be collected into the SST under fasting conditions. 
b 
If one 10 mL SST cannot be collected, a subsequent second attempt at 
collection should be scheduled for another time (Note: the subsequent draw 
time can be scheduled for later the same day, if deemed appropriate or can 
be rescheduled for another date.) If the two 10 mL Streck cfDNA tubes being 
shipped to the SWOG Biospecimen Bank (most likely the third and fourth 
Streck cfDNA tube draws) cannot be collected, a second attempt at collection 
of the two Streck cfDNA tubes being shipped to the SWOG Biospecimen Bank 
is not required. See Section 15.3c.4b for more information on Streck cfDNA 
requirements.   
c 
If the patient is subsequently deemed not evaluable for the CBALR TM 
substudy, do not submit any subsequent blood samples for the CBALR TM 
substudy. 
 
2. 
Correlative biomarker testing of above-referrenced specimens banked for 
planned future research will not occur until an amendment to this protocol 
(or separate correlative science protocol) is reviewed and approved in 
accordance with National Clinical Trials Network (NCTN) policies. 
 
 

S1007 
Page 163 
Version Date 12/10/2021 
 
 
 
 
 
 
e. 
Data Analysis 
 
These future analyses of cfDNA are planned. Given the tumor-based analyses 
being conducted by Exact Sciences Corporation (Section 18.2), including whole 
exome sequencing, the plan will be to conduct cfDNA analyses with a bespoke 
assay in collaboration with Exact Sciences Corporation. These analyses will not 
take place until the forthcoming statistical plan is reviewed and approved by CTEP. 
 
f. 
References 
 
1. 
Pan H, Gray R, Braybrooke J, et al: 20-Year Risks of Breast-Cancer 
Recurrence after Stopping Endocrine Therapy at 5 Years. N Engl J Med 
377:1836-1846, 2017. 
2. 
Zhang QX, Borg A, Wolf DM, et al: An estrogen receptor mutant with 
strong hormone-independent activity from a metastatic breast cancer. 
Cancer Res 57:1244-9, 1997. 
3. 
Segal CV, Dowsett M: Estrogen receptor mutations in breast cancer--new 
focus on an old target. Clin Cancer Res 20:1724-6, 2014. 
4. 
Takeshita T, Yamamoto Y, Yamamoto-Ibusuki M, et al: Prognostic role of 
PIK3CA mutations of cell-free DNA in early-stage triple negative breast 
cancer. Cancer Sci 106:1582-9, 2015. 
5. 
Chandarlapaty S, Chen D, He W, et al: Prevalence of ESR1 Mutations in 
Cell-Free DNA and Outcomes in Metastatic Breast Cancer: A Secondary 
Analysis of the BOLERO-2 Clinical Trial. JAMA Oncol 2:1310-1315, 2016. 
 
 

S1007 
Page 164 
Version Date 12/10/2021 
 
 
 
 
 
18.9 
Instructions for the SWOG Biospecimen Bank – Lab #201, Solid Tissue, Myeloma and 
Lymphoma Division 
 
a. 
Formalin-Fixed Paraffin-Embedded (FFPE) Tissue: The SWOG Biospecimen 
Bank will receive FFPE specimens as either blocks, punch biopsy or slides/sections 
at time of invasive recurrence (if recurrence occurs and where tissue is available 
from standard of care biopsy of metastatic site) (Registration Step 3). Upon receipt 
of FFPE tissue block, punch biopsy, or 20 unstained slides, Bank will accession and 
store at room temperature. 
 
b. 
Whole Blood in SST (Vacutainer): The SWOG Biospecimen Bank will receive one 
10mL (red top) SST at up to 3 timepoints. Upon receipt, the Bank will accession and 
process serum from the whole blood collected in the SST and store in aliquots in a -
80°C freezer for future analysis. 
 
c. 
Whole Blood in Streck Tubes: The SWOG Biospecimen Bank will receive 20mL 
ambient peripheral blood in two 10 mL Streck cfDNA tubes at up to 3 timepoints. Upon 
receipt, the Bank will accession and process for plasma and buffy coat. Plasma is 
processed using the following double-centrifugation protocol: 1,500xg for 10 minutes 
at room temperature with brake (buffy coat is removed at this point); plasma is 
removed and centrifuged again at 3,000xg for 10 minutes at room temperature with 
brake. Plasma will be stored in 1-mL aliquots, and buffy coat will be stored as 1 
aliquot; both plasma and buffy coat will be banked in a -80°C freezer until distribution. 
Planned future correlatives (cfDNA analysis) are planned for incorporation with a 
forthcoming revision. 
 
d. 
Distribution Instructions for Translational Medicine Objectives: Prospective 
validation of other prognostic/predictive indices of breast cancer outcomes:  
 
1.  Type and Volume of Samples to be Shipped 
 
a. Tissue 
 
The SWOG Biospecimen Bank will retrieve, perform QA pathology review, and 
ship the following for each patient with available tissue (FFPE slides): 11 
unstained 5-micron slides from the primary tumor at baseline submission 
timepoint along with the accompanying de-identified pathology report.  
 
Exact Sciences Corporation will receive two shipments of tissue.  The first will 
consist of samples for 60 patients.  It is estimated that a minimum of 6 
unstained slides sectioned at 5-micron thickness are required for testing (1 x 
5 microns for H&E to guide assessment and dissection; 5 x 5 microns for 
dissection and extraction of nucleic acids; sections will be mounted on charged 
glass slides and unbaked, and numbered sequentially from 1 to 6 to indicate 
the order in which they were sectioned from the tumor block).  Patients with 
less than 5 unstained slides will be recorded as “insufficient tissue available 
for testing”. Exact Sciences Corporation will conduct run-in testing on 
approximately 50 patient samples, then report out the process statistics on the 
run-in testing.  In the randomized run-in, Exact Sciences Corporation will 
confirm estimated yields with “preferred” vs. “minimum” number of slides, 
make any minor adjustments as appropriate for the analyses and convey to 
the SWOG Biospecimen Bank prior to the second shipment of tissue. 
 
If an FFPE block or a punch biopsy was submitted in lieu of slides, then the 
SWOG Biospecimen Bank will ship the FFPE block or the punch biopsy. Exact 
Sciences will be responsible for slide preparation and return (including return 
shipping cost) of all remaining tissue to the SWOG Biospecimen Bank. 

S1007 
Page 165 
Version Date 12/10/2021 
 
 
 
 
 
 
All tissue will be packaged in biohazard bags and shipped according to the 
SWOG Biospecimen Bank procedures. 
 
b. Blood (serum hormone studies) 
 
One 1 mL aliquots of serum processed and/or cryopreserved by the SWOG 
Biospecimen Bank (i.e., the Biopathology Center at Nationwide Children’s 
Hospital) will be provided for all patients that submitted baseline blood samples 
for analysis of serum estradiol, luteinizing hormone (LH), follicle-stimulating 
hormone (FSH), and anti-müllerian hormone (AMH)/Müllerian inhibiting factor 
(MIF).   Due to funding and logistical considerations, the samples to be shipped 
and tested will be limited to samples drawn from pre-menopausal patients 
under age 55.  
 
The SWOG Biospecimen Bank will retrieve and send a 1-mL aliquots from 
each of the estimated 1,364 eligible serum samples currently stored at -80°C. 
These samples will be shipped on dry ice to Dr. Godwin (in care of Dr. Harsh 
Pathak) at the University of Kansas Medical Center). For each of these patient 
samples the serum estradiol, luteinizing hormone (LH), follicle-stimulating 
hormone (FSH), and anti-müllerian hormone (AMH)/Müllerian inhibiting factor 
(MIF) levels will be measured. 
  
It is estimated that ~300 to 400 µL of each serum sample will be consumed to 
measure serum hormone levels (if the specimens are run in duplicate then 
~600 to 800 µL will be required). Any remaining residual serum will be 
destroyed in accordance with laboratory procedure. All data derived from 
processing will be forwarded to the SWOG Statistics and Data Management 
Center. 
 
2. Laboratory Conducting the Analyses 
 
a. Tissue 
 
Exact Sciences Corporation: Attention Kevin Chew 
701 Galveston Dr. 
BMR Room 104 
Redwood City, CA 94063 
Ph: 650-569-2402 
Email: kchew@exactsciences.com  
 
 
b. Blood (serum hormone studies) 
 
Andrew K. Godwin, PhD 
Professor and Division Director, Genomic Diagnostics 
c/o Harsh Pathak, PhD 
Biospecimen Repository Core Facility 
2106 Olathe Blvd 
Kansas City, KS 66160 
Wahl Hall East Rm. 4005 
Ph: 913-945-6378 
Fax: 913-945-6327 
Email: hpathak@kumc.edu  
 
 

S1007 
Page 166 
Version Date 12/10/2021 
 
 
 
 
 
3. Materials and Data Management 
 
a. Tissue 
 
All tissue will be returned to the SWOG Biospecimen Bank upon completion of 
processing. 
 
Exact Sciences Corporation will forward all marker data (raw and analyzed) to 
the SWOG Statistics and Data Management Center. 
 
b. Blood 
 
Any remaining residual serum will be destroyed in accordance with KUMC 
laboratory procedures. KUMC will forward all data derived from processing to 
the SWOG Statistics and Data Management Center.