Provider Referral Patterns Following Nephrectomy in High-Risk Locoregional Renal Cell Carcinoma
Conditions: Renal Cell Carcinoma
Sponsor: Pfizer

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NON-INTERVENTIONAL (NI) STUDY PROTOCOL
Title
Provider Referral Patterns Following Nephrectomy in High-Risk 
Locoregional Renal Cell Carcinoma
Protocol 
number
A6181230
Protocol 
version 
identifier
Final Version 4 (Amendment 1)
Date
27 March 2020
Research 
question and 
objectives
To estimate the proportion of patients diagnosed with locoregional renal 
cell carcinoma who are at high risk for recurrence following nephrectomy, 
describe referral patterns, and characterize treatment in this population. 
Outcomes including estimation of the incidence of recurrence and 
disease-free interval following nephrectomy will be reported overall and 
among the subgroup of patients receiving adjuvant systemic therapy with 
sunitinib following nephrectomy. 
Authors
Pfizer Inc.:
 PharmD, MSc
Duke University’s School of Medicine and Health System:
 MD
RTI Health Solutions:
 MS
 PhD
This document contains confidential information belonging to Pfizer. Except as otherwise agreed to in writing, 
by accepting or reviewing this document, you agree to hold this information in confidence and not copy or 
disclose it to others (except where required by applicable law) or use it for unauthorized purposes. In the event 
of any actual or suspected breach of this obligation, Pfizer must be promptly notified.

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1. TABLE OF CONTENTS
1. TABLE OF CONTENTS.......................................................................................................2
2. LIST OF ABBREVIATIONS................................................................................................4
3. RESPONSIBLE PARTIES....................................................................................................5
4. ABSTRACT...........................................................................................................................6
5. AMENDMENTS AND UPDATES.......................................................................................8
6. ANTICIPATED MILESTONES ...........................................................................................9
7. RATIONALE AND BACKGROUND................................................................................10
8. RESEARCH QUESTION AND OBJECTIVES .................................................................10
9. RESEARCH METHODS ....................................................................................................11
9.1. Study Design ...........................................................................................................12
9.1.1. Pilot Phase ..................................................................................................12
9.1.2. Part 2: Full Study........................................................................................13
9.1.3. Part 3: Expanded Data Collection...............................................................13
9.2. Setting......................................................................................................................14
9.2.1. Inclusion Criteria ........................................................................................14
9.2.2. Exclusion Criteria.......................................................................................14
9.3. Variables..................................................................................................................14
9.3.1. Patient Characteristics (all eligible study patients).....................................15
9.3.2. Baseline Clinical Characteristics (all eligible study patients) ....................15
9.3.3. Follow-up Visits (all eligible study patients)..............................................16
9.3.4. Referral Patterns (high-risk subgroup only) ...............................................16
9.3.5. Treatment Patterns (high-risk subgroup only)............................................16
9.3.6. Outcomes (high-risk subgroup only)..........................................................16
9.4. Data Sources............................................................................................................17
9.5. Study Size................................................................................................................17
9.6. Data Management ...................................................................................................18
9.6.1. Documentation of SAS Programming........................................................18
9.6.2. Validation of SAS Programs ......................................................................19
9.6.3. Log Review.................................................................................................19
9.6.4. Review of Data Listings and Tables of Summary Statistics.......................19

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9.6.5. Independent Programming..........................................................................19
9.6.6. Validation Documentation..........................................................................19
9.6.7. Data-collection Form..................................................................................20
9.6.8. Record Retention ........................................................................................20
9.7. Data Analysis ..........................................................................................................21
9.8. Quality Control........................................................................................................22
9.9. Limitations of the Research Methods......................................................................23
9.10. Other Aspects ........................................................................................................23
10. PROTECTION OF HUMAN SUBJECTS ........................................................................23
10.1. Patient Information................................................................................................24
10.2. Patient Consent......................................................................................................25
10.3. Institutional Review Board (IRB)/Independent Ethics Committee (IEC) ............25
10.4. Ethical Conduct of the Study ................................................................................25
11. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS ......................................................................................................................25
12. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS........27
13. REFERENCES ..................................................................................................................28
14. LIST OF TABLES.............................................................................................................29
15. LIST OF FIGURES ...........................................................................................................29
ANNEX 1. LIST OF STAND ALONE DOCUMENTS .........................................................29
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS .........................................29
ANNEX 3. ADDITIONAL INFORMATION.........................................................................29

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2. LIST OF ABBREVIATIONS
Abbreviation
Definition
AE
adverse event
AEM
adverse event monitoring
AIC
Akaike information criteria
CI
confidence interval
DCF
data collection form
ECOG
Eastern Cooperative Oncology Group
EMR
electronic medical record
HCRU
health care resource utilization
IEC
independent ethics committee
IRB
institutional review board
KPS
Karnofsky Performance Scale
NIS
non-interventional study
OQA
RTI-HS Office of Quality Assurance
RCC
renal cell carcinoma
RTI
RTI International
RTI-HS
RTI Health Solutions
SSIGN
stage, size, grade, and necrosis (score)
TNM
tumor, node, metastasis (cancer staging system)
UISS
UCLA Integrated Staging System
US
United States

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3. RESPONSIBLE PARTIES
Principal Investigator(s) of the Protocol
Name, degree(s)
Job Title
Affiliation
Address
 
PharmD, MSc
 
 
 MD
 
 
 
 
MS
Project Leader
 
 PhD
Project Supervisor
 
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD

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4. ABSTRACT
Provider Referral Patterns Following Nephrectomy in High-Risk Locoregional Renal 
Cell Carcinoma
Version 4 (27 March 2020)
Background and rationale: In 2017, renal cell carcinoma (RCC) accounted for nearly 
4% of new cancer cases in the United States. Among patients initially diagnosed with 
regional or distant disease, 5-year survival is 67% and 12%, respectively. Although only 
16% of patients are initially diagnosed with regional disease, up to 40% will experience 
relapse with distant metastases following nephrectomy. The high rate of recurrence among 
these patients highlights a continued unmet need for effective adjuvant treatment that can 
reduce recurrence risk, prolong the disease-free interval, and/or improved overall survival.
Yet, it is unclear whether postnephrectomy patients in real-world practice settings are 
typically assessed for recurrence risk postoperatively and whether patients at high risk of 
recurrence are seen by providers who can evaluate candidacy for adjuvant therapy, clinical 
trials, or alternative surveillance schedules. Additional evidence is needed to understand 
referral patterns and follow-up care following nephrectomy for patients at high risk of 
recurrence. Results from this study may provide needed evidence to understand populations 
of patients who are at the greatest risk of disease recurrence and investigate possible areas of 
unmet surveillance and treatment needs.
Objectives: To estimate the proportion of patients diagnosed with locoregional RCC who are 
at high risk for recurrence following nephrectomy, describe referral patterns, and characterize 
treatment in this population. Exploratory analyses may include estimation of the incidence of 
recurrence and disease-free interval following nephrectomy, if data are available.
Study design: Non-interventional, retrospective medical record review of patients diagnosed 
with locoregional RCC who received a nephrectomy in Duke University’s health system
(Duke). Using a published algorithm (eg, the UCLA Integrated Staging System [UISS] or the 
stage, size, grade, and necrosis [SSIGN] score) or adaptation of a published algorithm,
patients at high risk of recurrence following surgery will be followed until the end of their 
patient record, death, or disease recurrence to examine referral patterns, receipt of systemic 
therapy, disease recurrence, and death. The study will consist of a pilot phase to test the data 
abstraction tool and determine feasibility of assessing the study objectives with available data
and a full abstraction phase to compile the necessary data, conduct the analyses, and generate 
the documents for dissemination of the study results.
Population: Patients aged 18 years or older who were diagnosed with locoregional RCC and
underwent nephrectomy at Duke between 01 April 2014 and 31 December 2019. The final 
date range for patient inclusion was determined after the part 2 data collection was complete.

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Variables: Background (eg, age at nephrectomy, sex) and baseline clinical characteristics 
(eg, performance status, TNM [tumor, node, metastasis] stage, histology, tumor grade, 
categorical risk of recurrence following nephrectomy by commonly used clinical 
nomograms); postnephrectomy treatment and referrals; and disease recurrence events and 
survival will be assessed, where available.
Data sources: Duke researchers will abstract the necessary information from the electronic 
medical records of eligible patients and enter deidentified information into the study 
database. This study is retrospective; therefore, the collection of data will in no way influence 
prescribing patterns or treatment decisions.
Study size: Data will be abstracted from a target of 20 eligible patients during the pilot 
phase. During full abstraction, data for approximately 650 patients will be targeted for 
abstraction.
Data analysis: Descriptive summary of baseline characteristics by UISS risk categories
among patients with locoregional RCC. Among patients at high risk of recurrence, 
descriptive summary of postnephrectomy follow-up care. Time-to-event outcomes 
(eg, disease-free interval) will be described using the Kaplan-Meier method, if feasible.
Milestones: Key milestones include finalization of the protocol (December 2018),
finalization of the data-collection form (January 2019), completion of ethics submission 
(January 2019), completion of pilot phase and finalization of feasibility memo (June 2019),
start of data collection (July 2019), completion of part 2 data collection (September 2019), 
completion of part 2 data analysis (November 2019), and finalization of the part 2 study 
report (December 2019). Additional key milestones relevant to the expanded data collection 
include finalization of the updated protocol (Q1 2020), completion of ethics submission 
(Q1 2020), start of expanded data collection (Q2 2020), completion of expanded data 
collection (Q2 2020), completion of expanded data analysis (Q2 2020), and finalization of 
the updated study report (Q3 2020).

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5. AMENDMENTS AND UPDATES
Amendme
nt Number
Date
Protocol 
Section(s) 
Changed
Summary of Amendment(s)
Reason
1
11 June 2019
9.1. Study 
design
9.2.1. 
Inclusion 
criteria
The study period is now 01 April 
2014 to 31 March 2019. 
The study period has been updated 
to reflect the most recent 5-year 
period available in the data. The 
pilot phase feasibility study 
demonstrated that a 5-year period 
is more than sufficient to achieve 
the minimum desired sample size
of 500 eligible patients.
2
27 March
2020
Section 4 and 
Section 9
Section 4 and 
Section 9
Section 4 and 
Section 6
Update date ranges throughout
to reflect a study period through 
31 December 2019.
Increase the number of patient 
records abstracted to 650.
Update study timeline and 
milestones.
The new Common Rule does not 
require dates for retrospective 
studies. Updating the date 
limitation will allow for 
nephrectomies from 2019 to be 
collected and for follow-up to 
extend through the most recent 
medical record entry for previously 
identified patients.
Increase the number of subjects to 
include patients who have had 
more recent nephrectomies (up to 
650 total).

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6. ANTICIPATED MILESTONES
Milestone
Planned Date
Final protocol 
18 Dec 2018
Submit IRB applications
18 Jan 2019
Feasibility assessment (pilot phase)
05 Jun 2019
Start of full data collection 
01 Jul 2019
End of full data collection 
15 Sep 2019
Final analytic results
11 Dec 2019
Final study report
31 Dec 2019
Final updated protocol
Q1 2020
Submit revised IRB application
Q1 2020
Start expanded data collection
Q2 2020
End expanded data collection
Q2 2020
Final updated analytic results
Q2 2020
Final updated study report
Q3 2020
IRB = institutional review board.

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7. RATIONALE AND BACKGROUND
In the United States (US), renal cell carcinoma (RCC) accounts for nearly 4% of new cancer 
cases and resulted in an estimated 14,400 deaths in 2017 (National Cancer Institute, 2018).11
Five-year survival for patients with RCC is 74%; however, prognosis varies by disease stage. 
Among patients initially diagnosed with regional or distant disease, 5-year survival is 
67% and 12%, respectively.
Nephrectomy is the recommended treatment for most patients with localized or regional 
disease, followed by surveillance (Motzer et al., 2017).10 Although only 16% of patients are 
initially diagnosed with regional disease, up to 40% will experience relapse with distant 
metastases following nephrectomy (Janzen et al., 2003; Breda et al., 2007).6,2 The high rate 
of recurrence among these patients highlights a continued unmet need for effective adjuvant 
treatment that can reduce recurrence risk, prolong the disease-free interval, and/or improve 
overall survival.
Yet, it is unclear whether postnephrectomy patients in real-world practice settings are 
typically assessed for recurrence risk postoperatively and whether patients at high risk of 
recurrence are seen by providers who can evaluate candidacy for adjuvant therapy, clinical 
trials, or alternative surveillance schedules. Additional evidence is needed to understand 
postoperative referral patterns and follow-up care for patients at high risk of recurrence.
In this study, researchers at Duke University’s School of Medicine and Health System 
(Duke) and RTI Health Solutions (RTI-HS) will collaborate on a non-interventional, 
retrospective medical record review study aimed at examining postnephrectomy referral 
patterns and treatment characteristics in patients diagnosed with RCC. The feasibility of 
estimating disease recurrence and disease-free interval following nephrectomy in this 
population will also be explored. Results from this study may provide needed evidence to 
understand the proportion of postnephrectomy patients who are at the greatest risk of disease 
recurrence and investigate possible areas of unmet surveillance and treatment needs.
8. RESEARCH QUESTION AND OBJECTIVES
The aim of this study is to estimate the proportion of patients diagnosed with RCC who are at 
high risk for recurrence following nephrectomy, describe referral patterns, and characterize
treatment in this population. Exploratory analyses may include estimation of the incidence of 
recurrence and disease-free interval following nephrectomy, if data are available. Data for 
this study will be collected from a retrospective medical record review of patients diagnosed 
with locoregional RCC who underwent nephrectomy at Duke. The following primary 
objectives will be assessed:

Describe patient demographic and clinical characteristics of patients diagnosed with 
locoregional RCC who underwent nephrectomy.

Estimate the proportion of patients at high risk of recurrence following nephrectomy.

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
Characterize postoperative provider referrals among patients at high risk of 
recurrence, including the proportion of patients who were referred to other providers
and reasons for referral.

Describe treatment characteristics following nephrectomy among patients at high risk 
of recurrence, including the proportion of patients who received systemic therapy, 
type of systemic therapy received, dose and duration of treatment, reasons for 
treatment discontinuation, and participation in clinical trials, where available; perform 
subgroup analyses to describe treatment details among the subgroup of patients 
receiving adjuvant systemic therapy with sunitinib.

Estimate the incidence of disease recurrence and duration of the disease-free interval 
following nephrectomy among all patients at high risk of recurrence, and among the 
subgroup of patients receiving adjuvant systemic therapy with sunitinib.
9. RESEARCH METHODS
To achieve the study objectives, retrospective medical record data of adult patients diagnosed 
with locoregional RCC who received a nephrectomy at Duke will be compiled by Duke 
researchers and analyzed by RTI Health Solutions (RTI-HS) analysts. RTI-HS will develop a 
customized data-collection form (DCF) to capture detailed information on patient 
demographics, clinical characteristics, health outcomes, treatments, and postoperative 
referrals from the medical records of eligible patients. Patients will be selected based on 
specific inclusion and exclusion criteria described in Sections 9.2.1 and 9.2.2. All necessary 
study materials will be submitted to Duke’s institutional review board (IRB) for review and 
RTI International’s1 IRB for study classification.
Following receipt of each IRB’s classification or approval of the study (where required), 
Duke researchers will proceed with implementation of the pilot study (pilot phase). The pilot 
phase will consist of a pilot study to assess whether an adequate sample of the patient 
population of interest is available, evaluate the quality and completeness of available data, 
and quantify the duration of follow-up care available in Duke’s electronic medical record
(EMR) system. Using lessons learned from the pilot study, part 2 (the full study) will consist 
of abstracting data for a large sample of patients, analyzing the data, and preparing a study 
report and other materials for disseminating the study findings (ie, conference abstract, 
poster, and manuscript). Based on the temporal trends observed in part 2, the data abstraction 
will be expanded to include part 3 (the expanded study), which will consist of abstracting 
data on the additional patients who underwent nephrectomy through 2019 and expanded 
follow-up data collection (ie, referral patterns, treatment patterns, and outcomes) for 
previously identified patients at high risk of recurrence, to include follow-up dates through 
the most recent available medical record entry prior to the abstraction date.
                                                
1 RTI Health Solutions is a business unit of the not-for-profit research organization RTI International.

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9.1. Study Design
This study is a retrospective, observational medical record review of patients diagnosed with 
locoregional RCC who received a nephrectomy at Duke between 01 April 2014 and 
31 December 2019. The date of the nephrectomy will be considered the index date. 
Background clinical characteristics such as date of initial and locoregional RCC diagnoses 
will be identified during the period prior to the index date. Recurrence risk status will be 
assigned at the index date, using information available in the record at or around the index 
date. During the follow-up period (ie, the period between the index date and the last entry in 
the medical record, death, or disease recurrence), outcomes including treatment, referrals,
and disease recurrence will be assessed for patients who were determined to have been at 
high risk of recurrence following their nephrectomy, where data are available. Figure 1
provides a visual schematic of relevant observation periods.
Figure 1.
Patient Observation Periods
RCC = renal cell carcinoma.
9.1.1. Pilot Phase
To enable assessment of appropriate inclusion criteria and data availability, researchers will 
conduct an initial pilot study. Duke researchers have compiled a preliminary list of patients 
diagnosed with RCC who underwent nephrectomy between 01 November 2012, and 
31 October 2018, using DEDUCE, Duke’s EPIC query tool. A total of 1,069 patients were 
identified, of which approximately 75% (n = 801) are expected to have been diagnosed with
locoregional disease. A total of 883 patients were identified between 01 November 2013, and 
31 October 2018 (approximately 662 anticipated to have locoregional disease). At this time, 
the researchers anticipate that a total sample of approximately 500 patients diagnosed with 
locoregional RCC who underwent nephrectomy will be required to obtain a sample of 75 to 
100 patients considered to have been at high risk for disease recurrence after surgery.
Based on these preliminary counts, it is likely that inclusion of nephrectomies occurring 
between 01 November 2013, and 31 October 2018, will generate a sufficient sample. Duke 
researchers will determine preliminary annual aggregated counts, which RTI-HS will use to 
estimate the anticipated sample size of patients at high risk of recurrence, based on a 
published algorithm (eg, UCLA Integrated Staging System [UISS] risk status or stage, size, 

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grade, and necrosis [SSIGN] score) and proportions identified in published literature.
Assessing potential sample size during the pilot study will allow researchers to determine 
whether the proposed sampling strategy (ie, selecting nephrectomy between 01 November 
2013, and 31 October 2018) is adequate to obtain the desired sample size. If it is not, 
nephrectomies occurring from 01 November 2012, may be considered.
After the updated preliminary count is established and the study is approved by Duke’s IRB, 
Duke researchers will evaluate the quality and completeness of available data by abstracting
data for at least 20 eligible patients by reviewing patient medical records from a random 
sample of 50 patients identified by the DEDUCE query tool. This process will determine the 
proportion of eligible patients in the broader patient list identified by DEDUCE, and whether 
adequate information required to meet the study objectives are regularly available in the 
medical record. Results of the pilot study will be used to inform the final sample size 
expectation and refine study objectives, as needed. Note that a full assessment of data 
availability is dependent on abstraction of one or more patients that are classified as being at 
high risk of recurrence. If the first 20 eligible patients abstracted do not include a patient that 
is classified as high risk, additional patients will be included in batches of five until data for 
at least one patient at high risk of recurrence have been abstracted.
9.1.2. Part 2: Full Study
Results from the pilot phase feasibility assessment validated the sample size assumptions, 
with 83% of nephrectomies identified in the DEDUCE query confirmed eligible for the study 
and 15% of eligible nephrectomies classified as high risk. This indicates that the minimum 
sample of 500 patients, with 75-100 high risk, will likely be exceeded. Nephrectomies 
between 01 April 2014 and 31 March 2019 will be included to ensure the most up-to-date 
patient sample.
Part 2 will consist of abstracting data for the full sample of eligible patients, analyzing the
data, and reporting the results. Duke researchers will abstract data on the remaining sample 
of eligible patients. Baseline demographic and clinical characteristics will be abstracted for 
the anticipated sample of 500 patients. Of patients who are determined to be at high risk of 
recurrence following nephrectomy (anticipated sample of 75-100 patients), additional data on 
treatment characteristics, outcomes, and referrals will be abstracted.
Once the data are fully abstracted, anonymized patient-level data will be transferred to 
RTI-HS for analysis. All programming will be conducted using SAS statistical software
(version 9.4 or higher). The analysis will be descriptive, with exploratory models to examine 
possible factors associated with disease recurrence and disease-free interval, if the sample
size is sufficient.
9.1.3. Part 3: Expanded Data Collection
Results from the part 2 study indicated that referral and treatment patterns show an increasing 
trend from 2018 into 2019. To further capture this trend, an additional sample of all patients 
with nephrectomies occurring through 31 December 2019 will be abstracted. The additional 
sample size during this period is estimated to be approximately 115-150 patients, for a full 

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combined sample of up to 650 patients in total. In addition, expanded follow-up data
(ie, referral patterns, treatment patterns, and outcomes) will be collected for previously 
identified patients at high risk of recurrence, to include follow-up dates through the most 
recent available medical record entry prior to the abstraction date.
9.2. Setting
Data will be abstracted from the Duke EMR system. Patients whose data will be included in 
the study will have met the criteria described in Sections 9.2.1 and 9.2.2. Refer to Figure 1
for a depiction of the follow-up period. No minimum follow-up time will be required. 
Outcomes among patients who are determined to be at high risk of recurrence will be 
observed over each patient’s follow-up period—from the date of nephrectomy to death, 
disease recurrence, or the last date in their medical record (whichever occurs first).
9.2.1. Inclusion Criteria
Patients must meet all of the following inclusion criteria to be eligible for data abstraction:

Diagnosed with locoregional RCC (no distant metastasis at the time of diagnosis).

Underwent a nephrectomy at Duke between 01 April 2014, and 31 December 2019 
(final dates determined based on results from part 2 data collection).

Aged 18 years or older at nephrectomy.
9.2.2. Exclusion Criteria
There are no exclusion criteria for this study.
9.3. Variables
All variables will be gathered using the DCF developed by RTI-HS and described in 
Section 9.6.7. In the following sections, we describe the key analysis variables and study 
measures that will be gathered directly through the DCF or constructed during analysis. 
Limited data will be collected on all eligible patients with locoregional RCC nephrectomy, 
while additional variables will be collected for patients who are classified as having a high 
risk of recurrence (anticipated to be 15%-20% of the total population; see Section 9.5 for 
details).
A small portion of patients may undergo more than one nephrectomy during the study period
(anticipated to be 5%-10% of the total population). For these patients, all data will be 
collected in reference to the highest risk eligible tumor.
Exact dates will be collected in the DCF but will not be retained in the analytic file or 
transferred from Duke to RTI-HS. See Section 10 for a description of the method for 
anonymizing date data.

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9.3.1. Patient Characteristics (all eligible study patients)
Demographic characteristics available in patient medical records will be documented. The
following characteristics will be included:

Year of birth;

Age at nephrectomy;

Sex;

Race and/or ethnicity.
9.3.2. Baseline Clinical Characteristics (all eligible study patients)
A number of clinical characteristics related to the initial diagnosis of locoregional RCC and 
nephrectomy will be collected. The following characteristics may be included (when 
available):

Date of diagnosis of locoregional RCC;

Date of nephrectomy;

TNM [tumor, node, metastasis] stage;

Tumor grade;

Fuhrman grade (I-IV);

Tumor histology;

Clear cell predominant versus not clear cell predominant;

Tumor size (cm);

Tumor necrosis (present/absent);

Partial versus radical nephrectomy;

Performance status--ECOG (Eastern Cooperative Oncology Group); if a KPS 
(Karnofsky Performance Scale) score is abstracted, it will be converted to an ECOG
score (https://oncologypro.esmo.org/Oncology-in-Practice/Practice-
Tools/Performance-Scales).

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9.3.3. Follow-up Visits (all eligible study patients)
Information about the first postoperative visit following nephrectomy will be collected for all 
eligible patients, when available, and any decisions regarding follow-up plans made at this 
visit will be documented.

Date of first postoperative follow-up visit;

Follow-up plan determined at first postoperative visit:

Surveillance;

Adjuvant systemic therapy;

Transfer of care to a non-Duke provider;

Follow-up plan not recorded in the medical record.
9.3.4. Referral Patterns (high-risk subgroup only)
Information on provider referrals for oncologic or RCC-related care will be collected only for 
patients at high risk of recurrence, when available.

Dates of referral for oncologic/RCC-related care;

Reasons for referrals for oncologic/RCC-related care;

Referring provider type;

Type of provider referred to;

No documented referral for oncologic/RCC-related care.
9.3.5. Treatment Patterns (high-risk subgroup only)
Detailed information on treatment patterns will be collected only for patients at high risk of 
recurrence, when available. Note that for patients participating in a competitor clinical trial, 
detailed information on the specific agent used will not be collected.

Dates of subsequent surgery, procedures, and adjuvant systemic therapy;

Type and dose of systemic agents received;

Participation in clinical trials.
9.3.6. Outcomes (high-risk subgroup only)
Health outcomes will be collected only for patients at high risk of recurrence, when available.

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
Date of last follow-up encounter in the medical record;

Date of death;

Date of disease recurrence and method of confirmation;

Type of disease recurrence (eg, locoregional versus distant, if applicable);

Reasons for treatment discontinuation.
9.4. Data Sources
Data will be abstracted from medical records of patients receiving care within the Duke 
University Health System. This study is retrospective; therefore, the collection of data will in 
no way influence prescribing patterns or treatment decisions.
Medical record abstractions provide a unique opportunity to collect and analyze real-world 
data outside the highly controlled setting of clinical trials. Generally, medical record 
abstraction enables collection of detailed information on patient demographic and clinical 
characteristics, treatment patterns, health outcomes, and health care resource utilization 
(HCRU) that may otherwise be unavailable in a standardized manner. The use of medical 
record abstraction allows for the development of a highly customized DCF that meets the 
specific needs of this study.
Following ethics approval, the DCF will be programmed into an Excel-based data-collection 
instrument. The use of an Excel-based tool not only enables streamlined abstraction but also 
real-time consistency checks to improve the accuracy of the recorded data. Upon finalization 
of the DCF, physicians at Duke will proceed with data-collection activities. Physicians will 
screen their patients’ records to identify eligible patients. Physicians will be responsible for 
selecting patient medical records that meet the inclusion and exclusion criteria described in 
Section 9.2. After the physician identifies an eligible medical record, he or she will complete 
the DCF for the patient by retrospectively reviewing all available data in the medical record. 
The use of physicians to directly abstract patient medical record data eliminates interviewer 
or abstractor bias. Additionally, physicians are able to quickly and accurately interpret notes 
contained within a patient record, thereby providing additional information from a qualitative 
source. See Section 9.9 for a detailed review of the strengths and limitations of this study 
type.
9.5. Study Size
The total sample size will reflect the total number of eligible patients undergoing 
nephrectomy at Duke University Health System during the study period. At this time, it is 
estimated that this will be approximately 650 patients. Of this broader sample, it is 
anticipated that approximately 15%-20%, or 98-130 patients, will be classified as at high risk 
of recurrence and eligible for additional data collection to document treatment patterns and 
outcomes. As this study is exploratory in nature, no formal power calculations were 
conducted to determine the sample size for this study. Furthermore, this study does not 

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involve formal hypothesis testing and is primarily being conducted to understand clinical 
characteristics, treatment patterns, and health outcomes. Any significance testing will be 
exploratory in nature. Thus, the sample size considered for this study should be adequate to 
address the study objectives.
9.6. Data Management
RTI-HS will perform the analyses described in this proposal using a SAS statistical software 
application housed on RTI-HS’s secure, large-capacity, high-performance Linux mainframe. 
Experienced RTI-HS programmers and analysts will perform all analyses. To ensure the 
integrity and quality of the study results, we will follow our programming validation 
life-cycle process for all analyses. This includes quality-checking programs, logs, and output 
for accuracy according to relevant standard operating procedures.
To ensure the integrity and quality of study results, RTI-HS implements several practice 
standards for statistical programming, database management, and documentation for all 
projects involving databases analyses. The following three steps will be undertaken to 
achieve this high level of quality:

Documentation of SAS programming;

Validation of SAS programs;

Database storage and retention.
9.6.1. Documentation of SAS Programming
To ensure smooth transitions of analytic methods and work among programmers, reviewers, 
and other project personnel, documentation of the following information will be created for 
each SAS program:

Project name;

Program name;

Program purpose;

Program author;

Date the program was completed;

Descriptions of subsequent changes and/or enhancements, with name of programmer 
and date for each.
This information will be incorporated into each program in the form of a header. In addition 
to documenting this information in a general program header, each program will include 

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detailed comments throughout to describe the purpose and method of specific programming 
statements.
9.6.2. Validation of SAS Programs
In this section, we describe a variety of programming validation methods, including log 
review, review of data listings, and independent programming, which will be used to ensure 
that our SAS programs function as intended. The validation methods described in this section 
are not exhaustive, and additional measures will be implemented as appropriate.
9.6.3. Log Review
Programmers will review all SAS log files. This procedure is a widely accepted, basic level 
of program validation. The following issues must be addressed as part of a log review:

No errors should appear in a log file.

If warning messages or messages related to uninitialized variables are permitted in the 
log file, the programmer will document why they are permitted.

The programmer will account for the number of observations reported at each 
executed data step, especially when the number of observations increases or 
decreases.

The log file will contain all lines of the program as it was saved at the time of 
execution, and it will contain only those lines of code.
9.6.4. Review of Data Listings and Tables of Summary Statistics
Because an error-free log file does not necessarily demonstrate that a SAS program has 
functioned as intended, programmers will produce cell frequencies, means, and other 
summary statistics on specific data items to demonstrate that the program results are valid.
Where appropriate, we also will have a separate analyst review these listings independent of 
the programmer.
9.6.5. Independent Programming
For highly complex programming tasks, a second programmer will attempt (if necessary) to 
independently reproduce output generated by the initial programmer. If the outputs are 
equivalent, the test will be considered successful. If the outputs are not equivalent, the 
programmers will evaluate the differences and make appropriate corrections.
9.6.6. Validation Documentation
For each SAS program used to produce final study outputs for presentation, RTI-HS will 
complete and store a formal SAS validation document.

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9.6.7. Data-collection Form
As used in this protocol, the term DCF should be understood to refer to either a paper form or 
an electronic data record or both, depending on the data-collection method used in this study.
A DCF is required and should be completed for each included patient. The completed 
original DCFs are the sole property of Pfizer and should not be made available in any form to 
third parties, except for authorized representatives (ie, RTI-HS) of Pfizer or appropriate 
regulatory authorities, without written permission from Pfizer. The investigator shall ensure 
that the DCFs are securely stored at the study site in encrypted electronic form and will be 
password protected or secured in a locked room to prevent access by unauthorized third 
parties.
The investigator has ultimate responsibility for the collection and reporting of all clinical,
safety, and laboratory data entered on the DCF and any other data-collection forms (source 
documents) and ensuring that they are accurate, authentic/original, attributable, complete, 
consistent, legible, timely (contemporaneous), enduring, and available when required.
The source documents are the patient medical records; data collected on the DCFs must 
match those records.
9.6.8. Record Retention
To enable evaluations and/or inspections/audits from regulatory authorities or Pfizer, the 
investigator agrees to keep records, including the identity of all participating patients 
(sufficient information to link records, eg, DCFs and hospital records), copies of all DCFs, 
safety reporting forms, source documents, detailed records of treatment disposition, and 
adequate documentation of relevant correspondence (eg, letters, meeting minutes, and 
telephone call reports). The records should be retained by the investigator according to local 
regulations or as specified in the study agreement, whichever is longer. The investigator must 
ensure that the records continue to be stored securely for so long as they are retained.
If the investigator becomes unable for any reason to continue to retain study records for the 
required period (eg, retirement, relocation), Pfizer should be prospectively notified. The 
study records must be transferred to a designee acceptable to Pfizer, such as another 
investigator, another institution, or to an independent third party arranged by Pfizer.
Study records must be kept for a minimum of 3 years after completion or discontinuation of 
the study, as expressed in separate contractual agreements between Duke University, 
RTI-HS, and Pfizer.
The investigator must obtain Pfizer’s written permission before disposing of any records, 
even if retention requirements have been met.
RTI-HS and Duke will store in a secure location all copies of the original data files, as 
applicable. Data files stored on CD, DVD, or other media will be kept in a locked storage 
unit. Original data files will be housed on dedicated project space on RTI-HS’ Linux server. 

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To ensure the integrity of the original files, they will be stored on the Linux server in a 
designated folder that cannot be overwritten. Data sets derived from the original files during 
the data-cleaning process will be stored in a separate folder.
9.7. Data Analysis
All variables described in Section 9.3 will be summarized descriptively through the tabular 
display of mean values, 95% confidence intervals (CIs), medians, quartiles, and standard 
deviations of continuous variables of interest and frequency distributions for categorical 
variables. All open-ended text fields associated with the “other” answer option will be 
evaluated and described, as appropriate.
All study-eligible patients will be included in descriptive analyses of variables pertaining to 
patient characteristics, baseline clinical characteristics, and initial postoperative follow-up 
visits (see Sections 9.3.1, 9.3.2, and 9.3.3 for details). Patients who are categorized as having 
a high risk of recurrence will be included in additional analyses described below. Risk 
classification will be assessed using published algorithms (eg, UISS and SSIGN score) or 
adaptation of a published algorithm. The primary risk classification system used to designate 
the high-risk subgroup for this study will be chosen based on completeness of data available 
in the patient medical records. Completeness will be assessed during the pilot study. If data 
are available to support more than one classification system, the UISS risk classification will 
be used. If some data are not available to support classification using a published algorithm, 
an adapted version of an algorithm will be explored.
Additional descriptive analyses performed within the high-risk subgroup will include referral 
patterns, treatment patterns, and health outcomes (see Sections 9.3.4, 9.3.5, 9.3.6). In 
addition to descriptive analyses, time-to-event measures (ie, time to recurrence, overall 
survival) will be assessed. To adjust time-to-event measures, a Kaplan-Meier method that 
accounts for right-censoring will be implemented (Klein and Moeschberger, 2005).7 To 
evaluate time to recurrence, the endpoint will be programmed with the date of recurrence or 
date of death, whichever occurs first, as an eligible event; if neither of these events occurred, 
the outcome will be right censored at the date of the last medical record follow-up. To 
evaluate overall survival, the endpoint will be programmed with the date of death as an 
eligible event or right censored at the date of the last medical record follow-up.
Exploratory semiparametric Cox proportional hazards models will be used to evaluate factors 
associated with time to recurrence and overall survival. These outcomes will be defined as 
described previously. Separate models will be estimated for time to recurrence and overall 
survival. The models will take the following general form:
h(t) = h0(t) exp(β1DEMOGRAPHICi + β2CLINICALi), (Equation 2)
Where the following apply:

h(t) will be the hazard function of recurrence and overall survival as a function of 
explanatory variables.

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
h0(t) will be the baseline hazard of recurrence and overall survival.

DEMOGRAPHIC will be a vector of patient demographic characteristics, including
but not limited to the following:

Age;

Sex.

CLINICAL will be a vector of underlying clinical characteristics, including but not 
limited to the following:

Tumor histology;

Type and duration of systemic treatment;

Referral status;

Subsequent procedures.
The independent variables included in the final Cox proportional hazard models will be 
selected through an iterative process. First, separate univariate models assessing the 
relationship between each potential independent variable (eg, tumor histology) and the 
time-to-event outcome (ie, recurrence and overall survival) will be fit (Klein and
Moeschberger, 2005).7 The model with the lowest Akaike information criteria (AIC) will be 
selected for further evaluation. Next, each unselected variable will be added independently to 
the previously selected model to determine whether the addition of the specific variable 
results in a lower AIC. The model with the lowest AIC will be selected for further evaluation. 
This process will be repeated with each of the remaining unselected variables until the 
addition of unselected variables no longer lowers the AIC. The most parsimonious model 
will have the lowest AIC. Additionally, variables of clinical significance may be included in 
the model. The overall goodness-of-fit of the final model will be assessed using Cox-Snell 
residuals and the proportional hazards assumption for the final set of covariates (Klein and
Moeschberger, 2005).7
Cox proportional hazards models will generate a hazard ratio for each of the covariates 
included in the model, indicating the higher or lower rate of an event (relative to a reference 
category) at any given point in time following nephrectomy. Like odds ratios from a logistic 
model, a hazard ratio less than 1 indicates a lower rate of an event, while a ratio greater than 
1 indicates a higher rate of an event, relative to a reference category.
9.8. Quality Control
The DCF will be designed to perform data checks for illogical or unusual data (eg, treatment 
starting prior to diagnosis) during data collection, so that such errors may be immediately 
corrected by the physician.

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RTI-HS and its staff strive to meet the highest standards of professional performance and 
continuously improve our products and services. To ensure quality, we work with our clients 
to define requirements and clarify expectations, and we pledge that our products and services 
will comply with these requirements, meet or exceed client expectations, and deliver 
exceptional value.
The RTI-HS Office of Quality Assurance (OQA) is an independent unit that reports to the 
Vice President of RTI-HS and provides training on applicable regulations and guidelines, 
implements and maintains a series of standard operating procedures, and provides quality 
assurance monitoring for compliance with regulatory requirements.
RTI-HS will work closely with the selected subcontractors to establish and ensure a complete 
integration of procedures for the project. The OQA will perform audits and assessments that 
involve various aspects of the project, including but not limited to education and training 
documentation. Audits are conducted by the OQA according to established criteria in 
standard operating procedures and other applicable procedures. The OQA reports quality 
assurance observations to the Project Director and facilitates corrective actions, if necessary.
9.9. Limitations of the Research Methods
Retrospective medical record reviews are subject to the following general limitations:

Patients selected for study inclusion represent a sample of patients who received 
treatment at Duke. Therefore, study findings may not be generalizable to the overall 
population of patients with locoregional RCC or physicians who treat this disease in 
the US.

All data captured in the DCF will be limited to information available in the patients’ 
medical records held by Duke University. Information on health care services 
received outside the physician’s care setting that is not recorded in the medical record 
will be unavailable for this study (eg, treatment received through a non-Duke 
urologist or other health care provider [eg, medical oncologist]).

Data will be entered directly by the Duke research team and may be subject to entry 
errors and resulting inaccuracies in reporting. Although data checks will be in place to 
improve internal consistency of the data, responses will not be validated against the 
patients’ medical records by an independent reviewer.
9.10. Other Aspects
Not applicable.
10. PROTECTION OF HUMAN SUBJECTS
Patient medical record data may contain highly sensitive and private personal health 
information. Therefore, the following data-collection strategies will be implemented to 

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ensure that the data collected in this study strictly comply with definitions of deidentified or 
anonymous data:

At any point in this study, only the study team at Duke will have access to the 
patient’s medical record data containing identifiable information. The non-Duke 
study team (ie, RTI-HS and Pfizer) will only have access to the abstracted data.

The DCF will be programmed to calculate and retain the age at nephrectomy, rounded 
down to the integer year level, and the year of nephrectomy in the analytic file that 
will be transferred to RTI-HS for analysis. For example, the Duke researcher will 
enter a patient’s exact date of nephrectomy and exact date of birth into the DCF. The 
DCF will internally calculate the number of days between the two dates (ie, date of 
nephrectomy minus the date of birth) and retain only the date difference, in integer 
years, and the year of nephrectomy in the analytic file.

Exact dates relevant to study endpoints will be collected in the DCF but will not be 
retained in the analytic file or transferred from Duke to RTI-HS. The DCF will 
internally calculate the number of days between two dates (ie, study endpoint date 
minus the index date/date of nephrectomy) and retain only the date difference, in 
days, in the analytic file.
All study data transferred outside of Duke will be coded as a limited data set. This does not 
allow for the sharing of exact dates or other identifiers (such as name, medical record 
numbers, etc.). The risk of a breach of confidentiality is primarily from malicious system 
hacking in the presence of suboptimal network security in the case of electronic data 
collection. Outside of network security risks, identification of a single patient by members of 
the research investigative team, based on a combination of limited demographic information 
and treatment information, would require (in addition to malicious intent) access to all 
medical records and an extraordinary analytic effort, except, perhaps, in the case of 
exceedingly rare conditions, which the current study does not include. Based on the study 
design and data-collection procedures, the study team believes there is only a 
minimal/remote risk of identification of patients.
As stated previously, to protect the rights and freedoms of natural persons with regard to the
processing of personal data, no protected health information will be collected, and thereby,
no data containing patient identifiable information will be transferred to Pfizer.
10.1. Patient Information
All parties will comply with all applicable laws, including laws regarding the implementation 
of organizational and technical measures to ensure protection of patient personal data. Such 
measures will include omitting patient names or other directly identifiable data in any 
reports, publications, or other disclosures, except where required by applicable laws.
The data will be stored at the study site on a secure server and will be password protected to 
ensure that only authorized study staff have access. The study site will implement appropriate 

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technical and organizational measures to ensure that the personal data can be recovered in the 
event of disaster. In the event of a potential personal data breach, the study site shall be 
responsible for determining whether a personal data breach has in fact occurred and, if so, 
providing breach notifications as required by law.
To protect the rights and freedoms of natural persons with regard to the processing of 
personal data, when study data are compiled for transfer to Pfizer and other authorized 
parties, patient names will be removed and will be replaced by a single, specific, numerical 
code, based on a numbering system defined by Pfizer. All other identifiable data transferred 
to Pfizer or other authorized parties will be identified by this single, patient-specific code.
The investigator site will maintain a list of patients who participated in the study, linking 
each patient’s numerical code to his or her actual identity. In case of data transfer, Pfizer will 
maintain high standards of confidentiality and protection of patients’ personal data consistent 
with the study agreement and applicable privacy laws.
10.2. Patient Consent
As this study does not involve data subject to privacy laws according to applicable legal 
requirements, obtaining informed consent from patients by Pfizer is not required.
10.3. Institutional Review Board (IRB)/Independent Ethics Committee (IEC)
There must be prospective approval of the study protocol, protocol amendments, and other 
relevant documents (eg, informed consent forms if applicable) from the relevant IRBs/IECs.
All correspondence with the IRB/IEC must be retained. Copies of IRB/IEC approvals must
be forwarded to Pfizer.
10.4. Ethical Conduct of the Study
The study will be conducted in accordance with legal and regulatory requirements, as well as 
with scientific purpose, value, and rigor, and follow generally accepted research practices 
described in Guidelines for Good Pharmacoepidemiology Practices issued by the 
International Society for Pharmacoepidemiology and Good Practices for Outcomes Research
issued by the International Society for Pharmacoeconomics and Outcomes Research.
This study will be conducted in accordance with the standards for retrospective studies in the 
US. Information describing the deidentified nature of the data will be submitted to RTI’s IRB 
committee for review, requesting classification as a “non-interventional, not human data” 
study. If the IRB classifies the study as such, no additional reviews will be required.
11. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS
The reviewer is obligated to report adverse events (AEs) with explicit attribution to any 
Pfizer drug that appear in the reviewed information (defined per the patient population and 
study period specified in the protocol). Explicit attribution is not inferred by a temporal 
relationship between drug administration and an AE, but must be based on a definite 
statement of causality by a health care provider linking drug administration to the AE.

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The requirements for reporting safety events on the non-interventional study (NIS) adverse 
event monitoring (AEM) Report Form to Pfizer Safety are as follows:

All serious and non-serious AEs with explicit attribution to any Pfizer drug that 
appear in the reviewed information must be recorded on the DCF and reported, within
24 hours of awareness, to Pfizer Safety using the NIS AEM Report Form.

Scenarios involving drug exposure, including exposure during pregnancy, exposure 
during breast feeding, medication error, overdose, misuse, extravasation, lack of 
efficacy, and occupational exposure associated with the use of a Pfizer product must 
be reported, within 24 hours of awareness, to Pfizer Safety using the NIS AEM 
Report Form.
For these AEs with an explicit attribution or scenarios involving exposure to a Pfizer product, 
the safety information identified in the unstructured data reviewed is captured in the Event 
Narrative section of the report form, and constitutes all clinical information known regarding 
these AEs. No follow-up on related AEs will be conducted.
All the demographic fields on the NIS AEM Report Form may not necessarily be completed, 
as the form designates, since not all elements will be available due to privacy concerns with 
the use of secondary data sources. While not all demographic fields will be completed, at the 
very least, at least one patient identifier (eg, sex, age as captured in the narrative field of the 
form) will be reported on the NIS AEM Report Form, thus allowing the report to be 
considered a valid one in accordance with pharmacovigilance legislation. All identifiers will 
be limited to generalities, such as the statement “A 35-year-old female…” or “An elderly 
male…” Other identifiers will have been removed.
Additionally, the onset/start dates and stop dates for “Illness,” “Study Drug,” and “Drug 
Name” may be documented in month/year (mmm/yyyy) format rather than identifying the 
actual date of occurrence within the month/year of occurrence in the day/month/year 
(DD/MMM/YYYY) format.
All research staff members must complete the following Pfizer training requirements:

“YRR Training for Vendors Working on Pfizer Studies (excluding interventional 
clinical studies and non-interventional primary data collection studies with 
sites/investigators).”
These trainings must be completed by research staff members prior to the start of data 
collection. All trainings include a “Confirmation of Training Certificate” (for signature by 
the trainee) as a record of completion of the training, which must be kept in a retrievable 
format. Copies of all signed training certificates must be provided to Pfizer.
Re-training must be completed on an annual basis using the most current Your Reporting 
Responsibilities training materials.

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All necessary trainings for Duke and RTI-HS project staff will be coordinated by RTI-HS.
12. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS
In the event of any prohibition or restriction imposed (eg, clinical hold) by an applicable 
competent authority in any area of the world or if the investigator is aware of any new 
information that might influence the evaluation of the benefits and risks of a Pfizer product, 
Pfizer should be informed immediately.

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13. REFERENCES
1.
Atzpodien J, Schmitt E, Gertenback U, Fornara P, Heynemann H, Maskow A, et al. 
Adjuvant treatment with interleukin-2- and interferon-alpha2a-based 
chemoimmunotherapy in renal cell carcinoma post tumour nephrectomy: results of a 
prospectively randomised trial of the German Cooperative Renal Carcinoma 
Chemoimmunotherapy Group (DGCIN). Br J Cancer. 2005 Mar 14;92(5):843-6.
2.
Breda A, Konijeti R, Lam JS. Patterns of recurrence and surveillance strategies for renal 
cell carcinoma following surgical resection. Expert Rev Anticancer Ther. 2007 
Jun;7(6):847-62.
3.
Clark JI, Atkins MB, Urba WJ, Creech S, Figlin RA, Dutcher JP, et al. Adjuvant high-
dose bolus interleukin-2 for patients with high-risk renal cell carcinoma: a cytokine 
working group randomized trial. J Clin Oncol. 2003 Aug 15;21(16):3133-40.
4.
Frank I, Blute ML, Cheville JC, Lohse CM, Weaver AL, Zincke H. An outcome 
prediction model for patients with clear cell renal cell carcinoma treated with radical 
nephrectomy based on tumor stage, size, grade and necrosis: the SSIGN score. J Urol. 
2002 Dec;168(6):2395-400.
5.
Haas NB, Manola J, Uzzo RG, Flaherty KT, Wood CG, Kane C, et al. Adjuvant 
sunitinib or sorafenib for high-risk, non-metastatic renal-cell carcinoma (ECOG-ACRIN 
E2805): a double-blind, placebo-controlled, randomised, phase 3 trial. Lancet. 
2016 May 14;387(10032):2008-16.
6.
Janzen NK, Kim HL, Figlin RA, Belldegrun AS. Surveillance after radical or partial 
nephrectomy for localized renal cell carcinoma and management of recurrent disease.
Urol Clin North Am. 2003 Nov;30(4):843-52.
7.
Klein JP, Moeschberger ML. Survival analysis: techniques for censored and truncated 
data. Springer Science & Business Media; 2005.
8.
Lam JS, Shvarts O, Leppert JT, Pantuck AJ, Figlin RA, Belldegrun AS. Postoperative 
surveillance protocol for patients with localized and locally advanced renal cell 
carcinoma based on a validated prognostic nomogram and risk group stratification 
system. J Urol. 2005 Aug;174(2):466-72.
9.
Lenis AT, Donin NM, Johnson DC, Faiena I, Salmasi A, Drakaki A, et al. Adjuvant 
therapy for high risk localized kidney cancer: Emerging evidence and future clinical 
trials. J Urol. 2018 Jan;199(1):43-52.
10.
Motzer RJ, Jonasch E, Agarwal N, Bhayani S, Bro WP, Chang SS, et al. Kidney 
Cancer, Version 2.2017, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr 
Canc Netw. 2017;15(6):804-34.

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11.
National Cancer Institute. Cancer stat facts: kidney and renal pelvis cancer. Available at 
https://seer.cancer.gov/statfacts/html/kidrp.html. Accessed 06 February 2018.
12.
Passalacqua R, Caminiti C, Buti S, Porta C, Camisa R, Braglia L, et al. Adjuvant low-
dose interleukin-2 (IL-2) plus interferon-α (IFN-α) in operable renal cell carcinoma 
(RCC): a phase III, randomized, multicentre trial of the Italian Oncology Group for 
Clinical Research (GOIRC). J Immunother. 2014 Nov-Dec;37(9):440-7.
13.
Ravaud A, Motzer RJ, Pandha HS, George DJ, Pantuck AJ, Patel A, et al. Adjuvant 
sunitinib in high-risk renal-cell carcinoma after nephrectomy. N Engl J Med. 2016 Dec 
8;375(23):2246-54.
14.
Zisman A, Pantuck AJ, Dorey F, Said JW, Shvarts O, Quintana D, et al. Improved 
prognostication of renal cell carcinoma using an integrated staging system. J Clin 
Oncol. 2001 Mar 15;19(6):1649-57.
14. LIST OF TABLES
None.
15. LIST OF FIGURES
Figure 1.
Patient Observation Periods......................................................................12
ANNEX 1. LIST OF STAND ALONE DOCUMENTS
None.
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS
Not applicable.
ANNEX 3. ADDITIONAL INFORMATION
Not applicable.