Registry-based Non-interventional Analysis of Advanced/Metastatic Renal Carcinoma Treatment Patterns and Outcomes in the Hospital District of Southwest Finland.
Conditions: Renal Cell Cancer, Renal Cell Carcinoma, Cancer of Kidney, Cancer of the Kidney, Kidney Cancer, Kidney Neoplasms, Renal Cancer
Sponsor: Pfizer

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NON-INTERVENTIONAL (NI) STUDY PROTOCOL 
Study information 
Title 
Registry-based non-interventional analysis 
of advanced/metastatic renal carcinoma 
treatment patterns and outcomes in the 
Hospital district of Southwest Finland. 
Protocol number 
A4061098 
Protocol version identifier 
Version 1 
Date 
28 March 2022 
Active substance 
axitinib, ATC-code L01EK01 (previously 
L01XE17) 
sunitinib, ATC-code L01EX01 (previously 
L01XE04) 
Medicinal product 
Inlyta; Sutent 
Research question and objectives 
The aim of the study is to describe the 
characteristics, 
treatment 
pattern 
and 
outcomes 
of 
patients 
with 
advanced/metastatic renal cell carcinoma 
(RCC) with medical records in the HDSF data 
lake. The treatment sequence of mRCC 
patients and treatment outcomes (overall 
survival, time-to-next treatment) will be 
analysed with regard to individual risk score 
of the patient and over time. In addition, co-
morbidities, procedures and healthcare usage 
will be analyzed. As an exploratory objective, 
the coding practices especially with regard to 
risk score calculation are assessed. 
Author 
, PhD, 
 
 
email: 
  
tel. 
 
PPD
PPD
PPD
PPD

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TABLE OF CONTENTS 
1. TABLE OF CONTENTS .......................................................................................................2 
2. LIST OF ABBREVIATIONS ................................................................................................4 
3. RESPONSIBLE PARTIES ....................................................................................................5 
4. AMENDMENTS AND UPDATES .......................................................................................6 
5. MILESTONES .......................................................................................................................7 
6. RATIONALE AND BACKGROUND ..................................................................................7 
7. RESEARCH QUESTION AND OBJECTIVES ...................................................................9 
7.1. Primary objectives .....................................................................................................9 
7.2. Secondary objectives .................................................................................................9 
7.3. Exploratory objective ..............................................................................................10 
8. RESEARCH METHODS ....................................................................................................11 
8.1. Study design ............................................................................................................11 
8.2. Setting ......................................................................................................................11 
8.2.1. Inclusion criteria .........................................................................................12 
8.2.2. Exclusion criteria ........................................................................................13 
8.2.3. Patient stratification ....................................................................................13 
8.3. Variables ..................................................................................................................14 
8.4. Data sources ............................................................................................................16 
8.5. Study size ................................................................................................................17 
8.6. Data management ....................................................................................................17 
8.7. Data analysis ...........................................................................................................18 
8.7.1. Patient characteristics .................................................................................18 
8.7.2. Treatment patterns and treatment lines .......................................................19 
8.7.3. Treatment outcomes ....................................................................................20 
8.7.4. Morbidity ....................................................................................................21 
8.7.5. Healthcare resource utilization ...................................................................21 
8.7.6. Changes in coding practices over time .......................................................22 
8.8. Quality control .........................................................................................................22 
8.9. Limitations of the research methods .......................................................................22 
8.10. Other aspects .........................................................................................................23 

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9. PROTECTION OF HUMAN SUBJECTS ..........................................................................23 
9.1. Patient information ..................................................................................................23 
9.2. Patient consent .........................................................................................................23 
9.3. Institutional review board (IRB)/Independent ethics committee (IEC) ..................23 
9.4. Ethical conduct of the study ....................................................................................23 
10. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS ......................................................................................................................23 
11. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS........24 
12. REFERENCES ..................................................................................................................24 
13. LIST OF TABLES .............................................................................................................25 
14. LIST OF FIGURES ...........................................................................................................25 
ANNEX 1. LIST OF STAND ALONE DOCUMENTS .........................................................25 
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS .........................................25 
ANNEX 3. ADDITIONAL INFORMATION .........................................................................25 
 

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1. LIST OF ABBREVIATIONS 
Abbreviation Definition 
AJCC 
American Joint Committee on Cancer 
ATC 
Anatomic therapeutic chemical classification system 
BMI 
Body mass index 
HCRU 
Healthcare resource utilization 
HDSF 
Hospital District of Southwest Finland 
HTA 
Health Technology Assessment 
ICD-10 
International Classification of Diseases 10th revision 
ICMJE 
International Committee of Medical Journal Editors 
IMDC 
International Metastatic RCC Database Consortium 
LOT 
Line of treatment 
mRCC 
(Advanced/)metastatic RCC 
OS 
Overall survival 
PFS 
Progression free survival 
PO 
Primary objective 
RCC 
Renal cell carcinoma 
RWE 
Real-world evidence 
RWD 
Real-world data 
SAP 
Statistical analysis plan 
SO 
Secundary objective 
SoC 
Standard-of-Care 
TKI 
Tyrosine kinase inhibitor 
TNM 
Tumor – Node – Metastasis (classification of malignant tumors) 
TTNT 
Time to next treatment  
VEGFR 
Vascular endothelial growth factor receptor 
 

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2. RESPONSIBLE PARTIES 
Principal Investigator(s) of the Protocol 
Name, degree(s) 
Job Title 
Affiliation 
Address 
, PhD 
 
 
 
 
 
, PhD 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
, PhD 
 
 
 
 
, DI 
 
 
 
 
, TkK 
 
 
 
 
, PhD 
 
 
 
 
 
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD
PPD

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3. AMENDMENTS AND UPDATES 
 
None. 

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4. MILESTONES 
Milestone 
Planned date 
Auria permission and start of data collection  
01-May-2022 
End of data collection  
31-May-2022 
The following milestones are dependent on data set completion 
date. The planned dates have been estimated based on data 
completion by the end of May 2022: 
 
Data analyses  
01 September 2022  
Final study report 
01-Nov-2022  
Publication submission 
To be determined 
 
5. RATIONALE AND BACKGROUND 
Renal cell carcinoma (RCC) is among the 10 most frequently occurring cancers and the most 
common type of kidney cancer occurring in Western communities [1]. RCCs comprise a 
heterogeneous group of malignant neoplasms arising from the nephron. Risk factors for RCC 
include obesity, hypertension, cigarette smoking, diet, diabetes, and male gender [1]. 
After decades of increasing trends in RCC incidence and mortality rates, it seems that rates are 
stabilising or starting to decline in many Western countries [1]. The worldwide number of 
kidney cancer cases was 431,288 (62.9% male) and deaths 179,368 (64.4% male) in 2020 [2]. 
Kidney cancer is more common in males compared to females. The incidence was 7.8 and 
mortality 3.0 per 100,000 males in high human development index countries in 2020 [2]. In 
Finland, the number of new kidney cancer cases was 635 in males and 353 in females in 2019 
[3], and the number of prevalent patients was 4,943 males and 3,867 females in 2019 according 
to the Finnish Cancer Registry [4]. 
Localized RCC can be curatively treated with nephrectomy. However, about 20–30% of 
patients present with metastatic RCC (mRCC) at the time of diagnosis [5]. In addition, another 
20% of patients with localized RCC undergoing nephrectomy will have a relapse and develop 
mRCC during follow-up. Despite the recent advances in mRCC treatment, metastatic disease 
is often fatal [6]. 
Over the last decade, the treatment of advanced/metastatic RCC has been constantly evolving, 
especially in the last 2-3 years with the emergence of several novel treatment options in rapid 
succession. Current recommendations for first-line therapy of mRCC include several 
combination treatments, superseding the previously recommended antiangiogenic agent 
monotherapies. The novel options combine an anti-PD-1-antibody with either an 
antiangiogenic drug (vascular endothelial growth factor receptor (VEGFR)) tyrosine kinase 
inhibitor (TKI)), or an anti-CTLA-4-antibody. The combination treatments are recommended 

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variably according to the patient’s IMDC (International mRCC Database Consortium) risk 
score. IMDC represents a large collection of real-world data (RWD) on patients with advanced 
kidney cancer treated with targeted therapies [7,8]. IMDC combinations available for 
favourable risk patients include pembrolizumab + axitinib, nivolumab + cabozantinib and 
pembrolizumab + lenvatinib; for intermediate or poor risk patients the combination of 
ipilimumab and nivolumab is recommended in addition to the aforementioned three 
combinations. None of the recommended first-line treatment options have been compared 
head-to-head but all of the pivotal clinical studies have sunitinib monotherapy as a control, a 
former standard-of-care (SoC). The current second and later line treatment recommendations 
include VEGFR-TKI monotherapies, such as pazopanib and sunitinib, but will likely be 
reshaped in the coming years as clinical evidence on the optimal treatment sequence is 
accumulated.  
The prognostic model constructed by the IMDC has been used to stratify patients in 
contemporary clinical trials and to provide risk-directed treatment selection in everyday 
clinical practice. The IMDC prognostic model contains six independent predictors of poor 
survival, which are: Karnofsky performance status of less than 80%, less than 1 year from 
diagnosis to treatment, anaemia (haemoglobin concentration <lower limit of normal), 
hypercalcaemia (corrected calcium concentration >upper limit of normal), neutrophilia 
(neutrophil count >upper limit of normal), and thrombocytosis (platelet count >upper limit of 
normal). An IMDC risk score is determined for a patient according to the number of poor 
prognostic factors the patient has; favourable risk patients have 0 factors;  intermediate risk 
patients have one or two factors;  and poor risk patients have three or more factors. 
In Finland, the mRCC treatment landscape has been shaped by the access and reimbursement 
status of medications. Here, publicly funded medicines are processed via two different access 
and reimbursement processes based on the route of administration: outpatient or oral medicines 
(patient acquires medicine with a prescription from the pharmacy) and hospital medicines 
(medicines administered at hospital, mainly intravenous medicines).For oral medicines, the 
Finnish Social Insurance Institution (Kela) reimburses the patient for the costs of outpatient 
medicines if the Pharmaceuticals Pricing Board (Hila) has confirmed the reimbursement of the 
medicine. For oral drugs, the marketing authorization holder is responsible for applying for 
reimbursement. The Finnish Medicines Agency (Fimea) is the national competent authority 
for regulating pharmaceuticals. Fimea is responsible for initiating the evaluation of hospital 
medicines to be used in Finland, and makes the initial health technology assessment (HTA). 
This HTA-evaluation is not made automatically for all new pharmacotherapies or indication 
extensions, but at the discretion of Fimea. Hospital medicines assessed by Fimea are further 
assessed by the Council for Choices in Health Care in Finland (COHERE Finland) to issue 
recommendations on services that should be included in the selection of public health services. 
Hospital medicines are paid by the municipalities that fund the hospital districts. The use of 
hospital medicines and prices may also vary greatly from region to region. Use of combination 
treatments is often problematic due to the Finnish reimbursement system because the 
combination partners may fall under different processes (eg. a combination of an oral drug and 
an intravenously administered drug).  

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Finland has equal healthcare which is primarily funded by taxation. Thus, all permanent 
residents in Finland are entitled to public healthcare at a uniform level regardless of their 
financial situation. Finnish registries cover all individuals living in Finland and no patients are 
excluded from our study based on their social status or financial capability. In addition, health 
record data available via data lake technology enable extraction and analysis of large data sets 
including RWD on disease-related clinical and molecular characteristics and a number of 
medical procedures. Data for this study will be retrieved from the data lake of the Hospital 
District of Southwest Finland (HDSF). With a total of 470,000 residents and about 200,000 
patients each year, HDSF is one of the biggest hospital districts in Finland. 
The aim of this retrospective study is to investigate treatment patterns and outcomes of patients 
with advanced/metastatic RCC treated at the HDSF. In this protocol, mRCC refers to advanced 
and/or metastatic RCC. In addition, coding practices of related data and characteristics of all 
RCC patients will be reported. To our knowledge, this will be the first study to utilize regional 
Finnish data to characterize RCC patients, and investigate the treatment of the mRCC patient 
population. The resulting real-world evidence (RWE) is likely to be of interest for the national 
and global RCC scientific communities.  
 
6. RESEARCH QUESTION AND OBJECTIVES 
The objective of this study is to describe the characteristics and treatment outcomes of patients 
with advanced/metastatic RCC with medical records in the HDSF data lake. In the first primary 
objective, all RCC patients (with local or metastatic disease) are analyzed (treated and non-
treated mRCC patients separately). In all other objectives, only treated mRCC patients will be 
analyzed. The objectives of the study are to: 
6.1. Primary objectives 
1. Characterize patients with RCC and with advanced/metastatic RCC (treated and non-
treated separately) including e.g. demographics and IMDC risk score.  
2. Define treatment patterns and treatment sequences in mRCC. 
3. Assess outcomes by treatment line and from diagnosis 
a. Progression free survival (via proxies such as time-to-next treatment)  
b. Overall survival 
i. time to event analyses  
ii. Cox models  
6.2. Secondary objectives 
1. Assess morbidity of metastatic RCC including 
a. co-diagnoses and procedures  
b. infections and antibiotic use  
c. antihypertensive use before and after mRCC diagnosis, as applicable  

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2. Assess speciality care healthcare resource use (absolute, per patient, per patient year) 
a. cumulatively over time from diagnosis  
b. by treatment line  
6.3. Exploratory objective 
1. Assess changes in coding practices over time, specifically IMDC risk score 
a. including but not limited to changes in structured IMDC score recordings and 
the use of metastatic ICD-10 diagnosis codes (C77-C79) 
 
 

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7. RESEARCH METHODS  
7.1. Study design  
This is a retrospective registry-based cohort investigation, utilizing existing data generated 
during routine clinical practice and available in the Hospital District of Southwest Finland 
HDSF data lake. All adult patients (age ≥18 years) with RCC diagnosis (C64*; ‘*’ indicates 
any number) will be identified from the data lake of HDSF. 
The main purpose of this study is to characterize the patient population of advanced/metastatic 
RCC, and their treatment patterns and treatment outcomes using medical records retrieved 
from HDSF data lake. The main patient stratification will be the IMDC risk category (see 8.2.3 
Patient stratification). Patients with unknown risk score will be analyzed as an own patient 
group.   
7.2. Setting 
The target population of this study is adult patients with RCC and medical records available at 
HDSF data lake. Estimated number of patients in this study is 220-550. The inclusion criteria 
is a diagnosis of renal cell carcinoma (ICD-10: C64) between January 2010 and December 
2021 (Figure 1). Advanced/metastatic disease stage (mRCC) will be assessed based on ICD-
10 diagnosis code for metastasis (C77*-C79*), American Joint Committee on Cancer (AJCC) 
stage 4, visit to oncologist (specialty code 65), or initiation of treatment for mRCC. 
 
Figure 1. Graphical illustration of study time windows and corresponding analyses. 
The data collected has been generated as part of standard clinical care, treatment, and follow-
up of patients with RCC. In accordance with the Finnish Act on Secondary Use of Health and 
Social Data 552/2019 (in Finnish: Laki sosiaali- ja terveystietojen toissijaisesta käytöstä), 
health registry data can be processed in scientific studies without patient consent. The purpose 
of this act is to establish conditions for the effective and secure processing of, and access to, 
personal health and social data for certain secondary purposes, such as research and statistics, 
innovation and development, knowledge management, teaching and authority planning. Thus, 
the Secondary Act creates a clear legal basis for the use of such registered data for research 
and innovation related to, for example, the health and well-being of citizens, the prevention of 

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disease and the development of new treatment methods. This relatively new legislation is also 
a welcome unification of the fragmented Finnish national rules regarding the use of healthcare 
and social welfare data. In addition, it takes into consideration current data protection 
requirements. 
In the primary objective 1 (characteristics), all RCC patients will be analysed (local and 
metastatic diseases separately), while in the other objectives only treated mRCC patients will 
be analysed. Therefore, there are two cohorts to be analysed: 1) characteristics cohort 
(including all RCC patients), 2) mRCC cohort (including only treated mRCC patients).  
Definitions for mRCC cohort 
Index: Date of the first mRCC diagnosis; date of the metastatic disease identified as first of the 
following after the initial RCC diagnosis 
- 
ICD-10 diagnosis code (C77*-C79*) for metastatic disease 
- 
AJCC stage 4 
- 
Visit to oncologist (specialty code 65) with RCC as main diagnosis 
- 
Treatment initiation for mRCC (sunitinib, pazopanib, cabozantinib, ipilimumab, 
nivolumab) 
When analyzing the treatment outcomes, index is defined as the date of the treatment initiation. 
End of follow-up (whichever of the following occurs first):  
- 
Death 
- 
Moving outside of HDSF 
• Approximated using data of healthcare contacts; no contacts to specialty care 
of HDSF within 2 years (patient censored at the last recorded visit) 
- 
End of study (31.12.2021) 
Length of follow-up (in years): (‘end of follow-up’ – ‘index’ + 1)/365.25 
Definitions for characteristics cohort 
Index: 
- 
For mRCC patients, same as for the mRCC cohort (i.e. approximated metastasis date) 
- 
For RCC patients, the date of the first record of RCC diagnosis (ICD-10: C64) 
 
7.2.1. Inclusion criteria 
For the characteristics cohort, patients must meet all of the following inclusion criteria to be 
eligible for inclusion: 
- 
Diagnosis of renal cell carcinoma (ICD-10: C64) during 1.1.2010-31.12.2021 
- 
Age at least 18 years at index. 
- 
Resident of HDSF at index. 

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For the mRCC cohort, patients must meet the following inclusion criteria in addition to the 
above criteria to be eligible for inclusion: 
- 
metastatic RCC during 1.1.2010-31.12.2021; defined as 
• ICD-10 diagnosis code for metastasis (C77*-C79*), or 
• AJCC stage 4, or 
 AJCC stage data potentially not available for all patients  
• a visit to oncologist (specialty code 65) with RCC as main diagnosis, or 
 In Finland, the ICD-10 codes for metastatic disease are rarely used. 
In contrast, RCC patients visit oncologist, when and only when 
disease metastasises and therefore, the visit can be used as a proxy 
to a metastatic disease.  
• initiation of treatment for mRCC 
 
7.2.2. Exclusion criteria 
For the characteristics cohort, patients meeting any of the following criteria will be 
excluded from the study: 
- 
Prevalent mRCC patients (i.e. diagnosis of metastatic RCC before 1.1.2010)  
- 
Prevalent RCC patients (i.e. diagnosis of RCC before 1.1.2010) if there is no records of 
metastatic disease during 2010-2021 
For the mRCC cohort, patients meeting any of the following criteria will be excluded from 
the study: 
- 
Prevalent patients with mRCC (i.e. diagnosis of metastatic RCC before 1.1.2010) 
• Note that patients with local RCC before 2010 are included in this study if 
the disease has metastasised during 2010-2021 
- 
Patients without treatment for mRCC (see Table 3 for details) 
7.2.3. Patient stratification 
Analyses will be stratified by: 
- 
IMDC risk category (defined at the initiation of the first treatment for the metastatic 
RCC; see Table 1 and listing below for definitions) 
• Applied to all primary and secondary objectives 
- 
Treatment line 
• Applied to primary objective 2 and 3 
 
IMDC risk factors (each criterion accounts for +1 for the risk score): 
1. Less than a year from time of initial RCC diagnosis to initiation of treatment for the 
metastatic RCC 

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2. Performance status* <80% (Karnofsky) 
3. Hemoglobin* below normal (women < 117 g/l; men < 134 g/l) 
4. Serum calcium* above normal (> 2.51 mmol/l) 
5. Neutrophiles* above normal (> 6.3 x 109/l) 
6. Thrombocytes* above normal (> 350 x 109/l) 
* for performance status and laboratory values data of ± 3 months around the treatment 
initiation will be utilized due to possibly sprase data. If multiple records are available, the 
record closest to the treatment initiation will be utilized. 
Table 1. IMDC risk scores and categories based on two different approaches depending on 
the data coverage 
 
IMDC risk category 
Total score of 
IMDC risk 
factors 
Explanations/missing values 
Option 1* 
Favorable risk 
0 
no missing values allowed 
Intermediate risk 
1-2 
1) total score = 1; max 1 risk factor allowed 
to have missing value 
2) total score = 2; no missing values allowed 
Poor risk 
3 or more 
max 3 risk factors allowed to have missing 
values 
Unknown risk** 
-  
when none of the above risk categories can 
be assigned 
Option 2* 
Appear favorable  
0  
all non-missing values for the risk factors 
indicate favorable risk 
 
max 3 risk factors allowed to have missing 
values 
At least intermediate  
≥1 
at least one risk factor criterion is met 
 
max 3 risk factors allowed to have missing 
values 
Poor 
≥3 
at least three risk factor criteria is met 
 
max 3 risk factors allowed to have missing 
values 
Unknown** 
- 
when none of the above risk categories can 
be assigned, i.e. more than 3 risk factors have 
missing value 
* If small number of missing values is observed, the option 1 will be selected. If large number 
of missing values is observed and thus majority of patients were to belong to the “unknown” 
group of the option 1, the option 2 will be selected. The selection will be done after the data 
release and monitoring of data coverage.  
** Patients with unknown risk category, will be analysed as own patient group. 
 
7.3. Variables 
Source for all variables is the data lake of HDSF. 

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Table 2. List of study variables. Abbreviations: PO=primary objective, SO=secondary 
objective. 
Variable 
Role/Relevant objective 
Operational definition 
ICD-10 diagnoses; RCC 
diagnoses 
Patient inclusion/exclusion  
IMDC risk category 
yes/no 
ICD-10 diagnoses: co-diagnoses 
(e.g. renal insufficiency and 
hypertension) 
PO1, SO1 
yes/no; codiagnoses before and 
after index 
Date of birth 
Patient inclusion 
PO1 
Date; age defined at index based on 
birth date 
Date of death 
End of follow-up 
PO3 
Date 
Gender 
PO1 
Female/male 
Home municipality 
Patient inclusion 
End of follow-up 
Home municipality at each 
healtcare contact 
Weight 
PO1 
kg 
Height 
PO1 
m 
Body mass index (BMI) 
PO1 
derived from weight and height 
Smoking status (if available in 
structured format) 
PO1 
yes/no 
Outpatient visits (including 
emergency room visits) 
Patient inclusion and index 
definition (visits to 
oncologist) 
SO2 
Date, physician’s specialty, type of 
arrival  
Hospitalizations 
SO2 
Start and end dates 
Procedures and operations 
(including nephrectomy) 
PO1 
SO1 
SO2 
Procedure code, date 
Medical imaging 
SO1 
SO2 
Imaging code, date 
Medications; including 
- 
hospital medications 
- 
prescriptions 
Patient inclusion/exclusion 
and index definition 
PO2 
PO3 
SO1 
SO2 
Dates, ATC-codes, active 
substance 
Laboratory testing 
IMDC risk category  
PO1 
Dates, test id, result 
Zubrod/ECOG performance status 
IMDC risk category 
PO1 
scale 0-5; converted to Karnofsky 
PAD histology (if available in 
structured format) 
PO1 
 
Staging of RCC, the tumor-node-
metastasis (TNM) classification 
Patient inclusion and index 
definition 
PO1 
scale 1-4 (stages) 
 

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Table 3. List of medications for RCC treatment. ATC= Anatomical Therapeutic 
Chemical. 
Active substance 
Brand name 
ATC-code at the 
moment in use  
ATC-code 
previously in use 
Oral medications 
axitinib 
Inlyta 
L01EK01 
L01XE17 
everolimus 
Afinitor 
L01EG02 
L01XE10 
cabozantinib 
Cabometyx 
L01EX07 
L01XE26 
pazopanib 
Votrient 
L01EX03 
L01XE11 
sorafenib 
Nexavar 
L01EX02 
L01XE05 
sunitinib 
Sutent 
L01EX01 
L01XE04 
Intravenous 
medications 
ipilimumab 
Yervoy 
L01XC11 
  
nivolumab 
Opdivo 
L01XC17 
  
 
7.4. Data sources  
Cohort and data set formation overview is presented in Figure 2. The patient population will 
be selected from the health records at the data lake of HDSF based on diagnosis data and 
includes a personal identity code that is unique for every individual in Finland. For the 
identified RCC cohort, data of patient characteristics, diagnoses, healthcare contacts, 
treatments, laboratory and pathology tests, and performed procedures, operations and imagings 
will be collected from the same data lake of HDSF. The identification of the RCC cohort and 
collection of the additional data with personal identification numbers will be handled solely by 
the personnel of Auria Clinical Informatics. The identification codes are removed after linkage 
so that only pseudonymized data or group specific summary data is provided for analyses. 
This study is conducted using existing and available clinical electronic records accessible from 
Auria Clinical Informatics. The study protocol and associated data request for all data will 
therefore be submitted to Auria Clinical Informatics for approval.  
 

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Figure 2. Overview of cohorts and data set formation. 
 
7.5. Study size 
The expected number of patients eligible for this study is approximated based on publicly 
available data from the Finnish Cancer registry (https://syoparekisteri.fi/tilastot/tautitilastot/): 
- 
 In HDSF, there have been approximately 1,100 RCC patients during 2010-2021. 
- 
20-50% of RCC patients develop advanced/metastatic disease [9] and therefore, the 
size of mRCC-patient cohort is approximately 220-550 patients. 
7.6. Data management  
All data collection, storage and handling will be coordinated by Auria Clinical Informatics. 
Auria Clinical Informatics collects the required data, pseudonymizes the IDs and releases the 
row level pseudonymized data to a secure analysis environment maintained by Auria Clinical 

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Informatics. All data-analyses will be performed by the Medaffcon Oy analytics team in the 
secure analysis environment using the statistical software R (version 3.6.1. or higher). No 
patient level data will be transferred outside of this system. Only aggregate level and/or fully 
anonymous data and/or summary statistics may be transferred outside this system for reporting 
and publication purposes. Thus, individual patients cannot be identified from this data set. 
7.7. Data analysis  
Data will be analyzed using primarily descriptive measures, which include mean/median 
values for continuous variables and proportions for categorical variables. Costs will be 
estimated using data of visits, hospitalizations, procedures, etc. and utilizing publicly available 
price listings.  For treatment outcomes, Kaplan-Meier estimates and/or corresponding time to 
event competing risk models will be utilized. 
All analyses will be reported for the whole advanced/metastatic RCC patient population and 
stratified by the IMDC risk score. Additionally, treatment patterns and treatment outcomes will 
be reported by treatment lines.  
Analyses are based on structured data, with the exception for potential text-mining of IMDC 
risk score or its components. 
Due to the retrospective nature of the study, missing and/or incomplete data is expected in 
some of the medical records. Patients’ records will not be excluded because of missing values, 
and missing data will not be imputed, i.e. the data will be analyzed as they are recorded in the 
electronic medical records. The proportion of missing values per variable will be reported. 
Analyses will be performed using R, a language and environment for statistical computing, in 
Rstudio-server environment. 
7.7.1. Patient characteristics 
Primary objective 1: 
Demographical and clinical variables of RCC and mRCC patients will be summarized at index. 
Treated and non-treated mRCC patients will be analysed separately. For laboratory measures 
and performance status, the closest available measure +/- 90 days from index will be utilized. 
In case of a high rate of missing values, the time window can be extended to 6 months.  
The demographical and clinical variables include but are not limited to: 
- 
age at index 
- 
sex 
- 
history of renal insufficiency (any records until index) 
• ICD-10 code: N17-N19 
- 
history of dialysis (any records until index) 
• procedure codes: TK800, TK829, TK810,  
• ICD-10 code: Z49 

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- 
history of kidney transplant (any records until index) 
• procedure codes: KAS10, KAS20  
• ICD-10 code: Z94.0 
- 
history of nephroctomy (any records until index) 
• procedure codes: KAC*, KAD*, KAS40, KAS41 
• ICD-10 code: Z90.5 
- 
performance status at index 
• Karnofsky (converted from Zubrod/ECOG) 
- 
time from initial diagnosis of RCC to initiation of treatment for metastatic RCC 
- 
various laboratory measures (e.g. hemoglobin, serum calcium, neutrophiles, 
thrombocytes, creatinine, albumin, eGFR) 
- 
smoking status (if available in structured format) 
- 
histology (if available in structured format) 
- 
BMI (if available in structured format) 
  
For categorical variables, the number (N) and the proportion (%) of patients in each class will 
be reported. For continuous normally distributed variables, mean and standard deviation (SD) 
will be reported. For continuous, non-normally distributed variables, median, the 1st quartile 
and the 3rd quartile will be reported.  
The difference between strata will be tested using chi-squared/Fisher’s exact test (categorical 
variables), t-test (continuous normally distributed variables) and Kruskal-Wallis test 
(continuous non-normally distributed variables).  
7.7.2. Treatment patterns and treatment lines 
Primary objective 2: 
The treatment lines will be defined using drug administration and prescription data. The 
treatment options and lines will be visualized using Sankey plots and the proportion of patients 
per treatment type will be reported. 
In general in mRCC, line of treatment (LOT) changes when the active substance changes, as 
the treatments are mainly monotherapies and only a few options consist of two substances (e.g. 
combination of ipilimumab and nivolumab in 1L).  
The treatment lines will be defined post hoc using following process: 
- 
For each active substance, single administrations/prescriptions are merged to 
treatment continuums. 
- 
To identify, whether the treatment is monotherapy or combination of two active 
substances, the first records of the active substances will be considered 

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• if the first records of the two active substances are within 28 days, the treatment is 
considered as combination therapy of these two medications 
• otherwise the two active substances are considered as two separate treatment lines 
- 
The initiation of the treatment line is defined as the date of first record (dosing or 
prescription) of the active substance. 
7.7.3. Treatment outcomes 
Primary objective 3: 
The treatment outcomes will be assessed using time-to-event analysis, namely Kaplan-Meier 
fit or other relevant competing risk models. For each outcome, the time will be defined as 
follows (Figure 3): 
 
- 
overall survival:  
• time from index until death (event) or end of study (censoring event) 
o when analysing by treatment lines, start the time from initiation of each 
treatment line 
- 
progression free survival (PFS, defined using time to next treatment (TTNT) proxy):  
• time from initiation of the current treatment line until the initiation of the next 
treatment line (event), death (competing risk/event), or end of study (censoring 
event) 
 
The Kaplan-Meier fits will be visualized, and the median survival/PFS of the patients will be 
reported as well, if reached. 
 
Additionally, corresponding Cox proportional-hazards model will be fitted, including clinical 
variables as covariates (including but not limited to age, sex, IMDC risk score, diagnosis year, 
and treatment line number). The hazard ratios, 95% confidence intervals and p-values 
corresponding to each covariate will be reported. 
 
Figure 3. Graphical illustration of definitions of treatment outcomes. Abbreviations: LOT = 
line of treatment. 
 

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7.7.4. Morbidity 
Secondary objective 1: 
Morbidity will be assessed using data of co-diagnoses, procedures, and medications before 
and after diagnosis of advanced/metastatic RCC using all available data (ICD-10, procedure 
codes, and ATC-codes) in baseline and during the follow-up, respectively. The number (N) 
and proportion (%) of patients with each morbidity will be reported. 
The list of morbidities of interest are: 
• co-diagnoses using ICD-10 codes 
o especially interest of infections (ICD-10: A00*-B99*) and hypertension (ICD-
10: I10) 
• procedures related to kidneys  
o all KA* (kidneys and pelvis of kidneys) and KA_* (diagnostic radiology of 
kidney and pelvis of kidneys) procedures codes  
• use of antibiotics (ATC-code: J01*, J02* and J04*) and antihypertensive medication 
(ATC-code: C02*) 
If data coverage seems low, use of antibiotics and antihypertensives can be used as a proxy 
for infections and hypertension, respectively, along with the diagnosis (ICD-10) data. 
Therefore, diagnoses and medications will be analyzed as a combination instead of 
separately.  
7.7.5. Healthcare resource utilization 
Secondary objective 2: 
Healthcare resource utilization (HCRU) will be defined as number of outpatient clinic visits, 
ER visits, hospitalizations, hospital inpatient days, performed procedures, operations, 
imaging, and laboratory tests. The price will be evaluated for each entry using publicly 
available price listings. 
The absolute number of each HCRU type and the absolute costs associated will be reported. 
Additionally, the estimates will be scaled to “per-patient” estimates (by dividing the absolute 
estimates with the number of contributing patients) and to “per patient year” estimates (by 
dividing the absolute estimates by the number of contributing patient years). 
Additionally, assess the HCRU cumulatively over time, i.e. annual costs per patient during 
the first 5 years from index, each year separately (i.e., the costs during the first year after the 
diagnosis of advanced/metastatic RCC, during the second year, etc).  

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No statistical testing for difference between groups will be performed and estimates will be 
descriptive in nature. However 95% confidence intervals (CI) for the estimates will be 
derived using bootstrapping over patients.  
7.7.6. Changes in coding practices over time 
Exploratory objective 1: 
Assess changes in coding practices as a proportion of patients with data available respect to 
the diagnosis year of advanced/metastatic RCC. Variables of interest include but are not 
limited to 
• structured IMDC risk score 
• ICD-10 diagnosis for metastatic disease (C77*-C79*) 
Other aspects of changes in coding practices may also be analyzed, if reasonable. 
7.8. Quality control 
Internal quality will be assured by consulting a clinical expert on data integrity, clinical 
relevance, and plausibility of the results. 
A quality control will be performed, whereby all data will be sanity checked by the allocated 
data scientist(s). This control includes e.g. data coverages, number of individuals and data 
rows, changes as a function of time and checks for systematic gaps on data coverage and 
outliers in the data. Additionally, all the results will be sanity checked with a clinical expert 
and study team for plausibility and clinical relevance, and especially in case of unexpected 
results, both analytical methods and data will be discussed and validated with the whole 
Medaffcon analytics team. 
All R scripts to process and analyze the data will be saved, and there is version control and 
external back-ups for the scripts. At the end of the study, all scripts will be archived to assure 
analysis reproducibility, and plausible later audits (by client and/or from scientific publication 
side). 
7.9. Limitations of the research methods 
All the data is recorded by the hospital during everyday practice and most of the data is stored 
in structured format. Therefore, rather high quality of the data is expected. However, as with 
all RWD, it is plausible to have erroneous entries. Also due to the retrospective nature of the 
study, missing and/or incomplete data is expected in some of the medical records. Patients’ 
records will not be excluded because of missing values, and missing data will not be imputed, 
i.e. the data will be analyzed as they are recorded in the electronic medical records. The 
proportion of missing values per variable will be reported.  

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The treatment lines will be defined based on the medication data and therefore, 
misclassification of treatment lines is possible. However, the start and end dates of each main 
drug are expected to be recorded rather precisely, and the clinician 
 will be 
consulted when constructing the treatment lines. Thus, the majority of the treatment lines are 
expected to be defined correctly.  
7.10. Other aspects 
Not applicable. 
8. PROTECTION OF HUMAN SUBJECTS 
8.1. Patient information  
This study involves data that exist in anonymized structural or non-structural format and 
contain no patient personal information.  
8.2. Patient consent 
As this study involves anonymized structural data, which according to applicable legal 
requirements do not contain data subject to privacy laws, obtaining informed consent from 
patients by Pfizer is not required. 
8.3. Institutional review board (IRB)/Independent ethics committee (IEC) 
Per the Act on Secondary Use of Health and Social Data 552/2019 (in Finnish: Laki sosiaali- 
ja terveystietojen toissijaisesta käytöstä), no institutional review board or independent ethics 
committee for this retrospective registry study is required. 
8.4. Ethical conduct of the study 
Per the Act on Secondary Use of Health and Social Data 552/2019 (in Finnish: Laki sosiaali- 
ja terveystietojen toissijaisesta käytöstä), no ethical approval for this retrospective registry 
study is required. This study protocol will be evaluated and approved by the Auria Clinical 
Informatics before any activities.  
The study will be conducted in accordance with legal and regulatory requirements, as well as 
with scientific purpose, value and rigor and will follow generally accepted research practices 
described in the Guidelines for Good Pharmacoepidemiology Practices (GPP) [10].  
9. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS  
This study involves data that exist as structured data by the time of study start or a 
combination of existing structured data and unstructured data, which will be converted to 
structured form during the implementation of the protocol solely by a computer using 
automated/algorithmic methods, such as natural language processing. 
PPD

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In these data sources, individual patient data are not retrieved or validated, and it is not 
possible to link (ie, identify a potential association between) a particular product and medical 
event for any individual. Thus, the minimum criteria for reporting an adverse event (AE) 
(i.e., identifiable patient, identifiable reporter, a suspect product, and event) cannot be met. 
10. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS 
The detailed results obtained from this study will be available upon publication. Research 
results from this study will be published in peer reviewed scientific journals and/or 
international scientific congresses. The Authorship of any publications resulting from this 
study will be determined based on the International Committee of Medical Journal Editors 
(ICMJE) Recommendations for the Conduct, Reporting, Editing and Publication of Scholarly 
Work in Medical Journals. 
In the event of any prohibition or restriction imposed (e.g., clinical hold) by an applicable 
competent authority in any area of the world, or if the party responsible for collecting data 
from the participant is aware of any new information which might influence the evaluation of 
the benefits and risks of a Pfizer product, Pfizer should be informed immediately.   
11. REFERENCES 
[1] Ljungberg B, Campbell SC, Cho HY, Jacqmin D, Lee JE, Weikert S, et al. The 
Epidemiology of Renal Cell Carcinoma. European Urology 2011;60:615–21. 
https://doi.org/10.1016/j.eururo.2011.06.049. 
[2] Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global 
Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide 
for 36 Cancers in 185 Countries. CA A Cancer J Clin 2021;71:209–49. 
https://doi.org/10.3322/caac.21660. 
[3] Pitkäniemi J, Malila N, Tanskanen T, Degerlund H, Heikkinen S, Seppä K. Syöpä 2019. 
Tilastoraportti Suomen syöpätilanteesta. Helsinki: Suomen Syöpäyhdistys; 2021. 
[4] Suomen Syöpärekisteri. Suomen Syöpärekisteri datan. 
Https://TilastotSyoparekisteriFi/Syovat 2021. 
[5] Gupta K, Miller JD, Li JZ, Russell MW, Charbonneau C. Epidemiologic and 
socioeconomic burden of metastatic renal cell carcinoma (mRCC): A literature review. 
Cancer Treatment Reviews 2008;34:193–205. https://doi.org/10.1016/j.ctrv.2007.12.001. 
[6] Capitanio U, Montorsi F. Renal cancer. The Lancet 2016;387:894–906. 
https://doi.org/10.1016/S0140-6736(15)00046-X. 
[7] Heng DYC, Xie W, Regan MM, Warren MA, Golshayan AR, Sahi C, et al. Prognostic 
Factors for Overall Survival in Patients With Metastatic Renal Cell Carcinoma Treated 
With Vascular Endothelial Growth Factor–Targeted Agents: Results From a Large, 
Multicenter Study. JCO 2009;27:5794–9. https://doi.org/10.1200/JCO.2008.21.4809. 
[8] Heng DY, Xie W, Bjarnason GA, Vaishampayan UN, Donskov F, Wood L, et al. A 
unified prognostic model for first- and second-line targeted therapy in metastatic renal 
cell carcinoma (mRCC): Results from a large international study. JCO 2010;28:4523–
4523. https://doi.org/10.1200/jco.2010.28.15_suppl.4523. 

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[9] Flanigan RC, Campbell SC, Clark JI, Picken MM. Metastatic renal cell carcinoma. Curr 
Treat Options in Oncol 2003;4:385–90. https://doi.org/10.1007/s11864-003-0039-2. 
[10] 
International society for Pharmacoepidemiology. Guidelines for good 
pharmacoepidemiology practice (GPP). Pharmacoepidemiology and Drug Safety 
2016;25:2–10. https://doi.org/10.1002/pds.3891. 
 
12. LIST OF TABLES  
Table 1. IMDC risk scores and categories based on two different approaches depending 
on the data coverage .................................................................................14 
Table 2. List of study variables. Abbreviations: PO=primary objective, SO=secondary 
objective. ...................................................................................................15 
Table 3. List of medications for RCC treatment. ATC= Anatomical Therapeutic 
Chemical. ..................................................................................................16 
13. LIST OF FIGURES 
Figure 1. Graphical illustration of study time windows and corresponding analyses. ............11 
Figure 2. Overview of cohorts and data set formation. ............................................................17 
Figure 3. Graphical illustration of definitions of treatment outcomes. Abbreviations: 
LOT = line of treatment. ...........................................................................20 
ANNEX 1. LIST OF STAND ALONE DOCUMENTS 
None. 
ANNEX 2. ENCEPP CHECKLIST FOR STUDY PROTOCOLS 
Not required. 
ANNEX 3. ADDITIONAL INFORMATION 
Not applicable.