Treatment Patterns With Targeted Therapies in Metastatic Renal Cell Carcinoma (mRCC) in Sweden - A Retrospective Analysis of Data From National Registries
Conditions: Kidney Neoplasms
Sponsor: Pfizer

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NON-INTERVENTIONAL (NI) STUDY PROTOCOL 
 
 
 
 
 
 
 
 
 
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Study information 
Title 
Treatment patterns with targeted therapies in 
metastatic renal cell carcinoma (mRCC) in 
Sweden – A retrospective analysis of data 
from national registries. 
Protocol number 
A6181234 
Protocol version identifier 
Version 2.0 
Date 
13 April 2021 
Active substance 
L01XE04 (sunitinib) 
L01XE17 (axitinib) 
Medicinal product 
Sutent, Inlyta  
Research question and objectives 
The objectives of this study are to 
investigate treatment patterns and outcomes 
for sunitinib and axitinib mRCC patients in a 
nationwide population-based setting in 
Sweden. 
Author 
 PhD 
 
Sweden 
 
 
PPD
PPD
PPD

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1. TABLE OF CONTENTS 
Contents 
1. TABLE OF CONTENTS..................................................................................3 
2. LIST OF ABBREVIATIONS ...........................................................................5 
3. RESPONSIBLE PARTIES ...............................................................................7 
4. AMENDMENTS AND UPDATES...................................................................8 
5. MILESTONES.................................................................................................9 
6. RATIONALE AND BACKGROUND ..............................................................9 
7. RESEARCH QUESTION AND OBJECTIVES...............................................12 
8. RESEARCH METHODS ...............................................................................13 
8.1. Study design.......................................................................................13 
8.2. Setting ...............................................................................................13 
8.2.1. Study definitions.....................................................................14 
8.3. Variables............................................................................................18 
8.4. Data sources .......................................................................................20 
8.5. Study size...........................................................................................21 
8.6. Data management ...............................................................................21 
8.6.1. Case report forms (CRFs)/Data collection tools 
(DCTs)/Electronic data record......................................................23 
8.6.2. Record retention .....................................................................24 
8.7. Data analysis ......................................................................................24 
8.8. Quality control ...................................................................................28 
8.9. Limitations of the research methods ....................................................28 
8.10. Other aspects ....................................................................................29 
9. PROTECTION OF HUMAN SUBJECTS .......................................................29 
9.1. Patient information .............................................................................29 
9.2. Patient consent ...................................................................................30 
9.3. Institutional review board (IRB)/Independent ethics committee (IEC) ..30 
9.4. Ethical conduct of the study ................................................................30 

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10. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS ................................................................................................30 
11. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY 
RESULTS .....................................................................................................33 
12. REFERENCES ............................................................................................33 
13. LIST OF TABLES .......................................................................................34 
14. LIST OF FIGURES ......................................................................................35 
ANNEX 1. LIST OF STAND ALONE DOCUMENTS .......................................35 
ANNEX 3. ADDITIONAL INFORMATION .....................................................35 
 

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2. LIST OF ABBREVIATIONS 
 
Abbreviation 
Definition 
AE 
Adverse event 
AEM 
Adverse event monitoring 
ATC 
Anatomical Therapeutic Chemical  
CDR 
Cause of Death Register 
CI 
Confincence interval 
CRF 
Case report forms 
DCT 
 Data collection tool 
GPP 
Guidelines for Good Pharmacoepidemiology 
Practices 
ICD 
International Classification of Diseases 
IEC 
Independent ethics committee 
IRB 
Institutional review board 
ISPE 
International Society for Pharmacoepidemiology 
ISPOR 
International Society for Pharmacoeconomics and 
Outcomes Research 
KM 
Kaplan Meier 
mRCC 
metastatic renal cell carcinoma 
mTOR 
mammalian target of rapamycin 
NBHW 
National Board of Health and Welfare 
NI 
Non interventional 

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NIS 
Non interventional study 
NPR 
National Patient Register 
OS 
Overall Survival 
PDR 
Patient Drug Register 
PIN 
personal identification number 
RCC 
Renal cell carcinoma 
SCR 
Swedish Cancer Register 
SPC 
Summary of Product Characteristics 
TKI 
tyrasine kinase inhibitor 
TNF 
tumor necrosis factor  
VEGF 
vascular endothelial growth factor 
YRR 
your reporting responsibilities 
 
 
 

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

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4. AMENDMENTS AND UPDATES 
Amendment 
number 
Date 
Protocol 
section(s) 
changed 
Summary of amendment(s) 
Reason 
1 
April 13, 
2021 
8.2 
Change from 30 days grace period to 
90 days in base case, when 
calculating treatment duration 
Too many of the patients with a switch 
from 4:2 to 2:1 are lost with a 30 day 
grace period. The rational to move to 
90 days is that the likelihood of having 
a longer gap is higher than that the 
patients get a treatment in the gap (it 
also has to be a treatment that we 
cannot see, we capture all oral 
treatments, which makes it even more 
unlikely) 
 
2 
April 13, 
2021 
8.1, 8.2 
Time period for data collection 
modified; end date for data 
collection is changed to 31 
December 2019 
Access to data from SoS 
 
 

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5. MILESTONES 
 
Milestone 
Planned date 
Milestone 
Planned date 
Start of data collection  
15 December 2020 
End of data collection  
31 March 2021  
Final study report 
31 March 2021  
 
6. RATIONALE AND BACKGROUND 
Renal cell carcinoma (RCC) accounts for approximately 2% of all cancers worldwide, 
with the highest rates observed in North America, Australia and Europe [1]. In Western, 
Northern and Southern Europe, a total of over 87,000 patients are diagnosed with RCC 
each year, leading to an estimated 33,000 deaths [2].  RCC is often asymptomatic, or 
associated with non-specific symptoms such as fatigue, weight loss, fever and anemia [3]. 
Many patients present with advanced or unresectable disease, and around 30% of patients 
treated by nephrectomy for localized disease will relapse [4].  
 
The worldwide and European annual increase in RCC incidence is approximately 2%, 
however in Denmark and Sweden, a continuing decrease has been observed during the 
last two decades [5]. In 2016, there were 1267 new cases of renal malignancy (excluding 
the renal pelvis) reported in Sweden, of which a majority was above 65 years of age [6]. 
The Swedish RCC death ratio reaches approximately 550 cases per year.  
 
With the advent of modern targeted therapies, the prognosis of patients with metastatic 
RCC (mRCC) has improved. From a median survival of about a year, the new therapies 
reached a survival of over 2 years [7, 8]. These agents include the multitargeted receptor 
tyrosine kinase inhibitors (TKI) sunitinib (Sutent®, Pfizer Inc.), sorafenib (Nexavar®, 
Bayer HealthCare/Onyx Pharmaceuticals), pazopanib (Votrient®, GlaxoSmithKline Inc), 

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axitinib (Inlyta®, Pfizer Inc), cabozantinib (Cabometyx®, Ipsen), tivozanib (Fotivda®, 
EUSA Pharma), lenvatinib (Kisplyx®, EISAI), the vascular endothelial growth factor 
(VEGF) ligand-binding monoclonal antibody bevacizumab (Avastin®, Genentech, Inc.) 
and the mammalian target of rapamycin (mTOR) kinase inhibitors temsirolimus 
(Torisel®, Pfizer Inc) and everolimus (Afinitor®, Novartis).  
 
Great progress in the area of immunotherapy with nivolumab (Opdivo®, BMS) and the 
combinations nivolumab/ipilimumab (Opdivo®/Yervoy®, both BMS), 
pembrolizumab/axitinib, (Ketruda®/Inlyta®, MSD and Pfizer) and avelumab/axitinib 
(Bavencio®/Inlyta®, Merck and Pfizer) has also been made in recent years that will 
benefit patients with metastatic RCC. In such revolutionized treatment landscape, where 
immunotherapy-based combinations are the new standard of care, TKI monotherapy 
maintains a role in the treatment of certain mRCC patients who are not suitable for 
immunotherapy [9]. Notably, TKI monotherapy is still today in Sweden the 
recommended treatment for the subgroup of patients with favourable prognosis [10]. 
 
To date, limited information on real-world treatment patterns such as dosing and time 
from initiation to discontinuation or drug survival exist in the mRCC setting. For other 
disease areas drug survival is commonly analyzed in Europe and in the United States, see 
Hetland et al (2010) for an analysis of tumor necrosis factor (TNF) inhibitors [11].  
 
Wahlgren et al (2013) and Lindskog et al (2017), to some extent investigate mRCC 
treatment patterns in the Swedish setting but in a more general manner [12, 13]. Both 
these studies demonstrate a statistically significant improved survival for the Swedish 
mRCC patients treated with targeted therapies compared to no or a 
hormonal/chemotherapeutic intervention. In Redig et al (2019) the improved survival 
from modern targeted therapy is put in relation to the increased cost [14].  
 
During the last years studies investigating effects on safety and outcomes from different 
dosing schedules have been published, focusing on sunitinib and mostly based on smaller 

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selected patient populations.  Bracarda et al (2017) carried out a critical review of 
published studies until then and found that although the studies had a low level of 
evidence, the results indicated that the 2:1 schedule improved tolerability compared with 
the 4:2 schedule. Regarding efficacy no definitive conclusions could  be drawn due to the 
methodologic limitations of the available studies [15]. 
 
Another example of study in this area is Bracarda et al (2015) where a retrospective 
sample of 249 mRCC patients is analysed. The authors found a longer drug survival for 
patients that moved to a modified 2:1 schedule, both compared to patients that started on 
a 2:1 schedule and patients that did not modify the dosing scheme. They also found that 
patients who moved to a 2:1 schedule experienced an improved safety profile compared 
to during the initial 4:2 schedule [16].  Crumbaker et al (2018) investigated 63 Australian 
mRCC patients and found that patients starting on a 2:1 dosing schedule had a drug 
survival that was longer than the overall survival (OS) times seen in the trials using the 
4:2 schedule [17]. Boegemann et al (2018)  evaluated efficacy and safety regarding 
sunitinib treatment modification in first line treatment of mRCC and found that in 
addition to mitigating adverse events (AEs), sunitinib treatment modification may help 
improve efficacy outcomes by prolonging treatment duration [18].  
 
There is a need for additional research in this area and so far no studies based on Swedish 
data has been carried out. The current study aims at analyzing sunitinib drug survival and 
overall survival for Swedish mRCC patients treated in first line, and investigate how 
these outcomes are affected by different dosing schedules. The study will also investigate 
axitinib drug survival and overall survival in second line. Safety will not be analysed in 
this study due to the characteristics of the available data. 
 
Sweden has a unique opportunity in its large number of health data registers run by the 
National board of Health and Welfare (NBHW). These long-history, high-quality, 
registers constitute the foundation of a very successful Swedish research tradition in the 
field of clinical epidemiology, and cover health data in the entire population that is easily 

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accessible by researchers. From July 2005, the Prescribed Drug Register (PDR), covers 
date and amount of medication prescribed and dispensed to the patient. It also stores 
personal identification number, which enables linkage to other registers. The National 
Patient Register (NPR) covers inpatient care episodes and outpatient visits, including 
information of procedures (i.e. surgery) and diagnosis codes. The Swedish Cancer 
Register (SCR) (since 1958) contains tumor and pathology data from all patients 
diagnosed with cancer in Sweden. The national Cause of Death Register (CDR) (1961) 
contain information on the cause of death.  
 
Combining data from these four registers creates an opportunity to derive patterns of 
duration of treatment and overall survival for the full Swedish mRCC cohort.  
7. RESEARCH QUESTION AND OBJECTIVES 
The present study is an explorative retrospective study investigating treatment patterns 
and outcomes for sunitinib and axitinib mRCC patients in a nationwide population-based 
setting in sweden. 
In more detail the primary objective is to: 
• Investigate time to treatment discontinuation (treatment duration) for first line 
treatment with sunitinib for different treatment schedules: 4:2 (4 weeks on/2 
weeks off) and 2:1 (2 weeks on/1 week off). 
 
The secondary objectives are to: 
• Investigate overall survival (OS) for first line treatment with sunitinib, for 
different treatment schedules, 4:2 (4 weeks on/2 weeks off) and 2:1 (2 weeks on/1 
week off). 
• For second line treatment with axitinib, investigate time to treatment 
discontinuation (treatment duration) and OS. 
 

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8. RESEARCH METHODS  
8.1. Study design  
To address the research objectives, the study will be carried out as a national 
retrospective population-based register study based on data from the NBHW.  
Based on the study objectives, the primary endpoint in this study is: 
• Time to treatment discontinuation in first line sunitinib patients. Time to event 
measure from index date to discontinuation of treatment, from 01 July 2005 to 31 
December 2019 (assessed from index date up to 180 months). This will be 
investigated using Kaplan-Meier analysis.  
 
8.2. Setting 
The data used for the analyses includes all patients aged ≥ 18 years with at least one filled 
prescription of an oral targeted therapy relevant for treating mRCC registered in the 
Swedish Prescribed Drug Register between 01 July 2005 (there is no data available in the 
register before this date) and 31 December 2019. The Anatomical Therapeutic Chemical 
(ATC) codes for the oral drugs relevant for treating mRCC are the following: L01XE04 
(sunitinib), L01XE05 (sorafenib), L01XE11 (pazopanib), L01XE17 (axitinib), L01XE10 
(everolimus), L01XE26 (cabozantinib), L01XE34 (tivozantib), L01XE29 (lenvatinib). 
Selecting patients based on dispensed prescriptions ensure that all patients that have 
prescriptions on the relevant drugs are included in the analyses. The first identified 
prescription date will correspond to the patient’s index date that is relevant for capturing 
the age.  
 
The PDR does not provide any information on mRCC, which is the area of interest in this 
study. The analysis therefore combines the PDR, the SCR and the NPR with the aim to 
identify the mRCC cohort. The patients identified in the PDR that also are identified in 
the SCR with the International Classification of Diseases and Related Health Problems 

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(ICD)-7 diagnosis codes I800 or I809 and ICD-10 codes C64.0 and C64.9 from 
01January 2000 until 31 December 2019;excluding ICD-7 code I801 (cancer of the renal 
pelvis) will be included in the analysis set.  
 
The mRCC cohort derived above will then be further restricted into two different analysis 
sets that will be used to carry out the analyses. 
 
• Analysis Set 1: patients treated with sunitinib in the first line mRCC setting 
• Analysis Set 2: patients treated with axitinib in the second line mRCC setting 
 
Analysis Set 1 will be derived in the following way, from the full mRCC cohort 
described above, individuals will be selected that have sunitinib as the first filled 
prescription (the earliest date) of the relevant drugs: (sunitinib), L01XE05 (sorafenib), 
L01XE11 (pazopanib), L01XE17 (axitinib), L01XE10 (everolimus), L01XE26 
(cabozantinib), L01XE34 (tivozantib), L01XE29 (lenvatinib), and L03AB (cytokines 
medication). L03AB used to be a common treatment for this patient group in the 
beginning of the investigated period and is therefore needed to identify the correct 
treatment line.  
 
Analysis Set 2 will be derived in the following way, from the full mRCC cohort 
described above, individuals will be selected that have axitinib as the second filled 
prescription (the earliest date) of the relevant drugs: (sunitinib), L01XE05 (sorafenib), 
L01XE11 (pazopanib), L01XE17 (axitinib), L01XE10 (everolimus), L01XE26 
(cabozantinib), L01XE34 (tivozantib), L01XE29 (lenvatinib). In addition, to secure that 
axitinib is used as a second line treatment (i.e. not third line), L03AB (cytokines 
medication) is not allowed to have been dispensed before axitinib.  
  
8.2.1.  Study definitions 
 

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Time to treatment discontinuation 
Time to treatment discontinuation, or persistence, is defined as the difference between the 
start and end-dates for a treatment episode (accordance with the International Society for 
Pharmacoeconomics and Outcomes Research (ISPOR) Medication Compliance and 
Persistence Work Group) regardless of reason for discontinuation. The start date for a 
treatment episode is defined as the date of first dispensed package and the end date is 
defined as the date of the last dispensed package with the same ATC code, plus the 
number of days that package, as well as accumulated medicine (see more details below), 
is intended to cover. This end date is overruled if there is a new filled prescription of 
another relevant ATC code or death happens before this, then either of these dates 
represents the end date. If no end of prescribed supply is recorded, data is censored at 
latest available date in data. 
Time to treatment discontinuation will be calculated while allowing for patient 
accumulation of medicine. The number of days covered by the dispensed volume will be 
determined based on information in the Summary of Product Characteristics (SPC), the 
volume of dispensed drug, and for sunitinib in first line also by using the prescriber’s 
dosing instruction on the prescription available in the PDR.  
For sunitinib, the treatment is provided in 4 + 2 (or 2 + 1) week cycles, where there is a 
two-week break in treatment after four weeks of continuous drug intake. Hence, the 
assumed number of days covered by each filled prescription will be adjusted accordingly 
(i.e. the 14 or 7 days corresponding to the cycle will be added).  
 
When previously supplied dosing instructions cease to be specified, it is assumed that the 
daily dosage continues in accordance with the previous treatment pattern. Should there be 
a completeness issue with the variable containing dose information; the recommended 
average dose per day according to the SPC for each product will be used instead.  
 
For axitinib, the treatment is provided in 4 week cycles, without breaks in between. The 
analysis relies on data on information relating to dispensed pack size and strength;  

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Axitinib is available in pack size of 56 tablets, and in strength 1, 3, 5 and 7 mg. Given the 
dosing recommendations in SPC, a dispensed pack with the strength 1 mg is assumed to 
last 14 days, whereas the other packs are assumed to last 28 days.  
 
Patients will be allowed to have gaps between filled prescriptions, but once such a gap 
exceeds 90 days (the “grace period”) they will be defined as non-persistent. As the 
Swedish pharmacy system allows patients to refill prescriptions when two-thirds of the 
previous refill has been consumed (e.g. after two months of a three-month prescription) 
patients may accumulate large amounts of medication. To account for that, patients will 
be permitted to accumulate medication from overlapping prescriptions and use it to cover 
future gaps between filled prescriptions.  Figure 1 depicts the effect the grace period and 
accumulation of medication may have on persistence with the help of scenario 1 and 2.  
 
 
Figure 1. Grace period and accumulation of medication 
 
 
A
B
C
t
A
C
Scenario 1
Scenario 2
Gap <= XX days
(predefined and clinically meaningfull)
B
Discontinuation
Discontinuation
Index date
Gap > XX days
(predefined and clinically meaningfull)

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Both scenarios in Figure 1 showcase the same subject having filled three prescriptions (A, 
B and C) of the index treatment. The “grace period” is set to 90 days. In scenario 1, the 2nd 
prescription (B) is filled before the initial prescription (A) has run out. In scenario 1, the 
subject is not allowed to accumulate medication and therefore the subject will discontinue 
and stop being persistent with medication when the supply from prescription B has run out. 
In scenario 2, accumulation is allowed enabling filled prescription B to close the gap 
between B and C so that it is equal to or less than 90 days. The subject is now persistent 
with medication until the supply from filled prescription C runs out. Hence, both the 
definition of grace period and allowing for accumulation of medication will affect 
persistence. To investigate the impact of the length of the grace period a sensitivity analysis 
with a grace period of 60 and 120 days will be carried out. 
 
 
Dosing Schedule 
The different treatment schedules for sunitinib that will be analysed (starting on 4:2, 
starting on 2:1 and starting on 4:2 and then switching to 2:1) will be defined based on the 
dosing instruction provided by the prescriber and will be reviewed manually (the variable 
DOSER in the Swedish Prescribed Drug Register). In the case no instruction is provided 
at the start of the treatment, a 4:2 dosing scheme (recommended dose in the SPC) will be 
assumed. When previously supplied dosing instructions cease to be specified, it is 
assumed that the daily dosage continues in accordance with the previous treatment 
pattern. A patient is defined as having swithed from a 4:2 to a 2:1 schedule if the dosing 
instruction clearly indicates this. Other sunitinib dosing schedules than the ones described 
above will not be included in the analysis but will be included in descriptive statistics. 

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Overall survival  
Overall survival is defined as the time (number of days) from the start of the treatment (the 
date of the first dispensed package, of sunitinib or axitinib) until the date of death as 
documented in the Cause of Death Register. If no death is recorded, data is censored at latest 
available date in data. 
8.3. Variables 
Table 1 summarizes an overview of the variables needed for the outcomes and study 
variables of the proposed analyses.  
Table 1. Overview of study variables 
Variable 
Role 
Data source(s) 
Operational definition 
Total number of 
sunitinib 1L patients 
Outcome 
Prescription 
Register 
Number of sunitinib users with at 
least one filled prescription (in total 
and per year over time) 
Number of sunitinib 
1L 4:2 schedule users 
Outcome 
Prescription 
Register 
Number of sunitinib users that 
started on a 4:2 schedule and never 
had a modification in the schedule 
(total and per year over time) 
Number of sunitinib 
1L 2:1 schedule users 
Outcome 
Prescription 
Register 
Number of sunitinib users that 
started on a 2:1 schedule and never 
had a modification in the schedule 
(total and per year over time) 
Number of sunitinib 
1L patients that was 
switched from a 4:2 
schedule to a 2:1 
schedule 
Outcome 
Prescription 
Register 
Number of sunitinib users that 
started on a 4:2 shedule and later 
was swithed to a 2:1 schedule, in 
total and per year over time 

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Total number of 
axitinib second line 
patients  
Outcome 
Prescription 
Register 
Number of axitinib 2L users with at 
least one filled prescription (in total 
and per year over time) 
Gender 
Baseline 
characteristics 
Prescription 
Register 
Male/Female (binary) 
Age 
Baseline 
characteristics 
Prescription 
Register 
Age will be defined as age at the 
date of first filled prescription of  
relevant mRCC medication 
(continuous; years). 
Year of treatment 
initiation 
Baseline 
characteristics 
Prescription 
Register 
Defines the year the treatment was 
initiated. 
Region  
Baseline 
characteristics 
Prescription 
Register 
County council of the prescribing 
physician at first prescription date 
(categorical), see Table 6 in  Annex 
3 
Time to treatment 
discontinuation 
Outcome 
Prescription 
Register 
Time from date of first filled 
prescription to the end of the 
prescribed supply, or prescription of 
other ATC code or death if either of 
these happen before (details in 
Section 8.2).  
Overall survival 
Outcome 
Cause of Death 
Register, 
Prescription 
Register 
Time from date of first filled 
prescription of the relevant drug to 
date of death (number of days) 
where death is defined as all-cause 
death; If no date of death is 
recorded, data is censored at latest 
available date in data. 
 

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8.4. Data sources  
The Swedish administrative registries offer high quality data for research with nation-wide 
coverage and close to complete data for most available variables. Patient-level data from 
each register is available for research purposes and individual patients can be linked between 
all data sets via the personal identifier given to all citizens. The administrative registers to be 
used in this study are summarized in Table 2. 
Table 2. Overview of data sources 
 Type of register Name  
Data 
holder 
Start of data 
collection 
Variables 
Patient register 
Swedish National 
Patient Register 
NBHW 
1987/2001 
Diagnosis codes (ICD-9/10), 
dates, procedure codes and types 
of visit 
Prescription 
register 
Swedish Prescribed 
Drug Register 
NBHW 
2005 
Dispatch dates, type of 
medication (ATC codes), 
strengths and dosages 
Information on 
mortality 
Swedish Causes of 
Death Register 
NBHW 
1961 
Date and cause of death (ICD-10) 
Cancer register 
Swedish Cancer 
Register 
NBHW 
1958 
Morphological diagnosis of the 
tumour (ICD-O/3) 
 
The individual data will be extracted from the PDR and merged with the data from the SCR 
and the NPR using the personal identification numbers (PINs). The data extraction will cover 
all patients aged ≥ 18 years with at least one filled prescription of an oral targeted therapy 
relevant for treating mRCC registered in the Swedish Prescribed Drug Register between 01 
July 2005 (there is no data available in the register before this date) and 31 December 2019. 
The Anatomical Therapeutic Chemical (ATC) codes for the oral drugs relevant for treating 
mRCC are the following: L01XE04 (sunitinib), L01XE05 (sorafenib), L01XE11 
(pazopanib), L01XE17 (axitinib), L01XE10 (everolimus), L01XE26 (cabozantinib), 
L01XE34 (tivozantib), L01XE29 (lenvatinib).  

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The PDR does not provide any information on mRCC, which is the area of interest in this 
study. The analysis therefore combines the PDR, the SCR and the NPR with the aim to 
identify the mRCC cohort. The patients identified in the PDR that also are identified in the 
SCR with the International Classification of Diseases and Related Health Problems (ICD)-7 
diagnosis codes I800 or I809 and ICD-10 codes C64.0 and C64.9 from 01 January 2000 until 
31 December 2019; excluding ICD-7 code I801 (cancer of the renal pelvis) will be included 
in the analysis set.  
 
The two analysis sets described in Section 8.2 will be derived and used in the analyses.  
8.5. Study size 
An estimated 17,000 to 18,000 patients are diagnosed with RCC between 01 January 2000 
and 31 December 2019, approximately 1,000 patients per year. Of these patients, an 
estimated 4,000 to 5,000 are registered with at least one relevant dispensed prescription for 
mRCC. Approximately 1,000 of these patients are estimated to have received sunitinib as 
first line treatment during the investigated period. For axitinib, approximately 300 patients 
are estimated to have received it in second line during the investigated period.  
8.6. Data management  
In broad terms, the data management for this study will be initiated by the creation of a broad 
study population including patients with at least one filled prescription of (L01XE04 
(sunitinib), L01XE05 (sorafenib), L01XE11 (pazopanib), L01XE17 (axitinib), L01XE10 
(everolimus), L01XE26 (cabozantinib), L01XE34 (tivozantib), L01XE29 (lenvatinib)) 
identified in the PDR. A study key including the selected cases personal identifiable number 
(PIN) and a randomly created study identification number will be created by the NBHW.  The 
data that is being extracted from the NBHW is described in Table 3 below.  
 

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Based on the data extracted from the NBHW two completely pseudonymized analytical dataset 
comprising all observations and variables required for the planned analyses will be compiled, 
see details in Section 8.2. The analytic datasets will be person-level. 
All data management will be performed by ICON. A data validity quality check is always 
undertaken before data management is started to verify that all variables are complete and to 
create logs for corrupt or ambiguous data entries. Data will be analyzed using SAS version 9.2 
or later. 
One of the variables included in the material (DOSER) is in text format, requiring human 
review. The information in DOSER will be reviewed for Analysis Set 1 (patients indentified 
with sunitinib treatment in first line) and used to identify the initial dosing schedule and 
changes in the dosing schedule. The information in DOSER will be quantified in the following 
way. DOSER will be lifted out to an excel sheet together with study IDs and drug dispense 
dates. DOSER will be manually reviewed and dummy variables indicating the dosing schedule 
and dates for changes in the dosing schedule will be created. When the manual coding is done, 
the data will me merged with the original dataset based on the study IDs. 
Table 3. Variables extracted from the NBHW 
Variable 
Explanation 
Data source(s) 
ICD7 
ICD-7 code 
Swedish Cancer Register 
ICD9 
ICD-9 code 
Swedish Cancer Register 
ICDO10 
ICD-O/2-10 
Swedish Cancer Register 
ICDO3 
ICD-O/3 
Swedish Cancer Register 
ALDER 
Age at diagnosis 
Swedish Cancer Register 
M 
Spread of tumor at diagnosis, 
distant metastases 
Swedish Cancer Register 
N 
Spread of tumor at diagnosis, 
Lymph nodes 
Swedish Cancer Register 
DIADAT 
Date of RCC diagnosis 
Swedish Cancer Register 
DODSDAT 
Date of death 
Swedish Cancer Register 
DODSDATN 
Date of death numeric 
Swedish Cancer Register 
KON 
Gender 
Swedish Cancer Register 
SJUKHUS 
Hospital where diagnosis was set 
Swedish Cancer Register 
DODSDAT 
Date of death 
Swedish Cause of Death Register 
ALDER 
Age at visit 
National Patient Register 
AR 
Year of visit 
National Patient Register 
MVO 
Medical focus area  
National Patient Register 
SJUKHUS 
Hospital 
National Patient Register 
DIAGNOS 
Diagnosis 
National Patient Register 
HDIA 
Main diagnosis 
National Patient Register 
KON 
Sex 
National Patient Register 

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INDATUMA 
Date for start of visit 
National Patient Register 
OP 
Surgery  
National Patient Register 
UTDATUMA 
Date for end of visit 
National Patient Register 
VTID 
Duration of care 
National Patient Register 
ALDER 
Age at the end of the year 
Swedish Prescribed Drug Register 
ARBLAN 
The region of the prescribing 
clinic 
Swedish Prescribed Drug Register 
FDATE 
Prescription date 
Swedish Prescribed Drug Register 
EDATE 
Dispense date 
Swedish Prescribed Drug Register 
ANTAL 
Number of packages 
Swedish Prescribed Drug Register 
DOSER 
Dosing instructions 
Swedish Prescribed Drug Register 
EXPLAN 
Region/County of dispensing 
pharmacy 
Swedish Prescribed Drug Register 
FVARUNR 
Dispensed drug goods number 
Swedish Prescribed Drug Register 
ATC 
ATC code 
Swedish Prescribed Drug Register 
PRODUKT 
Name of product 
Swedish Prescribed Drug Register 
FORPS 
Package size 
Swedish Prescribed Drug Register 
STYRKALF 
Strength of the product 
Swedish Prescribed Drug Register 
STYRKAENHET 
Unit of the strength 
Swedish Prescribed Drug Register 
KON 
Gender 
Swedish Prescribed Drug Register 
 
8.6.1. Case report forms (CRFs)/Data collection tools (DCTs)/Electronic data record 
As used in this protocol, the term DCT 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 DCT is required and should be completed for each included patient.  The completed 
original DCTs are the sole property of Pfizer and should not be made available in any form to 
third parties, except for authorized representatives of Pfizer or appropriate regulatory 
authorities, without written permission from Pfizer.  ICON shall ensure that the DCTs are 
securely stored at the study site in encrypted electronic form and will be password protected 
to prevent access by unauthorized third parties. 
ICON has ultimate responsibility for the collection and reporting of all clinical, safety, and 
laboratory data entered on the DCTs 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 DCTs must 
be signed by ICON staff or by an authorized staff member to attest that the data contained on 
the DCTs are true.  Any corrections to entries made in the DCTs or source documents must 
be dated, initialed, and explained (if necessary) and should not obscure the original entry. 

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The source documents are the hospital or the physician's chart.  In these cases, data collected 
on the DCTs must match those charts.  
8.6.2. Record retention 
To enable evaluations and/or inspections/audits from regulatory authorities or Pfizer, ICON 
agrees to keep all study-related records, including the identity of all participating patients 
(sufficient information to link records, e.g., CRFs and hospital records), copies of all DCTs, 
safety reporting forms, source documents, detailed records of treatment disposition, and 
adequate documentation of relevant correspondence (e.g., letters, meeting minutes, and 
telephone call reports).  The records should be retained by ICON according to local 
regulations or as specified in the vendor contract, whichever is longer.  ICON must ensure 
that the records continue to be stored securely for so long as they are retained. 
If ICON becomes unable for any reason to continue to retain study records for the required 
period, Pfizer should be prospectively notified.  The study records must be transferred to a 
designee acceptable to Pfizer. 
Study records must be kept for a minimum of 15 years after completion or discontinuation of 
the study, unless ICON and Pfizer have expressly agreed to a different period of retention via 
a separate written agreement.  Record must be retained for longer than 15 years if required by 
applicable local regulations.   
ICON must obtain Pfizer's written permission before disposing of any records, even if 
retention requirements have been met. 
8.7. Data analysis  
An overview of the planned analyses are presented in this section. In general, the study is 
descriptive and does not involve hypothesis testing. Any major modifications of primary 
endpoint definitions or their analyses would be reflected in a protocol amendment. 
Time-to-event analyses will be carried out using standard Kaplan-Meier methods. Kaplan-
Meier survival functions will be estimated with relevant events as failure. Time-to-event tables 

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and Kaplan-Meier curves will be presented. Log-Rank tests will be used to assess differences 
across cohorts. In addition, to explore potential determinants of persistence /drug survival and 
to adjust for differences across cohorts, semi-parametric cox-proportional hazard models will 
be deployed based on different covariates.  
 
Relevant events for this study include: 
- 
Time to treatment discontinuation  
- 
Death 
 
Time-to-event tables will present: 
- 
Failed/Censored n (%). 
- 
Median time to event. 
- 
95% confidence intervals of median. 
- 
The 25th and 75th percentiles (q1 and q3). 
- 
Min and max. 
- 
n at risk by unit. 
- 
Time point estimates and 95% Confidence Intervals (CI)by unit. 
 
As described in Section 8.2 the analyses will be carried out based on two analysis sets. 
Analysis Set 1 consists of all patients indentified with sunitinib as the first line treatment. 
Analysis Set 2 consists of all patients indentified with axitinib as the second line treatment.  
 
The Table 4 below displays the output from the time to treatment discontinuation and overall 
survival analyses that will be carried out based on Analysis Set 1. The output will be 
presented for three different dosing schemes of interest, patients that started on a 4:2 
schedule and that did not switch, patients that started on a 4:2 schedule but later switched to a 
2:1 schedule and patients that started on a 2:1 schedule and did not switch. Output will also 
be presented as Kaplan Meier (KM) curves.  
 

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To explore potential determinants drug survival and to adjust for differences across cohorts, 
semi-parametric cox-proportional hazard models will be deployed based on the following 
covariates: age, gender, year of treatment initiation, region.  
 
Table 4. Time to treatment discontinuaton and OS, first line treatment with sunitinib 
 
L01XE04 
Started on 4:2 
schedule, no switch 
N=xxx 
L01XE04 
Started on 4:2 
schedule, switch to 
2:1 schedule 
N=xxx 
L01XE04 
Started on 2:1 
schedule 
N=xxx 
  Censored n (%) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  Failed n (%) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
Survival time (Unit) 
 
 
 
  Median (KM) 
xx.x 
xx.x 
xx.x 
  95% CI of median  (KM) 
xxx.x , xxx.x 
xxx.x , xxx.x 
xxx.x , xxx.x 
  Q1, Q3 (KM) 
xxx.x , xxx.x. 
xxx.x , xxx.x. 
xxx.x , xxx.x 
  Min , Max 
xx.x , xx.x 
xx.x , xx.x 
xx.x , xx.x 
Kaplan-Meier survival point 
estimates – n at risk,  
% (95% CI) 
 
 
 
  1 unit 
x, x.xx (x.xx,x.xx) x, x.xx (x.xx,x.xx) x, x.xx (x.xx,x.xx) 
  2 unit 
x, x.xx (x.xx,x.xx) x, x.xx (x.xx,x.xx) x, x.xx (x.xx,x.xx) 
  . 
. 
. 
. 
  . 
. 
. 
. 
  . 
. 
. 
. 
n units 
x, x.xx (x.xx,x.xx) x, x.xx (x.xx,x.xx) x, x.xx (x.xx,x.xx) 
 
 

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The Table 5 below displays the output from the time to treatment discontinuation and overall 
survival analyses that will be carried out based on Analysis Set 2. Output will also be 
presented as KM curves.  
 
To explore potential determinants drug survival and to adjust for differences across cohorts, 
semi-parametric cox-proportional hazard models will be deployed based on the following 
covariates: age, gender, year of treatment initiation, region.  
Table 5. Time to treatment discontinuation and OS, second line treatment with axitinib 
 
L01XE 
All 2L patients 
N=xxx 
  Censored n (%) 
xx (xx.x) 
  Failed n (%) 
xx (xx.x) 
Survival time (Unit) 
 
  Median (KM) 
xx.x 
  95% CI of median  (KM) 
xxx.x , xxx.x 
  Q1, Q3 (KM) 
xxx.x , xxx.x 
  Min , Max 
xx.x , xx.x 
Kaplan-Meier survival point 
estimates – n at risk,  
% (95% CI) 
 
  1 unit 
x, x.xx (x.xx,x.xx) 
  2 unit 
x, x.xx (x.xx,x.xx) 
  . 
. 
  . 
. 
  . 
. 
n units 
x, x.xx (x.xx,x.xx) 
 

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8.8. Quality control 
Data to be used in this study will be extracted from the registers managed by the NBHW and 
will be of the highest quality. The SCR has nearly 100% completeness and the coverage for 
inpatient data is almost 100% and nearly 80% for outpatient data.  
Data will be ordered through a so-called research request, assessed by the NBHW after 
ethical approval of the study protocol. Data will be released on an individual basis but with a 
serial number instead of a social security number, thus preventing individual patients from 
being identified. Data will be treated with privacy and according to the Swedish Personal 
Data Act. It is the responsibility of the NBHW to ensure completion of, and to review and 
approve all the data, and to verify that data is verified to source data. 
Quality control of data extraction will be done by reviewing of critical variables. Variables 
will be checked against the delivery specification from the NBHW. Errors will be listed, 
rectified, and sent to NBHW for correction. Further, the errors will be rectified in the analysis 
database. Pfizer will perform all programming of the final analysis data set, study database. 
Data management at Pfizer is tracked so that data editing, i.e. correction, and other data 
corrections in the preparation of the analysis data sets will be summarized.  
The original data extraction from NBHW, or any copy, are the sole property of Pfizer and 
should not be made available, without written permission from Pfizer, in any form to third 
parties except for authorized representatives of Pfizer or appropriate authorities. 
8.9. Limitations of the research methods 
The retrospective design entails a risk of bias in the analyses, especially selection and 
misclassification bias. Furthermore, information on medication not dispensed on prescription 
(medication administered in a hospital) is not available at the NBHW. This will have as a 
consequence that potentially not all patients treated with oral targeted mRCC drugs are 
included in the analysis. Selecting patients based on dispensed prescriptions and a registered 
RCC diagnosis might have the consequence that some included patients also suffer from 
other malignancies for which they were treated with one of the specified drugs. However, we 

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believe that risk to be small. Insights from previous studies using this type of data (Wahlgren 
et al (2013) and Lindskog et al (2017)) will help us handle this in the best way possible. One 
additional limitation that concerns the definition of treatment line is that the data only allows 
us to evaluate the chronological order of received treatments, but no data on disease 
progression is available. 
8.10. Other aspects 
Not applicable. 
 
 
9. PROTECTION OF HUMAN SUBJECTS 
9.1. Patient information  
Data will be presented on an aggregate level and will not be possible to track individual 
patients. 
The variable DOSER will go through manual review, data is unstructured data that require 
human review.  
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.  
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, any patient names will be removed and will be replaced by a single, specific, 
numerical code.  All other identifiable data transferred to Pfizer or other authorized parties 
will be identified by this single, patient-specific code.  In case of data transfer, Pfizer will 
maintain high standards of confidentiality and protection of patients’ personal data consistent 
with the vendor contract and applicable privacy laws. 

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9.2. 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.   
9.3. Institutional review board (IRB)/Independent ethics committee (IEC) 
There must be prospective approval of the study protocol, protocol amendments, and other 
relevant documents (e.g., 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.  
This study will be sent to the Swedish Ethical Review Authority for approval. 
9.4. 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 (GPP) issued by the 
International Society for Pharmacoepidemiology (ISPE) and Good Practices for Outcomes 
Research issued by the International Society for Pharmacoeconomics and Outcomes 
Research (ISPOR). 
10. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE 
REACTIONS  
Structured Data Analysis  
This study involves structured 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. 
In these data sources, individual patient data are not retrieved or validated, and it is not 
possible to link (i.e., identify a potential association between) a particular product and 
medical event for any individual.  Thus, the minimum criteria for reporting an adverse event 

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(AE) (i.e., identifiable patient, identifiable reporter, a suspect product, and event) cannot be 
met. 
Human Review of Unstructured Data 
In this study the analysis is based on one variable from the NBHW that is unstructured and 
that required human review. This study protocol requires human review of patient-level 
unstructured data; unstructured data refer to verbatim medical data, including text-based 
descriptions and visual depictions of medical information, such as medical records, images of 
physician notes, neurological scans, X-rays, or narrative fields in a database.  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 healthcare provider linking drug administration to the AE. 
 
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 DCT 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 

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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 (e.g., gender, 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:    
•  “Your Reporting Responsibility (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.  
 

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11. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS 
The results in this study is planned to be reported in an abstract, conference presentation and 
at least one manuscript that will be sent to a scientific journal for review and publication.  
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 party responsible for collecting data 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.   
12. REFERENCES 
1. Padala SA, Barsouk A, Thandra KC, et al. Epidemiology of Renal Cell 
Carcinoma. World J Oncol. 2020;11(3):79-87. doi:10.14740/wjon1279 
2. World Health Organization. Global Health Observatory. Geneva: World Health 
Organization; 2018. who.int/gho/database/en/. Accessed November 25, 2020. 
3. Motzer, R. J, Jonasch, E, Agarwal, N, et al. (2017). Kidney Cancer, Version 2.2017, 
NCCN Clinical Practice Guidelines in Oncology, Journal of the National 
Comprehensive Cancer Network J Natl Compr Canc Netw , 15(6), 804-834. 
4. Chin, Arnold I., et al. "Surveillance strategies for renal cell carcinoma patients 
following nephrectomy." Reviews in urology 8.1 (2006): 1-7. 
5. Lindblad P. Epidemiology of renal cell carcinoma. Scand J Surg 2004;93:88-96. 
6. Cancer in Numbers (Cancer i siffror) 2018: National board of health and Welfare, 
Sweden; 2018.  
7. Negrier, S., et al. (1998) ”Recombinant human interleukin-2, recombinant human 
interferon alfa-2a, or both in metastatic renal-cell carcinoma.” New England Journal 
of Medicine, 338, 1272-1278. 
8. Motzer, et al. (2009) Overall survival and updated results for sunitinib compared with 
interferon alfa in patients with metastatic renal cell carcinoma, Journal of Clinical 
Oncology, Aug 1;27(22):3584-90 
9. Escudier, B., et al (2019) Renal cell carcinoma: ESMO Clinical Practice Guidelines 
for diagnosis, treatment and follow-up†. Annals of Oncology 0: 1-15 and following 
eUpdates available at https://www.esmo.org/guidelines/genitourinary-cancers/renal-
cell-carcinomaat (accessed November 30th 2020) 

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10. Nationellt vårdprogram Njurcancer, version 3.0 Juni 2019. 
11. Hetland ML, Christensen IJ, Tarp U, et al. Direct comparison of treatment responses, 
remission rates, and drug adherence in patients with rheumatoid arthritis treated with 
adalimumab, etanercept, or infliximab: results from eight years of surveillance of 
clinical practice in the nationwide Danish DANBIO registry. Arthritis Rheum. 
2010;62:22–32. 
12. Wahlgren T, Harmenberg U, Sandström P, et al. Treatment and overall survival in 
renal cell carcinoma: a Swedish population-based study (2000–2008). Br J Cancer 
2013;108(7):1541-9 
13. Lindskog M. et al. Overall survival in Swedish patients with renal cell carcinoma 
treated in the period 2002 to 2012: Update of the RENCOMP study with subgroup 
analysis of the synchronous metastatic and elderly populations, Urologic Oncology: 
Seminars and Original Investigations, Volume 35, Issue 9, September 2017, Pages 
541.e15-541.e22 
14. Redig J. et al. Real-world cost-effectiveness of targeted therapy in metastatic renal 
cell carcinoma in Sweden: a population-based retrospective analysis, Cancer 
Management and Research (2019), Volume 2019:11 Pages 1289—1297  
15. Bracarda S et al, How clinical practice is changing the rules: the sunitinib 2/1 
schedule in metastatic renal cell carcinoma. Expert Rev Anticancer Ther. 2017 
Mar;17(3):227-233 
16. Bracarda, Sergio, et al. "Sunitinib administered on 2/1 schedule in patients with 
metastatic renal cell carcinoma: the RAINBOW analysis." Annals of Oncology 26.10 
(2015): 2107-2113. 
17. Crumbaker, Megan, et al. "Real‐world experience of the feasibility and tolerability of 
the 2/1 dosing schedule with sunitinib in the treatment of patients with advanced renal 
cell carcinoma in Australia." Asia‐Pacific Journal of Clinical Oncology 14.2 (2018): 
e45-e49. 
18. Boegemann M, Hubbe M et al. Sunitinib Treatment Modification in First-Line 
Metastatic Renal Cell Carcinoma: Analysis of the STAR-TOR Registry. Anticancer 
Res. 2018 Nov;38(11):6413-6422. 
 
13. LIST OF TABLES 
Table 1. Overview of study variables 
Table 2. Overview of data sources 

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Table 3. Variables extracted from the NBHW 
Table 4. Time to treatment discontinuaton and OS, first line treatment with sunitinib 
Table 5. Time to treatment discontinuation and OS, second line treatment with axitinib 
Table 6. Region codes 
 
14. LIST OF FIGURES 
Figure 1. Grace period and accumulation of medication 
 
ANNEX 1. LIST OF STAND ALONE DOCUMENTS 
None. 
ANNEX 3. ADDITIONAL INFORMATION 
Table 6. Region codes 
County name 
County code 
Region Stockholm 
01 
Region Uppsala 
03 
Region Sörmland 
04 
Region Östergötland 
05 
Region Jönköpings län 
06 
Region Kronoberg 
07 
Region Kalmar län 
08 
Region Gotland 
09 
Region Blekinge 
10 
Region Skåne 
12 
Region Halland 
13 
Region Västra Götaland 
14 
Region Värmland 
17 
Region Örebro 
18 
Region Västmanland 
19 
Region Dalarna 
20 

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Region Gävleborg 
21 
Region Västernorrland 
22 
Region Jämtland Härjedalen 
23 
Region Västerbotten 
24 
Region Norrbotten 
25