Evaluation of Xeljanz Access Barriers Via Patient OOP Costs and TNFi Cycling
Conditions: Rheumatoid Arthritis
Sponsor: Pfizer

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NON-INTERVENTIONAL (NI) STUDY PROTOCOL
Title
Evaluation of Xeljanz Access Barriers
via Patient OOP Costs and TNFi
cycling
Protocol number
Pfizer protocol ID A3921346
Protocol version identifier
Version number 1.1
Date
October 7, 2019
Active substance
L04AA29 (tofacitinib)
Medicinal product
Xeljanz (tofacitinib)

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Research question and objectives
Primary Objectives:
To evaluate the impact of (1a) Xeljanz
index prescription OOP costs and (1b)
TNFi cycling with etanercept and 
adalimumab vs. switching to Xeljanz on 
treatment persistence.
Secondary Objectives:
2) To compare (1) high vs. low
Xeljanz index prescription OOP
costs, and, (2) TNFi cycling
(2 groups) with etanercept and
adalimumab vs. switching to 
Xeljanz (2 groups) on:
• Differences in demographic
and clinical characteristics.
• Treatment patterns including
dosing, concomitant
medication use, adherence,
switching and a 6- factor
effectiveness proxy measure
(Curtis algorithm) between
comparator cohorts.
• Post-index and change
(Post-Pre) in All-cause and
RA-related health care
utilization associated costs.
 
 
 
 
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Author
, PharmD,MS
,
 
PHI, Pfizer Inc.
PPD
PPD
PPD

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1. TABLE OF CONTENTS
1. TABLE OF CONTENTS.......................................................................................................4
LIST OF TABLES.....................................................................................................................6
LIST OF FIGURES ...................................................................................................................6
APPENDICES ...........................................................................................................................6
2. LIST OF ABBREVIATIONS................................................................................................7
3. RESPONSIBLE PARTIES....................................................................................................9
4. AMENDMENTS AND UPDATES.....................................................................................10
5. MILESTONES.....................................................................................................................11
6. RATIONALE AND BACKGROUND................................................................................12
7. RESEARCH QUESTION AND OBJECTIVES .................................................................13
7.1. Primary Objectives..................................................................................................13
7.2. Secondary Objectives..............................................................................................13
8. RESEARCH METHODS ....................................................................................................14
8.1. Study Design ...........................................................................................................14
8.2. Setting......................................................................................................................15
8.2.1. Inclusion Criteria ........................................................................................15
8.3. Variables..................................................................................................................17
8.3.1. Health Care Cost and Utilization................................................................26
8.4. Data Source .............................................................................................................28
8.4.1. Truven MarketScan Research Database .....................................................28
8.5. Study Size................................................................................................................29
8.6. Data Management ...................................................................................................30
8.7. Data Analysis ..........................................................................................................30
8.7.1. Primary Objectives .....................................................................................30
8.7.1.1. To Compare 12-month Post-Index Medication Persistence 
Duration (days) by TOFA Index Prescription OOP Costs and 
TNFi Cycling with ETN and ADA vs. TOFA Switching ................30
8.7.2. Secondary Objectives .................................................................................30
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8.7.2.1. Explore the Differences in Demographic and Clinical 
Characteristics Between TOFA Index Prescription OOP Costs 
and TNFi Cycling with ETN and ADA vs. TOFA Switching 
Cohorts ..............................................................................................30
8.7.2.2. Compare Treatment Patterns Including Dosing,
Adherence, Persistence Treatment Patterns Between TOFA 
Index Prescription OOP Costs and TNFi Cycling with ETN 
and ADA vs. TOFA Switching Cohorts...........................................30
8.7.2.3. Compare All-Cause and RA-Related Health Care 
Utilization Between TOFA Index Prescription OOP Costs and 
TNFi Cycling with ETN and ADA vs. TOFA Switching
Cohorts ..............................................................................................31
8.7.2.4. Compare All-Cause and RA-Related Healthcare Costs 
Between TOFA Index Prescription OOP Costs and TNFi 
Cycling with ETN and ADA vs. TOFA Switching Cohorts.............31
 
 
 
 
8.7.3. Descriptive Analysis...................................................................................32
8.7.4. Multivariate Analysis..................................................................................32
8.7.5. Cost Data.....................................................................................................33
8.7.6. Dichotomous Data ......................................................................................33
8.8. Quality Control........................................................................................................34
8.9. Limitations of the Research Methods......................................................................34
8.10. Other Aspects ........................................................................................................35
9. PROTECTION OF HUMAN SUBJECTS...........................................................................35
9.1. Patient Information..................................................................................................35
9.2. Patient Consent........................................................................................................35
9.3. Institutional Review Board (IRB)/Independent Ethics Committee (IEC) ..............35
9.4. Ethical Conduct of the Study ..................................................................................35
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10. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE
REACTIONS ......................................................................................................................36
11. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS........36
12. REFERENCES ..................................................................................................................37
13. LIST OF TABLES.............................................................................................................39
14. LIST OF FIGURES ...........................................................................................................39
15. ANNEX 1. LIST OF STAND ALONE DOCUMENTS....................................................39
16. APPENDICES ...................................................................................................................40
LIST OF TABLES
Table 1.
EXCLUSIONARY DIAGNOSES............................................................16
LIST OF FIGURES
Figure 1.
Study Diagram..........................................................................................15
APPENDICES
Appendix 1. ADVANCED THERAPIES................................................................................40
Appendix 2. NON-BIOLOGIC (TRADITIONAL) DMARDS ...............................................41
Appendix 3. CLAIMS-BASED INDEX OF RA SEVERITY (CIRAS) .................................42
Appendix 4. COMORBIDITIES OF INTEREST ...................................................................44
Appendix 5. LIST OF OTHER RA-RELATED MEDICATIONS .........................................46

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2. LIST OF ABBREVIATIONS
Abbreviation
Definition
ADA
Adalimumab
AE
Adverse Event
AHRQ
Agency for Healthcare Research and Quality
ARRA
American Recovery and Reinvestment Act
CIRAS
Claims-based index for RA severity
CMS
Centers for Medicare & Medicaid Services
COB
Coordination of benefits
COPD
Chronic obstructive pulmonary disease
CPI
Consumer price index
CPT
Current Procedural Terminology
ED
Emergency department
ETN
Etanercept
FDA
Food and Drug Administration
GLM
Generalized linear model
HCFA
Care Financing Administration
HCPCS
Healthcare Common Procedure Coding System
HIPAA
Health Insurance Portability and Accountability Act
ICD-9/10 CM
The International Classification of Diseases, 9th and 10th Revision,
Clinical Modification
IEC
Independent Ethics Committee
IRB
Institutional review board
ISPOR
International society for pharmacoeconomics and outcomes research
IV
Intravenous
LIS
Low income subsidy
MOA
Mechanism of action

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Abbreviation
Definition
MTX
Methotrexate
NB-DMARD
Non-biologic disease modifying antirheumatic drug
NDC
National Drug Code
NIS
Non-interventional study
NSAID
Non-steroidal anti-inflammatory drug
OOP
Out-of-pocket
PDC
Proportion of Days Covered
RA
Rheumatoid Arthritis
RAPID3
Routine assessment of patient index data
RX
Outpatient pharmacy
TNFi
Tumor-Necrosis Factor-alpha inhibitor
TOFA
Tofacitinib
UB
Uniform Bill
US
United States

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3. RESPONSIBLE PARTIES
Principal Investigator(s) of the Protocol
Name,degree(s)
Title
Affiliation
Address
Pfizer Inc
NY
, PhD
Pfizer Inc
Groton,
, PhD
 
 
Pfizer Inc
, New
York, NY
 PhD
, 
Pfizer Inc.
 
PA, 
PPD
PPD
PP
DPPD
PPD
PPD
PPD
PPD
PPD
PPD
PP
DPPD
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
7 October 2019
7, 8.1, 
8.2,8.3, 8.4.2, 
8.4.3
Removed references to the 
Optum Clinformatics and 
Pharmetrics Plus databases.
Truven Marketscan database is 
sufficient for answering the research 
questions.
1
7 October 2019
3
Updated responsible parties
Reflecting changes in function and 
role

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5. MILESTONES
Milestone
Planned date
Start of data collection
21 December 2018
End of data collection
30 June 2019
Final study report
30 September 2019

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6. RATIONALE AND BACKGROUND
Tofacitinib (Xeljanz) was approved by the US Food and Drug Administration (FDA) in
November 2012 as the first oral JAK inhibit or for the treatment of adult patients with 
moderately to severely active rheumatoid arthritis (RA) who have had an inadequate
response or intolerance to methotrexate. This advanced therapy may be used as monotherapy
or in combination with methotrexate (MTX) or other nonbiologic disease-modifying
antirheumatic drugs (NB-DMARDs). In February 2016, a once-daily Xeljanz XR
formulation was approved, offering an option to the already approved twice daily immediate
release formulation.
The most commonly used advanced therapies for RA are the Tumor-Necrosis Factor-alpha
inhibitors (TNFi), in particular, adalimumab (Humira) and etanercept (Enbrel). Use of
consecutive TNFis has been further reinforced by payer restrictions that often require failure
of two or more TNFi’s for receiving alternative MOA products like tofacitinib (TOFA).
However, there has been a growing body of largely observational evidence on the detriments
of such TNFi cycling vs. switching to alternative MOA in patients with RA including:

Shorter treatment persistence/duration;1-4

Higher likelihood of switching to third line advanced therapy;2,3,5

Higher costs;1,2

Lower effectiveness using 6-factor algorithm;2,3

Potentially poorer disease activity scores;4,6,7 however, further information on the
impact of joint erosion associated with TNFi cycling vs. switching is not currently
available.
In addition to step edits and prior authorization, another barrier to receiving advanced therapy
for RA is the increased out-of-pocket (OOP) cost sharing for patients. An analysis of claims
data for over 40,000 RA patients starting bDMARDs between 01/2004 and 12/2013 found 
that the average cost per prescription remained relatively unchanged, at approximately
$2300 per prescription, while OOP expenditures increased from $36 (2.5%) per prescription 
to $128 (7%).8  An analysis of insurance claims data for Medicare Advantage Part D 
patients with RA found bDMARD prescription abandonment (claim reversal without 
subsequent fill) ranged from 1.3% for the lowest out-of-pocket (OOP) cost group ($0-$250) 
to 32.7% for the highest OOP cost group (> $550). Further, the odds of refilling bDMARD
therapy were significantly lower for each OOP cost range ($250.01-$400.00,
$400.01-$550.00, and >$550.00) relative to OOP cost range of ≤$250.9 An analysis of 
insurance claims for self-insured health plan members with RA starting etanercept or 
adalimumab demonstrated about 1 week of therapy lost per $5.50 increase in weekly OOP
expenditures. Those with weekly cost >$50 were 58% more likely to discontinue than
patients with lower OOP costs (hazard ratio 1.58, P<0.001).10 Additionally, Doshi et al11

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found using the 5% sample Medicare data that patients with RA belonging to a non-low
income subsidy (LIS) group had a higher average OOP cost for Part D bDMARDs of
$484 (29.9% cost sharing) versus $5 (0.3% cost sharing) in an LIS group which was
associated with a 42% lower odds of filling Part D biologic agents while being more than 
twice as likely to receive Part B biologic agents and having a 31% lower odds of using any
biologic agent vs. patients in the LIS group.
The current study is intended to evaluate the impact of restrictions on TOFA including OOP
cost sharing and TNFi cycling with adalimumab and etanercept vs. switching to Tofacitinib 
on treatment persistence, treatment patterns, healthcare resource use, and costs.
7. RESEARCH QUESTION AND OBJECTIVES
The primary and secondary objectives will be evaluated using insurance claims for patients
with rheumatoid arthritis (RA) identified in the Truven Health MarketScan database (see
Section 8.4).
7.1. Primary Objectives
To evaluate the impact of (1a) TOFA index prescription OOP costs and (1b) TNFi cycling
with etanercept (ETN) and adalimumab (ADA) vs. switching to TOFA on treatment 
persistence duration (see Section 8.3).
7.2. Secondary Objectives
To compare patients with (1) high (>median) vs. low (≤median) TOFA index prescription
OOP costs, and, (2) TNFi cycling with ETN and ADA vs. switching to TOFA on:
•
Differences in demographic and clinical characteristics;
•
Treatment patterns including dosing, concomitant medication use, adherence, and
switching, and a 6-factor effectiveness proxy (ie, Curtis algorithm) between
comparator cohorts;
•
Post-index and change (Post-Pre) in All-cause and RA-related health care utilization
associated costs.
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8. RESEARCH METHODS
8.1. Study Design
This is a retrospective cohort study to evaluate patient characteristics, treatment patterns
including a 6-factor effectiveness proxy measure, health care resource use and associated
costs among RA patients initiating treatment comparator groups of interest between January
2014 and September 2016 across three US insurance claims databases. This period was
selected since we typically have 5-year data license and wanted at least 2 years potential 
pre-index history, 2 years to capture treatmtent initation and 1 year for follow-up.
Further, we wanted to minimize channeling bias for TOFA in the first year of introduction
where ADA and ETN were well established for a decade and based on prior analyses using
2012-2014 data indicating majority of TOFA use for 3rd line plus vs. ADA/ETN were mostly
used for 2nd line treatment of RA (Chastek et al.2 Poster presented at the ACR/ARHP Annual
Scientific Meeting, San Francisco, CA, USA, November 6–11, 2015).
 
 
 
 
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C
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Figure 1.
Study Diagram
8.2. Setting
This study will leverage the de-identified, insurance claims database Truven Health
MarketScan, between January of 2012 and September 2017. The database is further
described in Section 8.4.
8.2.1. Inclusion Criteria
Patients must meet all of the following inclusion criteria to be eligible for inclusion in the 
study:
1. The first pharmacy claim for TOFA and then ETN or ADA between Jan 2014 and
Sep 2016 represents the index claim (See Appendix 1 for codes). Selection of
comparator groups will be hierchical per the following:
a.
First, select patients receiving ≥1 tofacitinib (TOFA) pharmacy claim
(Jan 2014–Sep 2016) who did not have a TOFA claim anytime prior to index.
b. Amongst remaining patients, select those receiving ≥1 ETN or ADA pharmacy
claim, assign per whichever occurs first, over same time period (Jan 2014-Sep
2016) who did not have a respective pharmacy or administration claim for index
medication anytime prior to index.
2. Patients do have >1 advanced therapy filled on index date.

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3. Physician diagnosis of RA (in any position) during the 1-year pre-index period, or on 
the index date:

ICD-9 = 714.0x–714.4x, 714.81;

ICD-10 = M05.x, M06.0–M06.3, M06.8–M06.9.
4. Patients don’t have claims for other conditions for which TOFA and/or advanced
therapies are used, during the anytime pre-index period or on the index date.
Table 1.
Exclusionary Diagnoses
Disease
ICD-9 diagnosis code
ICD-10 diagnosis code
AnkylosingSpondylitis
720.0x
M45.0 - M45.9
Crohn's Disease
555.xx
K50.*
Psoriasis
696.1x
L40.0*-L40.4*,L40.8*-L40.9*
Psoriatic Arthritis
696.0x
L40.5*
Ulcerative Colitis
556.xx
K51.*
5. Commercially insured or Medicare beneficiaries at index.
6. Continuous enrollment during 1 (360 days)-year pre- (pre-index period) and 
1-year post- index.
7. Age 18+ years at index.
8. Study cohorts.
a.
TOFA Advanced Therapy Naïve OOP Cost Cohort.

Identify those with no advanced therapy (bDMARDs/JAK inhibitors) anytime
before index TOFA prescription.
b. ETN or ADA to TOFA OOP Cost and TNFi Cycling Cohort.

Identify those that had ADA or ETN, but not both, and no other advanced
therapy anytime pre-index TOFA (See Appendix 1).
c.
ADA to ETN TNFi Cycling Cohort.

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
In those newly starting ETN, patient must have a claim for ADA and no other 
advanced therapy (See Appendix 1), including index ETN (pharmacy/admin
claims), anytime pre- index ETN.
d. ETN to ADA TNFi Cycling Cohort.

In those newly starting ADA, patient must have a claim for ETN and no other
advanced therapy (See Appendix 1), including index ADA (pharmacy/admin
claims), anytime pre- index ADA.
NOTE: Advanced therapy = TNFi and nonTNFi bDMARDs and JAK inhibitors;
Alternative MOA medications= nonTNFi bDMARD and JAKi.
8.3. Variables
There are two primary baseline periods of interest from which variables of interests will be
evaluated: 1) 12-months fixed pre-index period and 2) a variable length baseline period is the
maximal continuous enrollment window prior to index and at least 1-year pre-index.  The
primary post-index period is 12 months including the index date. Other observation periods
are noted below.
Variable
Role
Data
source(s)
Operational definition
Demographics (Table 1)
Age
Baseline Characteristic All
Age will be defined as of the index year.
Age groups
Baseline Characteristic All
Patients will be assigned to one of the following age
groups based index age: 18–44, 45–64, and 65yo.
Gender
Baseline Characteristic All
Gender will be captured from enrollment data.
Insurance type
Baseline Characteristic All
Whether the patient was covered under a commercial
or Medicare Supplemental (Truven DataType)
insurance plan will be captured.
Plan type
Baseline Characteristic All
HMO, EPO, GPO, etc via.
PlanType.
Geographic region
Baseline Characteristic All
The United States (U.S.) region in which the study
patient is enrolled in a health plan will be determined
and reported and states will be categorized into five
geographic regions: Northeast, South, Midwest, West,
Unknown (https://www2.census.gov/geo/pdfs/maps-
data/maps/reference/us_regdiv.pdf).
Variable length baseline Baseline Characteristic All
Identify the duration of variable length (ie, all
available pre-index continuous enrollment) baseline
period.

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Variable
Role
Data
source(s)
Operational definition
RA-Related Medication Use in Pre-Index (Table 2)
Pre-index biologic
DMARD use
Baseline Characteristic All
A count of unique (on different days) pharmacy/admin
claims on different days for ADA/ETN will be created
during the 12 month baseline period.
Time from last pre-
index bDMARD to
index
Baseline Characteristic All
A variable for the interval between last ADA/ETN
pharmacy/administration claimand index. Stratify by
<3 mos, 3-<6 mos and
6-12 mos pre-index.
Time from first pre-
index bDMARD to
index
Baseline Characteristic All
A variable for the interval between first ADA/ETN
pharmacy/administration claim during the variable
length baseline and index.
Stratify by <6, 6-12,
≥12 mos.
Pre-index NB- DMARD
use
Baseline Characteristic All
The use of the 4 main NB- DMARDS (methotrexate-
MTX,sulfasalazine-SSZ, hydroxychloroquine-HCQ,
and leflunomide- LEF), and the other NB-DMARDS
(See codes in Appendix 2) will be identified during the
pre-index period.
Indicator variables will identify the
specific medications (MTX, SSZ, HCQ, LEF and
other NB-DMARDs) used during the 12 mos
pre-index period. A count will be created to identify
the number of different NB-DMARDS during
variable length baseline and number of
prescriptions/administrations on different days
received during the 12-mos pre-index period.

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Variable
Role
Data
source(s)
Operational definition
RA-Related Medical History (Table 2)
Pre-index
hospitalization for RA
0/1 flags will be created to determine if the patient had
an inpatient visit (length of stay>1 day) with an RA
diagnosis (any claim position) in the 90 days before
the index date and in the
12 months before the index date. A separate variable
will be created for identifying the number of RA
related hospitalizations during the entire 12-month
baseline period.
Disease duration
Baseline Characteristic All
The number of days from the earliest claim with a
diagnosis of RA in the variable length baseline until
the index date will be identified.
Pre-index Claims based
Index of RA Severity
(CIRAS)
Baseline Characteristic Al
The Claims-based Index for RA Severity will be
implemented. CIRAS (12) provides a single value of
severity using the following 9 measures: age, gender,
inflammatory marker tests, rehabilitation visits, Felty
Syndrome, platelet orders, rheumatoid factor tests,
chemistry panels, and rheumatologist visits (See
Appendix 3).
Comorbidities (Table 3)
Pre-index Quan-
Charlson Comorbidity
Index score
Baseline Characteristic All
A comorbidity score will be calculated based on the
presence of diagnosis codes on medical claims in the
12-months pre-index period. The Quan-Charlson (13)
Comorbidity Index (QCCI) score will also be
categorized into the following groups: zero, one to
two, three to four, and five or more CCI
comorbidities.
Comorbidities of
interest
Baseline Characteristic All
0/1 flags will be created to identify the
presence of the following comorbidities
during the 12-month baseline period (see
Appendix 4).

Cardiovasculardiseases.

Chronic obstructive pulmonary disease (COPD).

Asthma.

Kidneydisease.

Diabetes.

Depression.

Anxiety.

Liver disease.

Sleep disorders.

Hypertension.

Hyperlipidemia.

Interstitial lung disease.

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Variable
Role
Data
source(s)
Operational definition
Cumulative OOP Costs
pre-index
Baseline
Characteristic
All
The total, pharmacy and medical OOP costs
(deductible+copay+coinsurance) resourceuse
from January 1 of index year through Index.
Index Date OOP costs
Baseline
Characteristic
All
Total, pharmacy (excluding index medication)
and medical OOP costs on index date.
Index Medication (Table 4)
Index Prescriber
Baseline
Characteristic
All
Top 5 index medication prescriber specialties
and other or unknown will be identified.
Index month/year
Baseline
Characteristic
All
The month and year of the patient’s index date
(start of TOFA, ETN, ADA) will be identified.
Index Medication OOP
costs
Baseline
Characteristic
All
The index medication pharmacy OOP costs
(deductible+copay+coinsurance) willbe identified
for the first index medication rx and cumulative by
month (1-12) of follow-up (only looking at
pharmacy claims here noting index event is a
prescription fill).
Index combination vs.
monotherapy regimen
status
Baseline
Characteristic
All
Patients with a use of one of the 4 main NB-
DMARDs (injectable and oral MTX, SSZ, HCQ, 
LEF) within 90 days on or after the index date will
be considered as being treated with combination
therapy regimen, others will be classified as
monotherapy. For monotherapy, will evaluate
6-mos pre-index use of each of the four main and
other NB- DMARDs. For combination regiment,
will stratify by 6 mos pre-index use of the four
main and other NB-DMARDs.
Post-Index Treatment Patterns (Table 4)
Treatment Persistence
(5 groups)
Outcome
All
Persistent with the index medication will be
defined as not having a gap in therapy of at
least 60 days between fills/admins. For retail
pharmacy (rx) claims the day supply will be
utilized and rounded to the nearest 28-day
supply for ETN and ADA and 30- day supply
for TOFA. For subcutaneous ETN and ADA
administrations, a 28-day supply will be
assumed.

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Variable
Role
Data
source(s)
Operational definition
A gap of at least 60 days between the run- out
date (rx/admin date + day supply-1) and the
next rx/admin date will be considered
non-persistence. Patients with early refills will
be allowed to accumulate a stockpile of the
index medication of up to 14 days for later use.
However, an administration will negate
accumulation of index medication. A 0/1 flag
will be created to identify if the patient is
persistent with their index medication before
the end of the 12 month follow-up period.
Patients who are not persistent for the entire
follow-up period will be classified into the
following mutually exclusive categories based
on the first occurrence of non-persistence:
Switch immediately: Patients will be
classified as switching immediately if they
initiate a non-index advanced therapy (see all
medications in Appendix1) before end of a
60-day gap in index.
Discontinue then switch: Gap in the index
therapy of at least 60 days and the first
medication observed after the gap is an
advanced therapy different from index
medication.
Discontinue then restart: Gap in the index
therapy of at least 60 days and the first
advanced therapy observed after the gap is the
index medication.
Discontinue without switch or restart: Gap in
index therapy of at least 60 days and there are
no claims for either the index med or a
different advanced therapy for the remainder
of the follow-up period.
Switch any time
Outcome
All
In addition to the 4 mutually exclusive
treatment patterns, patients with a switch
medication any time during the 12-month
follow-up period will be identified.

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Variable
Role
Data
source(s)
Operational definition
Days to immediate
switch
Outcomes
All
Days to immediate switch =immediate
switch date-index date+1.
Days to any switch
Outcomes
All
Day to any switch =immediate/delayed
switch date-index date+1.
Days to discontinue
Days to discontinue= date of last persistent
index medication rx/administration+days
supply- index date+1.
Index Medication
Persistence duration of
therapy
Outcome
All
Days to discontinue or immediate switch or or
end of 1yr post-index period if remained
persistent (whichever comes first).
NB-DMARD use
Outcome
All
1.For patients who initiate combination
therapy, will look for select NBDMARD
(MTX, SSZ, LEF, HCQ) discontinuation or
switch from start of NB-DMARD through end
of 12-month post-index period.
Definitions of treatment patterns are similar to
5 persistent groups above for index advanced
therapy medications and using a 60 day gap. A
28-day supply will be assumed for MTX
administrations.
2. For those who initiated advanced
monotherapy, addition of one for four main or
other NBDMARDs will be evaluated.

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Variable
Role
Data
source(s)
Operational definition
Medication
Effectiveness Proxy
Algorithm (Curtis et
al)14
Outcome
All
Medication effectiveness at one year after the
index date will be determined using the
following six criteria. For each of the 6 criteria,
a 0/1 flag will be created. Patients who are
effectively treated for each of the 6 criteria will
be considered effectively treated. Patients who
fail any of the 6 criteria are therefore not
effectively treated.
1.High adherence to index agent: For all
medications, a proportion of days covered
(PDC) will be calculated based on total days
supply over the 1 year follow-up. The PDC will
be calculated by using the date of service and the
day supply for each fill of the index medication.
Patients with early refills will be allowed to
stockpile medications up to a maximum of
14 days total for later use.
Patients with PDC ≥0.8 will be considered
highly adherent and effectively treated. The
original Curtis algorithm referenced an
MPR;however, more recent studies are using
PDCs or similarly described measure.15

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Variable
Role
Data
source(s)
Operational definition
2.No increase in dose (see below)
for index medication compared to the
starting dose. Dose escalation will be
identified per the criteria listed
below.
ADA: At least 1 claim in the follow-up period with
an average weekly dose of at least 40 mg/week.
ETN: At least 1 claim in the follow-up
period with an average weekly dose of at
least 100 mg/week.
TOFA: At least 1 claim in the
follow-up period with an average
weekly dose of at least 20 mg/day
for IR and 22 mg/day for XR.
3.No switching from the index medication
to a different advanced therapy. A switch
will be defined as use of a different bDMARD
or JAKi any time during the follow-up period
noting the availability of newer advanced
therapies after original 2011 Curtis algorithm
publication.
4.No adding of a new non-biologic
DMARD to the index therapy.
Measure has been modified to
distinguish outcomes for advanced
monotherapyvs. NB-DMARD
comobination regiments, noting
patients may not have NB-DMARD in
6-mos pre-indes but start a
combination regimen. For those
starting a monotherapy index
medication regimen, the initiation of a
select NB-DMARD will be identified
in the follow up period as addition of
NB-DMARD. For those starting a
combination index medication
regimen, presence of a different NB-
DMARD in follow-up will be flagged
as failing the algorithm.

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Variable
Role
Data
source(s)
Operational definition
5. Oral glucocorticoids. Only National Drug
Code (NDC) codes for oral glucocorticoids will be
included.
5a. For patients with no claims for oral
glucocorticoid prescriptions in the six months
prior to the index date: cannot receive more than
30 days of oral glucocorticoids between (index
date + 89) to (index date + 359). 30 days of oral
glucocorticoids will be determined by summing
up the day supply of all glucocorticoids claims
with a fill date between (index date + 89) to (index
date + 359).
5b. For patients with claims for oral
glucocorticoids during the six months prior to the
index date: No increase in oral glucocorticoid dose
≥20% during months 6- 12 after index compared
to the 6 months before the index date. Increase in
oral glucocorticoids will be determined from the
prednisone equivalent dose for all glucocorticoid
claims filled during the respective time periods.
6. At most one parenteral or
intra- articular glucocorticoid joint injection
on unique days after the patient had been on
biologic treatment for more than three months
between (index date + 89) to (index date + 359).
CPT codes 20600, 20605, 20610.
Change in Resource Use and Costs (Tables 5 and 6)
RA-related healthcare
resource use
Outcome
All
The number of patients with and number of encounters
(including zeros) for each
RA- related medical and pharmacy resource use will
be evaluated in the 12-month pre- and post-index
periods.
See Section 8.3.1 for details on calculating cost and
healthcare utilization.
All-cause healthcare
resource use
Outcome
All
The number of patients with and number of claims
(including zeros) for each all-cause medical and
pharmacy resource use will be evaluated in the
12-month pre- and post-index periods.
See Section 8.3.1 for details on calculating cost and
healthcare utilization.

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Variable
Role
Data
source(s)
Operational definition
Healthcare Costs
Outcome
All
RA-related and all-cause resource use attributable
health care costs will be computed as the combined
health plan/other payer (ex, Coordination of Benefits
for Medicare Supplemental in Truven) and patient
paid amounts.
See Section 8.3.1 for details on calculating cost and
healthcare utilization.
8.3.1. Health Care Cost and Utilization
All cost and utilization measures will be identified in the 12-month pre-index period and the
12- month post-index period. Claims occurring on the index date will be considered part of
the post-index period.  Baseline and follow-up costs and the change in 12-month costs from
baseline to follow-up will then be examined.  Cost measures will comprise the total amount
paid by the health plan and patient.

All-cause health care resource utilization- Medical resource utilization will be
calculated for outpatient visits, emergency department (ED) visits, and inpatient
admissions and pharmacy utilization will include all paid prescription claims.

RA-related resource health care utilization.

Medical resource utilization related to RA will be calculated for outpatient visits,
ED visits, and inpatient admissions with an RA diagnosis in any claim position.

RA-related treatment administrations (with and without a concurrent RA
diagnosis) will also be identified by presence of HCPCS codes for ADA, ETN,
other TNFI and other advanced therapy; methotrexate or other NB-DMARD; low,
medium and high potency orticosteroids; NSAIDS; and strong and weak opioids
(See Appendices Appendix 1, Appendix 2, Appendix 5).

Pharmacy utilization will included all paid prescription claims for TOFA, ADA,
ETN, another TNFI or alternative MOA; methotrexate, sulfasalazine, leflunomide,
hydroxychrolorquine and other NB-DMARDs; low, medium, high potency
corticosteroids; NSAIDS; and weak and strong opioids (See Appendices
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
Health care costs-Health care costs will be computed as the combined health plan
and patient paid amounts. Costs will be calculated as total costs, pharmacy/treatment
costs, and medical costs.
Medical costs will be further broken down into outpatient
costs, emergency room costs, and inpatient costs. Costs will be adjusted using the
annual medical care component of the Consumer Price Index (CPI) to reflect
inflation between 2014 (the earliest start of the pre-index period) and 2017 (the cost
of claims occurring in 2018 will not be adjusted).16

Costs from other payers are of importance for older patients dually eligible for
commercial and Medicare coverage. Payments from Medicare (and other payers) will 
be estimated based on coordination of benefits information obtained by the health
plan in its usual course of business. This study will incorporate the amounts
estimated to be paid by other payers for a total paid or allowable amount.17

All-cause health care costs- calculated as total of medical (outpatient, inpatient and
ED) visits regardless of reason and all prescription costs.

RA-related health care costs- RA-related health care costs will be calculated as total
medical and treatment costs related to RA.

RA-related medical costs will include costs for outpatient, inpatient and ED vists
with an RA diagnosis in any claim position

For outpatient visits with an RA diagnosis and administration of an RA-
related treatment (see below), the non-adminsitration costs will be
characterized as part of RA-related Medical costs and the administration costs
will be part of RA-related Treatment costs below.

Outpatient visits without an RA diagnosis, but with administration of an RA-
related treatment will not be included in the RA-related Medical costs, but will be
evaluated for administration costs as part of RA-relatedTreatment costs below.
Note: given variability in capture of HCPCS codes in inpatient setting across databases,
RA- related treatement costs are limited to outpatient visits only.

RA-related treatment costs will include the cost of:

outpatient administration of bDMARDs, NB-DMARDs, corticosterioids,
NSAIDS, and opioids based on HCPCS codes regardless of RA diagnosis on
claim, AND,

cost of prescription fills for TOFA/ADA, ETN, other advanced therapies,
NB-DMARDs, corticosterioids, NSAIDS, and opioids.

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8.4. Data Source
8.4.1. Truven MarketScan Research Database
The Truven Health MarketScan Research Databases reflects the combined healthcare service
use of individuals covered by Truven Health clients (including employers, health plans, and
hospitals) nationwide.  Truven Health builds databases comprise the healthcare experience of
the clients’ covered populations, as well as information about the populations themselves and
the providers that serve them.  MarketScan Research Databases provide detailed cost,
utilization, and outcomes data for healthcare services performed in both inpatient and
outpatient settings. In the claims databases, the medical services are linked to outpatient
prescription drug claims and person-level enrollment data using unique enrollee identifiers.
The MarketScan Commercial Database contains the healthcare experience of privately
insured individuals.  Coverage is provided under a variety of fee-for-service, fully capitated,
and partially capitated health plans, including preferred provider organizations, point of
service plans, indemnity plans, and health maintenance organizations.
The data that make up the Commercial Database are stored in the following tables:

The Inpatient Admissions Table contains records that summarize information about a
hospital admission. Truven Health constructs this table after identifying all of the
service records associated with an admission (eg, the hospital claims, physician
claims, surgeon claims, and claims from independent labs). Similar information
(such as payments for professional services) is then summed across the claims. The
admission record includes the principal procedure and diagnosis, Major Diagnostic
Category, and Diagnosis-Related Group. It also includes all diagnoses and
procedures (up to 14 each) found on the service records.

The Inpatient Services Table contains the individual claims that are summed to create
the inpatient admission records.  An admission identifier on both the Inpatient
Admissions and the Inpatient Services Tables identifies the claims that make up each
admission record.

The Outpatient Services Table comprises services that were rendered in a doctor’s
office, hospital outpatient facility, or other outpatient facility.

The Facility Header Table contains the header records from facility claims for
inpatient and outpatient services, including full diagnosis information.

The Outpatient Pharmaceutical Claims Table contains outpatient prescription drug
data from multiple sources, including mail-order data.  Each record includes National
Drug Code (NDC), therapeutic class, ingredient cost, dispensing fee, copayment,
deductible, total gross payment, and other data elements.

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
The RED BOOK™Supplement Table contains RED BOOK variables that enhance
prescription drug analyses. These variables are linked to the Outpatient
Pharmaceutical Claims Table by NDC.

The Annual Enrollment Summary Table provides a single record per year for each
enrollee, showing enrollment start and end dates and, for some demographic
variables, the most prevalent demographic and plan information; for other variables,
monthly values are included.

The Enrollment Detail Table provides a single record per month of enrollment for
each enrollee, with detailed demographic information.

The Population Aggregate Table provides average counts of the covered (insured)
population to use for rate-supported analysis. The counts are recorded by several
demographic variables (eg, age group, gender, region, etc.).
The MarketScan Medicare Supplemental Database contains the healthcare experience of
individuals with Medicare supplemental insurance paid for by employers.  Both the
Medicare-covered portion of payment (represented as Coordination of Benefits Amount, or
COB) and the employer-paid portion are included in this database. The tables that make up
the Medicare Supplemental Database are the same as those that make up the Commercial
Database.
Claims are not included in the database until they have been adjudicated; there is a lag of
approximately six months after the close of a calendar year or a quarter between services
provided and their inclusion in the Research Databases.  However, the Early View Database
has a 90-day lag that includes paid amounts for 100 percent of prescription drugs,
approximately 85 percent of physician office visits, and approximately 70 percent of hospital
claims.  The MarketScan Early View Database includes all of the components found in the
standard MarketScan Commercial and Medicare Supplemental Databases. It includes
standardized inpatient, outpatient, pharmaceutical, and health-plan enrollment data. The
MarketScan Early View Database captures healthcare services incurred up to 90 days before
data release and includes only adjudicated claims. However, the medical component of care
for some patients will not be complete, since some claims (particularly inpatient claims) take
longer to be adjudicated. Because this study is examining only comorbidities prior to and
treatments during or prior to tofacitinib initiation fully adjudicated claims are not required 
and all available data will be used including Commercial, Medicare Supplemental, and Early
View Databases.
8.5. Study Size
The sample size for this study is fixed by the duration of the observation window. No formal
sample size computation was performed.  All patients who meet inclusion/exclusion criteria
will be included in the analyses.

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8.6. Data Management
All data is electronically obtained from the US Claims databases and delivered to Pfizer. The
data are stored in the Real World Data and Analysis DataMart (Teradata Server Version 15).
Analysis is done using SAS Version 9.4 on Red Hat Linux.
8.7. Data Analysis
8.7.1. Primary Objectives
8.7.1.1. To Compare 12-month Post-Index Medication Persistence Duration (days) by
TOFA Index Prescription OOP Costs and TNFi Cycling with ETN and ADA vs. TOFA
Switching
For this objective both descriptive and multivariable analysis will be conducted. For the
descriptive analysis, treatment persistence duration (days) with index medication at
12-months will be compared for those with low (≤median) vs. high (> median) OOP costs 
and for those who switch from ADA to ETN vs. ADA to TOFA and ETN to ADA vs. ETN 
to TOFA. 
8.7.2. Secondary Objectives
8.7.2.1. Explore the Differences in Demographic and Clinical Characteristics Between
TOFA Index Prescription OOP Costs and TNFi Cycling with ETN and ADA vs. TOFA
Switching Cohorts
For this objective descriptive analysis will be conducted.  The goal of this objective will be to
describe the respective cohorts and explore the presence of demographic and clinical
characteristics differences between the cohorts that will inform multivariable analyses.
Known demographic characteristics (eg, age, gender, geographic location) will be
summarized.  In addition, other patient characteristics (eg, pre-index RA medication use and
medical history, comoribidity status, cumulative/index OOP costs) will be evaluated. Index
medication prescriber, regimen, and OOP costs will also be described.
8.7.2.2. Compare Treatment Patterns Including Dosing, Adherence, Persistence
Treatment Patterns Between TOFA Index Prescription OOP Costs and TNFi Cycling 
with ETN and ADA vs. TOFA Switching Cohorts
For this objective, treatment patterns will be summarized across the cohorts of interest.
Specific treatment patterns include changes in use of concomitant NB-DMARDs, number and
proportion of patients in the five treatment persistent groups (persistent, switch immediately,
discontinue and switch, discontinue and restart, discontinue and no switch or restart), switch
anytime, or effectively treated (meeting each of 6 Curtis algorithm criteria) as well as times to
immediate and anytime switch and discontinuation. Times to discontinuation, switching or
either will be assessed with Kaplan-Meier curves and Cox proportional hazards models.
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8.7.2.3. Compare All-Cause and RA-Related Health Care Utilization Between TOFA
Index Prescription OOP Costs and TNFi Cycling with ETN and ADA vs. TOFA
Switching Cohorts
For this objective descriptive analysis will be conducted.  All-cause and RA-related
pharmacy and medical resource utilization measures (flags and 12-month counts) will be
presented per patient during the 12-month baseline and follow-up periods. In addition,
changes from baseline to follow-up will be evaluated.
8.7.2.4. Compare All-Cause and RA-Related Healthcare Costs Between TOFA Index
Prescription OOP Costs and TNFi Cycling with ETN and ADA vs. TOFA Switching
Cohorts
For this objective descriptive and multivariable analysis will be conducted. For the
descriptive analysis, 12-month pre- and post-index cost measures will be presented per
patient during the baseline and follow-up. The change in 12-month costs from the baseline 
to the follow-up will also be calculated. In addition, total all-cause cost will be presented in 
each of the months of the baseline and follow-up. The mean cost in each month will be
included on a figure demonstrating the trend in costs over time.  Multivariable analysis of
follow-up health care cost will also be conducted using generalized linear models (see 
Section 8.7.4).
 
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8.7.3. Descriptive Analysis
All study variables, including pre- and post-index measures and changes in these measures,
will initially be analyzed descriptively. In general, numbers and percents will be provided for
dichotomous and polytomous variables, while means, medians, and standard deviations will
be provided for continuous variables. Missing or unavailable data will not be imputed.
Results will be stratified by treatment cohort, bivariate comparisons of pre- and post-index
measures will be provided, and appropriate tests (eg, t-test, Mann Whitney-U test, chi-square
test) will be used based on the distribution of the measure. The analysis that is performed 
(ie, the methods that are used and the patients who are included) will be specific to the 
objective being examined. Descriptive techniques will be implemented for each objective.
8.7.4. Multivariate Analysis
To control for possible confounding of the relationship between the outcomes and
independent variable of interest, select objectives will be conducted utilizing multivariable
methods as described above.
Final outcomes for multivariate analysis will be selected after review of descriptive results.
Possible outcomes of interest include: total all-cause health care cost, total RA-related health
care cost, cost of bDMARDs/tofacitinib/administration/NB-DMARDS, medication
effectiveness (yes vs. no).
For each model, specific predictors to be included will be determined based upon clinical
rationale and statistical significance. Variables listed in Section 8.3 will be considered for
inclusion in the multivariable models. Additional variables identified throughout the course
of the study will also be considered. Following standard procedure, regression diagnostics
will be performed for each model to assess goodness of fit and violations of model
assumptions (eg, multicollinearity, heteroskedasticity).  When there are violations of the
model, programmers will note them and make appropriate corrections to the data
(ie, typically through transformation of either the independent or dependent variables) or in 
the method of estimation.
In particular, generalized linear models will be fit, using appropriate distributions and links 
for the nature of the data (eg, normally-distributed data with identity link, binary data and
logit link). Results will be displayed on the original scale (that is, the inverse link). If
sufficient sample size, tofacitinib IR and tofacitinib XR will be treated as separate groups.
That is, contrast statements will be used to average the two groups when comparing to 
bDMARDs.  Point estimates (that is, mean differences, ratios, odds ratios), 95 percent
confidence intervals, and p- values will be presented for contrasts; ANOVA table will be 
presented to display the strength of the independent variables, including point estimates and
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8.7.5. Cost Data
Because health care costs are often skewed, estimated cost measures will be modeled using a
gamma regression model. Coefficients from a generalized linear model (GLM) are estimated
cost ratios. Cost ratios, 95 percent confidence intervals, and p-values will be presented for
each covariate included in the final model.  For ease of interpretation and comparison with 
the bivariate results, the average cost will be predicted for each cohort and may also be 
predicted for pre-determined levels of other patient characteristics (eg, combination vs. 
monotherapy, gender).
If a significant number of patients have zero values for costs, estimated cost measures will be
compared using a two-part model (ie, one equation estimating the probability of any cost and
a GLM with a gamma distribution and log link estimating the level of cost). This method
avoids potential difficulties introduced by transformation and retransformation of the
dependent variable.
If there is an excessive number of zero-dollar cost patients, then only logistic regression
prediciting the probability of nonzero costs will be run.
Odds ratios, 95 percent confidence intervals, and p-values will be presented for each
covariate included in the logistic model estimating the probability of non-zero costs. Cost 
ratios, 95 percent confidence intervals, and p-values will be presented for each covariate 
included in the GLM model estimating the level on costs.  Combined results will displayed.
8.7.6. Dichotomous Data
The probability of being effectively treated, persistent, and anytime switching to advanced
therapy at one year will be modeled using logistic regression. Logistic regression models fit
a maximum-likelihood logit model.  For ease of interpretation, the results of logistic
regression will be presented as odds ratios, 95 percent confidence intervals, and p-values for
each covariate included in the final model.
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8.8. Quality Control
This is a retrospective study, so issues of quality control at study sites, eg, data queries, do
not apply. Analyses are programmed according the specifications in the protocol, and if
applicable, the statistical analysis plan and documented in a programming plan. Final
deliverables are reviewed and verified by a second, independent programmer who may also
perform double programming. All quality checks are documented in the programming plan.
8.9. Limitations of the Research Methods
Limitations that are general to claims database analyses and specific to this study should be
noted. First, diagnosis of autoimmune conditions will be identified using ICD-9/10-CM
diagnosis codes, which are subject to potential miscoding. Second, clinical and laboratory
data are not available, thus we are relying on adjudicated claims data for characterizing
medical history, treatment exposure and outcomes. Along these lines, we may be missing
information on services or resources for which claims were not submitted such as medication
samples. We will use 2-year pre-index continuous enrollment to increase the likelihood of
capturing patient baseline characteristics including prior advanced therapy experience.
However, this may not be sufficient and may bias the sample to patients who stay in health 
plans and may be healthier.
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Further, we require 1-year of post-index enrollment across groups to ensure similar follow
up, but this may not be representative of health plan enrollees and may bias toward longer
treatment duration or higher healthcare resource use and costs. This study will include an
examination of medication effectiveness at 1 year among all biologic users. Effectiveness
will be measured using a validated algorithm; however, the algorithm was not validated for
all medications being included. Specifically, tofacitinib was approved for treatment of RA
after the algorithm was developed. Although this study will also evaluate outcomes
 
using multivariable analysis to control for observable
differences between groups, there may be unobservable differences as common with
observational research designs.
8.10. Other Aspects
Not Applicable.
9. PROTECTION OF HUMAN SUBJECTS
All parties will ensure protection of patient personal data and will not include patient names
on any sponsor forms, reports, publications, or in any other disclosures, except where
required by laws.  In case of data transfer, Pfizer will maintain high standards of
confidentiality and protection of patient personal data.
As this is a retrospective non-interventional study using fully anonymized secondary data, no
additional informed consent is required.
9.1. Patient Information
This study involves data that exist in anonymized structured format and contain no patient
personal information.
9.2. Patient Consent
As this study involves anonymized structured 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.
9.3. Institutional Review Board (IRB)/Independent Ethics Committee (IEC)
IRB is not required for this study as it uses commercially available de-identified secondary
data sources and is considered exempt from the requirements for “human subjects research”
in the US.
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 Good Practices for Outcomes Research issued by the International Society for
Pharmacoeconomics and Outcomes Research (ISPOR).
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10. MANAGEMENT AND REPORTING OF ADVERSE EVENTS/ADVERSE
REACTIONS
This study involves data that exist as structured data by the time of study start. 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) (ie, identifiable
patient, identifiable reporter, a suspect product, and event) cannot be met.
11. PLANS FOR DISSEMINATING AND COMMUNICATING STUDY RESULTS
For all publications relating to the Study, Pfizer will comply with recognized ethical
standards concerning publications and authorship, including Section II - “Ethical
Considerations in the Conduct and Reporting of Research” of the Uniform Requirements for
Manuscripts Submitted to Biomedical Journals,
http://www.icmje.org/index.html#authorship, established by the International Committee of 
Medical Journal Editors.
In the event of any prohibition or restriction imposed (eg, clinical hold) by an applicable
competent authority in any area of the world, or if the investigator is aware of any new
information which might influence the evaluation of the benefits and risks of a Pfizer
product, Pfizer should be informed immediately.

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12. REFERENCES
1.
Chastek B, Chen CI, Proudfoot C, Shinde S, Kuznik A, Wei W.Treatment Persistence
and Healthcare Costs Among Patients with Rheumatoid Arthritis Changing Biologics
in the USA.Adv Ther. 2017 Nov;34(11):2422-2435. doi: 10.1007/s12325-017-0617-5.
Epub 2017 Oct 16.
2.
Chastek B, Becker LK, Chen CI, Mahajan P, Curtis JR.Outcomes of tumor necrosis
factor inhibitor cycling versus switching to a disease-modifying anti-rheumatic drug
with a new mechanism of action among patients with rheumatoid arthritis. J Med Econ.
2017 May;20(5):464-473. doi: 10.1080/13696998.2016.1275653. Epub 2017 Jan 4.
3.
Bonafede MM, Curtis JR, McMorrow D, Mahajan P, Chen CI. Treatment effectiveness
and treatment patterns among rheumatoid arthritis patients after switching from a
tumor necrosis factor inhibitor to another medication. Clinicoecon Outcomes Res. 2016 
Dec 2;8:707-715.
4.
Wei W, Knapp K, Wang L, Chen CI, Craig GL, Ferguson K, Schwartzman S.Treatment
Persistence and Clinical Outcomes of Tumor Necrosis Factor Inhibitor Cycling or 
Switching to a New Mechanism of Action Therapy: Real-world Observational Study of
Rheumatoid Arthritis Patients in the United States with Prior Tumor Necrosis Factor
Inhibitor Therapy.Adv Ther. 2017 Aug;34(8):1936-1952. doi: 10.1007/s12325-017-
0578-8. Epub 2017 Jul 3.
5.
Harnett J, Wiederkehr D, Gerber R, Gruben D, Koenig A, Bourret J3Real-world 
evaluation of TNF-inhibitor utilization in rheumatoid arthritis. J Med Econ.
2016;19(2):91-102. doi: 10.3111/13696998.2015.1099538. Epub 2015 Oct 27.
6.
Gottenberg JE, Brocq O, Perdriger A, et al.  Non-TNF-Targeted Biologic vs a Second
Anti- TNF Drug to Treat Rheumatoid Arthritis in Patients With Insufficient Response
to a First Anti-TNF Drug: A Randomized Clinical Trial.JAMA. 2016 Sep
20;316(11):1172-1180. doi: 10.1001/jama.2016.13512.
7.
Emery P, Gottenberg JE, Rubbert-Roth A, et al. Rituximab versus an alternative TNF
inhibitor in patients with rheumatoid arthritis who failed to respond to a single previous
TNF inhibitor: SWITCH-RA, a global, observational, comparative effectiveness
study.Ann Rheum Dis. 2015 Jun;74(6):979-84. doi: 10.1136/annrheumdis-2013-
203993. Epub 2014 Jan 17.
8.
Atzinger CB, Guo JJ. Biologic Disease-Modifying Antirheumatic Drugs in a National,
Privately Insured Population: Utilization, Expenditures, and Price Trends. Am Health
Drug Benefits. 2017 Feb;10(1):27-36.
9.
Hopson S, Saverno K, Liu LZ, AL-Sabbagh A, Orazem J, Costantino ME, Pasquale
MK. Impact of Out-of-Pocket Costs on Prescription Fills Among New Initiators of
Biologic Therapies for Rheumatoid Arthritis. J Manag Care Spec Pharm. 2016 
Feb;22(2):122-30. doi: 10.18553/jmcp.2016.14261. Epub 2015 Dec 14.

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10.
Curkendall S, Patel V, Gleeson M, Campbell RS, Zagari M, Dubois R.Compliance with
biologic therapies for rheumatoid arthritis: do patient out-of-pocket payments matter?
Arthritis Rheum. 2008 Oct 15;59(10):1519-26. doi: 10.1002/art.24114.
11.
Doshi JA, Hu T, Li P, Pettit AR, Yu X, Blum M.Specialty Tier-Level Cost Sharing and
Biologic Agent Use in the Medicare Part D Initial Coverage Period Among
Beneficiaries With Rheumatoid Arthritis. Arthritis Care Res (Hoboken). 2016 
Nov;68(11):1624-1630. doi: 10.1002/acr.22880.
12.
Ting G, Schneeweiss S, Scranton R, Katz JN, Weinblatt ME, Young M, Avorn J,
Solomon DH. Development of a health care utilisation data-based index for rheumatoid 
arthritis severity: a preliminary study.  Arthritis Res Ther. 2008;10(4):R95. doi: 
10.1186/ar2482. Epub 2008 Aug 21.
13.
Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, Januel JM, Sundararajan V.
Updating and validating the Charlson comorbidity index and score for risk adjustment 
in hospital discharge abstracts using data from 6 countries. Am J Epidemiol.
2011;173(6):676- 82.
14.
Curtis JR, Baddley JW, Yang S, et al., Derivation and preliminary validation of an
administrative claims-based algorithm for the effectiveness of medications for
rheumatoid arthritis. Arthritis Res Ther, 2011. 13(5): p. R155.
15.
Curtis JR, Chastek B, Becker L, et al.  Cost and effectiveness of biologics for
rheumatoid arthritis in a commercially insured population. J Manag Care Spe Pharm.
2015 Apr; 21 (4): 318-29.
16.
US Department of Labor, Bureau of Labor Statistics. Consumer Price Index. Medical
Care. Series ID: CUUR0000SAM. Washington, DC: U.S. Dept. of Labor, Bureau of
Labor Statistics. http://data.bls.gov/cgi-bin/surveymost?cu.
CCI

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13. LIST OF TABLES
SEE ATTACHED EXCEL WORKBOOK FOR DRAFT TABLES
TABLE 1. DEMOGRAPHICS
TABLE 2. RA CHARACTERISTICS
TABLE 3.  COMORBIDITIES TABLE
TABLE 4. TREATMENT PATTERNS
TABLE 5.  HEALTHCARE RESOURCE USE
TABLE 6.  COSTS
14. LIST OF FIGURES
Figure 1.
Study Diagram..........................................................................................15
15. ANNEX 1. LIST OF STAND ALONE DOCUMENTS
None.

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16. APPENDICES
Appendix 1. ADVANCED THERAPIES
Generic Name^
Brand Name
Route of Admin. GPI
codes^
HCPCS
TNFi
Adalimumab
Humira
SC
66270015
J0135
Etanercept
Enbrel
SC
66290030
J1438
Golimumab
Simponi, Aria
SC/ IV
66270040
J1602
Certolizumab pegol
Cimzia
SC
52505020
C9249, J0717, J0718
Infliximab
Remicade,
Renflexis,
Inflectra
IV
52505040
J1745, Q5102
Alternative MOA
Tofacitinib
Xeljanz
PO
66603065
None
Baricitinib
Olumiant
PO
66603010
None
Abatacept
Orencia
IV/SC
66400010
C9230 J0129
Anakinra
Kineret
SC
66260010
None
Tocilizumab
Actemra
IV/SC
66500070
C9264 J3262
Rituximab
Rituxan
IV
21353060
J9310
Sarilumab
Kevzara
SC
66500060
None
Unspecified
J3590, J3490
^GPI codes from MediSpan;
https://www.azahcccs.gov/PlansProviders/Downloads/PharmacyUpdates/AHCCCSPreferredDrugs_04_01_201
8.pdf;
https://www.bluecrossmn.com/healthy/public/portalcomponents/PublicContentServlet?contentId=P11GA_1630
6146.

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Appendix 2. NON-BIOLOGIC (TRADITIONAL) DMARDS
Generic Names^
GPI Codes^
J-codes
Hydroxychloroquine
13000020
n/a
Methotrexate
21300050
66250050
J8610, J9250, J9260
Leflunomide
66280050
n/a
Sulfasalazine
52500060
n/a
OtherMedications:
Chloroquine
13000010
J0390
Combos
1399000220
n/a
Cyclosporine
99402020
J7502, J7515, J7516,
C9438, J7503, K0121,
K0122, K0418
Thalidomide
99392070
n/a
Azathioprine
99406010
J7500, J7501, C9436,
K0119,
Cyclophosphamide
21101020
J8530, J9070, J9080,
J9090, J9091, J9092,
J9093, J9094, J9095,
J9096, J9097, C9420,
C9421
Auranofin
66200010
n/a
Aurothioglucose
66200020
J2910
Gold Sodium Thiomalate 66200030
J1600
Penicillamine
99200030
n/a
Tacrolimus
99404080
J7507, J7525, C9006,
J7508
Minocycline/Tetracyclin
04000040
J2265
^ GPI codes from MediSpan.

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Appendix 3. CLAIMS-BASED INDEX OF RA SEVERITY (CIRAS)
Measure6
Score
Age(continuous)
-0.066
Gender
0: male
1: female
-0.092
Inflammatory marker test ordered 0: no
1: yes
0.60
Rehabilitationvisit 0: no
1: yes
0.69
Rheumatoid factor test 0: no
1: yes
2.1
Felty’ssyndrome 0: no
1: yes
2.3
Number of platelet counts ordered 0 = 0 visits
1 = 1 visit
2 = 2 visits
3 = 3 visits
4 = 4+ visits
0.42
Number of chemistrypanels ordered 0 = 0
panels
1 = 1 panel
2 = 2 panels
3 = 3 panels
4 = 4 panels
5 = 5+ panels
-0.14
Rheumatologist visitcount 1 = 0 visits
2 = 1-4 visits
3 = 5+ visits
0.52
Intercept
6.5
Number of platelet counts, chemistry panels, and rheumatologist visits are counted 1 per person per day.

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Codes for CIRAS Calculation
Codes
Visits/Tests
Rehabilitation
OT/PT Codes: G0151,G0152,G0157,G0158,
G0159,G0160,S9129,S9131,97001,97002,970
03,97004
Occupationaltherapy/physical
therapy visits
Rheumatoid
CPT 86430,86431
Rheumatoid Factor Test Qual,
Factor
Rheumatoid Factor Test Quant
Felty’s syndrome
ICD-9/10: 714.1, M0500
Platelet counts
CPT: 85049
Automated platelet count
Chemistry panels
CPT: 80053, 82248, 82465, 82977, 83540,
83615, 84100, 84478, 84550
A/G Ratio, Albumin, Alkaline
Phosphatase, Alanine
Aminotransferase, Asparate
Aminotransferase, Direct and
Total Bilirubin, BUN/Creatinine
Ratio, Calcium, Carbon Dioxide,
Chloride, Cholesterol,
Creatinine, Gamma
Glutamyltransferase,Globulin,
Glucose, Iron, Lactate
Dehydrogenase,Phosphate,
Potassium, Total Protein,
Sodium, Triglycerides, Urea
Nitrogen (BUN), Uric Acid

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Appendix 4. COMORBIDITIES OF INTEREST
Disease
ICD-9 codes
ICD-10 codes
Cardiovascular
Disease
Ischemic heart
disease
411.xx 413.xx 414.xx
I241, I200, I240, I248, I208, I201, I209
I2582, I2583, I2584, I255, I259, I2589, I2510, I25810, I25811, I2
5812, I253, I2541, I2542, I253
Congestive heart
failure
428.xx
I509,I501, I5020-5023,I503-5033,I5040-5043
Myocardial
infarction
410.xx,
I2109, I2119, I2111, I2129, I213, I214
Peripheral vascular
disease
441.xx, 443.9x
I711-716, I718-719, I7100-7103, I739
PROC codes: 38.13, 38.18,
38.48
Hypertension
401.xx, 437.2x
I10,I169, I674
Dyslipidemia
272.xx
E7800-7801, E781-786, E881, E770-771, E7521-7522,
E75249, E7881, E7889, E8889, E789
Diabetes
250.xx
E119,E109, E1165, E1065, E1169, E1310 E1010, E1165,
E1169,E1065, E1100, E1101, E1069, E1100, E1165, E1069,
E11641, E1011, E10641, E1101, E1165, E1011, E1065, E1129,
E1029, E1121, E1165, E1021, E1065, E1136, E1139, E11311
E11319, E1036, E1037X1, E1037X2, E1037X3, E1037X9,
E1039,E10311, E10319, E1136, E1139, E1165 E11311,
E11319, E1036, E1039, E1065, E10311, E10319, E1140,
E1040, E1140, E1165 ,E1040, E1065, E1151, E1051, E1151,
E1165, E1051, E1065, E1165. E1169, E11618, E11620,
E11621, E11622, E11628, E11630, E11638 E11649, E1065,
E1069, E10618, E10620, E10621,E10622, E10628, E10630,
E10638, E10649, E1165, E1169, E1065, E1069 E118, E108,
E118, E1165 ,E108, E1065
Depression
300.4x, 309.0x, 309.1x,
309.28, 311.xx
F341, F4321,F4323, F329
COPD
491.21
J441
Asthma
493.xx
J4520, J4522, J4521, J4520,J4522,
J4521, J449, J440, J441, J45990
J45991, J45909, J45998, J45902, J45901

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Disease
ICD-9 codes
ICD-10 codes
Kidney disease
250.4x
403.xx, 404.xx, 405.01,
405.11, 405.91
580.xx, 581.xx, 582.xx,
583.xx, 584.xx
585.xx, 586.xx, 587.xx,
588.xx, 589.xx 753.0x, 753.1x
791.0x V45.1x
V56.xx
E1129,E1029,E121,E1165,E1021,E1065
I129, I120, I1310, I130, I1311, I132, I150, N003, N013, N009,
N09, N008, N044, N022, N043, NO40, N049, N032, N033,
N035, N038, N039, N08, N048,N05,N052,N055,
N059,N171,N172,N059,  N08,N058, N170, N171,
N172,N178, N179, N181-186, N189, N19, N269, N250,
N251, N2581, N2589, N270, N271, N279, Q602, Q605,
Q619,Q6100,Q6101,Q613, Q612, Q6119, Q614,
Q615,Q615,Q618,Q610, R803, R809, Z992, Z9115, Z4931,
Z4901, Z4902, Z4932, Z4931
Liver disease
decompensated cirrhosis
070.44, 070.71, 348.3x,
456.0, 456.1, 456.2x, 572.2,
572.3, 572.4, 782.4, 789.59;
hepatocellular carcinoma 155;
or liver transplant (V42.7, 50.5
or CPT codes 47135, 47136)
B182, B1921, G9340, G9341, G9349, I6783, I8501, I8500,
I8511, I8510, K7290, K7291, K766, K767, R17, R168, C220,
C222, C227, C228, C221, C229, Z944, J64
Anxiety
300.01, 300.3x, 309.81,
300.23, 300.21, 300.22,
300.2, 300.20, 300.29,
300.02, 293.84, 309.21,
300.0, 300.00,
300.09,300.1x
780.4x, 785.0x-785.1x,
786.01, 786.05, 786.09
F410, F422,F423, F428, F429, F4310, F4312, F4010, F4001,
F4002, F409, F4001, F4002, F4010, F408, F40218, F40240,
F40241, F409, F411, F064, F930, F419, F410, F411, F418,
F99, F489, F449, F444, F446, F440, F441, F4481, F449,
F4489, F6811, F688,R42, R000, R002, R064, R0602, R063,
R0600, R0609, R0683, R0689
Sleep disorders
307.4x, 780.5x, 786.03,
V69.4x
F519, F5102 ,F5109, F5101, F5103, F5109, F5119, F5111,
F5112, F5119,  F518,F513, F518, G479, G4730, G4700,
G4730, G4710, G4720, G478, G4730, F518, G478, R0681,
Z72820
Interstitial lung
disease
516.9
J84.9

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Appendix 5. LIST OF OTHER RA-RELATED MEDICATIONS
GPI Codes ^
HCPCS
Prednisone
Eq Dose
SYSTEMICGLUCOCORTICOIDS
High Potency
betamethasone
22100010
J7624
0.60
dexamethasone
J1094, J1095,
22100020
J1100, J8540,
0.75
Q0137,
Q0138,
S0173
MediumPotency
Fludrocortisone
2220003010
n/a
methylprednisolone
22100030
J1020, J1030,
4
J1040, J2920,
J2930, J7509
prednisolone
22100045
J1680, J2640, J2650,
J7510
5
prednisone
22100040
J1690, J7506, K0125
5
Triamcinolone
22100050
J3300, J3301, J3302,
J3303
4
Low Potency
Cortisone
22100015
J0810
25
Hydrocortisone
22100025
20
NSAIDs/Salicylates
6610, 66998, 6410
J1885, J1130, J0131,
C9283, J1741, C9279
N/A
Opioids
N/A
Strong (morphine, methadone,
fentanyl,hydromorphone,
oxymorphone,oxycodone,
hydrocodone,buprenorphine,
butrophanol,nalbuphine,
levorphanol)
65100055,655100050,
65100025,65100035,6
5100080,6500075,651
00030,65200010,6520
0020,65200030,65100
040
J2270, J2271,J2274 ,
J2275 ,Q9974 S0093 ,
J1230 ,S0109
J1170 S0092 J2410
J0570 ,
J0572, J0575 ,J0592
J1810 ,J3010
J2300
N/A

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GPI Codes ^
HCPCS
Prednisone
Eq Dose
Weak (codeine, tramadol,
combinations w/
acetaminophen/aspirin,
pentazocine, meperidine,
tapentadol)
65100020,
65100095,65200040,6
5100091,65100045,
6599
J2175 ,J2180 J3070
J0745
N/A
GPI codes from MediSpan.
Prednisone Eq Dose from https://globalrph.com/medcalcs/corticosteroid-converter-based-on-anti-inflammatory-
potency/; http://www/nadf.us/downloads/adrenal/hormone.pdf.
Low, medium, high potency corticosteroid groups defined by anti-inflammatory activity relative to
hydrocortisone/; http://www/nadf.us/downloads/adrenal/hormone.pdf.
Strong opioids = opioid oral morphine equivalate conversion factor ≥1; fentanyl classified based on patch
Factory-March-2015.pdf).
(https:www.cms.gov/Medicare/Prescription-Drug-Coverage/PrescriptionDrugCovContra/Downloads/Opioid-
Morphine-EQ-Conversion-Factory-March=2015.pdf).