Bioethics Paper

Received: 8 December 2017 Revised: 5 April 2018 Accepted: 11 April 2018

DOI: 10.1002/pbc.27228

Pediatric Blood & Cancer The American Society ofPediatric Hematology/Oncology

R E S E A R C H A R T I C L E

Sickle Cell Clinical Research and Intervention Program (SCCRIP): A lifespan cohort study for sickle cell disease progression from the pediatric stage into adulthood

Jane S. Hankins1 Jeremie H. Estepp1 Jason R. Hodges1

Martha A. Villavicencio1 Leslie L. Robison2 Mitchell J. Weiss1 Guolian Kang3

Jane E. Schreiber4∗ Jerlym S. Porter4 Sue C. Kaste5,6,7 Kay L. Saving8

Paulette C. Bryant9 Jeffrey E. Deyo10 Kerri A. Nottage11 Allison A. King12

Amanda M. Brandow13 Jeffrey D. Lebensburger14 Oyebimpe Adesina15

Stella T. Chou16 Babette S. Zemel17 Matthew P. Smeltzer18 Winfred C. Wang1

James G. Gurney18

1Department of Hematology, St. Jude Children's Research Hospital, Memphis, Tennessee

2Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee

3Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee

4Department of Psychology, St. Jude Children's Research Hospital, Memphis, Tennessee

5Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee

6Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee

7Department of Radiology, University of Tennessee Health Science Center, Memphis, Tennessee

8OSF Healthcare Children's Hospital of Illinois, University of Illinois College of Medicine, Peoria, Illinois

9Department of Pediatric Hematology and Oncology, Novant Health Hemby Children's Hospital, Charlotte, North Carolina

10Department of Pediatric Hematology/Oncology, Our Lady of the Lake Children's Hospital, Baton Rouge, Louisiana

11Janssen Research & Development, Raritan, New Jersey

12Program in Occupational Therapy, Washington University in St. Louis, St. Louis, Missouri

13Section of Pediatric Hematology/Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin

14Department of Pediatric Hematology and Oncology, University of Alabama at Birmingham, Birmingham, Alabama

15Division of Hematology, University of Washington, Seattle, Washington

16Division of Hematology and the Apheresis Program, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania

17Department of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania

18School of Public Health, University of Memphis, Memphis, Tennessee

Correspondence

JaneS.Hankins,DepartmentofHematology,St.

JudeChildren'sResearchHospital,332Danny

ThomasPlace,MailStop800Memphis,TN

38105.

Email: [email protected]

∗JaneE.Schreiber'snewaffiliationiswithinthe

DepartmentofChildandAdolescentPsychiatry

andBehavioralSciences,Children'sHospitalof

Philadelphia,Philadelphia,Pennsylvania.

Grantsponsor:ALSAC

Abstract Background: Previous natural history studies have advanced the understanding of sickle cell

disease (SCD), but generally have not included sufficient lifespan data or investigation of the

role of genetics in clinical outcomes, and have often occurred before the widespread use of

disease-modifying therapies, such as hydroxyurea and chronic erythrocyte transfusions. To fur-

ther advance knowledge of SCD, St. Jude Children's Research Hospital established the Sickle Cell

ClinicalResearchandInterventionProgram(SCCRIP),toconductresearchinaclinicallyevaluated

cohort of individuals with SCD across their lifetime.

Abbreviations: CDC, Centers for Disease Control and Prevention; EMR, electronic medical record; Hb, hemoglobin; NIH, National Institutes of Health; PRO, patient-reported outcome; SCCRIP,

Sickle Cell Clinical Research and Intervention Program; SCD, sickle cell disease; St. Jude, St. Jude Children's Research Hospital

Pediatr Blood Cancer. 2018;65:e27228. c© 2018 Wiley Periodicals, Inc. 1 of 12wileyonlinelibrary.com/journal/pbc https://doi.org/10.1002/pbc.27228

2 of 12 HANKINS ET AL.

Procedures: Initiated in 2014, the SCCRIP study prospectively recruits patients diagnosed with

SCD and includes retrospective and longitudinal collection of clinical, neurocognitive, geospatial,

psychosocial, and health outcomes data. Biological samples are banked for future genomics and

proteomics studies. The organizational structure of SCCRIP is based upon organ/system-specific

working groups and is opened to the research community for partnerships.

Results: As of August 2017, 1,044 (92.3% of eligible) patients with SCD have enrolled in the study

(860 children and 184 adults), with 11,915 person-years of observation. Population demographics

included mean age at last visit of 11.3 years (range 0.7–30.1), 49.8% females, 57.7% treated with

hydroxyurea, 8.5% treated with monthly transfusions, and 62.9% hemoglobin (Hb) SS or HbSB0-

thalassemia, 25.7% HbSC, 8.4% HbsB+-Thalassemia, 1.7% HbS/HPFH, and 1.2% other.

Conclusions: The SCCRIP cohort will provide a rich resource for the conduct of high impact multi-

disciplinary research in SCD.

K E Y W O R D S

disease-modifying therapy, natural history, sickle cell anemia

1 INTRODUCTION

An estimated 100,000 individuals in the United States live with sickle

cell disease (SCD),1 and worldwide an estimated 300,000 babies are

born with the disease each year.2,3 The clinical consequences are

severe and include recurrent episodes of acute severe pain, chronic

pain, cerebrovascular events, progressive organ damage, and early

death.

In the United States and other high-income countries, survival

to adulthood of children with SCD has increased over the past five

decades from 50% to greater than 95%.1,4–7 This survival increase is

primarily due to mandatory newborn screening, infection prevention

with penicillin prophylaxis and pneumococcal vaccination, improved

supportive care, and increased use of disease-modifying therapies,

such as hydroxyurea and chronic erythrocyte transfusions.8–13 How-

ever, accumulation of end-organ damage to the heart, lungs, brain,

kidneys, and bones continues to occur.14 This organ damage man-

ifests in young adults with higher rates of acute health utilization,

emergency room reliance, and hospitalization.15,16 Disease-related

mortality rises in young adults and the median age of death among

adults with hemoglobin (Hb) SS and HbS𝛽0-thalassemia is mid to late

40s.1,17,18

Understanding the natural history of SCD across the lifespan

in the contemporary medical environment is crucial, because the

substantial improvement in pediatric survival contrasts with lesser

gains in health outcomes among adults. A particular challenge is

the assessment of clinical outcomes during the vulnerable period of

transition from the pediatric to the adult care setting. During this

transitional period, deficits in preparation, planning, care coordi-

nation, and available skilled adult care providers lead to low rates

of engagement in adult care and interrupt care continuity.19,20

Without an appropriate infrastructure to collect longitudinal

health outcomes data as children age into adulthood, informa-

tion will be limited, insufficient to answer questions examining

disease progression, and unlikely to stimulate progress in the

field.

1.1 Knowledge gained from early SCD cohorts

Three early cohort studies have informed much of our understanding

of the epidemiology and natural history of SCD, although each began

prior to the advent and widespread use of current disease-modifying

therapies; these are the Jamaican Cohort Study (1973–1981),21,22

the Cooperative Study of Sickle Cell Disease (1979–1999),23,24 and

the Dallas cohort study (1983 to present)25 (Table 1). These stud-

ies provided the foundation for understanding variations in the dis-

ease severity phenotype, acute complications of SCD, survival rates,

mortality risks, laboratory values, and the basis for sepsis and stroke

prevention.6,26–41 Over the past decade, clinical trials have demon-

strated the benefit of hydroxyurea 42,43 and erythrocyte transfusions

for stroke prevention, building on the knowledge from earlier cohort

studies. More recently, smaller retrospective and prospective cohort

studies have shown that hydroxyurea may reduce mortality and pre-

vent organ damage.44–48 Thus, SCD cohort studies that factor in long-

term health effects of disease-modifying therapies, such as hydrox-

yurea and chronic erythrocyte transfusions begun in childhood, should

be the gold standard for observational and interventional research

studies in the modern era.

From our current perspective, important limitations of these ear-

lier cohorts were the lack of sufficient longitudinal data to cover the

full lifespan (i.e., studies were focused on either children or adults), the

limited genotype–phenotype studies, and the insufficient exposure to

disease-modifying therapies. The long-term follow-up of the phase III

BABY HUG study (NCT00890396) has been monitoring the long-term

effects of hydroxyurea therapy, but this cohort study is relatively small

and data collection has ended. More recent cohorts that have included

patients exposed to disease-modifying therapies have lacked sufficient

internalcomparativegroups,suchaspatientsnotexposedtotherapies,

limiting their external validity.

1.2 Scientific importance of SCCRIP

Longitudinal evaluation of outcomes throughout the lifespan will

enhance our understanding of disease progression, identify early

HANKINS ET AL. 3 of 12

T A B L E 1

L a n d m a rk

co h o rt st u d ie s in si ck le ce ll d is e a se

C o h o rt st u d y

D a te

S a m p le

si ze

# si te s

O b je ct iv e s

C o n ti n u it y fr o m

th e p e d ia tr ic

st a g e in to

a d u lt h o o d

D is e a se -

m o d if y in g

th e ra p y

e x p o su re

S y st e m a ti c

o rg a n

fu n ct io n

a ss e ss m e n t

K n o w le d g e g a in e d

E li g ib il it y

B io lo g ic a l

sa m p le s

b a n k e d

Ja m a ic a n C o h o rt

S tu d y 2 1 ,2 2

1 9 7 3 –

1 9 8 1

5 8 0

1 To

d e fi n e a n a tu ra l

h is to ry

o f S C D a n d

id e n ti fy m o d u la ti o n

fa ct o rs

N o n e

N o n e

N o

F re q u e n cy

a n d

cl in ic a l

p re se n ta ti o n o f

a cu te

co m p li ca ti o n s

N e w b o rn s b o rn

b e tw

e e n 1 9 7 3 a n d

1 9 8 1 ,b o rn

in Ja m a ic a ,a n d

sc re e n e d p o si ti v e

fo r S C D

N o

C o o p e ra ti v e S tu d y o f

S ic k le C e ll D is e a se

(C S S C D )2 3 ,2 4

1 9 7 9 –

1 9 9 9

4 ,0 8 5

2 3

To d e te rm

in e a

n a tu ra lh is to ry

o f

S C D a n d id e n ti fy

fa ct o rs

co n tr ib u ti n g to

m o rb id it y a n d

m o rt a li ty

in S C D

L im

it e d

N o n e

N o

F re q u e n cy

a n d

cl in ic a l

p re se n ta ti o n o f

a cu te

co m p li ca ti o n s,

se v e ri ty

ri sk

fa ct o rs ,m

o rt a li ty

ca u se s,

h e m a to lo g ic

in d ic e s

N e w b o rn

to 2 5 y e a rs

o f a g e ;B

la ck

m a le

o r fe m a le s w it h

S C D

D N A

D a ll a s N e w b o rn

C o h o rt

2 5

1 9 8 3 to

p re se n t

9 4 0

1 To

d e te rm

in e

co n te m p o ra ry

su rv iv a ld a ta

fo r

ch il d re n w it h S C D

th a t re fl e ct m o d e rn

S C D th e ra p y

L im

it e d

L im

it e d

N o

M o rt a li ty

ca u se s, ri sk

p re d ic ti o n o f

d is e a se

se v e ri ty

N e w b o rn s w it h S C D

a s id e n ti fi e d b y

n e w b o rn

sc re e n in g

p ro g ra m in Te x a s

N o

S C C R IP

2 0 1 4 to

p re se n t

1 ,0 4 4 cu r-

re n tl y

5 To

cr e a te

a li fe ti m e

lo n g it u d in a lc o h o rt

a n d b a n k

b io sp e ci m e n s

Y e s

Y e s

Y e s

P e n d in g a n a ly se s

A d ia g n o si s o f S C D

D N A ,

p la sm

a ,

u ri n e

4 of 12 HANKINS ET AL.

predictors of later outcomes, elucidate the roles of genetic, pro-

teomics, and environmental factors on health outcomes, and define

the long-term impact of therapies. To address these goals and circum-

vent the limitations of prior studies, we initiated the Sickle Cell Clinical

Research and Intervention Program (SCCRIP, NCT 02098863). Here

we describe the design of SCCRIP, including its systematic approach

to data abstraction according to developmental stage, particularly the

transition from pediatric to adult care, and how the phenotype data

are being classified in a fashion that can be compared across multiple

institutions.

2 METHODS

2.1 Study aims and design

Initiated in April 2014, SCCRIP is a cohort study with prospective

follow-up, ongoing data accrual, and retrospective collection of exten-

sive clinical history. The overarching goal of SCCRIP is to under-

stand the clinical, biological, and psychosocial progression of SCD

and factors contributing to early mortality across the lifespan, with

the ultimate goal of facilitating effective therapies. The objectives

are two-fold: (1) to establish a longitudinal clinical cohort of patients

with SCD; and (2) to establish a biorepository of DNA, urine, and

plasma.

2.2 SCCRIP participating sites

SCCRIP enrolls patients from five institutions (Figure 1). These sites

were chosen based on the size of their SCD population, their relation-

ship with St. Jude Children's Research Hospital (St. Jude), and ability to

perform uninterrupted data collection from birth through adulthood.

St. Jude, the clinical and data coordinating site, treats 850 children

with SCD from birth to age 18 years. Through Tennessee and Missis-

sippi State Health Department contracts, St. Jude has been the referral

treatment center for new SCD cases from west Tennessee and north

Mississippi, diagnosed through the newborn screening programs in

those states, for the past 20 years. Following referral to St. Jude, 100%

of infants with newly diagnosed SCD are seen in the SCD clinic and

initiate penicillin prophylaxis within 2 months.49 Care provided by St.

Jude is free (including medications), and support with transportation

and meals is provided during regular and study visits.50 Approximately

80% of St. Jude patients transfer care to the Comprehensive Sickle

Cell Program in the partnering Methodist University Hospital, ensur-

ing care continuity and uninterrupted research data ascertainment.51

The Methodist University Hospital is located 2.5 miles from the St.

Jude campus, and currently cares for 300 adults, of whom approxi-

mately90%areformerSt.Judepatients.Aftertransitionofcare,adults

are followed similarly to children, with health-maintenance visits at

least twice per year when chronic end-organ damage is performed as

standard of care. The remaining three sites belong to the St. Jude Affil-

iate Program and share the purpose of extending protocol-structured

treatment and research through clinical, research, and academic part-

nerships. Support with meal expenses and transportation costs related

FIGURE 1 SCCRIP participants’ geographical distribution. The 1,044 SCCRIP participants are distributed among the following five sites in four states: two in Memphis, TN (St. Jude Children's Research Hospital and Methodist University Hospital), one in Peoria, IL (OSF Healthcare Children's Hospital of Illinois), one in Charlotte, NC (Novant Health Hemby Children's Hospital), and one in Baton Rouge, LA (Our Lady of the Lake Children's Hospital)

to study visits are provided by St. Jude. Collectively, these five insti-

tutions care for approximately 1,600 individuals with SCD and con-

tribute geographic, social, and environmental diversity to the SCCRIP

clinical cohort.

2.3 SCCRIP organizational structure

The SCCRIP multidisciplinary research team blends expertise in

pediatric and adult hematology, nephrology, pulmonology, cardiology,

radiology, pain, psychology, bone metabolism, transfusion medicine,

epidemiology, genetic epidemiology, biostatistics, social sciences, com-

putational biology, bioinformatics, geocoding, and data management.

Research-related activities within SCCRIP are divided into nine Work-

ing Groups, which focus on questions related to a specific organ sys-

tem, disease complication, or therapy, and provide primary oversight

for the development and conduct of research initiatives. Investiga-

tors seeking to answer specific research questions are required to

collaborate with the appropriate Working Group(s) and complete a

concept proposal (Supplementary Material S1) that is reviewed and

HANKINS ET AL. 5 of 12

FIGURE 2 SCCRIP organizational structure. SCCRIP's scientific ini- tiatives are driven by the Working Groups, which are composed of St. Jude and external investigators. The Steering Committee vets all con- cept proposals from the Working Groups and follows recommenda- tions from the Executive Committee regarding major study delibera- tions. Plans are in place to expand SCCRIP collaboration to the SCD community by allowing access to the SCCRIP resource to external col- laborators beyond current collaborators

approved by the Steering Committee, comprised of SCCRIP investi-

gators. The SCCRIP Steering Committee evaluates the quality of the

science,design,andanalyticalplanforeachnewresearchproposal.The

Executive Committee is responsible for major deliberations and con-

flict resolution within SCCRIP. A number of committees provide over-

sight of activities related to the publication of results from SCCRIP,

and access and utilization of the SCCRIP resource. An external advi-

sory committee, consisting of pediatric oncologists, pediatric hema-

tologists, epidemiologists, and biostatisticians, provides input into the

currentandfutureactivities.Inthefuture, it isourplantoopenSCCRIP

data access to the broader SCD research community. In this model,

non-SCCRIP investigators will have access to SCCRIP data and sam-

ples, once approved by the Steering Committee. Figure 2 outlines the

organizational structure for SCCRIP.

2.4 Subject sampling and follow-up strategy

Participants are prospectively recruited if they have a diagnosis of

SCD of any type and receive treatment at one of the five participat-

ing sites. Participants are not selected based on disease severity or

treatment exposure. Prospective data collection starts at study enroll-

ment, but existing clinical and laboratory data, when available, are ret-

rospectively collected from the point of first encounter with the health

care system. This strategy for data collection allows for reconstruc-

tion of the participant's entire medical and treatment history regard-

less of the age at enrollment. There is no final enrollment goal for the

study. Rather, we plan to approach and enroll the entire SCD popu-

lation managed by all participating sites. Once enrolled, participants

are categorized according to one of the following six developmental

age cohorts: newborn (0 to 5.9 months), infant-toddler (6 months to

5.9 years), school age child (6–11.9 years), adolescent (12–17.9 years),

young adult (18–24.9 years), and older adult (25 and older). This cohort

categorization allows for the classification of clinical and laboratory-

based variables according to age, facilitating both longitudinal and

age-stratified analyses.

2.5 Data variables

All clinical and laboratory assessments performed as standard of care

for SCD are defined by national standards or institutional clinical

practice.52 SCCRIP data are collected at standard intervals and classi-

fied into the following three tiers (Table 2): universal (e.g. Hb fraction-

ation, urine microalbumin), risk-based (e.g. transcranial Doppler ultra-

sound in children aged 2–16 years with HbSS and HbS0-thalassemia),

and symptom-based (e.g. magnetic resonance imaging to investigate

osteonecrosis due to prolonged joint pain, impaired range of motion,

and debility). Healthcare utilization (e.g. admission, acute care vis-

its) and educational attainment data are also collected for the entire

cohort. Additionally, participants are offered optional research activ-

ities every 6 years, including banking of biospecimens (urine, plasma,

and DNA), measurement of high sensitivity C-reactive protein, and

assessment of health-related quality of life using the PedsQLTM

instrument (generic, SCD, and multidimensional fatigue modules, and

the corresponding adult versions once participants reach adult age)

(Table 2).53–55 After transition from pediatric to adult clinical care,

SCCRIP adult participants return to St. Jude every 6 years for compre-

hensive data collection to assess disease status.

2.6 Consenting process and institutional review

board oversight

Subjects are approached during nonacute health maintenance visits

and informed consent is obtained directly from participants who are

18 years of age and older or their legal guardian, if subjects are minors.

Verbal assent is obtained from minors who are between the ages of 7

and 13 years, and signed assent from those between 14 and 17 years

of age. When participants reach the age of majority (18 years), they are

reconsented into the study.

A tiered consent provides subjects with opt-in/opt-out choices

for participating in the research activities beyond the collection

of past and future standard of care data (Table 2, optional evalua-

tions). Extensive discussion regarding future genetic testing takes

place during informed consent, including the information that these

studies are performed in a laboratory not approved by Clinical

Laboratory Improvement Amendments and will not be returned to

the participants. Opt-in/opt-out choices for recontacting partici-

pants due to incidental findings are provided. Examples of potential

future research with subjects’ biospecimens and the potential

risks to loss of privacy are discussed in the context of genomics

research. Public sharing of genetic data will occur according to

the National Institutes of Health (NIH) Genomic Data Sharing Policy

(https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html)

for NIH-funded projects. Access requests from non-SCCRIP investiga-

tors for combined genetic and phenotypic data for hypothesis-driven

research may be approved after completion of a concept proposal

(Supplementary Material S1). The SCCRIP Steering Committee will

evaluate external concepts on the scientific significance, innovation,

and approach of their proposed project as well as the investigative

team, research environment, and funding availability.

6 of 12 HANKINS ET AL.

T A B L E 2

S C C R IP

ti e re d sc h e d u le o f e v a lu a ti o n s

C o h o rt

N e w b o rn

In fa n t- to d d le r

S ch o o la g e

Te e n a g e r

Y o u n g a d u lt

M a tu re

a d u lt

T ie r

E v a lu a ti o n a g e ± 1 (y e a rs )

0 – 0 .5 9

2 4

6 8

1 0

1 2

1 4

1 6

1 8

2 0

2 2

2 4

A t le a st e v e ry

2 y e a rs fr o m

a g e 2 6

E v e ry

6 y e a rs

fr o m a g e 3 0

1 V it a ls ig n s, a n th ro p o m e tr ic

m e a su re s, p h y si ca le x a m

x x

x x

x x

x x

x x

x x

x x

C B C a n d re ti cu lo cy te

co u n t

x x

x x

x x

x x

x x

x x

x x

H e m o g lo b in fr a ct io n a ti o n

x x

x x

x x

x x

x x

x x

x x

U /A ,u ri n e p ro t/ cr e a t ra ti o ,

m ic ro a lb u m in

x x

x x

x x

x x

x x

x x

x x

C M P, L D H ,c y st a ti n C ,2 5 O H

v it a m in D

x x

x x

x x

x x

x x

x x

x x

R e ti n o p a th y sc re e n

x x

x x

x x

x x

x

D is e a se -s p e ci fi c li te ra cy

a x

x x

x x

x x

x x

x

T ra n si ti o n re a d in e ss

x

P a rv o v ir u s B 1 9 in d ex

ti te r

x x

x x

x

P u lm

o n a ry

fu n ct io n te st

x x

x x

x

C T D E X A sc a n

x x

x x

x

B ri g a n ce

D e v e lo p m e n ta lt e st

x x

N e u ro p sy ch o lo g ic a ls cr e e n in g

x x

x x

x x

2 T ra n sc ra n ia lD

o p p le r u lt ra so u n d

x x

x x

x x

x x

S e ru m fe rr it in ,E p o ,R B C A b

x x

x x

x x

x x

x x

x x

x x

L iv e r R 2 a M R I

x x

x x

x x

x x

x x

x x

x

T 9 9 li v e r/ sp le e n sc a n

x x

x

G lo m e ru la r fi lt ra ti o n ra te

x x

x x

x

3 B ra in M R I/ M R A a n d jo in t M R I

x x

x x

x x

x x

x x

x x

x

E K G /E ch o ca rd io g ra m

x x

x x

x x

x x

x x

x x

x

P o ly so m n o g ra p h y

x x

x x

x x

x x

x x

x x

x

P a ra th y ro id h o rm

o n e le v e l

x x

x x

x x

x x

x x

x x

x

O p ti o n a lt e st s

D N A ,s e ru m ,

a n d u ri n e ,

h s- C R P

x x

x x

x x

H R Q O L

x x

x x

x x

x

C B C ,c o m p le te

b lo o d co u n t; p ro t/ cr e a t, p ro te in to

cr e a ti n in e ra ti o ;C

M P, co m p le te

m e ta b o li c p ro fi le ;C

T D E X A ,d u a l- e n e rg y X -r ay

a b so rp ti o m e tr y ;L D H ,l a ct a te

d e h y d ro g e n a se ;E p o ,e ry th ro p o ie ti n ;R

B C A b ,r e d b lo o d

ce ll a n ti b o d y sc re e n ;h s- C R P, h ig h -s e n si ti v it y C -r e a ct iv e p ro te in ;M

R I, m a g n e ti c re so n a n ce

im a g in g ;M

R A ,m

a g n e ti c re so n a n ce

a n g io g ra p h y ;E K G ,e le ct ro ca rd io g ra m ;U

/A ,u ri n e a n a ly si s; H R Q O L ,h e a lt h -r e la te d q u a li ty

o f li fe m e a su re d w it h P e d s Q L T M g e n e ri c, fa ti g u e ,a n d S C D m o d u le s.

T ie r 1 ,u n iv e rs a ld a ta

co ll e ct io n ;T ie r 2 ,r is k -b a se d d a ta

co ll e ct io n ,d o n e o n th o se

a t ri sk

o f a co m p li ca ti o n (e .g .t ra n sc ra n ia ld o p p le r v e lo ci ti e s fo r H b S S /H

b S 𝛽 0 -t h a la ss se m ia a g e s 2 – 1 6 y e a rs ,l iv e r R 2 *M

R I fo r th o se

o n

ch ro n ic tr a n sf u si o n s) ;T ie r 3 ,s y m p to m -b a se d (e .g .M

R I o f th e h ip to

in v e st ig a te

o st e o n e cr o si s in a p a ti e n t w it h p e rs is te n tl y se v e re

h ip p a in ).

a D is e a se -s p e ci fi c li te ra cy

co ll e ct e d fr o m p a re n t u p to

a g e 2 y e a rs a n d fr o m p a ti e n t a ft e r a g e 2 y e a rs .

HANKINS ET AL. 7 of 12

FIGURE 3 Consort diagram for SCCRIP. The overall acceptance par- ticipation rate is 92.3% and acceptance of optional research activities (biobanking of DNA, urine, and plasma) is 97.9%

3 DATA MANAGEMENT

SCCRIP study staff document all interactions with eligible and enrolled

participants through an electronic tracking database. The program

generates reports that summarize enrollment and study-related

information and notifies study staff of upcoming study events for

each subject, such as time to complete age of majority consents and

time to enter study-specific orders. Data sources for SCCRIP include

patient-reported outcome (PRO) surveys and data electronically or

manually abstracted from medical charts. PRO data are gathered

electronically using a mobile device (tablet), and stored in an electronic

data management system, to later be extracted and deposited into

the SCCRIP database. Clinical data are extracted in a table format

from each site's electronic medical record (EMR, Cerner R© or Epic R©

software systems) through a series of queries or custom reports, which

local information technology staff develop and execute regularly. Data

from external sites are securely transmitted and uploaded to St. Jude

regularly using Health Insurance Portability and Accountability Act–

compliant protocols. Participants’ addresses are geocoded annually

using ArcGIS (Esri, Redlands, CA) to determine the socio-economic

characteristics of participants’ neighborhoods and proximity to both

resources (e.g. food access, parks, schools) and environmental hazards

(e.g. interstates, airports). Once collected, SCCRIP phenotype data

undergo an additional iterative step to match the clinical events

according to the consensus measures for phenotypes and exposures

(PhenX) toolkit. (https://www.phenxtoolkit.org).56 Approximately

80% of SCCRIP and PhenX data are concordant (Supplementary

Table S1).

To facilitate data analyses, an annual data freeze is performed. For

each data domain, computer programs (1) download and perform qual-

ity control checks; (2) merge data from disparate sources; (3) import

relevant data fields from other external sources; and (4) save a sin-

gle analytical dataset containing all required data elements. SCCRIP

data management operations require a substantial amount of human

resources. Currently, the study has two data managers who perform

data extraction, data structuring, and data cleaning and seven research

coordinators who perform patient consenting, PRO collection, and

manual data abstraction, and help coordinate data transfer from all

sites.

3.1 Data analysis plan and lost-to-follow-up tracing

The assigned study statistician will conduct the analytical plan and

return aggregate results and graphical display of data to the inves-

tigators for manuscript or grant preparation. A system to trace

lost-to-follow-up from death is in place through annual searches of

the National Death Index, a program maintained by the National

Center for Health Statistics from the Centers for Disease Control

and Prevention (CDC). These annual searches will allow for mor-

tality ascertainment (date and cause of death) for lost-to-follow-up

cases.

4 RESULTS

4.1 Participant enrollment

As of August 27, 2017, 1,044 subjects (860 children and 184 adults)

with SCD have enrolled across the five participating sites, yielding

in 11,915 person-years of observation. The overall participation

acceptance rate is 92.3% (Figure 3). Of the 1,131 subjects approached

to date, only 30 (2.7%) declined participation. An additional 57 sub-

jects refused enrollment when initially approached, but asked to be

re-approached at a future date. Of those who agreed to participate,

1,022 (97.9%) consented to optional tests including quality of life

questionnaires and biospecimen banking (Figure 3). Among the 22

subjects who refused the optional studies, the most common reason

for refusal was “do not want to spend extra time due to research

activities”.

The characteristics of enrolled participants are shown in Table 3.

Most participants (860, 82.4%) are younger than the age of 18 years.

Collectively, 66.4% of participants are exposed to disease-modifying

therapy; hydroxyurea 57.7%, chronic erythrocyte transfusions 8.5%,

and bone marrow transplant 0.2%. The mean ages when hydrox-

yurea and chronic transfusions were initiated were 7.3 (±5.41) and 5.3 (±3.68) years, respectively. The mean age at the time of the bone mar- row transplantation procedure was 11.9 (±5.59) years. For the sub- jects exposed to disease-modifying therapies, the observation period

(in person-years) is slightly greater before study enrollment than that

post enrollment, that is, 4,035 versus 3,438 person-years, respectively.

8 of 12 HANKINS ET AL.

TABLE 3 SCCRIP participants’ characteristics

Age cohort

Newborn, 0–0.59 years

Infant- toddler, 0.6–5.9 years

School age, 6.0–11.9 years

Adolescent, 12.0–17.9 years

Young adult, 18.0–24.9 years

Mature adult, >25.0 years Totala

Number enrolled (%)

0 259 (24.8) 366 (35.1) 235 (22.5) 173 (16.6) 11 (1.1) 1,044

Mean age in years (±1 SD)

0 4 (1.6) 10 (1.6) 15.9 (1.7) 21.2 (1.7) 27 (1.6) 11.3 (6.4)

Gender (% female) 0 51.9 48.5 48.7 50.9 54.5 49.8

Race (%)

Black/African American (%)

0 257 (99.2) 361 (98.6) 235 (100) 172 (99.4) 11 (100) 1,036 (99.2)

White 0 1 (0.4) 3 (0.8) 0 1 (0.6) 0 5 (0.5)

Other 0 1 (0.4) 2 (0.6) 0 0 0 3 (0.3)

Health insurance (%)

Governmentb 0 201 (77.6) 264 (72.1) 173 (73.6) 111 (64.2) 6 (54.5) 755 (72.3)

Commercial 0 56 (21.6) 93 (25.4) 55 (23.4) 42 (24.3) 1 (9.1) 247 (23.7)

Uninsured 0 2 (0.8) 9 (2.5) 7 (3.0) 20 (11.6) 4 (36.4) 42 (4.0)

Disease-modifying therapy (%)

Hydroxyurea 0 114 (44.0) 192 (52.4) 134 (57.0) 153 (88.4) 9 (81.8) 602 (57.7)

Monthly erythrocyte transfusions

0 5 (1.9) 32 (8.7) 31 (13.2) 21 (12.1) 0 89 (8.5)

Hematopoietic stem cell transplant

0 0 1 (0.3) 1 (0.4) 0 0 2 (0.2)

Mean distance from site (miles)

≤30 0 185 (71.4) 215 (58.7) 165 (70.2) 123 (71.1) 8 (72.7) 696 (66.6)

31–50 0 21 (8.1) 39 (10.6) 18 (7.6) 10 (7.4) 1 (9.1) 89 (8.5)

51–100 0 41 (15.8) 84 (22.9) 47 (20.0) 35 (20.2) 2 (18.1) 209 (20.0)

>100 0 12 (4.6) 28 (7.6) 5 (2.1) 5 (2.8) 0 50 (4.7)

Sickle genotypes (total number)

HbSS or HbS𝛽0- thalassemia

0 167 213 158 113 6 657

HbSC 0 63 108 48 45 4 268

Hbs𝛽+- thalassemia

0 20 33 22 12 1 88

HbS/HPFH 0 5 7 3 3 0 18

HbSD 0 1 3 0 0 0 4

HbS/Black (A𝛾𝛿𝛽)0- thalassemia

0 1 0 1 0 0 2

HbSOArab 0 1 0 1 0 0 2

HbS/N Baltimore

0 1 0 0 0 0 1

HbSE 0 0 2 0 0 0 2

HbS/Hope 0 0 0 1 0 0 1

HbC Harlem disease

0 0 0 1 0 0 1

HPFH denotes hereditary persistence of fetal hemoglobin. aTotal count includes participants who expired while on study. bGovernment insurance includes Medicaid and Medicare.

HANKINS ET AL. 9 of 12

This order will reverse as the cohort ages. The distribution of sickle

genotype and gender is similar among age cohorts, although treat-

ment exposure and the proportion of uninsured subjects increase with

age (Table 3). Approximately 40% of participants live within a census

tract defined as high vulnerability using the CDC's Social Vulnerabil-

ity Index.57 There were no significant differences in sex, age distribu-

tion, sickle genotype, or treatment exposure between subjects who

agreed (N = 1,044) and those who declined (N = 30) to participate in SCCRIP.

4.2 Subject retention

Since enrollment initiation in 2014, four subjects have died and four

have asked to be removed from the study. No participants have been

lost to follow-up. Of the 10 participants who have reached the age of

majority (18 years) and transferred from pediatric to adult care, nine

reconsented to remain in the cohort, while one requested to leave the

cohort. All but one of these nine consenting young adults elected to

continue participating in the optional biobanking activity.

5 DISCUSSION

The progression of end-organ damage and early mortality among indi-

viduals with SCD is not fully understood. Cohort studies are essential

to evaluate the disease course and long-term effects of therapies.

The SCCRIP modern cohort is designed to address these long-term

objectives while addressing limitations of prior studies by (1) providing

lifespan data that include the critical period when children become

adults and end-organ damage becomes evident, (2) banking DNA,

plasma, and urine for future genomic and proteomic studies, (3)

harmonizing data variables with established classification of SCD

phenotypes, and (4) providing an organizational structure that focuses

its multidisciplinary/multi-institutional team of experts on elucidating

SCD progression by organ system and disease complication.

The design of a prospective cohort like SCCRIP provides rigorous

comprehensive, standardized interval classification of multiple patient

exposures and outcomes over time. Contemporary cohort studies that

canfollowpatientsforthedurationoftheirlifetimearerareandmostly

found in European countries where healthcare is centralized and uni-

versal. SCCRIP parallels European cohorts by tracking participants’

clinical acute and chronic outcomes and response to therapies in a sim-

ilar fashion, but extends them by collecting PROs and systematic pul-

monary, bone, developmental, and neurocognitive data, and through

biobanking.12,58

SCCRIP is a large prospective lifetime cohort study of SCD with

over 1,000 subjects enrolled that addresses many of the limitations

of prior studies by providing a rigorous methodology for systematic

data collection during the pediatric-adolescent years and into adult-

hood, and provides a platform for biomarker studies, including those

of serum protein and metabolite levels and genetics. Furthermore,

SCCRIP examines the influence of social determinants of health on

clinical outcomes.59

Overall acceptance rates have been high for the study. In addition,

acceptance of the optional banking of DNA for future genetic stud-

ies has been remarkably high (97.9%). Research study acceptance and

enrollment have been traditionally low for SCD,60–65 and some reports

have indicated that African Americans are less likely than other racial

and ethnic groups to support genetic studies that require a broad con-

sentfortheuseofbiospecimensingeneticsresearch.66,67 Weattribute

our high rate of enrollment to the possible benefit of genetic studies

perceivedbyourpatientpopulation.Additionally,trustintheproviders

and low data collection burden (most data collection is passive) may

playaroleinthishighacceptancerate.SCCRIPparticipantshaveraised

no significant concerns regarding the use of their biospecimens for

futuregeneticstudies,andmostcitepossiblycontributingtothedevel-

opment of curative therapies as a motivation for study participation.

Currently, important knowledge gaps impede progress in develop-

ing strategies for the surveillance and prevention of complications of

SCD, and evaluation of effectiveness of new treatments. Examples

include, but are not limited to (1) the long-term effects of hydroxyurea,

hematopoietic stem cell transplantation, and transfusion therapy and

the role of new interventions (e.g. anti-inflammatory agents,68,69

Hb affinity modulators,70–72 anti-oxidants,73 and gene therapy74) in

cumulative organ damage; (2) cognitive impairment, both its underly-

ing mechanisms and the impact on social function; (3) the impact of the

environment on the disease course, including poverty, which is preva-

lent in the SCD population; (4) pain control, particularly in patients

who progress to chronic pain; (5) risk factors for bone mineral loss

and osteonecrosis, including vitamin D deficiency, which is prevalent

in SCD,75 and establishment of prevention and treatment guidelines;

(6) risk factors for sickle nephropathy in older children and adults and

the role of renal-modifying therapies; (7) factors underlying the sharp

increase in mortality in young adults, as compared to children; and (8)

how biomarkers can be used to monitor treatment response and dis-

ease severity.76

A major long-term goal of SCCRIP is to utilize genomic studies

to predict SCD outcomes and guide treatment. Biomarkers of SCD

severity, including fetal Hb level and hemolysis indices have a high

heritability and numerous genetic variants are associated with these

traits.77,78 Organ-specific problems, such as sickle nephropathy79

and susceptibility to red blood cell alloimmunization80 are influ-

enced by genetic information that will likely be used prospectively

for therapeutic decisions. We use pharmacogenetics data routinely

to guide codeine use in SCD.81 Thus, we plan to obtain genetic

information on SCCRIP participants in order to interpret their

clinical course in the context of variants known to influence SCD

outcomes, plan prospective studies using this information, and elu-

cidate new genetic modifiers of SCD through phenotype-genotype

correlations.

The strengths of the study design are enrollment of a large unse-

lected population, near complete coverage of the total local population

for each participating institution (i.e. all site patients are approached),

systematic ascertainment of multilevel health outcomes, and a robust

data management infrastructure and plan. In addition, because clin-

ical and laboratorial events are classified according to established

phenotype (PhenX), it allows for cross analysis between SCCRIP and

10 of 12 HANKINS ET AL.

other studies. Another major strength is how the cohort will serve

as a resource to the broader SCD research community in the future.

Non-SCCRIP investigators will be able to request access to SCCRIP

data by developing concept proposals that are vetted by the Steer-

ing Committee, in addition to combining their own datasets with

that of SCCRIP to bolster sample size, whenever applicable. Limi-

tations of the study include the exclusion of subjects not treated

by the participating institutions, limiting generalization beyond the

geographical location of the participating sites. In addition, if sub-

jects join the cohort, but were previously treated by other institu-

tions, complete past health records may be unavailable. However,

participants without complete retrospective records are a minority

(<1%) of the study population, minimizing the risk of incomplete ret-

rospective data ascertainment. Finally, because SCCRIP initiated in

2014, and participants joined the cohort at different ages, the obser-

vation time for the period prior to study enrollment was greater

than that post enrollment, that is, 10,077.4 and 1,837.4 person-years,

respectively. However, except for the optional research activities that

only occur after enrollment, the methodology for data abstraction

form the EMR for the period prior to and after enrollment is the

same.

SCCRIP is a contemporary natural history cohort study of SCD that

provides data on disease progression, education outcomes, and health-

care utilization throughout the lifespan of patients with SCD, some

exposed to current and future disease-modifying therapies, such as the

newly approved L-glutamine.82–84 The detailed and standardized char-

acterization of the disease phenotype in SCCRIP, coupled with future

genetic,socio-environmental-behavioral,andproteomicstudieswillbe

a unique resource for advancing the understanding of SCD. Elucidation

of predictors of disease progression from SCCRIP studies may accel-

erate efforts to develop and improve precision medicine in the SCD

population.

CONFLICT OF INTEREST

J.H.E. receives research support from Pfizer and Eli Lilly and Co.

and serves as a consultant for Daiichi Sankyo and Global Blood

Therapeutics. W.C.W. receives research support from Global Blood

Therapeutics. J.S.H. receives research support from Novartis and

Global Blood Therapeutics and consultant fees from bluebird bio.

K.L.S. receives financial support from Molina Healthcare Clinical

Quality Improvement Committee to conduct quality improvement

projects, and owns Pfizer stocks. P.C.B. receives research support

and speaker fees from Novo Nordisk. M.J.W. is a consultant for

Glaxo SmithKline and Novartis and an advisory board member

for Rubius, and receives research funding from Biogen. The other

authors have no financial relationships relevant to this article to

disclose.

ACKNOWLEDGMENTS

We thank the following individuals from St. Jude Children's Research

Hospital: Chris Vukadinovich, Jennifer Lanctot, Pei-Lin Chen, and

Shannon Wright for coding and programming of databases and sys-

tems; Tiana Thomas, Madelene Wilson, Gail Fortner, Ashley Coley, and

Ivanka Rankovic for data collection; Kathleen Helton, Scott Hwang,

Nicole Alberts, Lisa Jacola, Latika Puri, Doralina Anghelescue, Daniel

Garrison, Wassim Chemaitilly, Yan Zheng, Kevin Krull, Sean Phipps,

John Brooke, Yutaka Yatsui, Evadnie Rampersaud, Gang Wu, and Ken-

neth Ataga, for intellectual input on planning future initiatives; and

Courtney Mays and Teresa Carr for support with study infrastructure

and regulatory matters.

ORCID

Jane S. Hankins http://orcid.org/0000-0003-4439-7321

REFERENCES

1. Hassell KL. Population estimates of sickle cell disease in the U.S. Am J Prev Med. 2010;38:S512–S521.

2. Piel FB, Hay SI, Gupta S, Weatherall DJ, Williams TN. Global burden

of sickle cell anaemia in children under five, 2010–2050: modelling

based on demographics, excess mortality, and interventions. PLoS Med. 2013;10:e1001484.

3. Piel FB, Patil AP, Howes RE, et al. Global epidemiology of sickle

haemoglobin in neonates: a contemporary geostatistical model-

based map and population estimates. Lancet. 2013;381:142– 151.

4. Platt OS, Brambilla DJ, Rosse WF, et al. Mortality in sickle cell dis-

ease. Life expectancy and risk factors for early death. N Engl J Med. 1994;330:1639–1644.

5. Scott RB. Health care priority and sickle cell anemia. JAMA. 1970;214:731–734.

6. Quinn CT, Lee NJ, Shull EP, Ahmad N, Rogers ZR, Buchanan GR. Pre-

diction of adverse outcomes in children with sickle cell anemia: a study

of the Dallas Newborn Cohort. Blood. 2008;111:544–548.

7. Hamideh D, Alvarez O. Sickle cell disease related mortality in the

United States (1999–2009). Pediatr Blood Cancer. 2013;60:1482– 1486.

8. Gaston MH, Verter JI, Woods G, et al. Prophylaxis with oral penicillin

in children with sickle cell anemia. A randomized trial. N Engl J Med. 1986;314:1593–1599.

9. Payne AB, Link-Gelles R, Azonobi I, et al. Invasive pneumococcal dis-

ease among children with and without sickle cell disease in the United

States, 1998 to 2009. Pediatr Infect Dis J. 2013;32:1308–1312.

10. Wang WC, Dwan K. Blood transfusion for preventing primary and sec-

ondary stroke in people with sickle cell disease. Cochrane Database Syst Rev. 2013;11:CD003146.

11. Lobo CL, Pinto JF, Nascimento EM, Moura PG, Cardoso GP, Hankins

JS. The effect of hydroxcarbamide therapy on survival of children with

sickle cell disease. Br J Haematol. 2013;161:852–860.

12. Le PQ, Gulbis B, Dedeken L, et al. Survival among children and adults

with sickle cell disease in Belgium: benefit from hydroxyurea treat-

ment. Pediatr Blood Cancer. 2015;62:1956–1961.

13. Benson JM. History and current status of newborn screening for

hemoglobinopathies. Semin Perinatol. 2010;34:134–144.

14. van Tuijn CFJ, Schimmel M, van Beers EJ, Nur E, Biemond BJ.

Prospective evaluation of chronic organ damage in adult sickle cell

patients: a seven-year follow-up study. Am J Hematol. 2017;92:E584– E590.

15. Blinder MA, Duh MS, Sasane M, Trahey A, Paley C, Vekeman F. Age-

related emergency department reliance in patients with sickle cell dis-

ease. J Emerg Med. 2015;49:513.e1–522.e1.

HANKINS ET AL. 11 of 12

16. Brousseau DC, Owens PL, Mosso AL, Panepinto JA, Steiner CA. Acute

care utilization and rehospitalizations for sickle cell disease. JAMA. 2010;303:1288–1294.

17. Gardner K, Douiri A, Drasar E, et al. Survival in adults with sickle cell

disease in a high-income setting. Blood. 2016;128:1436–1438.

18. Maitra P, Caughey M, Robinson L, et al. Risk factors for mortality in

adult patients with sickle cell disease: a meta-analysis of studies in

North America and Europe. Haematologica. 2017;102:626–636.

19. Porter JS, Wesley KM, Zhao MS, Rupff RJ, Hankins JS. Pediatric to

adult care transition: perspectives of young adults with sickle cell dis-

ease. J Pediatr Psychol. 2017;42:1016–1027.

20. Jordan L, Swerdlow P, Coates TD. Systematic review of transition from

adolescent to adult care in patients with sickle cell disease. J Pediatr Hematol Oncol. 2013;35:165–169.

21. SerjeantBE,ForbesM,WilliamsLL,SerjeantGR.Screeningcordbloods

for detection of sickle cell disease in Jamaica. Clin Chem. 1974;20:666– 669.

22. Serjeant GR, Serjeant BE. Management of sickle cell disease; lessons

from the Jamaican Cohort Study. Blood Rev. 1993;7:137–145.

23. Gaston M, Rosse WF. The Cooperative Study of Sickle Cell Disease:

review of study design and objectives. Am J Pediatr Hematol Oncol. 1982;4:197–201.

24. Gaston M, Smith J, Gallagher D, et al. Recruitment in the Cooperative

Study of Sickle Cell Disease (CSSCD). Control Clin Trials. 1987;8:131S– 140S.

25. QuinnCT,RogersZR,BuchananGR.Survivalofchildrenwithsicklecell

disease. Blood. 2004;103:4023–4027.

26. De Ceulaer K, McMullen KW, Maude GH, Keatinge R, Serjeant GR.

Pneumonia in young children with homozygous sickle cell disease: risk

and clinical features. Eur J Pediatr. 1985;144:255–258.

27. Balkaran B, Char G, Morris JS, Thomas PW, Serjeant BE, Serjeant GR.

Stroke in a cohort of patients with homozygous sickle cell disease.

J Pediatr. 1992;120:360–366.

28. John AB, Ramlal A, Jackson H, Maude GH, Sharma AW, Serjeant GR.

Prevention of pneumococcal infection in children with homozygous

sickle cell disease. Br Med J (Clin Res Ed). 1984;288:1567–1570.

29. Emond AM, Collis R, Darvill D, Higgs DR, Maude GH, Serjeant GR.

Acute splenic sequestration in homozygous sickle cell disease: natural

history and management. J Pediatr. 1985;107:201–206.

30. Serjeant GR, Topley JM, Mason K, et al. Outbreak of aplastic crises

in sickle cell anaemia associated with parvovirus-like agent. Lancet. 1981;2:595–597.

31. Quinn CT, Rogers ZR, McCavit TL, Buchanan GR. Improved sur-

vival of children and adolescents with sickle cell disease. Blood. 2010;115:3447–3452.

32. Gill FM, Sleeper LA, Weiner SJ, et al. Clinical events in the first decade

in a cohort of infants with sickle cell disease. Cooperative Study of

Sickle Cell Disease. Blood. 1995;86:776–783.

33. West MS, Wethers D, Smith J, Steinberg M. Laboratory profile of sickle

cell disease: a cross-sectional analysis. The Cooperative Study of Sickle

Cell Disease. J Clin Epidemiol. 1992;45:893–909.

34. Leikin SL, Gallagher D, Kinney TR, Sloane D, Klug P, Rida W. Mortality

in children and adolescents with sickle cell disease. Cooperative Study

of Sickle Cell Disease. Pediatrics. 1989;84:500–508.

35. Bray GL, Muenz L, Makris N, Lessin LS. Assessing clinical severity in

childrenwithsicklecell disease.Preliminaryresultsfromacooperative

study. Am J Pediatr Hematol Oncol. 1994;16:50–54.

36. Platt OS, Thorington BD, Brambilla DJ, et al. Pain in sickle cell disease.

Rates and risk factors. N Engl J Med. 1991;325:11–16.

37. Vichinsky EP, Styles LA, Colangelo LH, Wright EC, Castro O, Nick-

erson B. Acute chest syndrome in sickle cell disease: clinical presen-

tation and course. Cooperative Study of Sickle Cell Disease. Blood. 1997;89:1787–1792.

38. Moser FG, Miller ST, Bello JA, et al. The spectrum of brain MR abnor-

malities in sickle-cell disease: a report from the Cooperative Study of

Sickle Cell Disease. AJNR Am J Neuroradiol. 1996;17:965–972.

39. Ohene-Frempong K, Weiner SJ, Sleeper LA, et al. Cerebrovascu-

lar accidents in sickle cell disease: rates and risk factors. Blood. 1998;91:288–294.

40. Wang W, Enos L, Gallagher D, et al. Neuropsychologic performance

in school-aged children with sickle cell disease: a report from the

Cooperative Study of Sickle Cell Disease. J Pediatr. 2001;139:391– 397.

41. Armstrong FD, Thompson RJ Jr, Wang W, et al. Cognitive functioning

and brain magnetic resonance imaging in children with sickle cell dis-

ease. Neuropsychology Committee of the Cooperative Study of Sickle

Cell Disease. Pediatrics. 1996;97:864–870.

42. Hankins JS, McCarville MB, Rankine-Mullings A, et al. Prevention

of conversion to abnormal transcranial Doppler with hydroxyurea in

sickle cell anemia: a Phase III international randomized clinical trial.

Am J Hematol. 2015;90:1099–1105.

43. Ware RE, Davis BR, Schultz WH, et al. Hydroxycarbamide versus

chronic transfusion for maintenance of transcranial Doppler flow

velocities in children with sickle cell anaemia-TCD With Transfusions

Changing to Hydroxyurea (TWiTCH): a multicentre, open-label, phase

3, non-inferiority trial. Lancet. 2016;387:661–670.

44. Estepp JH, Smeltzer MP, Wang WC, Hoehn ME, Hankins JS, Aygun

B. Protection from sickle cell retinopathy is associated with elevated

HbF levels and hydroxycarbamide use in children. Br J Haematol. 2013;161:402–405.

45. Voskaridou E, Christoulas D, Bilalis A, et al. The effect of prolonged

administration of hydroxyurea on morbidity and mortality in adult

patients with sickle cell syndromes: results of a 17-year, single-center

trial (LaSHS). Blood. 2010;115:2354–2363.

46. Aygun B, Mortier NA, Smeltzer MP, Shulkin BL, Hankins JS, Ware

RE. Hydroxyurea treatment decreases glomerular hyperfiltration

in children with sickle cell anemia. Am J Hematol. 2013;88:116– 119.

47. Hankins JS, Aygun B, Nottage K, et al. From infancy to adolescence: fif-

teenyearsofcontinuoustreatmentwithhydroxyureainsicklecellane-

mia. Medicine. 2014;93:e215.

48. Wang WC, Ware RE, Miller ST, et al. Hydroxycarbamide in very young

children with sickle-cell anaemia: a multicentre, randomised, con-

trolled trial (BABY HUG). Lancet. 2011;377:1663–1672.

49. Smeltzer MP, Nolan VG, Yu X, et al. Birth prevalence of sickle cell

trait and sickle cell disease in Shelby County, TN. Pediatr Blood Cancer. 2016;63:1054–1059.

50. Smeltzer MP, Nolan VG, Yu X, et al. Distance from an urban sickle cell

center and its effects on routine healthcare management and rates of

hospitalization. Hemoglobin. 2016;40:10–15.

51. Nolan VG, Anderson SM, Smeltzer MP, et al. Pediatric to adult care

co-location transitional model for youth with sickle cell disease. Am J Hematol. 2018;93:E30–E32.

52. Yawn BP, Buchanan GR, Afenyi-Annan AN, et al. Management of sickle

cell disease: summary of the 2014 evidence-based report by expert

panel members. JAMA. 2014;312:1033–1048.

53. Panepinto JA, Paul Scott J, Badaki-Makun O, et al. Determining the

longitudinal validity and meaningful differences in HRQL of the Ped-

sQL Sickle Cell Disease Module. Health Qual Life Outcomes. 2017;15: 124.

12 of 12 HANKINS ET AL.

54. Varni JW, Limbers CA, Bryant WP, Wilson DP. The PedsQL multidi-

mensional fatigue scale in pediatric obesity: feasibility, reliability and

validity. Int J Pediatr Obes. 2010;5:34–42.

55. Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the

Pediatric Quality of Life Inventory version 4.0 generic core scales in

healthy and patient populations. Med Care. 2001;39:800–812.

56. Eckman JR, Hassell KL, Huggins W, et al. Standard measures for sickle

cell disease research: the PhenX Toolkit sickle cell disease collections.

Blood Adv. 2017;1:2703–2711.

57. Gay JL, Robb SW, Benson KM, White A. Can the social vulnerability

indexbeusedformorethanemergencypreparedness?Anexamination

using youth physical fitness data. J Phys Act Health. 2016;13:121–130.

58. Couque N, Girard D, Ducrocq R, et al. Improvement of medical care in

a cohort of newborns with sickle-cell disease in North Paris: impact of

national guidelines. Br J Haematol. 2016;173:927–937.

59. Tewari S, Brousse V, Piel FB, Menzel S, Rees DC. Environmen-

tal determinants of severity in sickle cell disease. Haematologica. 2015;100:1108–1116.

60. Guilcher GM. Can preconsent eliminate some barriers to clinical trial

enrollment of children with sickle cell disease in crisis?. Pediatr Blood Cancer. 2016;63:1511–1512.

61. Haywood C Jr, Lanzkron S, Diener-West M, et al. Attitudes toward

clinical trials among patients with sickle cell disease. Clin Trials. 2014;11:275–283.

62. Lebensburger JD, Sidonio RF, Debaun MR, Safford MM, Howard TH,

Scarinci IC. Exploring barriers and facilitators to clinical trial enroll-

mentinthecontextofsicklecellanemiaandhydroxyurea.PediatrBlood Cancer. 2013;60:1333–1337.

63. Nimmer M, Czachor J, Turner L, et al. The benefits and challenges of

preconsent in a multisite, pediatric sickle cell intervention trial. Pediatr Blood Cancer. 2016;63:1649–1652.

64. Patterson CA, Chavez V, Mondestin V, Deatrick J, Li Y, Barakat LP.

Clinical trial decision making in pediatric sickle cell disease: a qualita-

tive study of perceived benefits and barriers to participation. J Pediatr Hematol Oncol. 2015;37:415–422.

65. Stevens EM, Patterson CA, Li YB, Smith-Whitley K, Barakat LP. Mis-

trust of pediatric sickle cell disease clinical trials research. Am J Prev Med. 2016;51:S78–S86.

66. McQuillan GM, Porter KS, Agelli M, Kington R. Consent for genetic

research in a general population: the NHANES experience. Genet Med. 2003;5:35–42.

67. McQuillan GM, Porter KS. Consent for future genetic research: the

NHANES experience in 2007–2008. IRB. 2011;33:9–14.

68. Chang J, Patton JT, Sarkar A, Ernst B, Magnani JL, Frenette PS. GMI-

1070, a novel pan-selectin antagonist, reverses acute vascular occlu-

sions in sickle cell mice. Blood. 2010;116:1779–1786.

69. Ataga KI, Kutlar A, Kanter J, et al. Crizanlizumab for the preven-

tion of pain crises in sickle cell disease. N Engl J Med. 2017;376:429– 439.

70. Metcalf B, Chuang C, Dufu K, et al. Discovery of GBT440, an orally

bioavailable R-state stabilizer of sickle cell hemoglobin. ACS Med Chem Lett. 2017;8:321–326.

71. Ferrone FA. GBT440 increases haemoglobin oxygen affinity, reduces

sickling and prolongs RBC half-life in a murine model of sickle cell dis-

ease. Br J Haematol. 2016;174:499–500.

72. Dufu K, Lehrer-Graiwer J, Ramos E, Oksenberg D. GBT440 inhibits

sickling of sickle cell trait blood under in vitro conditions mimicking strenuous exercise. Hematol Rep. 2016;8:6637.

73. Hoppe C, Jacob E, Styles L, Kuypers F, Larkin S, Vichinsky E. Simvas-

tatin reduces vaso-occlusive pain in sickle cell anaemia: a pilot efficacy

trial. Br J Haematol. 2017;177:620–629.

74. Ribeil JA, Hacein-Bey-Abina S, Payen E, et al. Gene therapy in a patient

with sickle cell disease. N Engl J Med. 2017;376:848–855.

75. Nolan VG, Nottage KA, Cole EW, Hankins JS, Gurney JG. Prevalence

of vitamin D deficiency in sickle cell disease: a systematic review. PLoS One. 2015;10:e0119908.

76. Penkert RR, Hurwitz JL, Thomas P, et al. Inflammatory molecule reduc-

tion with hydroxyurea therapy in children with sickle cell anemia.

Haematologica. 2018;103:e50–e54.

77. Lettre G. The search for genetic modifiers of disease severity

in the beta-hemoglobinopathies. Cold Spring Harb Perspect Med. 2012;2:a015032.

78. Habara A, Steinberg MH. Minireview: genetic basis of heterogene-

ity and severity in sickle cell disease. Exp Biol Med (Maywood). 2016;241:689–696.

79. Saraf SL, Shah BN, Zhang X, et al. APOL1, alpha-thalassemia, and

BCL11A variants as a genetic risk profile for progression of chronic

kidney disease in sickle cell anemia. Haematologica. 2017;102:e1– e6.

80. Chou ST, Jackson T, Vege S, Smith-Whitley K, Friedman DF, Westhoff

CM. High prevalence of red blood cell alloimmunization in sickle cell

disease despite transfusion from Rh-matched minority donors. Blood. 2013;122:1062–1071.

81. Gammal RS, Crews KR, Haidar CE, et al. Pharmacogenetics for safe

codeine use in sickle cell disease. Pediatrics. 2016;138:e20153479.

82. Wilmore DW. Food and Drug Administration approval of glutamine

for sickle cell disease: success and precautions in glutamine research.

JPEN J Parenter Enteral Nutr. 2017;41:912–917.

83. Niihara Y, Matsui NM, Shen YM, et al. L-glutamine therapy reduces

endothelial adhesion of sickle red blood cells to human umbilical vein

endothelial cells. BMC Blood Disord. 2005;5:4.

84. Niihara Y, Zerez CR, Akiyama DS, Tanaka KR. Oral L-glutamine therapy

for sickle cell anemia: I. Subjective clinical improvement and favorable

change in red cell NAD redox potential. Am J Hematol. 1998;58:117– 121.

SUPPORTING INFORMATION

Additional supporting information may be found online in the Support-

ing Information section at the end of the article.

How to cite this article: Hankins JS, Estepp JH, Hodges JR,

et al. Sickle Cell Clinical Research and Intervention Program

(SCCRIP): A lifespan cohort study for sickle cell disease pro-

gression from the pediatric stage into adulthood. Pediatr Blood

Cancer. 2018;65:e27228. https://doi.org/10.1002/pbc.27228