Communicating Health Information and Improving Coordination With Primary Care - an Ancillary Study of the Childhood Cancer Survivor Study
Phase: NA
Conditions: Hypertension, Dyslipidemias, Diabetes, Childhood Cancer
Sponsor: Fred Hutchinson Cancer Center

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FRED HUTCHINSON CANCER RESEARCH CENTER 
UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE 
SEATTLE CHILDREN’S 
 
7/10/20 
 
Title of Protocol: 
Communicating Health Information and Improving Coordination with Primary Care (CHIIP) Study 
 
 
Investigators List: 
Eric J. Chow, MD, MPH 
Associate Professor, FHCRC, Associate Professor of Pediatrics, 
UW 
(206) 667-4630 
Gregory T. Armstrong, 
MD, MSCE 
Member, St. Jude Children’s Research Hospital 
 
Laura-Mae Baldwin, 
MD, MPH 
Professor of Family Medicine, UW 
 
Melissa Hudson, MD 
Member, St. Jude Children’s Research Hospital 
 
Lisa Johnson, PhD 
Senior Staff Scientist, FHCRC 
 
Paul Nathan, MD, MSc 
Professor of Pediatrics, University of Toronto 
 
Kevin Oeffinger, MD 
Professor of Medicine, Duke University 
 
Charles Sklar, MD 
Professor of Pediatrics, Memorial Sloan-Kettering Cancer 
Center 
 
Karen Syrjala, PhD 
Professor, FHCRC 
 
Yutaka Yasui, PhD 
Member, St. Jude Children’s Research Hospital 
 
 
SPONSOR:  National Cancer Institute 
  
Coordinating Center: 
Fred Hutchinson Cancer Research Center 
Additional Performance Sites: 
St. Jude Children’s Research 
Hospital  
Gregory T. Armstrong, MD, MSCE 
(901) 595-6078 
 
 
 

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PROTOCOL SYNOPSIS 
 
Protocol Title 
CHIIP Study (Communicating Health Information & Improving coordination with Primary care) 
Protocol No. 
FH IRB Files 8543 and 8543-A and Clinical Trial NCT03104543 
Sponsor 
National Cancer Institute 
Trial Type 
Randomized clinical trial of a counseling/educational intervention 
Clinical 
Indication 
Survivors of childhood cancer are known to be at higher risk of developing premature, serious 
cardiovascular disease compared with the general population. Hypertension, dyslipidemia, 
and diabetes increase this risk beyond that attributable to one’s original cancer therapy 
exposures. Research has shown that childhood cancer survivors also have a high burden of 
underdiagnosis and undertreatment of these potentially modifiable conditions.  
Study 
Objectives 
1. To determine the prevalence of underdiagnosis and undertreatment of common 
cardiometabolic conditions (i.e., hypertension, dyslipidemia, diabetes) in survivors of 
childhood cancer at high-risk of future serious cardiovascular disease. 
2. Among survivors who are found to be underdiagnosed or undertreated, to determine (via 
randomized clinical trial) the efficacy of a counseling/educational intervention to improve 
control of these cardiometabolic conditions.  
3. Determine barriers on among survivors enrolled on the randomized trial and their primary 
healthcare providers that contribute to undertreatment of the study’s targeted 
cardiometabolic conditions.  
Study Design 
Aim 1 is an observational study. Aims 2 and 3 are based on a randomized clinical trial design.  
Population 
Participants in the existing Childhood Cancer Survivor Study cohort who are classified as high-
risk for future cardiovascular disease based on their demographic and cancer therapy 
exposures.  
Primary 
Endpoints 
Aim 1: Prevalence of underdiagnosis and undertreatment of hypertension, dyslipidemia, and 
diabetes.  
Aim 2: Probability of having an undertreated condition 
Secondary 
Endpoints 
Aim 3: Determine whether intervention and control arms differ in terms of survivor 
knowledge, self-efficacy, and medication adherence, as well as differences in their providers’ 
knowledge and self-efficacy related to the care of childhood cancer survivors.  
Type of control 
Delayed intervention control (i.e., can choose to receive the intervention at the end of the 
study period).  
Trial Blinding 
Study staff performing home visits and study statisticians will be blinded. Participants and 
study staff delivering the counseling intervention cannot be blinded given the nature of the 
study.  
Treatment 
Groups  
Group A: upfront intervention group (30 minute counseling session focused on survivorship 
care plan, personalized action plan; 15 minute booster session at 4 months) 
Group B: delayed intervention control group (30 minute counseling session focused on 
survivorship care plan, personalized action plan) 
Treatment 
Schedule 
Baseline: educational materials (survivorship care plan, personalized action plan, and 30 
minute counseling intervention 
4 months: 15 minute booster session  
Efficacy 
Assessments 
Baseline: patient questionnaire and 1st home visit 
4 months: action plan scoring by study staff 
12 months: patient questionnaire and 2nd home visit 
No. subjects 
Anticipate 800 for Aim 1, and project that ~480 maybe eligible to participate on Aims 2 and 3.  
Estimated 
duration 
5-years 
Duration of 
Participation 
1-year interval between initial survey and home visit and follow-up survey and home visit.  

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Table of Contents 
1.0 
GENERAL INFORMATION .................................................................................................................................... 5 
2.0 
INTRODUCTION ................................................................................................................................................... 5 
2.1 
Introduction ........................................................................................................................................... 5 
2.2 
Clinical Data to Date .............................................................................................................................. 8 
2.3 
Risks/Benefits ...................................................................................................................................... 10 
3.0 
OVERVIEW OF CLINICAL TRIAL .......................................................................................................................... 11 
3.1 
Study Objectives .................................................................................................................................. 11 
3.2 
Study Population.................................................................................................................................. 12 
3.3 
Study Design ........................................................................................................................................ 12 
3.4 
Estimated Accrual ................................................................................................................................ 13 
3.5 
Sponsor/Funding Source ...................................................................................................................... 13 
4.0 
SAFETY CONSIDERATIONS ................................................................................................................................. 13 
5.0 
SUBJECT ELIGIBLITY ........................................................................................................................................... 14 
5.1 
Inclusion Criteria .................................................................................................................................. 14 
5.2 
Exclusion Criteria, applicable to all participants .................................................................................. 15 
6.0 
SUBJECT RECRUITMENT & REGISTRATION ....................................................................................................... 15 
6.1 
Recruitment ......................................................................................................................................... 15 
6.2 
Registration .......................................................................................................................................... 16 
7.0 
TREATMENT PLAN ............................................................................................................................................. 17 
7.1 
Treatment Plan Overview .................................................................................................................... 17 
7.2 
Assignment of Study Group ................................................................................................................. 17 
7.3 
Intervention Group .............................................................................................................................. 18 
7.4 
Delayed Intervention Control .............................................................................................................. 18 
7.5 
Interaction with Primary Healthcare Providers ................................................................................... 18 
7.6 
Duration of Therapy and Follow-Up .................................................................................................... 19 
8.0 
STUDY PROCEDURES ......................................................................................................................................... 20 
8.1 
Baseline Questionnaire ........................................................................................................................ 20 
8.2 
First Home Visit .................................................................................................................................... 21 
8.3 
Baseline Counseling Session (Intervention Group) .............................................................................. 21 
8.4 
Baseline Return of Results (Control Group) ......................................................................................... 22 
8.5 
Handling of Critical Results .................................................................................................................. 22 
8.6 
Four-month Booster Session ............................................................................................................... 23 
8.7 
Second Questionnaire and Home Visit ................................................................................................ 23 
8.8 
Primary healthcare provider measurements ....................................................................................... 24 
8.9 
Materials returned to participants and primary healthcare providers ............................................... 24 
8.10 
Remote blood pressure monitoring pilot ............................................................................................ 25 

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9.0 
OFF STUDY CRITERIA ......................................................................................................................................... 26 
10.0 
ADVERSE EVENTS .............................................................................................................................................. 26 
10.1 
Expected Adverse Events ..................................................................................................................... 26 
10.2 
Monitoring and Recordings Adverse Events ........................................................................................ 27 
11.0 
DATA AND SAFETY MONITORING PLAN ............................................................................................................ 27 
12.0 
DATA MANAGEMENT/CONFIDENTIALITY ......................................................................................................... 27 
13.0 
STATISTICAL CONSIDERATIONS ......................................................................................................................... 27 
13.1 
Aim 1 Analytic Plan .............................................................................................................................. 28 
13.2 
Aim 2 Analytic Plan .............................................................................................................................. 28 
13.3 
Aim 3 Analytic Plan .............................................................................................................................. 29 
13.4 
Ethnic and Gender Distribution Chart ................................................................................................. 32 
14.0 
REFERENCES ...................................................................................................................................................... 33 
15.0 
APPENDICES ...................................................................................................................................................... 37 
 
 
 
 

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1.0 
GENERAL INFORMATION 
 
Children and adolescents diagnosed with cancer now have on average >80% 5-year survival. However, 
premature cardiovascular (CV) disease has become the leading non-cancer cause of late mortality 
among childhood cancer survivors. Our existing work has shown that traditional CV risk factors such as 
hypertension, dyslipidemia, insulin resistance/diabetes remain very important, by increasing (in 
synergistic fashion) the risk of major CV events such as ischemic heart disease and heart failure. 
However, the existing research has been limited by misclassification of CV risk factor status (i.e., when 
defined by self-report or medication usage alone), including issues with both underdiagnosis (i.e., 
people with these risk factors present but who are unaware) and uncertainty of disease control (i.e., 
potential undertreatment).  
 
This NCI-funded proposal will utilize the largest, best characterized childhood cancer survivor cohort in 
the world, the Childhood Cancer Survivor Study (CCSS; n=24,466). The CCSS, known to study participants 
as the “Long Term Follow-Up [LTFU] Study”, is a National Cancer Institute (NCI) funded resource with its 
data coordination center at St. Jude Children’s Research Hospital and its statistical center at FHCRC.1 
CCSS promotes the development of “ancillary” studies that obtain supplemental funding to extend 
cohort research beyond what the parent grant can accomplish. Thus, for the proposed CHIIP Study, we 
will use CCSS-derived validated risk prediction algorithms to select CCSS survivors at high risk of serious 
heart disease (n~800) based on past cancer treatment exposures. Among these 800 survivors, we 
propose to determine the magnitude of underdiagnosis and undertreatment of hypertension, 
dyslipidemia, and diabetes via in-person (home-based) measurements supplemented by medical record 
review. We predict that around 60% of survivors (n~480) will be underdiagnosed or undertreated with 
respect to one of these three CV risk factors. Survivors who are underdiagnosed or undertreated will 
then be eligible to participate in a 1-year long randomized controlled trial, where we will measure the 
efficacy of an Institute of Medicine (IOM) recommended personalized survivorship care plan (SCP) 
emphasizing CV risk, supplemented by a remotely delivered clinician-led self-management counseling 
intervention, to improve control of these three CV risk factors (i.e., reduce rates of undertreated 
hypertension, dyslipidemia, and diabetes). Survivors randomized to the control arm can receive the 
intervention on a delayed basis. Finally, our proposal seeks to better understand barriers among 
survivors and their primary healthcare providers that contribute to CV risk factor undertreatment.  
 
Knowledge derived from this study will improve the assessment and treatment of important CV risk 
factors in this high risk population. The proposed intervention, if successful, will be disseminable and 
low cost, and will have the potential to improve health and reduce mortality in these younger adults 
who live the majority of their lives as cancer survivors at increased risk of serious CV disease. The 
protocol described below is classified as clinical research and will be conducted in compliance with the 
Fred Hutchinson Cancer Research Center / Cancer Consortium’s approved policies/procedures, and in 
compliance with all associated Federal regulations.  
 
 
2.0 
INTRODUCTION  
 
2.1 Introduction 
There are nearly half a million survivors of childhood cancer estimated to be living in the United States.2 
Premature CV disease is a leading contributor to late morbidity and mortality in this population.3-7 
Cohort studies from North America and Europe, including the CCSS, have consistently shown that 

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survivors have a 5+ fold increased risk of serious CV morbidity or mortality vs. the general population, 
corresponding to ~5% cumulative incidence by age 45 years.3-11 Among survivors that have been 
exposed to cardiotoxic cancer treatments (i.e., anthracyclines and chest radiotherapy), this risk can be 
markedly greater (Table 1).6,7 Demographic characteristics such as age at treatment and gender, and off-
target and indirect effects of both radiotherapy and chemotherapy may also affect CV health.6,7,12-14 
 
TABLE 1. Cardiovascular (CV) risk group outcomes among the original CCSS cohort through age 50. 
 
Predicted low risk* 
 
Predicted high risk* 
Serious CV event 
No. events  
/ no. at risk 
Cumulative incidence / 
relative risk (RR) vs. siblings  
No. events 
/ no. at risk 
Cumulative incidence / 
relative risk (RR) vs. siblings 
Ischemic heart disease 
73 / 8801 
2.3% / RR=2.3, p<0.001 
 
89 / 764 
19.9% / RR=17.8, p<0.001 
Heart failure  
18 / 5197 
1.0% / RR=1.8, p=0.11 
 
108 / 2059 
12.4% / RR=41.5, p<0.001 
*Risk prediction for 5-yr survivors (n=13,060) through age 50, based on sex, diagnosis age, anthracycline and 
chest radiotherapy doses.12,15 Area under the curve [AUC]/C-indices for these models ranged 0.70-0.76 (CCSS), 
and 0.66-0.82 (external validation cohorts).  
 
Multiple studies in childhood and adult cancer survivors also 
have shown that even after considering treatment exposures, 
the presence of conventional CV risk factors such as 
hypertension, diabetes, and dyslipidemia are important, and 
may further increase the risk of serious CV disease in more 
than additive fashion.7,16,17 Among CCSS participants, 
hypertension was associated with significantly increased 
relative excess risks due to interaction [RERI] for ischemic 
heart disease (after chest radiotherapy) and heart failure 
(after anthracyclines; Figure 1); RERI was also significantly 
increased for dyslipidemia and diabetes.7 Furthermore, 
survivors predicted to be at high risk for ischemic heart 
disease and heart failure, on the basis of their cancer 
treatment exposures alone, also had higher self-reported 
rates of hypertension, dyslipidemia, and diabetes vs. survivors 
predicted to be at low risk (Table 2). Among childhood cancer 
survivors, the development of these conditions also tends to 
occur at younger ages compared with siblings or the general 
population.18-21 Given the relatively young age of onset of 
these conditions that occur more typically in older adults, and 
the limited knowledge of cancer survivor-specific screening 
guidelines among general practitioners,22,23 most high risk 
survivors likely do not receive recommended CV screening 
studies.24-26 Thus, there is a compelling rationale to develop 
interventions for this high risk population designed to target these modifiable CV risk factors. 
 
A frequent limitation of many studies that have examined the relationship between hypertension, 
dyslipidemia, diabetes, and subsequent more serious outcomes in survivors of childhood cancer, 
including some of our own work, is reliance on self-report and/or the use of medications as surrogates 
for these risk factors, in lieu of physiologic or more objective clinical data. Where such data have been 
available, they often have been collected retrospectively, in a non-standardized fashion, or are only 
available in cross-sectional analyses with either relatively limited sample sizes, recruited from a single 
FIGURE 1. Relative risk of serious CV 
outcomes in CCSS per treatment 
exposures & hypertension status.9  
ANTH[racycline]; CRT, chest radiotherapy; 
HTN, hypertension. Relative excess risk due 
to interaction (RERI) between  treatment 
exposure & hypertension for these 2 
outcomes: †RERI=24 (95% CI 12-40), 
‡RERI=45 (95% CI 17-106). RERI>0 indicates 
that interaction was more than additive. 
*P<0.01 vs. referent. 

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center, and/or a focus on a single cancer type, all of which limit generalizability.5,19,20 However, these 
studies support the hypothesis that underdiagnosis of these CV risk factors is common among survivors.  
 
Also unanswered is the degree to which survivors known to have hypertension, dyslipidemia, or 
diabetes are adequately treated (undertreatment). We are unaware of studies that have attempted to 
examine CV risk factor undertreatment among childhood cancer survivors, and such studies are rare 
among survivors of adult cancers.27-31 Our prior research showed that survivors with these CV risk 
factors, defined on the basis of medication use, were at significantly greater risk of more serious CV 
events (e.g., ischemic heart disease, heart failure) vs. other survivors.7,17 Thus, we hypothesize that 
survivors may be significantly undertreated even when diagnosed. The drivers of undertreatment may 
be related to healthcare providers not intervening sufficiently and/or non-adherence to appropriate 
interventions among survivors themselves.27,32,33  
 
TABLE 2. Prevalence of selected CV risk factors by 10-year age groups, stratified by CV-risk status* 
among the original CCSS cohort (n=13,060) and a sibling comparison group (n=4,023). 
 
Ischemic heart disease risk model 
Heart failure risk model 
Hypertension† 
Dyslipidemia† 
Diabetes† 
Prediction AUC (C-index)‡ 
Ischemia 
Heart failure 
  with the above risk factors 
0.76 (0.74) 
0.76 (0.78) 
  without the 3 risk factors 
0.74 (0.73) 
0.75 (0.77) 
  Difference in model fit 
p=0.01 (p=0.07) 
p=0.04 (p=0.03) 
*Low and high risk groups for ischemic heart disease and heart failure based on prediction models developed for 
5-yr cancer survivors (see Table 1). †Defined as those who reported being diagnosed by a physician for the 
condition(s) and who took specific medications to treat that condition(s) for >1 month or for ≥30 days in a 1 year 
period during the previous 2 years. ‡Prediction AUC (C-indices) based on 10,521 survivors with CCSS questionnaire 
data, and incorporates presence of CV risk factor information (†) present at baseline risk assessment (age 26). 
 
The study’s intervention will feature an IOM-recommended survivorship care plan [SCP], which is 
designed to promote knowledge/awareness of personal health risks among survivors and to help 
disseminate that information to primary healthcare providers.34 Prior research has shown that >80% of 
adult survivors of childhood cancer are followed by primary care providers,25,26,35 and that while the 
majority of internists and family practitioners report caring for childhood cancer survivors, receipt of a 
SCP remains uncommon and the vast majority of surveyed providers do not report familiarity with long-
0
10
20
30
40
50
60
Prevalence, %
0
10
20
30
40
50
60
0
10
20
30
40
50
Prevalence, %
0
10
20
30
40
50
0
5
10
15
20
<30y
30-39y
40-49y
≥50y
Prevalence, %
0
5
10
15
20
<30y
30-39y
40-49y
≥50y

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term follow-up guidelines for childhood cancer survivors.22,23 Our SCP intervention also will be enhanced 
by the use of recently developed and validated individual CV risk predictors our group has created 
specifically for childhood cancer survivors (Tables 1, 2). Although the SCP is by itself a tool to foster self-
management, we will further supplement it with well-established, focused chronic disease self-
management strategies now being applied to improve coordination of cancer survivorship care (Figure 
2).36-39 Collection of directly measured data also offers an opportunity to further refine risk prediction in 
the future, beyond using self-report alone (Table 2).  
 
In summary, our proposal will systematically assess the magnitude of underdiagnosis and 
undertreatment, along with contributing survivor- and provider-specific barriers, among adult-aged 
CCSS participants predicted to be at high risk of future serious CV disease. Results from this proposal 
may significantly advance our understanding of CV disease risk among childhood cancer survivors of all 
ages, given that many of the cancer treatments CCSS participants received remain in common use 
today.40,41 If successful, our IOM-based personalized intervention will increase the proportion of 
survivors and healthcare providers who are aware of current screening guidelines, who receive/deliver 
more appropriate CV treatment, and who adhere to these guidelines and treatments. The cumulative 
effect will be a mitigation of survivors’ long-term CV risks. 
 
2.2 Clinical Data to Date 
The home sampling methodology 
proposed is based on the NHLBI-
supported Women’s Health 
Initiative’s (WHI) recently completed 
Long Life Study, where women (age 
≥63 years) underwent home-based 
sample collection using Examination 
Management Services, Inc. (EMSI). 
Among 14,000 eligible women, 66% 
consented, and 85% of those who 
consented had a biospecimen 
collected with excellent results (≥95% 
successful collection). With WHI 
investigator input, CCSS conducted 
an EMSI pilot study from Fall 2014 to 
Spring 2015, approaching 200 
randomly selected CCSS participants 
living within a 50-mile radius of 2 
metropolitan areas (Minneapolis & 
Philadelphia) to complete a home 
visit featuring a 12-page 
questionnaire, followed by physical 
measurements and a fasting blood 
draw. Participants received a $50 gift card after study completion and prompt notification (<72 hours) of 
any clinically meaningful lab results (standard metabolic panel, lipid profile, hemoglobin [Hb] A1c). After 
6 months, 60% of participants had consented (11% active refusals). The median age of participants was 
43 years (range 30-57). Among those who consented, 90% completed home-based data collection (all 
with viable samples, n=107) as of April 2015. Although women were more likely to participate than men 
(58% vs. 42%), participation did not differ significantly by race/ethnicity, age, or treatment era. Overall, 
FIGURE 2. Survivorship self-management model (adapted from 
Schulman-Green, McCorkle, and colleagues.46 
 
 
 

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the CCSS results approximate those from WHI, despite having a population that is half men, who 
generally have lower participation rates than women.42 Given concerns that more urban CCSS 
participants may differ from others, we found that those who lived <50 vs. >50 miles from an existing 
CCSS center (all major metropolitan areas) were similar with respect to demographic and treatment 
characteristics, except that racial/ethnic minority status was more common among participants residing 
<50 miles (18% vs. 11%).  
 
Direct measurement of participants from 
the EMSI pilot study plus data from 
randomly selected CCSS participants 
directly measured in 2013 found that 
abnormal blood pressure, fasting lipid, or 
blood glucose values were common 
(median age 42; 45% male). 37% of 
participants had ≥1 value (blood 
pressures ≥140/90 mmHg, LDL 
cholesterol ≥160 mg/dL or triglyceride 
≥150 mg/dL, blood glucose ≥126 mg/dL 
or HbA1c ≥6.5%) meeting commonly 
accepted clinical standards for 
therapeutic intervention (i.e., lifestyle 
prescription and/or medication 
management). This included 23% of 
survivors who did not have a self-reported history of any of these 3 conditions (i.e., potential 
underdiagnosis). If thresholds included higher pre-hypertension values (≥130/85 mmHg) and pre-
diabetes (glucose ≥100 mg/dL or HbA1c ≥5.7%), the prevalence of those with an abnormal value 
increased to 50% (Figure 3). Specifically, among 52 high CV risk survivors, ~60% had an abnormal CV 
measurement, with the prevalence of individual risk factors ranging 20-40%. Among those with 
abnormalities, ~40% were undertreated (prevalence of individual undertreated conditions 5-20%) and 
~80% had a potentially underdiagnosed condition (prevalence of individual underdiagnosed conditions 
15-30%). 20% of survivors also had underdiagnosis of 1 condition and undertreatment of another 
condition. These data support our hypotheses that both underdiagnosis and undertreatment of CV risk 
factors are common among adult-aged survivors of childhood cancer, and that previously published rates 
based on self-report, particularly if restricted to medication use, underestimate and misclassify the true 
burden of these risk factors. 
 
The randomized intervention component of the CHIIP study will be based upon past CCSS intervention 
studies that incorporated distance-based delivery of SCPs (led by Drs. Oeffinger & Hudson, both co-
investigators).  
 
PROJECT VISION (PI: Oeffinger; Livestrong; 2003-05) enrolled 62 (86% participation rate) adult-aged 
Hodgkin lymphoma survivors at increased risk for either breast cancer or cardiomyopathy to test the 
acceptability of an IOM-based SCP supplemented by a study website and an effort to engage 
participants’ primary care providers.43 92% of participants completed a 6-month post-intervention 
survey; 75% remembered receiving, reading, and understanding the SCP. Among participants, prior 
knowledge of mammogram and echocardiogram screening recommendations was low (32% and 12% 
respectively). During the 6-month study period, 41% and 20% of eligible respondents obtained a 
mammogram and echocardiogram, respectively, with another 35% (for both tests) planning to do so 
FIGURE 3. Yield of directly measured data in relation to self-
report among randomly selected CCSS participants (n=175). 
*Per self-report. †Among those with self-reported condition if home 
sampled value was beyond standard therapeutic range. ‡No prior self-
reported history of respective condition with abnormal value.  
22.5
24.6
13.7
5.7
13.7
5.6
20.6
15.4
17.7
0
5
10
15
20
25
30
Hypertension
Dyslipidemia
Diabetes
Prevalence, %
Before home visit*
Undertreated†
Underdiagnosed‡

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within the next 6 months. As such, these data guide our planned intervention follow-up period of 12 
months between assessments. Similar to other studies,44 website usage was limited among these young 
adult survivors (29% visit rate). Primary care providers demonstrated limited engagement: only 19% of 
providers volunteered to participate; none visited the study website or contacted the study team.43  
 
The ECHOS trial (co-PI: Hudson; R01 CA136912; 2009-13) extended the methods in VISION to directly 
test the efficacy of a SCP supplemented by 2 nurse practitioner-led phone self-management counseling 
sessions on cardiomyopathy screening (vs. mailed SCP alone).45 After 1-year, the randomized 
intervention group had higher rates of obtaining recommended echocardiograms per self-report 
validated by medical records (52% vs. 22% SCP alone [p<0.001]; RR 2.3, 95% CI 1.7-3.1). The intervention 
group also was less likely to report lack of physician recommendation as a reason for not obtaining an 
echocardiogram, suggesting that the counseling further enhanced communication between recipients 
and their primary care provider beyond what a SCP alone would have accomplished.46 The study had an 
87% retention rate at 1-year follow-up (n=411 of 472).45  
 
2.3 Risks/Benefits 
The proposed home visits and biosample and data collection itself pose minimal risk to participants. 
Anthropometric measurements are all non-invasive. There would be a blood draw (thus potential for 
brief mild pain) associated with any home visit (1 to 2 over the course of the study for any given 
participant). The study team will ensure that the amount drawn at any visit is safe from a blood volume 
standpoint. It is possible, but unlikely, that some survey questions may cause participants to feel 
uncomfortable. All instruments proposed have been previously used in other research.  
 
For participants selected to participate in the randomized intervention trial, it is possible that receipt of 
clinical lab results may cause some participants to feel uncomfortable or anxious. Similarly, receipt of a 
SCP with an individual’s predicted cardiovascular risk may cause anxiety or discomfort. We will be 
monitoring self-reported anxiety and depression as part of our study. Nevertheless, we feel that 
providing such information, even when unexpected, may be important and have important future 
health consequences, as the research data to be provided to participants are all results with clinical 
interpretation and significance. For participants on the intervention arm, they will get a telephone or 
web video session by which any results are given and explained to them by a survivorship trained 
clinician, approximating a normal clinical exchange. Participants on the control arm will only get a letter 
summarizing clinically relevant results, and will be encouraged to discuss any abnormal results with their 
primary healthcare provider. The study has in place, a process by which critical test results will be 
reported to the study team in real time, in which case, the PI or his designee, can notify the participant 
more quickly to seek medical follow-up. This process is similar to and adapted from that used by the 
CDC-sponsored NHANES for their in-person mobile assessments. For participants (either intervention or 
delayed control) with clinically actionable results but who have no current healthcare provider, the 
study team has access to resources to aid participants in finding providers in their area who have 
expertise in treating survivors of childhood cancer. This will be clearly explained on their results letter.  
 
Control participants will get access to the SCP with personalized recommendations and a self-
management counseling session with formal written summary “action plan” following the 2nd home visit 
if they chose to. Finally, all healthcare providers designated by the study participant will also receive a 
copy of the same clinically relevant study test results. Providers of intervention study participants also 
will receive a copy of the SCP with personalized recommendations following both home visits. SCPs are 
IOM-recommended documents now felt to be integral to cancer care, but whose efficacy in modifying 

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clinical endpoints has not been rigorously studied. Prior CCSS and other research also have shown that 
most cancer survivors have not previously received a SCP. 
 
 
3.0 
OVERVIEW OF CLINICAL TRIAL 
 
3.1 Study Objectives 
We propose to determine the magnitude of hypertension, dyslipidemia, and diabetes underdiagnosis 
(i.e., people with these risk factors but unaware) and undertreatment (i.e., previously diagnosed but not 
achieving standard treatment goals) among a national sample of childhood cancer survivors. We will 
then test, in a randomized controlled design, the efficacy of an Institute of Medicine (IOM) 
recommended personalized survivorship care plan (SCP) intervention designed to improve control (i.e., 
reduce undertreatment) of these three CV risk factors. SCPs contain a summary of one’s past cancer 
treatment and an evidence-based follow-up plan. They are devised to bridge the knowledge gap 
regarding cancer treatment late effects among both survivors and primary healthcare providers. 
However, despite endorsement of SCPs by the IOM and other groups, few studies have examined the 
efficacy of SCPs in modifying clinical endpoints. Finally, we will attempt to understand barriers to CV risk 
factor undertreatment among both survivors and healthcare providers – an understudied area among 
cancer survivors. home) assessments.  
 
3.1.1 
Primary Aim 1. 
Determine the prevalence of underdiagnosis and undertreatment of conventional 
CV risk factors (i.e., hypertension, dyslipidemia, and diabetes) among CCSS 
participants predicted to be at high risk (n~800) for future serious CV disease (i.e., 
ischemic heart disease, cardiomyopathy/heart failure) on the basis of their original 
cancer treatment exposures (e.g., chest radiotherapy, anthracycline doses).   
• 
Hypothesis: At the initial home-visit, ~60% (n~480) will have a blood pressure, 
lipid, and/or glucose value that meets clinical thresholds for intervention. 
Among those with abnormalities, 40% will have a known pre-existing CV risk 
factor diagnosis but are undertreated, and 80% will be newly diagnosed.  
 
3.1.2 
Primary Aim 2 
Among survivors found to be underdiagnosed or undertreated (Aim 1), in a 
randomized controlled design, compare changes in blood pressure, lipid, and blood 
glucose values from baseline to 1-year between those receiving the intervention 
(providing clinical results and survivorship care plans [SCPs] to participants and 
their healthcare providers, supplemented by clinician-led remote counseling 
sessions with participants to review SCP contents and teach CV risk factor self-
management strategies) vs. control (providing clinical results without SCP to 
participants and their healthcare providers; with delayed access to the 
intervention).  
• 
Hypothesis: At the 1-year follow-up home visit, survivors randomized to the 
intervention arm will have a lower probability of having an undertreated CV risk 
factor compared with survivors in the control arm.  
 
3.1.3 
Primary Aim 3 
Determine barriers among (Aim 2) survivors (at baseline and 1-year: knowledge of 

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past cancer treatment, self-efficacy, health-related attitudes, medication 
adherence) and their primary healthcare providers (at 1-year only: knowledge and 
self-efficacy towards childhood cancer survivorship care) that contribute to 
undertreatment of hypertension, dyslipidemia, and diabetes. 
• 
Hypothesis 1: At baseline, underdiagnosis and undertreatment will be 
associated with lower knowledge, self-efficacy, and medication adherence, as 
well as a “self-controlling” health attitude among survivors.  
• 
Hypothesis 2: At 1-year follow-up, intervention-arm participants will report 
improved knowledge, self-efficacy, and medication adherence vs. controls; 
healthcare providers who received the SCP will report improved knowledge and 
self-efficacy towards CV risk and survivorship care vs. providers of controls. 
 
3.2 Study Population 
The study would seek to enroll ~800 current participants of the Childhood Cancer Survivor Study (CCSS) 
cohort, an existing NIH-funded resource study with >24,000 cohort members that has been actively 
funded for >20 years. The study would secondarily also survey participants’ designated primary 
healthcare provider regarding knowledge and self-efficacy related to care of childhood cancer survivors. 
 
3.3 Study Design 
The study’s first primary aim will be answered by recruiting a cross-sectional sample of predicted high 
CV risk patients. Those who meet eligibility criteria will then be randomized to a controlled intervention 
with delayed intervention controls to answer the study’s second and third primary aims.  
 
3.3.1 
Primary Aim 1 Endpoint: Prevalence of underdiagnosis and undertreatment of the 
following target CV conditions. Underdiagnosis defined for each as: 
• 
Hypertension: Joint National Committee (JNC7/8)47,48 considers systolic 
120-139 and diastolic pressures 80-89 mmHg to be suggestive of pre-
hypertension; lifestyle intervention is recommended.47,49 Hypertension is 
suspected if systolic ≥140 or diastolic ≥90 mmHg, and in addition to 
lifestyle modification, pharmacologic treatment is recommended for adults 
<60 years (treatment threshold ≥150 systolic if ≥60 years).48 We will 
ascertain the prevalence of pre-hypertension and hypertension; both may 
be eligible for Aim 2. However, with the introduction of the 2017 ACC/AHA 
hypertension guidelines, the classification system has shifted such that 
systolic ≥130 or diastolic ≥80 mmHg are now considered Stage 1+ 
hypertension (with treatment threshold reduced accordingly).50 As such, 
with our 12/2017 protocol modification, we will adopt these slightly more 
stringent thresholds for eligibility and drop the prior “pre-hypertension” 
category.   
• 
Dyslipidemia: American Heart Association and American Academy of 
Pediatrics recommend intervening (lifestyle modification first; if 
unsuccessful, consider pharmacologic therapy) among childhood cancer 
survivors for LDL ≥160 mg/dL or fasting triglyceride ≥150 mg/dL.51 As 
fasting blood draws are not as commonly done in most primary care 
settings now for initial screening, for non-fasting (<10 hours) samples, a 
triglyceride ≥200 mg/dL is considered high. This study will use these cut-
points to define dyslipidemia. These thresholds were largely in-line with 

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those defined by a recent NIH-sponsored expert panel,52 and largely similar 
to prior NCEP Adult Treatment Panel recommendations.53  
• 
Diabetes: American Diabetes Association classifies fasting blood glucose 
100-125 mg/dL or HbA1c 5.7-6.4% as suggestive of impaired glucose 
tolerance (pre-diabetes). Similar to dyslipidemia, as fasting blood draws are 
not as commonly done in most primary care settings now for initial 
screening, for non-fasting (<8 hours) samples, blood glucose 140-199 
mg/dL will be classified as suggestive of pre-diabetes if HbA1c was <5.7%. 
Lifestyle intervention is recommended (metformin prevention considered 
for select high risk populations).54 Diabetes requires fasting blood glucose 
≥126 mg/dL or HbA1c ≥6.5%. If not-fasting, random blood glucose ≥200 
mg/dL would be concerning for diabetes if HbA1c was <6.5%. In addition to 
lifestyle modifications, metformin is typically started with additional agents 
as indicated. We will ascertain the prevalence of pre-diabetes and 
diabetes; both may be eligible for Aim 2. 
 
Undertreatment defined for each as: 
• 
While any participant who was previously undiagnosed is also technically 
undertreated, we will reserve this definition to those who previously or 
currently reported to CCSS as being diagnosed with hypertension, 
dyslipidemia, or diabetes (either managed by lifestyle modifications or 
medication therapy), if their home-sampled value falls outside the 
recommended therapeutic range: blood pressure ≥130/80 mmHg, LDL ≥160 
mg/dL, triglyceride ≥150 mg/dL (if fasting <10 hours: ≥200 mg/dL), or HbA1c 
≥7.0% (different than the HbA1c diabetes diagnosis threshold65). 
 
3.3.2 
Primary Aim 2 Endpoint: Probability of intervention subjects having an 
undertreated CV condition compared with the control group at 1-year follow-up. 
 
3.3.3 
Primary Aim 3 Endpoint: Barriers among survivors and their primary healthcare 
providers that contribute to undertreatment of hypertension, dyslipidemia, and 
diabetes.  
 
3.4 Estimated Accrual 
The proposal would seek to enroll up to 800 participants to answer Primary Aim 1. If 60% of those 
participants are found to have an abnormal CV condition, up to 480 would then be eligible to participate 
in the randomized controlled trial as part of Primary Aims 2 and 3 (n=240 in each study arm).  
 
3.5 Sponsor/Funding Source 
The study is funded by the National Institutes of Health (National Cancer Institute).  
 
 
4.0 
SAFETY CONSIDERATIONS 
 
We believe this protocol/study will be minimal risk. The proposed home visits and biosample and data 
collection pose minimal risk to participants. Anthropometric measurements are all non-invasive. There 
would be a blood draw (thus potential for brief mild pain) associated with any home visit (1 to 2 over the 

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course of the study for any given participant). The study team will ensure that the amount drawn at any 
visit is safe from a blood volume standpoint. It is possible, but unlikely, that some survey questions may 
cause participants to feel uncomfortable. All instruments proposed have been previously used in other 
research. For participants selected to participate in the randomized intervention trial, it is possible that 
receipt of clinical lab results may cause some participants to feel uncomfortable or anxious. Similarly, 
receipt of a SCP with an individual’s predicted cardiovascular risk may cause anxiety or discomfort. We 
will be monitoring self-reported anxiety and depression as part of our study. Prior CCSS studies have not 
shown that receipt of such survivorship care plans to be a source of significant anxiety.43 We feel that 
providing such information, even when unexpected, may be important and have important future 
health consequences, as the research data to be provided to participants are all results with clinical 
interpretation and significance. For participants on the intervention arm, they will get a phone or web 
video session by which any results are given and explained to them by a survivorship trained clinician, 
approximating a normal clinical exchange. Participants on the control arm will only get a letter 
summarizing clinically relevant results, and will be encouraged to discuss any abnormal results with their 
primary healthcare provider. The study has in place, a process by which critical test results will be 
reported to the study team in real time, in which case, the PI or his designee, can notify the participant 
more quickly to seek medical follow-up. This process is similar to and adapted from that used by the 
CDC-sponsored NHANES for their in-person mobile assessments. For participants (either intervention or 
delayed control) with clinically actionable results but who have no current healthcare provider, the 
study team has access to resources to aid participants in finding providers in their area who have 
expertise in treating survivors of childhood cancer. This will be clearly explained on their results letter. 
 
 
5.0 
SUBJECT ELIGIBLITY 
 
5.1 Inclusion Criteria  
 
For Primary Aim 1: 
 
5.1.1 
CCSS participant who is age ≥18 years at time of initial consent. 
 
5.1.2 
High CV risk status based on CCSS risk prediction models for cardiomyopathy and 
ischemic heart disease. 
 
5.1.3 
Living in the U.S., within 50 miles of a designated exam service provider (e.g., EMSI) 
based on CCSS’s available contact information at the time of approach. 
 
5.1.4 
Able to read, write, and speak English.   
 
5.1.5 
Ability to understand and the willingness to provide informed consent. 
 
For Primary Aim 2, in addition to the satisfying the above criteria, participants must also meet 
the following criteria: 
 

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5.1.6 
Abnormal CV condition identified on home visit. Defined as having at least one of 
the following: 
• 
Average blood pressure ≥130/80 mmHg (≥130/80 if existing hypertension 
diagnosis) 
• 
LDL ≥160 mg/dL 
• 
Triglyceride ≥150 mg/dL (if ≥10 hours fast) or ≥200 mg/dL (if <10 hours fast) 
• 
If not known to be diabetic: Glucose ≥100 mg/dL (if ≥8 hours fast) or ≥140 
mg/dL (if <8 hours fast)  
• 
HbA1c ≥5.7% (if not known to be diabetic), HbA1c ≥7% (if known diabetic). 
 
5.1.7 
Be free of any known (self-reported) ischemic heart disease or cardiomyopathy. 
 
5.1.8 
Have access to a telephone or computer to receive a phone or web video 
counseling/intervention session at baseline and at 4 months.  
 
5.2 Exclusion Criteria, applicable to all participants 
 
5.2.1 
Individuals with known cardiomyopathy or ischemic heart disease based on prior 
CCSS surveys are excluded. While not likely to be common, participants who newly 
report in our study’s baseline survey that they have cardiomyopathy or ischemic 
heart disease can have a home visit completed but will then be done with the 
study regardless of their home visit results.  
 
5.2.2 
Not currently known to be pregnant; individuals known to be pregnant and 
otherwise eligible for the study can be enrolled once no longer known to be 
pregnant. Participants who report being pregnant AFTER randomization can remain 
in the study. 
 
5.2.3 
Individuals receiving active cancer treatment. Participants who report starting 
active cancer treatment AFTER randomization can remain in the study. 
 
 
 
6.0 
SUBJECT RECRUITMENT & REGISTRATION  
 
6.1 Recruitment 
A list of eligible patients for Aim 1 will be generated using existing CCSS data. Staff at the CCSS Data 
Coordinating Center at St. Jude will be responsible for sending out approach packets to these patients 
(introductory letter, Consent, Healthcare Provider Form, HIPAA, study questionnaire, and upfront 
honorarium). We will also have the Consent/ Healthcare Provider Form/ HIPAA Form and the study 
questionnaire available online. For non-responders, St. Jude interviewers will follow-up with phone calls 
using their standard process. As part of St. Jude’s standard CCSS process for other CCSS activities, 
participants will have the option of indicating consent by signing the paper form, signing an online 
consent, or by providing verbal consent to a CCSS St. Jude interviewer. Similarly, questionnaires can also 
be completed by interview.  
 

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With our 12/2017 protocol modification, we will also pilot alternative approach packets to see if smaller 
packets that request less of participants upfront can improve accrual. Specifically, in addition to the 
existing approach process, we will pilot a 2nd process by which we exclude the printed study 
questionnaire from the approach packet (an option to complete this on-line will still be mentioned in 
the cover letter). Participants who consent in this fashion but who do not complete the on-line 
questionnaire will then be sent a paper version. A 3rd process will also be piloted which will feature a 
tiered consent process by which the initial consent will just be to complete the initial home visit without 
consenting to the subsequent randomized intervention trial. For those participants who consent in this 
fashion, after they complete the initial home visit and are found to be eligible for the randomized 
intervention trial, they will then receive the second consent form that describes the trial. If one of these 
alternative approach processes results in a substantially higher enrollment rate, that process will then 
be adopted as our standard approach.  
 
Contact information for interested participants will then be forwarded to a designated exam service 
provider (e.g., EMSI) who may then directly communicate and schedule a home visit with the 
participant. As part of the home visit, for those participants who did not provide a paper-signed copy of 
their HIPAA authorization / Medical Record Release form (since we are unsure electronic or verbal 
signatures will be acceptable for primary care providers’ offices), staff will also ask participants for their 
willingness to sign a HIPAA authorization and Medical Record Release (to enable the study to obtain 
their primary care provider’s medical records).  
 
Based on the study’s eligibility criteria, we do not believe patients who are approached will be 
subsequently found to be ineligible. It is possible (although unlikely) that we may identify someone who 
has died since their last CCSS contact. CCSS staff at St. Jude are trained to deal with this situation and 
CCSS records will be updated accordingly. Also unlikely but possible, an otherwise eligible participant 
may have moved and may now live in at an address outside the exam service provider area. Should this 
occur, the study will send the participant a thank you/acknowledgment letter indicating that they will 
not be able to participate this time (Appendix).  
 
6.2 Registration 
Information on consented patients will then also be forwarded to the Fred Hutch study coordinator and 
entered into a study specific tracking database. A copy of the signed consent form and HIPAA 
authorization and Medical Record Release will also be sent to the Fred Hutch study coordinator.  
 
 

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7.0 
TREATMENT PLAN 
 
7.1 Treatment Plan Overview 
 
 
 
 
* ≥1 of the 
following: blood 
pressure ≥130/80 
mmHg (≥130/80 if 
existing 
hypertension 
diagnosis); LDL ≥160 
mg/dL; triglyceride 
≥150 mg/dL 
(fasting) or ≥200 
mg/dL (non-
fasting); if not 
known to be 
diabetic, glucose 
≥100 mg/dL 
(fasting) or ≥140 
mg/dL (non-fasting) 
or HbA1c ≥5.7% (if 
not previously 
diabetic), HbA1c 
≥7% (if known 
diabetic). †Controls 
can receive the 
intervention after 
the 2nd home visit & 
survey completion. 
 
7.2 Assignment of Study Group 
Among those who meet eligibility criteria for primary aim 1 but not primary aim 2, participation will end 
after the 1st home visit. Similarly, if we adopt a tiered consent process, those who could be eligible for 
aim 2 but who do not provide consent to the randomized intervention portion of the study, their 
participation will end after the 1st home visit.  
 
Among participants who meet eligibility for primary aim 2, there this will be a computer randomization 
on a 1:1 basis to intervention: control assignment, with the control group eligible to receive the 
intervention on a delayed basis (following the 2nd home visit). The study’s goal will be to review in-
person collected test results in real-time (within 1-2 days of being received at St. Jude) and determine 
eligibility with randomization assignment the same day. Given the intervention, it cannot be blinded to 

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either participant or study clinician. Staff who perform the home visits and the study biostatisticians will 
be blinded to the study group assignment.    
 
7.3 Intervention Group 
The intervention is a personalized clinician-led SCP-focused self-management counseling session that is 
generalizable to a real clinical setting. A printed SCP with personalized health history, recommendations, 
and clinically meaningful results from the initial home visit (i.e., average blood pressure, lipid profile, 
diabetes screening, BMI) will first be mailed to survivors on the intervention arm. We will then schedule 
participants for a remote counseling session via telephone or HIPAA-compliant web video if the 
participant prefers. The 1st session with a study clinician will ideally be ≤30 minutes to review the SCP 
and make mutually agreed upon goals and an action plan (see Appendix). We will ask scripted questions 
designed to address understanding of the SCP, elicit intentions to act on the SCP information, and elicit 
potential barriers and their solutions related to any planned actions. After the session, the personalized 
action plan will be mailed to the participant. 
 
Approximately 4-months after the initial counseling session, participants will schedule a 2nd session by 
telephone, or HIPAA-compliant web video if the participant prefers, with the study clinician to follow-up 
on the action plan, address any barriers to the plan and mutually agree on a revised plan if needed 
(ideally ≤15 min). The clinician will also rate the survivor’s completion of the action plan from 0 (none of 
the plan completed and no apparent intention to complete the plan) to 10 (action plan complete; see 
Appendix). 
 
For the both the baseline and 4-month follow-up sessions, the duration of the sessions will be recorded 
to determine the feasibility of delivering the intervention within the time allotted (≤30 and ≤15 minutes, 
respectively). The sessions also will be audiotaped for process evaluation of content and fidelity of the 
clinician adherence to the intervention manual. This is further described in Section 8.  
 
7.4 Delayed Intervention Control 
Survivors in the control arm will receive a copy of clinically meaningful baseline home visit results, with a 
general recommendation to seek medical follow-up in instances where any of those values are abnormal 
since we consider it unethical to withhold such information. A copy also will be sent to their designated 
healthcare provider. As such, the control group’s health may be improved simply by study participation. 
At 4-months, participants will receive a generic thank you letter by mail for participating. This will 
include a reminder of the 2nd home visit, and to enhance control group retention, control participants 
will be told that they can receive the study intervention (minus the 4-month booster session) after 
completing the 2nd home visit and any associated surveys. This will include reviewing an SCP and self-
management strategies with the study clinician, but we will avoid using those exact terms to minimize 
control group contamination. 
 
7.5 Interaction with Primary Healthcare Providers 
All participants, at time of consent, will be asked to list their current and past (within the last 2 years) 
primary healthcare provider(s). Current designated providers will receive a copy of all materials sent to 
study participants. Thus, healthcare providers of participants randomized to the intervention arm will be 
mailed a print copy of the SCP with home visit results and the survivors’ personalized action plan. We 
will directly send the SCP to providers because studies have shown that reliance on survivors alone to 
disseminate a copy of their SCP to their provider is problematic.46,55 An analysis of existing CCSS data 
showed that receipt of a print media intervention and fostering increased survivor-physician dialogue 
was associated with increasing adherence to screening.26 Providers can contact the research team with 

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any questions regarding the SCP and action plan contents.  
 
 
• 
Following the 1st home visit, healthcare providers designated by participants randomized to the 
control arm will be mailed a print copy of the home visit results only.  
 
• 
Following the 2nd home visit, healthcare providers of participants on both study arms will be 
surveyed with regards to their self-efficacy (including self-reported knowledge) towards 
providing care for childhood cancer survivors. The survey will be accompanied by a cover letter, 
copies of clinical results (both groups), a SCP (intervention group only), and the patient’s signed 
HIPAA authorization and Medical Record Release (if available), requesting records from the past 
3 years. If the budget permits, the study will provide an upfront honorarium to providers (not 
exceeding $20). Non-responding providers will receive a 2nd survey packet (inclusive of clinical 
results, SCP if applicable, and the signed HIPAA authorization and Medical Record Release if 
available) approximately a month later with an alternative cover letter. No honorarium will 
accompany the 2nd packet. This will be faxed to the provider’s office if a fax number is available, 
and/or mailed. We will repeat this process two more times if no response is received after 
another month.  
 
For participants (either intervention or delayed control arm) with clinically actionable results but who 
have no current healthcare provider, the study team has access to resources to aid participants in finding 
providers in their area who have expertise in treating survivors of childhood cancer. This will be clearly 
explained on their results letter and by phone or web-video.  
 
7.6 Duration of Therapy and Follow-Up 
All study participants will be followed through their 2nd home visit, approximately 1-year after their 1st 
home visit unless they withdraw consent from the study prior. All participants following the 2nd home 
visit will receive a copy of their clinically relevant results embedded in a SCP. As mentioned above, those 
on the control arm can then have the option of having a 30 minute counseling session to review those 
results and the SCP with the study clinician.  
 
 
 

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8.0 
STUDY PROCEDURES 
 
An overview of study procedures can be found in Table 3.  
 
TABLE 3. Summary of required observations. 
 
Initial home visit 
Baseline 
counseling session 
4-month  
booster 
2nd home visit 
Intervention 
group 
Questionnaires* 
Anthropometrics 
Blood draw 
Goals/Action Plan 
Call duration 
Call fidelity 
Rating of Action 
Plan completion 
Questionnaires* 
Anthropometrics 
Blood draw 
Control group 
Same as intervention 
group 
- 
- 
Same as intervention 
group 
Primary 
healthcare 
provider(s)  
- 
- 
- 
Provider survey 
Clinical records 
Time window to 
complete 
<2 mo of enrollment 
(max: <6 mo) 
<2mo of home 
visit (max: <3 mo) 
3-5 mo from 
baseline 
11-15 mo from 1st 
home visit (no max)) 
*Participants will be asked to complete the questionnaires prior to the scheduling of their home visits.  
 
8.1 Baseline Questionnaire 
This will include items on: 1) past medical history, 2) current health and medication adherence, 3) 
lifestyle habits, and 4) attitudes towards healthcare and current mood (Table 4; Appendix). 
 
TABLE 4. Components of baseline questionnaire, exclusive of questions on past medical history 
and lifestyle habits.  
*Health-related self-
efficacy56 
10-item (4-point Likert scale) survey (will be reduced to 5-items) that 
measures perceived ability to set-goals, cope and recover from setbacks. 
Results have been found to be a strong predictor of subsequent health 
behavior change.96  
*PROMIS anxiety & 
depression57,58 
These domains (adult 4-item survey; all 5-point Likert scale) are of 
secondary interest. Prior research via a longer instrument (Profile of Mood 
States) did not show SCPs associated with mood changes or anxiety.50,85 
*Multidimensional 
Health Locus of Control 
[MHLC]59  
18-item survey (6-point Likert scale) will classify participants with regards to 
their attitudes towards healthcare screening into “worried”, “collaborative” 
and “self-controlling” typologies, which have been associated with 
differential likelihoods of obtaining recommended screening in 
retrospective CCSS analyses.78  
*Medication Adherence 
Scale (MMAS-4)60  
Well-established 4-item (0=high, 1-2=medium, 3-4=low adherence) 
instrument initially used to study hypertension, but since validated for other 
diseases.100 Will be administered separately for blood pressure, lipid, and 
diabetes medications. Secondary analyses will examine adherence by 
medication burden. 
 
 
 

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8.2 First Home Visit 
This will include: 
• 
Signature on HIPAA authorization and Medical Record Release form (optional).  
• 
Standing height: in centimeters, to the nearest 0.1 cm.  
• 
Weight: in kilograms, to the nearest 0.1 kg.  
• 
Blood pressure at rest: 3 times; each at least 3 minutes apart.  
• 
Waist circumference: in centimeters, to the nearest 0.1 cm; just above the uppermost lateral 
border of the right ilium [hip bone]; at the end of a normal expiration.  
• 
Blood draw (no fasting required): lipid profile, blood glucose, hemoglobin A1c, insulin, and 
samples for ancillary biological studies (Table 5).  
 
TABLE 5. Overview of blood samples, draw order, vial type, volume. 
Draw order / Analyte 
Vial type 
Volume 
1) Lipid profile, glucose, insulin level* 
Heparin plasma separator tube (green top) 
3.0 mL  
2) Hemoglobin A1c* 
EDTA tube (lavender top) 
1.0 mL 
3) Protein & DNA-based assays 
EDTA tube (lavender top) 
7.5 mL 
4) General chemistries 
Serum separator tube (red/gray top) 
7.5 mL 
5) Proteomics, metabolomics 
EDTA separator tube (pearl) 
7.5 mL 
6) RNA for gene expression 
PAXgene tube 
2.5 mL 
*These also will be drawn at the 2nd home visit; remaining tubes would NOT be drawn at the 2nd home visit unless 
they could not be successfully drawn at the first visit.  2nd home visit only: blood spot offered for failed venous 
draws. 
 
With our 7/2020 protocol modification, in response to the unexpected closure of the study’s original 
exam service provider (EMSI), replacement service providers may include those that do not provide 
home-based services but rather fixed laboratory / service centers that the participant travels to in order 
to obtain the specified research blood draw. In these instances, only tubes 1-2 (Table 5) will be drawn 
and processed on-site (i.e., tubes 3-6 will not be drawn).  
 
Rarely, in past experiences with our pilot data and similar CCSS home visit-based studies, exam service 
staff will be unsuccessful in obtaining blood given technical issues. In this situation, the participant will 
be offered the choice of having the procedure be rescheduled to another date. If the participant refuses 
and the primary study endpoints (lipid profile, blood glucose, and hemoglobin A1c) cannot be collected, 
then the patient will not be eligible to continue on the study. Any partial results will still be sent back to 
the participant and their designated primary care provider.  
 
8.3 Baseline Counseling Session (Intervention Group) 
A printed SCP with personalized health history, recommendations, and clinically meaningful results from 
the home visit (i.e., average blood pressure, lipid profile, diabetes screening, BMI) will first be sent to 
survivors on the intervention arm. Interpretation of these results is as defined in Section 3.3.1. We will 
then schedule participants for a remote counseling session by phone or web video, per participant 
choice). This will be scheduled as soon as possible following the initial home visit with a goal of having 
this being completed within 2 months of the home visit. Sessions completed outside of the 2-month 
window will be flagged (but remain eligible for analysis). The following outcomes will be measured at 
this time point: 
 
• 
Creation of a personalized goals and action plan (Appendix).  

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• 
Counseling session completion rates, with goal of obtaining ≥85% completion within 2 months 
of the initial home visit.  
• 
Call duration, with goal of achieving ≥85% being ≤30 minutes in duration.  
• 
Study clinician fidelity to the intervention. Fidelity will be scored using standard methods across 
8 levels with the 8th a global rating (Appendix). Trainers will review audiotapes of sessions, with 
fidelity ratings and feedback to the clinician until the mean of 4 consecutive global ratings are 
≥3.5 (scale: 0 [poor] to 5 [very good]). Once certified, trainers will review audio recordings and 
complete fidelity ratings for 15% of sessions, more if fidelity dips below a global rating of 3 
(satisfactory) for 3 of 10 sessions.  
 
It is possible that some randomized participants will fail to schedule a session despite multiple contact 
attempts. We will cease scheduling attempts if no session has been scheduled by 3 months after the 
initial home visit. These participants will not be eligible for the 4 month booster session (discussed 
below). However, we will still attempt to re-assess their health status at the 1-year time point with a 2nd 
questionnaire and home visit. If a participant has to cancel and reschedule, the rescheduled date can fall 
outside the 3 month deadline and we will attempt to do the booster session within the target time range 
still. 
 
8.4 Baseline Return of Results (Control Group) 
Survivors in the control arm will receive a copy of clinically meaningful baseline home visit results, with a 
general recommendation to seek medical follow-up in instances where any of those values are abnormal 
since we consider it unethical to withhold such information. Interpretation of these results is as defined 
in Section 3.3.1. A copy also will be sent to their designated healthcare provider. These will be issued 
within one month of the home visit.  
 
8.5 Handling of Critical Results 
 Staff will be asked to ship out blood samples within 24 hours (could be slightly longer on weekends) of 
collection, and data forms will be faxed, both to the CCSS data coordination center at St. Jude. Once 
received, labs will be processed in real-time (i.e., not batched) by the CLIA-certified lab at St. Jude. 
Copies of data forms and any examiner shipping manifest will be forwarded to the study team at FHCRC. 
In the event that a critical test result is found (see Table 6), the PI or his designee, will attempt to notify 
the participant more quickly by phone to seek medical follow-up (rather than waiting for a letter to be 
generated and mailed to the participant). This process is similar to and adapted from that used by the 
CDC-sponsored NHANES for their in-person mobile assessments.  
 
TABLE 6. Classification of test results, as discussed in Section 8.5. 
 
Goal 
Borderline 
Abnormal 
Critical 
Systolic blood pressure (mmHg)* 
Diastolic blood pressure (mmHg) 
<120 
<80 
120-129 systolic 
 
130-179 
80-119 
≥180 
≥120 
LDL cholesterol (mg/dL) 
<130 
130-159 
≥160 
- 
Triglyceride (mg/dL), if fasted ≥10 hrs 
<150 
- 
150-749 
≥750 
Triglyceride (mg/dL), if not fasting 
<200 
- 
200-749 
≥750 
Glucose (mg/dL), if fasted ≥8 hrs 
<100 
100-125 
126-299 
≥300† or ≤50‡ 
Glucose (mg/dL), if not fasting 
<140 
140-199 
200-299 
≥300† or ≤50‡ 
Hemoglobin A1c (%) 
<5.7 
5.7-6.4 
≥6.5 
- 
*We will drop the highest of 3 systolic measurements, and average the remaining 2 for systolic & diastolic 
values. †If not previously known to have a diagnosis of diabetes. ‡If known diabetic only, as this would be 
concerning for therapy-related hypoglycemia. 
 

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8.6 Four-month Booster Session 
Among the intervention group, the study will attempt to schedule the participant for a brief 15-minute 
check-in by phone or web-video 4-months (±1 month) after the initial counseling session. For 
intervention subjects who have such booster sessions outside the 3-5 month window, their data will be 
flagged but would still remain eligible for analysis. The following outcomes will be captured at this time 
point: 
 
• 
Study clinician rating of participants’ action plan completion, ranging from 0 (none of the plan 
completed and no apparent intention to complete the plan) to 10 (action plan complete; see 
Appendix). 
• 
Similar to the baseline session, we will cease trying to schedule this booster session if no session 
has been scheduled by 5 months after the initial counseling session. We will still attempt to re-
assess their health status at the 1-year time point with a 2nd questionnaire and home visit. If a 
participant has to cancel and reschedule, the rescheduled date can fall outside the 5 month 
deadline. 
 
Among the control group, participants will receive a generic thank you letter by mail for participating. 
No outcomes will be measured in this group at this time point.  
 
8.7 Second Questionnaire and Home Visit 
The 2nd questionnaire and home visit should take place approximately 1-year after the initial 
questionnaire and home visit. The study will send participants an abridged version of the baseline 
questionnaire (by mail, with phone/email follow-up as necessary) with a reminder that a 2nd home visit 
is also due soon. After the participants complete the follow-up questionnaire, the study will work with 
the exam service provider to contact the participant to arrange for the 2nd home visit. The study will 
attempt to have all 2nd home visits occur within 3 months of the 1-year anniversary, and visits that occur 
outside that 3-month window will be flagged (but remain eligible for analysis). The following outcomes 
will be measured at this time point: 
 
• 
Same physical measurements as before: standing height, weight, blood pressure at rest (3 
times), and waist circumference. 
• 
Blood draw (no fasting required): lipid profile, blood glucose, hemoglobin A1c, and insulin (Table 
5; other assays will not be drawn unless they could not be drawn at the first home visit).  
• 
If the exam service provider is unsuccessful in obtaining blood due to a technical issue, or the 
participant refuses the venous blood draw at the second visit, we will offer the participant the 
option of a finger poke to obtain a blood spot sample (i.e., dried blood spot, DBS). Blood spots 
will only be offered as a back-up option at the second visit.  
• 
Handling of any critical results will be conducted similarly as per the baseline home visit (see 
Section 8.5 above). In contrast to venous samples, DBS-based measurements of the lipid profile, 
glucose, insulin, and hemoglobin A1c will not be released back to participants or their providers. 
This is because such measurements are not performed in a CLIA-certified setting and are 
currently designed for epidemiologic research only (and not for clinical care), and also will be 
batched (in contrast to venous samples which are processed in near real-time).  
 
Should home visits be completely declined or impossible to conduct (e.g., due to COVID-19 or other 
public health issues where social distancing is encouraged/mandated), the protocol will permit 

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substitution of a completely remote assessment procedure for the follow-up visit. This would necessarily 
be slightly modified from the exam service provider-obtained home visit in the following ways: 
 
• 
Physical measurements will only include: weight and blood pressure at rest (3 times). These will 
be collected using a scale and blood pressure cuff that the study can provide to study 
participants. If participants already have a digital scale at home, they can use their own scale in 
place of a scale the study provides.  Blood pressure cuff and scale can be kept by participants 
and do not need to be returned to the study team. These results can be returned to participant 
and their primary healthcare provider, but would be clearly noted as participant-collected.   
• 
Blood draw will be replaced by the DBS method specified above, with the same caveat that DBS 
results cannot be returned to participants.  
 
8.8 Primary healthcare provider measurements 
Following the 2nd home visit, accompanying the mailing of a copy of participant materials (intervention 
group: clinical results and SCP; control group: clinical results only), all designated providers will be asked 
to answer questions adapted from the NCI/ACS SPARCCS (see Appendix).61  
 
We will also request outpatient clinical records (clinician notes, medication lists, laboratory results) 
spanning the study period (and up to 2 years prior to the 1st home visit) from all participants’ primary 
healthcare providers. We will abstract records for: 1) documentation of the participant’s prior cancer 
history and CV risk status in relation to past cancer exposures; 2) any reference to a SCP or long-term 
follow-up guideline; 3) any CV 
screening planned or undertaken 
[coded separately]; 4) presence of any  
 of the three target CV risk factors as a 
diagnosis/problem; and 5) 
interventions to address any CV risk 
factor [coding lifestyle or drug 
prescription separately]. Medications 
will be reviewed to examine whether, 
among those undertreated at the 1st 
home visit, there is subsequent 
treatment intensification (e.g., going from lifestyle prescription alone to adding medication; from lower 
to higher drug doses; from single to multiple drugs; Table 7), and whether treatment intensity differs 
across study arms after the intervention. 
 
Description of how the study will engage with primary healthcare providers is otherwise described in 
Section 7.5. 
 
8.9 Materials returned to participants and primary healthcare providers 
Information the study will send (by mail) back to study participants and their designated current primary 
healthcare provider are summarized in Table 8.  
 
TABLE 8. Information the study will mail back to study participants and their current primary 
healthcare providers. 
 
After the initial home 
visit / baseline counseling 
session 
After the 4-month  
booster 
After the 2nd home visit 
TABLE 7. Examples of CV medications & dose categories (mg) 
Medication (class) 
Low Medium High 
Hypertension 
 
 
 
  Lisinopril (ACE-inhibitor) 
≤10 
11-30 
>30 
  Amlodipine (calcium channel blocker) 
≤2.5 
2.6-9.9 
≥10 
High cholesterol 
 
 
 
  Simvastatin (HMG CoA reductase inhibitor) <20 
20-39 
≥40 
Diabetes 
 
 
 
  Glipizide (sulfonylurea) 
<10 
10-19 
≥20 
  Insulin 
Any dose 

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Intervention group  
(participant & provider) 
Clinical results 
Survivorship care plan 
Action Plan 
Updated Action Plan 
Clinical results 
Survivorship care plan 
Control group 
(participant & provider) 
Clinical results 
- 
Clinical results 
Survivorship care plan* 
*Mailing of the care plan would not occur until AFTER the control group’s designated healthcare providers are surveyed.  
 
8.10 Remote blood pressure monitoring pilot 
Following completion of the intervention, we will also approach participants regarding their willingness 
to perform home blood pressure monitoring (HBPM) via mHealth (i.e., Bluetooth-enabled) devices. The 
rationale for this is that compared with our standard measurement approach, home monitoring is likely 
to be more accurate, both in ruling out “white coat” hypertension as well as ruling in “masked” 
hypertension.50 This pilot would seek to enroll 40 participants who have just completed their 2nd home 
visit (or 1st home visit if all values were normal and they were otherwise not eligible to participate in the 
randomized controlled trial) and ask them to collect home blood pressures 3 times a week for 4 weeks. 
A Bluetooth-enabled blood pressure monitor would be provided free of cost to study participants. 
Participants would be requested to download the blood pressure manufacturer’s mHealth application 
(app) which will collect measured blood pressure values as well as a 2nd study-specific mHealth app 
(Eureka, UC San Francisco), which is designed to facilitate mHealth research and transmit research-
specific reminders (e.g., phone notifications or texts) and instructions to participants, as well as provide 
investigators the ability to access the blood pressure values collected on the monitors.  
 
The primary goals of this pilot would be to determine the feasibility of HBPM, including participation 
rate and the proportion of participants who transmit >75% of requested data (>9 measurements in one 
month). Secondary goals would be to determine the proportion of individuals who may have “white 
coat” hypertension (i.e., in-person collected values are systolic ≥130 or diastolic ≥80 mmHg but HBPM 
average is lower) or “masked” hypertension (i.e., in-personcollected values are systolic <130 and 
diastolic <80 mmHg, but average HBPM is greater). Data from this pilot will be used to inform the 
feasibility of a future follow-up study that involves using HBPM as part of the study assessment and 
intervention.  
 
Participants would be approached as part of their final home visit results mailing, and those interested 
would be instructed to download the Eureka app onto their smartphone and provide informed consent 
on that app. The study team would follow-up by phone (including text messaging) and/or email among 
non-responders to determine interest. Participants would be eligible for an additional incentive upon 
completing this 1-month pilot (choice of either keeping their home blood pressure monitor or a $50 gift 
card). As all blood pressure measurements will be visible to participants on both the monitor as well as 
the manufacturer’s app on their phones, they will be encouraged to share any values with their 
healthcare provider if they have concerns.  
 
Specific eligibility for this follow-up pilot study would include: 
• 
CHIIP study participant who has completed their 2nd home visit (or 1st home visit if all values 
were normal and they were otherwise not eligible to participate in the randomized controlled 
trial); 
• 
Has access to an internet-connected smart phone capable of downloading apps from either 
Apple or Android-based “app stores”; 

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• 
Consents to this follow-up study, which includes being willing to download both the blood 
pressure monitor manufacturer app as well as research Eureka app, and being willing to receive 
study-specific reminders (phone notifications and/or text reminders); 
• 
Arm circumference is within the parameters of the home blood pressure monitor manufacturer 
specifications.  
 
 
9.0 
OFF STUDY CRITERIA 
 
This would occur if: 
 
• 
A participant withdrew consent for any further data submission, or 
• 
The participant was unable to complete the initial home visit procedures (e.g., unsuccessful 
blood draw), or 
• 
Once a participant has completed all study assessments.  
 
 
10.0 ADVERSE EVENTS 
 
10.1 Expected Adverse Events  
The CHIIP study is considered a low-risk educational and behavioral intervention study. The proposed 
home visits and biosample and data collection itself pose minimal risk to participants. Anthropometric 
measurements are all non-invasive. There would be a blood draw (thus potential for brief mild pain) 
associated with any home visit (1 to 2 over the course of the study for any given participant). The study 
team will ensure that the amount drawn at any visit is safe from a blood volume standpoint. It is 
possible, but unlikely, that some survey questions may cause participants to feel uncomfortable. All 
instruments proposed have been previously used in other research. 
 
For participants selected to participate in the randomized intervention trial, it is possible that receipt of 
clinical lab results may cause some participants to feel uncomfortable or anxious. Similarly, receipt of a 
SCP with an individual’s predicted cardiovascular risk may cause anxiety or discomfort. We will be 
monitoring self-reported anxiety and depression as part of our study. Prior CCSS studies have not shown 
that receipt of such survivorship care plans to be a source of significant anxiety.43 We feel that providing 
such information, even when unexpected, may be important and have important future health 
consequences, as the research data to be provided to participants are all results with clinical 
interpretation and significance. For participants on the intervention arm, they will get a phone session or 
web video by which any results are given and explained to them by a survivorship trained clinician, 
approximating a normal clinical exchange. Participants on the control arm will only get a letter 
summarizing clinically relevant results, and will be encouraged to discuss any abnormal results with their 
primary healthcare provider. The study has in place, a process by which critical test results will be 
reported to the study team in real time, in which case, the PI or his designee, can notify the participant 
more quickly to seek medical follow-up. This process is similar to and adapted from that used by the 
CDC-sponsored NHANES for their in-person mobile assessments. For participants (either intervention or 
delayed control) with clinically actionable results but who have no current healthcare provider, the 
study team has access to resources to aid participants in finding providers in their area who have 
expertise in treating survivors of childhood cancer. This will be clearly explained on their results letter.   
 

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Otherwise, the only other anticipated risks would be related to participant privacy. The PI and study 
team will have clear and standard procedures to manage and protect individually identifiable private 
information. These include: appropriate human subjects research training for all staff with potential 
access to private information; technological safeguards such as use of encrypted data transmission 
between sites, secure password protection on computer servers; removal of identifiers at the earliest 
possible time and using separate unique study IDs instead; keeping any cross-walk files separate from 
the main analytic dataset(s); and avoiding showing individual data in any presentation or publication. 
 
10.2 Monitoring and Recordings Adverse Events 
As the CHIIP study is considered a low-risk educational and behavioral intervention, the FHCRC Data 
Safety Monitoring Committee, during the study’s grant application, made an initial determination that 
overall data and safety monitoring can be overseen by the PI and the FHCRC IRB. All adverse events 
(expected or unexpected) will be reported to the FHCRC and St. Jude IRBs in accordance with the 
respective IRBs’ policies.  
 
 
11.0 DATA AND SAFETY MONITORING PLAN 
 
The study will use the FHCRC Data and Safety Monitoring Committee (DSMC). The DSMC will review the 
summary of all adverse events collected as part of a protocol’s data safety monitoring plan and reported 
by the PI at time of continuing IRB renewal, any expedited reports made to the IRB, and may refer 
protocols to the IRB for evaluation when modifications might be required to mitigate risks. The DSMC 
may also suspend or close the study based on review of the above information. The DSMC will review 
the accrual, patient safety, and other data at pre-specified intervals (at least annually), and make any 
determinations regarding interim analyses and stopping rules. On the basis of its review, the DSMC will 
provide a study with full approval (accrual continues, no changes), conditional approval (accrual 
continues but protocol changes required), suspension (accrual is stopped until protocol changes have 
been made but previously enrolled patients may continue the intervention), or closure (accrual is 
stopped and all interventions must stop). 
 
 
12.0 DATA MANAGEMENT/CONFIDENTIALITY 
 
The investigators will ensure that data collected conform to all established guidelines. Each participant 
has a pre-assigned CCSS ID number that will be used to protect subject confidentiality. Subjects will not 
be referred to by this number, by name, or by any other individual identifier in any publication or 
external presentation. Subject research files will be stored in a secure place (or database). Access is 
restricted to authorized personnel, with supervision by the PIs at FHCRC (Chow) and St. Jude 
(Armstrong). An existing data transfer/sharing agreement between FHCRC and St. Jude covers the 
exchange and sharing of existing and newly collated CCSS data. Data will not be shared with any other 
entity or outside investigators (external to those approved by CCSS) without approval by the relevant 
IRBs.  
 
 
13.0 STATISTICAL CONSIDERATIONS 
 

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13.1 Aim 1 Analytic Plan 
Hypothesis: Approximately 60% of participants will have an abnormal CV risk-factor finding that meets 
clinical intervention thresholds, and among those with abnormalities, 40% will be undertreated and 80% 
newly diagnosed. 
 
Primary analyses: We will calculate the prevalence of hypertension, dyslipidemia, and diabetes by self-
report and by physiologic measurement. We will then calculate the proportions (with exact 95% 
confidence intervals) of participants who may be underdiagnosed as well as the proportions 
undertreated (like Figure 3). We will calculate the prevalence of directly measured pre-diabetes 
separately. Secondary analyses: We will examine whether rates differ by: sex; current age; time since 
cancer diagnosis; obese (BMI ≥30 kg/m2) vs. not; health insurance vs. not; recent history of being seen in 
a dedicated long-term follow-up clinic for survivors vs. not; and lifestyle factors (smoking, low 
fruit/vegetable intake, low physical activity).  
 
Sample size considerations: Based on prevalence 
estimates from CCSS surveys and our pilot (Table 
2, Figure 3), we expect ~60% of high CV risk 
participants (n~480) to have an abnormal CV risk 
factor measurement; prevalence of individual risk 
factors ranging 20-40% (less when stratified by 
underdiagnosis/undertreatment status). With an 
overall sample n=800, we expect reasonable precision for our primary prevalence estimates (Table 9). 
Power to detect differences <10% in secondary analyses may be more limited.  
 
Potential pitfalls / solutions: Our EMSI pilot achieved 60% enrollment. Funding from this proposal will 
enhance recruitment rates by providing an upfront (rather than conditional) participation incentive, 
which has been associated with higher rates of study participation.62,63 We will closely examine the 
demographic characteristics, past cancer treatment exposures, and self-reported burden of CV and 
other chronic conditions of survivors who are approached vs. not approached, and who ultimately 
participate vs. not. If differences are found, we will apply inverse probability weighting as a way to 
assess the sensitivity of our estimates. 
 
13.2 Aim 2 Analytic Plan 
Hypothesis: survivors randomized to the intervention will have a lower probability of having an 
undertreated CV risk factor compared with the control group at 1-year follow-up. 
 
Primary analyses: We will describe baseline characteristics (including mean/median values of our target 
CV parameters) and proportions of underdiagnosis and undertreatment of our 3 CV risk factors. Our 
primary analysis will focus on the difference in the probability of having a CV risk factor undertreated 
after the 2nd home visit across the 2 study arms. As in Aim 1, undertreatment of hypertension, 
dyslipidemia, and diabetes at the 2nd home visit will be defined as blood pressure ≥130/80 mmHg, LDL 
≥160 or triglyceride ≥150 mg/dL (if fasting <10 hours: ≥200 mg/dL), or HbA1c ≥7%, respectively. 
Survivors with pre-diabetes at baseline will be undertreated at the 2nd home visit if fasting glucose ≥100 
mg/dL (non-fasting ≥140 mg/dL) or HbA1c≥5.7%. As some survivors may contribute up to 3 outcomes 
(persistent hypertension, dyslipidemia, and diabetes/pre-diabetes), we will use generalized estimating 
equations (GEE), accounting for intra-individual correlation of the 3 outcomes, to estimate the overall 
intervention effect as a single parameter (3-element vector). If multiple survivors share the same 
primary healthcare provider (unlikely), we will apply random effects models in lieu of GEE given multiple 
TABLE 9. Estimated power for Aim 1 analyses.  
Prevalence±95% CI Minimum detectable proportions* 
N=800 
N=320:480 
N=200:200 
5% ± 1.5% 
5% vs. 1/11% 
5% vs. 0/14% 
20% ± 2.8% 
20% vs. 12/29% 
20% vs. 10/33% 
50% ± 3.5% 
50% vs. 40/60% 
50% vs. 36/64% 
*2-sample Fisher’s exact test, 80% power, α=0.05. 

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cluster types. Analyses will be conducted per intent-to-treat, and include all survivors with available end 
points.  
 
Secondary analyses: In case survivors who were newly diagnosed (i.e., underdiagnosed) following their 
1st home visit differ in their response to the intervention vs. those previously diagnosed but 
undertreated, we will examine estimates stratified by diagnosis status at the 1st home visit. For similar 
reasons, we also will examine estimates if pre-diabetes are excluded. In our primary model, we also will 
explore whether differences vary by sex, current age, time since cancer diagnosis, obese (BMI ≥30 
kg/m2) vs. not, health insurance vs. not, and recent history of being seen in a dedicated long-term 
follow-up clinic for survivors vs. not. We also will explore, among intervention participants, whether 
action plan scores from the 4-month session are associated with differential undertreatment rates (as a 
single parameter). Finally, we plan to also compare across the study arms, the measured CV risk factor 
values from the 2nd home visit separately: 1) average systolic pressure, 2) average diastolic pressure, 3) 
LDL, 4) triglyceride, 5) blood glucose, and 6) HbA1c. For this subanalysis we will use linear models, 
adjusting for the value at the 1st home visit as a covariate.  
 
Sample size considerations: Assuming 60% of Aim 1 participants (n=800) meet Aim 2 eligibility with a 
subsequent conservative 20% drop-out rate, ~380 survivors (190/arm) would have complete data. The 
study would be 80% powered (α=0.05) to detect RRs ≤0.88 (i.e., ≥12% reduction in the intervention vs. 
control group) if the prevalence of having an undertreated CV risk factor among controls after the 2nd 
home visit was 90% (10% reduction from baseline). If controls had an unlikely 50% reduction, we can still 
detect RRs ≤0.71. Analyses stratified by initial underdiagnosis or undertreatment status (~75-150/arm) 
will be able to detect RRs ≤0.79 to ≤0.86, respectively. Systematic reviews have reported RRs 0.6-0.8 for 
strategies similar our proposed interventions in the general population.64,65 For continuous outcomes 
(secondary analyses), we will be powered to detect change equaling ~30% of 1 standard deviation, 
which equates to 5 mmHg systolic blood pressure, 3 mmHg diastolic pressure, 10 mg/dL LDL, 30 mg/dL 
triglyceride, 10 mg/dL glucose, and 0.3% HbA1c. Differences within these ranges have been reported by 
others for interventions conducted in the general population.66-68 
 
Potential pitfalls / solutions: We will closely monitor rates of abnormalities identified in Aim 1, as that 
influences the number of survivors eligible for Aim 2. As discussed earlier, we will oversample survivors 
known to have rarer target conditions (e.g., diabetes) such that the power to detect differences in Aim 2 
is enhanced. Separately, given the nature of the intervention, participants and the study clinician cannot 
be blinded. However,  exam staff will be blinded to randomization status. 
 
13.3 Aim 3 Analytic Plan 
Hypotheses: 1) at baseline, underdiagnosis & undertreatment are associated with lower knowledge, self-
efficacy, and medication adherence (if applicable), as well as a “self-controlling” health attitude among 
survivors; 2) at 1-year follow-up, compared with the control arm, the intervention arm will be associated 
with improved knowledge, self-efficacy, and adherence rates among survivors, and improved knowledge 
and self-efficacy among healthcare providers. 
 
Baseline survivor-specific factors: Using data from all Aim 1 participants, determine whether those 
underdiagnosed and undertreated at the time of the 1st home visit have lower knowledge (i.e., less 
accurate recall of prior anthracycline or chest radiotherapy exposures [chi-square test]) and lower 
health-related self-efficacy [t-test or Wilcoxon rank-sum] compared with those not affected. Similarly, 
among those who report medications for the CV risk factors of interest, determine whether those 
undertreated have lower medication adherence (i.e., lower mean MMAS-4 scores [t-test or Wilcoxon 

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rank-sum]) vs. those not undertreated. Finally, determine if different health-related behavioral attitudes 
(“worried”, “collaborative” and “self-controlling”)69 are associated with differential rates of 
underdiagnosis and undertreatment [chi-square test]. A priori, we hypothesize that the proportion 
undertreated will be greatest among “self-controlling” survivors vs. “collaborative” and “worried” (least 
undertreated) survivors. In subanalyses, we will analyze underdiagnosed participants (i.e., newly 
diagnosed per 1st home visit) separately from those undertreated (i.e., existing diagnosis but not 
meeting standard therapeutic goals) relative to the referent group (those without any abnormal CV risk 
factor). We also will use a combined logistic regression model to determine if knowledge, medication 
adherence, and health-related behavioral attitudes remain associated with underdiagnosis and 
undertreatment (combined and separately) after multivariate adjustment. Exploratory covariates are 
similar as before, and include sex, current age, insurance status, healthcare utilization, self-perceived CV 
risk, and family history of CV disease.  
 
Post-intervention analysis: Among Aim 2 participants (and their designated healthcare provider), we 
will examine the differences between intervention and control groups following the 2nd home visit with 
respect to 1) survivor knowledge [chi-square test], 2) survivor self-efficacy [t-test or Wilcoxon rank-sum], 
3) survivor-reported medication adherence [t-test or Wilcoxon rank-sum], and 4) provider-reported 
knowledge and self-efficacy [chi-square tests] related to the care of childhood cancer survivors. All 
analyses will be intent-to-treat and include all survivors and providers with available end points. 
Subanalyses can stratify these outcomes by initial underdiagnosis vs. undertreatment status. We also 
will analyze practice changes over the 1-year intervention period using clinical records. This includes 
comparing [chi-square test] whether documentation rates differ across study arms of: 1) any CV-related 
screening, 2) CV-related interventions [both lifestyle and drug prescriptions], and 3) treatment intensity 
(Table 7 earlier). If any survivors share the same healthcare provider, we will apply bootstrap methods 
to account for the effects of clustering. In secondary analyses, we will determine, via logistic regression 
adjusting for randomization status, whether providers of survivors who remain undertreated have lower 
self-reported knowledge and self-efficacy related to the care of childhood cancer survivors vs. providers 
of survivors no longer undertreated.  
 
Sample size: For covariates assessed at baseline in Aim 3, we will be able to detect differences ≥5%, RRs 
≤0.8 / ≥1.2, and ≥20% of 1 standard deviation (Table 10). Among randomized participants (240/arm) and 
subanalyses (e.g., analyzing undertreatment, underdiagnosis separately: ~75-150/arm), detectable 
differences will be less.  
 
TABLE 10. Minimum detectable differences (80% power; α=0.05) per chi-square (proportions, 
relative risks) or t-test (% standard deviation). * ~60% (480 of 800) with abnormal CV finding.  
Covariate frequency 
Baseline* 
Post-intervention & subanalyses 
N=320:480 
240:240 
150:150 
75:75 
10%  (e.g., primary care provider self-efficacy 
towards childhood cancer survivorship care27,28) 
5%/17% 
RR 0.5/1.7 
3%/20% 
RR 0.3/2.0 
2%/22% 
RR 0.2/2.2 
- /28% 
RR -/2.8 
25% (e.g., MHLC self-controlling or worried 
typologies69; survivor anthracycline self-
knowledge70) 
17%/34% 
RR 0.7/1.4 
15%/37% 
RR 0.6/1.5 
12%/40% 
RR 0.5/1.6 
8%/47% 
RR 0.3/1.9 
60%  (e.g., MHLC collaborating typology69; survivor 
radiotherapy self-knowledge70; high medication 
adherence30,31,67,71,72) 
50%/70% 
RR 0.8/1.2 
47%/72% 
RR 0.8/1.2 
44%/75% 
RR 0.7/1.3 
37%/81% 
RR 0.6/1.3 
% standard deviation  (e.g., MMAS-4,60 survivor self-
efficacy56) 
20% 
26% 
33% 
46% 
 

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Potential pitfalls / solutions: Self-reported medication adherence is not as accurate as data from 
pharmacy databases.100 However, use of these databases is unlikely to be feasible even in large 
integrated health systems given the relative rarity of childhood cancer survivors. Given upfront 
randomization, any reporting biases should be similar across study arms. Should our study uncover a 
suggestive association with adherence, this would provide data to support the use of more expensive 
medication monitoring devices in a follow-up study.100 We also anticipate some missing healthcare 
provider responses. It is possible that providers on the intervention arm who receive the SCP could be 
more motivated to respond (all providers will get clinically relevant results from home visits). We will 
closely monitor response rates for providers across the study arms, and will compare the characteristics 
of responding vs. non-responding providers using American Medical Association databases (physicians 
only) and publically available information from state licensing boards and the internet (physicians and 
other providers).28,102 In sensitivity analyses, we can examine the differences across study arms after 
adjustment for characteristics that appear to differ between responding and non-responding primary 
healthcare providers. 
 
 

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13.4 Ethnic and Gender Distribution Chart 
 
Projected Target Accrual 
ETHNIC AND GENDER DISTRIBUTION CHART 
 
TARGETED / PLANNED ENROLLMENT: Number of Subjects 
Ethnic Category 
 
Sex / Gender 
 
Females 
Males 
Total 
Hispanic or Latino 
54 
34 
88 
Not Hispanic or Latino 
428 
284 
712 
Ethnic Category Total of All Subjects* 
 
 
 
 
Racial Categories 
 
 
American Indian / Alaska Native 
1 
0 
1 
Asian 
11 
11 
22 
Native Hawaiian or Other Pacific Islander 
0 
0 
0 
Black or African American 
38 
24 
62 
White 
406 
268 
674 
More Than One Race 
26 
15 
41 
Racial Categories: Total of All Subjects* 
482 
318 
800 
 
 
 

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14.0 REFERENCES 
 
1. Robison LL, Armstrong GT, Boice JD, et al: The Childhood Cancer Survivor Study: a National Cancer 
Institute-supported resource for outcome and intervention research. J Clin Oncol 27:2308-2318, 
2009 
2. Robison LL, Hudson MM: Survivors of childhood and adolescent cancer: life-long risks and 
responsibilities. Nat. Rev. Cancer 14:61-70, 2014 
3. Oeffinger KC, Mertens AC, Sklar CA, et al: Chronic health conditions in adult survivors of childhood 
cancer. N. Engl J Med 355:1572-1582, 2006 
4. Mertens AC, Liu Q, Neglia JP, et al: Cause-specific late mortality among 5-year survivors of childhood 
cancer: the Childhood Cancer Survivor Study. J Natl Cancer Inst 100:1368-1379, 2008 
5. Hudson MM, Ness KK, Gurney JG, et al: Clinical ascertainment of health outcomes among adults 
treated for childhood cancer. JAMA 309:2371-2381, 2013 
6. Lipshultz SE, Adams MJ, Colan SD, et al: Long-term cardiovascular toxicity in children, adolescents, 
and young adults who receive cancer therapy: pathophysiology, course, monitoring, management, 
prevention, and research directions: A scientific statement from the American Heart Association. 
Circulation 128:1927-1995, 2013 
7. Armstrong GT, Oeffinger KC, Chen Y, et al: Modifiable risk factors and major cardiac events among 
adult survivors of childhood cancer. J. Clin. Oncol 31:3673-3680, 2013 
8. Reulen RC, Winter DL, Frobisher C, et al: Long-term cause-specific mortality among survivors of 
childhood cancer. JAMA 304:172-179, 2010 
9. Tukenova M, Guibout C, Oberlin O, et al: Role of cancer treatment in long-term overall and 
cardiovascular mortality after childhood cancer. J. Clin. Oncol 28:1308-1315, 2010 
10. Kero AE, Jarvela LS, Arola M, et al: Cardiovascular morbidity in long-term survivors of early-onset 
cancer: a population-based study. Int. J Cancer 134:664-673, 2014 
11. van der Pal HJ, van Dalen EC, Hauptmann M, et al: Cardiac function in 5-year survivors of childhood 
cancer: a long-term follow-up study. Arch. Intern. Med 170:1247-1255, 2010 
12. Chow EJ, Chen Y, Kremer LC, et al: Individual prediction of heart failure among childhood cancer 
survivors. J Clin Oncol 33:394-402, 2015 
13. Brouwer CA, Postma A, Hooimeijer HL, et al: Endothelial damage in long-term survivors of childhood 
cancer. J Clin Oncol 31:3906-3913, 2013 
14. Baker KS, Chow EJ, Goodman PJ, et al: Impact of treatment exposures on cardiovascular risk and 
insulin resistance in childhood cancer survivors. Cancer Epidemiol. Biomarkers Prev 22:1954-1963, 
2013 
15. Chow EJ, Chen Y, Armstrong GT, et al: Individual risk prediction of major cardiovascular events after 
cancer: a Childhood Cancer Survivor Study report. J Clin Oncol 32, 2014 
16. Armenian SH, Sun CL, Vase T, et al: Cardiovascular risk factors in hematopoietic cell transplantation 
survivors: role in development of subsequent cardiovascular disease. Blood 120:4505-4512, 2012 
17. Chow EJ, Wong K, Lee SJ, et al: Late cardiovascular complications after hematopoietic cell 
transplantation. Biol. Blood Marrow Transplant 20:794-800, 2014 
18. Dengel DR, Kelly AS, Zhang L, et al: Signs of early sub-clinical atherosclerosis in childhood cancer 
survivors. Pediatr. Blood Cancer 61:532-537, 2014 
19. Oeffinger KC, Adams-Huet B, Victor RG, et al: Insulin resistance and risk factors for cardiovascular 
disease in young adult survivors of childhood acute lymphoblastic leukemia. J Clin Oncol 27:3698-
3704, 2009 

Protocol 8543: Version 7/10/20 
Page 34 of 40 
20. Chow EJ, Simmons JH, Roth CL, et al: Increased cardiometabolic traits in pediatric survivors of acute 
lymphoblastic leukemia treated with total body irradiation. Biol Blood Marrow Transplant 16:1674-
1681, 2010 
21. van Waas M, Neggers SJ, Pieters R, et al: Components of the metabolic syndrome in 500 adult long-
term survivors of childhood cancer. Ann Oncol 21:1121-1126, 2010 
22. Nathan PC, Daugherty CK, Wroblewski KE, et al: Family physician preferences and knowledge gaps 
regarding the care of adolescent and young adult survivors of childhood cancer. J Cancer Surviv 
7:275-282, 2013 
23. Suh E, Daugherty CK, Wroblewski K, et al: General internists' preferences and knowledge about the 
care of adult survivors of childhood cancer: a cross-sectional survey. Ann Intern Med 160:11-17, 
2014 
24. Shankar SM, Marina N, Hudson MM, et al: Monitoring for cardiovascular disease in survivors of 
childhood cancer: report from the Cardiovascular Disease Task Force of the Children's Oncology 
Group. Pediatrics 121:e387-e396, 2008 
25. Nathan PC, Greenberg ML, Ness KK, et al: Medical care in long-term survivors of childhood cancer: a 
report from the childhood cancer survivor study. J Clin Oncol 26:4401-4409, 2008 
26. Cox CL, Hudson MM, Mertens A, et al: Medical screening participation in the childhood cancer 
survivor study. Arch. Intern Med 169:454-462, 2009 
27. Baldwin LM, Dobie SA, Cai Y, et al: Receipt of general medical care by colorectal cancer patients: a 
longitudinal study. J Am Board Fam. Med 24:57-68, 2011 
28. Blaser BW, Kim HT, Alyea EP, III, et al: Hyperlipidemia and statin use after allogeneic hematopoietic 
stem cell transplantation. Biol Blood Marrow Transplant 18:575-583, 2012 
29. Shin DW, Kim SY, Cho J, et al: Comparison of hypertension management between cancer survivors 
and the general public. Hypertens. Res 35:935-939, 2012 
30. Calip GS, Boudreau DM, Loggers ET: Changes in adherence to statins and subsequent lipid profiles 
during and following breast cancer treatment. Breast Cancer Res. Treat 138:225-233, 2013 
31. Calip GS, Hubbard RA, Stergachis A, et al: Adherence to oral diabetes medications and glycemic 
control during and following breast cancer treatment. Pharmacoepidemiol. Drug Saf 24:75-85, 2015 
32. Cabana MD, Rand CS, Powe NR, et al: Why don't physicians follow clinical practice guidelines? A 
framework for improvement. JAMA 282:1458-1465, 1999 
33. Khatib R, Schwalm JD, Yusuf S, et al: Patient and healthcare provider barriers to hypertension 
awareness, treatment and follow up: a systematic review and meta-analysis of qualitative and 
quantitative studies. PLoS. One 9:e84238, 2014 
34. Committee on Cancer Survivorship: Improving Care and Quality of Life NCPB: From Cancer Patient to 
Cancer Survivor: Lost in Transition, in Hewitt M, Greenfield S, Stovall E (eds). Washington, D.C., 
Institute of Medicine and National Research Council, National Academies Press, 2006 
35. Casillas J, Oeffinger KC, Hudson MM, et al: Identifying Predictors of Longitudinal Decline in the Level 
of Medical Care Received by Adult Survivors of Childhood Cancer: A Report from the Childhood 
Cancer Survivor Study. Health Serv. Res, 2015 
36. Glasgow RE, Funnell MM, Bonomi AE, et al: Self-management aspects of the improving chronic 
illness care breakthrough series: implementation with diabetes and heart failure teams. Ann Behav. 
Med 24:80-87, 2002 
37. Glasgow RE, Hampson SE, Strycker LA, et al: Personal-model beliefs and social-environmental 
barriers related to diabetes self-management. Diabetes Care 20:556-561, 1997 
38. Lorig K, Ritter PL, Laurent DD, et al: Online diabetes self-management program: a randomized study. 
Diabetes Care 33:1275-1281, 2010 
39. Schulman-Green D, Bradley EH, Knobf MT, et al: Self-management and transitions in women with 
advanced breast cancer. J Pain Symptom. Manage 42:517-525, 2011 

Protocol 8543: Version 7/10/20 
Page 35 of 40 
40. Hudson MM, Neglia JP, Woods WG, et al: Lessons from the past: opportunities to improve childhood 
cancer survivor care through outcomes investigations of historical therapeutic approaches for 
pediatric hematological malignancies. Pediatr. Blood Cancer 58:334-343, 2012 
41. Green DM, Kun LE, Matthay KK, et al: Relevance of historical therapeutic approaches to the 
contemporary treatment of pediatric solid tumors. Pediatr. Blood Cancer 60:1083-1094, 2013 
42. Galea S, Tracy M: Participation rates in epidemiologic studies. Ann Epidemiol 17:643-653, 2007 
43. Oeffinger KC, Hudson MM, Mertens AC, et al: Increasing rates of breast cancer and cardiac 
surveillance among high-risk survivors of childhood Hodgkin lymphoma following a mailed, one-page 
survivorship care plan. Pediatr. Blood Cancer 56:818-824, 2011 
44. Syrjala KL, Stover AC, Yi JC, et al: Development and implementation of an Internet-based 
survivorship care program for cancer survivors treated with hematopoietic stem cell transplantation. 
J Cancer Surviv 5:292-304, 2011 
45. Hudson MM, Leisenring W, Stratton KK, et al: Increasing cardiomyopathy screening in at-risk adult 
survivors of pediatric malignancies: a randomized controlled trial. J Clin Oncol 32:3974-3981, 2014 
46. Hill-Kayser CE, Vachani CC, Hampshire MK, et al: Impact of internet-based cancer survivorship care 
plans on health care and lifestyle behaviors. Cancer 119:3854-3860, 2013 
47. Chobanian AV, Bakris GL, Black HR, et al: The Seventh Report of the Joint National Committee on 
Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 
289:2560-72, 2003 
48. James PA, Oparil S, Carter BL, et al: 2014 evidence-based guideline for the management of high 
blood pressure in adults: report from the panel members appointed to the Eighth Joint National 
Committee (JNC 8). JAMA 311:507-520, 2014 
49. Eckel RH, Jakicic JM, Ard JD, et al: 2013 AHA/ACC guideline on lifestyle management to reduce 
cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task 
Force on Practice Guidelines. Circulation 129:S76-99, 2014 
50. Whelton PK, Carey RM, Aronow WS, et al: 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/ 
NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood 
Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task 
Force on Clinical Practice Guidelines. Hypertension, 2017 
51. Kavey RE, Allada V, Daniels SR, et al: Cardiovascular risk reduction in high-risk pediatric patients: a 
scientific statement from the American Heart Association Expert Panel on Population and 
Prevention Science; the Councils on Cardiovascular Disease in the Young, Epidemiology and 
Prevention, Nutrition, Physical Activity and Metabolism, High Blood Pressure Research, 
Cardiovascular Nursing, and the Kidney in Heart Disease; and the Interdisciplinary Working Group on 
Quality of Care and Outcomes Research: endorsed by the American Academy of Pediatrics. 
Circulation 114:2710-38, 2006 
52. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and 
adolescents: summary report. Pediatrics 128 Suppl 5:S213-S256, 2011 
53. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, 
Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final 
report. Circulation 106:3143-3421, 2002 
54. Standards of medical care in diabetes--2015: summary of revisions. Diabetes Care 38 Suppl:S4, 2015 
55. Spain PD, Oeffinger KC, Candela J, et al: Response to a treatment summary and care plan among 
adult survivors of pediatric and young adult cancer. J Oncol Pract 8:196-202, 2012 
56. Schwarzer R, Luszczynska A: Self-efficacy, 2015 
57. Hinds PS, Nuss SL, Ruccione KS, et al: PROMIS pediatric measures in pediatric oncology: valid and 
clinically feasible indicators of patient-reported outcomes. Pediatr. Blood Cancer 60:402-408, 2013 

Protocol 8543: Version 7/10/20 
Page 36 of 40 
58. Cella D, Choi S, Garcia S, et al: Setting standards for severity of common symptoms in oncology using 
the PROMIS item banks and expert judgment. Qual. Life Res, 2014 
59. Wallston KA, Wallston BS, DeVellis R: Development of the Multidimensional Health Locus of Control 
(MHLC) Scales. Health Educ. Monogr 6:160-170, 1978 
60. Morisky DE, Green LW, Levine DM: Concurrent and predictive validity of a self-reported measure of 
medication adherence. Med Care 24:67-74, 1986 
61. Forsythe LP, Parry C, Alfano CM, et al: Use of survivorship care plans in the United States: 
associations with survivorship care. J Natl. Cancer Inst 105:1579-1587, 2013 
62. Rosoff PM, Werner C, Clipp EC, et al: Response rates to a mailed survey targeting childhood cancer 
survivors: a comparison of conditional versus unconditional incentives. Cancer Epidemiol. 
Biomarkers Prev 14:1330-1332, 2005 
63. Alexander GL, Divine GW, Couper MP, et al: Effect of incentives and mailing features on online 
health program enrollment. Am. J Prev. Med 34:382-388, 2008 
64. Baker R, Camosso-Stefinovic J, Gillies C, et al: Tailored interventions to overcome identified barriers 
to change: effects on professional practice and health care outcomes. Cochrane. Database. Syst. 
Rev:CD005470, 2010 
65. Unverzagt S, Peinemann F, Oemler M, et al: Meta-regression analyses to explain statistical 
heterogeneity in a systematic review of strategies for guideline implementation in primary health 
care. PLoS. One 9:e110619, 2014 
66. Glynn LG, Murphy AW, Smith SM, et al: Interventions used to improve control of blood pressure in 
patients with hypertension. Cochrane. Database. Syst. Rev:CD005182, 2010 
67. Schedlbauer A, Davies P, Fahey T: Interventions to improve adherence to lipid lowering medication. 
Cochrane. Database. Syst. Rev:CD004371, 2010 
68. Wens J, Vermeire E, Hearnshaw H, et al: Educational interventions aiming at improving adherence to 
treatment recommendations in type 2 diabetes: A sub-analysis of a systematic review of 
randomised controlled trials. Diabetes Res. Clin Pract 79:377-388, 2008 
69. Cox CL, Zhu L, Hudson MM, et al: Survivor typologies predict medical surveillance participation: the 
childhood cancer survivor study. Psychooncology 22:1534-1542, 2013 
70. Kadan-Lottick NS, Robison LL, Gurney JG, et al: Childhood cancer survivors' knowledge about their 
past diagnosis and treatment: Childhood Cancer Survivor Study. JAMA 287:1832-1839, 2002 
71. Schmittdiel JA, Uratsu CS, Karter AJ, et al: Why don't diabetes patients achieve recommended risk 
factor targets? Poor adherence versus lack of treatment intensification. J Gen. Intern Med 23:588-
594, 2008 
72. Daugherty SL, Powers JD, Magid DJ, et al: The association between medication adherence and 
treatment intensification with blood pressure control in resistant hypertension. Hypertension 
60:303-309, 2012 
 
 
 

Protocol 8543: Version 7/10/20 
Page 37 of 40 
15.0 APPENDICES 
 
The following documents are available as appendix (supplemental) items: 
 
• 
Approach (study introduction) letter 
• 
Consent template 
• 
Ineligible participant thank you letter 
• 
Patient baseline questionnaire 
• 
Patient follow-up questionnaire 
• 
Healthcare provider cover letter 
• 
Healthcare provider questionnaire 
• 
Survivorship care plan template 
• 
Action Plan template 
• 
Counseling fidelity rating form 
• 
 
References 
 
 
1. 
Robison LL, Armstrong GT, Boice JD, et al: The Childhood Cancer Survivor Study: a National 
Cancer Institute-supported resource for outcome and intervention research. J Clin Oncol 27:2308-2318, 2009 
 
2. 
Robison LL, Hudson MM: Survivors of childhood and adolescent cancer: life-long risks and 
responsibilities. Nat. Rev. Cancer 14:61-70, 2014 
 
3. 
Oeffinger KC, Mertens AC, Sklar CA, et al: Chronic health conditions in adult survivors of 
childhood cancer. N. Engl J Med 355:1572-1582, 2006 
 
4. 
Mertens AC, Liu Q, Neglia JP, et al: Cause-specific late mortality among 5-year survivors of 
childhood cancer: the Childhood Cancer Survivor Study. J Natl Cancer Inst 100:1368-1379, 2008 
 
5. 
Hudson MM, Ness KK, Gurney JG, et al: Clinical ascertainment of health outcomes among adults 
treated for childhood cancer. JAMA 309:2371-2381, 2013 
 
6. 
Lipshultz SE, Adams MJ, Colan SD, et al: Long-term cardiovascular toxicity in children, 
adolescents, and young adults who receive cancer therapy: pathophysiology, course, monitoring, management, 
prevention, and research directions: a scientific statement from the American Heart Association. Circulation 
128:1927-1995, 2013 
 
7. 
Armstrong GT, Oeffinger KC, Chen Y, et al: Modifiable risk factors and major cardiac events 
among adult survivors of childhood cancer. J Clin Oncol 31:3673-80, 2013 
 
8. 
Reulen RC, Winter DL, Frobisher C, et al: Long-term cause-specific mortality among survivors of 
childhood cancer. JAMA 304:172-179, 2010 
 
9. 
Tukenova M, Guibout C, Oberlin O, et al: Role of cancer treatment in long-term overall and 
cardiovascular mortality after childhood cancer. J Clin Oncol 28:1308-1315, 2010 
 
10. 
Kero AE, Jarvela LS, Arola M, et al: Cardiovascular morbidity in long-term survivors of early-onset 
cancer: a population-based study. Int. J Cancer 134:664-673, 2014 
 
11. 
van der Pal HJ, van Dalen EC, Hauptmann M, et al: Cardiac function in 5-year survivors of 
childhood cancer: a long-term follow-up study. Arch. Intern. Med 170:1247-1255, 2010 
 
12. 
Chow EJ, Chen Y, Kremer LC, et al: Individual prediction of heart failure among childhood cancer 
survivors. J Clin Oncol 33:394-402, 2015 
 
13. 
Brouwer CA, Postma A, Hooimeijer HL, et al: Endothelial damage in long-term survivors of 
childhood cancer. J Clin Oncol 31:3906-3913, 2013 
 
14. 
Baker KS, Chow EJ, Goodman PJ, et al: Impact of treatment exposures on cardiovascular risk and 
insulin resistance in childhood cancer survivors. Cancer Epidemiol. Biomarkers Prev 22:1954-1963, 2013 

Protocol 8543: Version 7/10/20 
Page 38 of 40 
 
15. 
Chow EJ, Chen Y, Armstrong GT, et al: Individual risk prediction of major cardiovascular events 
after cancer: a Childhood Cancer Survivor Study report. J Clin Oncol 32, 2014 
 
16. 
Armenian SH, Sun CL, Vase T, et al: Cardiovascular risk factors in hematopoietic cell 
transplantation survivors: role in development of subsequent cardiovascular disease. Blood 120:4505-4512, 2012 
 
17. 
Chow EJ, Wong K, Lee SJ, et al: Late cardiovascular complications after hematopoietic cell 
transplantation. Biol. Blood Marrow Transplant 20:794-800, 2014 
 
18. 
Dengel DR, Kelly AS, Zhang L, et al: Signs of early sub-clinical atherosclerosis in childhood cancer 
survivors. Pediatr. Blood Cancer 61:532-537, 2014 
 
19. 
Oeffinger KC, Adams-Huet B, Victor RG, et al: Insulin resistance and risk factors for cardiovascular 
disease in young adult survivors of childhood acute lymphoblastic leukemia. J Clin Oncol 27:3698-3704, 2009 
 
20. 
Chow EJ, Simmons JH, Roth CL, et al: Increased cardiometabolic traits in pediatric survivors of 
acute lymphoblastic leukemia treated with total body irradiation. Biol Blood Marrow Transplant 16:1674-1681, 
2010 
 
21. 
van Waas M, Neggers SJ, Pieters R, et al: Components of the metabolic syndrome in 500 adult 
long-term survivors of childhood cancer. Ann Oncol 21:1121-1126, 2010 
 
22. 
Nathan PC, Daugherty CK, Wroblewski KE, et al: Family physician preferences and knowledge 
gaps regarding the care of adolescent and young adult survivors of childhood cancer. J Cancer Surviv 7:275-282, 
2013 
 
23. 
Suh E, Daugherty CK, Wroblewski K, et al: General internists' preferences and knowledge about 
the care of adult survivors of childhood cancer: a cross-sectional survey. Ann Intern Med 160:11-17, 2014 
 
24. 
Shankar SM, Marina N, Hudson MM, et al: Monitoring for cardiovascular disease in survivors of 
childhood cancer: report from the Cardiovascular Disease Task Force of the Children's Oncology Group. Pediatrics 
121:e387-e396, 2008 
 
25. 
Nathan PC, Greenberg ML, Ness KK, et al: Medical care in long-term survivors of childhood 
cancer: a report from the childhood cancer survivor study. J Clin Oncol 26:4401-4409, 2008 
 
26. 
Cox CL, Hudson MM, Mertens A, et al: Medical screening participation in the childhood cancer 
survivor study. Arch. Intern Med 169:454-462, 2009 
 
27. 
Baldwin LM, Dobie SA, Cai Y, et al: Receipt of general medical care by colorectal cancer patients: 
a longitudinal study. J Am Board Fam. Med 24:57-68, 2011 
 
28. 
Blaser BW, Kim HT, Alyea EP, III, et al: Hyperlipidemia and statin use after allogeneic 
hematopoietic stem cell transplantation. Biol Blood Marrow Transplant 18:575-583, 2012 
 
29. 
Shin DW, Kim SY, Cho J, et al: Comparison of hypertension management between cancer 
survivors and the general public. Hypertens. Res 35:935-939, 2012 
 
30. 
Calip GS, Boudreau DM, Loggers ET: Changes in adherence to statins and subsequent lipid 
profiles during and following breast cancer treatment. Breast Cancer Res. Treat 138:225-233, 2013 
 
31. 
Calip GS, Hubbard RA, Stergachis A, et al: Adherence to oral diabetes medications and glycemic 
control during and following breast cancer treatment. Pharmacoepidemiol. Drug Saf 24:75-85, 2015 
 
32. 
Cabana MD, Rand CS, Powe NR, et al: Why don't physicians follow clinical practice guidelines? A 
framework for improvement. JAMA 282:1458-1465, 1999 
 
33. 
Khatib R, Schwalm JD, Yusuf S, et al: Patient and healthcare provider barriers to hypertension 
awareness, treatment and follow up: a systematic review and meta-analysis of qualitative and quantitative studies. 
PLoS. One 9:e84238, 2014 
 
34. 
Committee on Cancer Survivorship: Improving Care and Quality of Life NCPB: From Cancer 
Patient to Cancer Survivor: Lost in Transition, in Hewitt M, Greenfield S, Stovall E (eds). Washington, D.C., Institute 
of Medicine and National Research Council, National Academies Press, 2006 
 
35. 
Casillas J, Oeffinger KC, Hudson MM, et al: Identifying Predictors of Longitudinal Decline in the 
Level of Medical Care Received by Adult Survivors of Childhood Cancer: A Report from the Childhood Cancer 
Survivor Study. Health Serv. Res, 2015 
 
36. 
Glasgow RE, Funnell MM, Bonomi AE, et al: Self-management aspects of the improving chronic 
illness care breakthrough series: implementation with diabetes and heart failure teams. Ann Behav. Med 24:80-87, 
2002 
 
37. 
Glasgow RE, Hampson SE, Strycker LA, et al: Personal-model beliefs and social-environmental 
barriers related to diabetes self-management. Diabetes Care 20:556-561, 1997 

Protocol 8543: Version 7/10/20 
Page 39 of 40 
 
38. 
Lorig K, Ritter PL, Laurent DD, et al: Online diabetes self-management program: a randomized 
study. Diabetes Care 33:1275-1281, 2010 
 
39. 
Schulman-Green D, Bradley EH, Knobf MT, et al: Self-management and transitions in women with 
advanced breast cancer. J Pain Symptom. Manage 42:517-525, 2011 
 
40. 
Hudson MM, Neglia JP, Woods WG, et al: Lessons from the past: opportunities to improve 
childhood cancer survivor care through outcomes investigations of historical therapeutic approaches for pediatric 
hematological malignancies. Pediatr. Blood Cancer 58:334-343, 2012 
 
41. 
Green DM, Kun LE, Matthay KK, et al: Relevance of historical therapeutic approaches to the 
contemporary treatment of pediatric solid tumors. Pediatr. Blood Cancer 60:1083-1094, 2013 
 
42. 
Galea S, Tracy M: Participation rates in epidemiologic studies. Ann Epidemiol 17:643-653, 2007 
 
43. 
Oeffinger KC, Hudson MM, Mertens AC, et al: Increasing rates of breast cancer and cardiac 
surveillance among high-risk survivors of childhood Hodgkin lymphoma following a mailed, one-page survivorship 
care plan. Pediatr. Blood Cancer 56:818-824, 2011 
 
44. 
Syrjala KL, Stover AC, Yi JC, et al: Development and implementation of an Internet-based 
survivorship care program for cancer survivors treated with hematopoietic stem cell transplantation. J Cancer 
Surviv 5:292-304, 2011 
 
45. 
Hudson MM, Leisenring W, Stratton KK, et al: Increasing cardiomyopathy screening in at-risk 
adult survivors of pediatric malignancies: a randomized controlled trial. J Clin Oncol 32:3974-3981, 2014 
 
46. 
Hill-Kayser CE, Vachani CC, Hampshire MK, et al: Impact of internet-based cancer survivorship 
care plans on health care and lifestyle behaviors. Cancer 119:3854-3860, 2013 
 
47. 
Chobanian AV, Bakris GL, Black HR, et al: The Seventh Report of the Joint National Committee on 
Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 289:2560-72, 
2003 
 
48. 
James PA, Oparil S, Carter BL, et al: 2014 evidence-based guideline for the management of high 
blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 
8). JAMA 311:507-520, 2014 
 
49. 
Eckel RH, Jakicic JM, Ard JD, et al: 2013 AHA/ACC guideline on lifestyle management to reduce 
cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on 
Practice Guidelines. Circulation 129:S76-99, 2014 
 
50. 
Whelton PK, Carey RM, Aronow WS, et al: 2017 
ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, 
Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of 
Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension, 2017 
 
51. 
Kavey RE, Allada V, Daniels SR, et al: Cardiovascular risk reduction in high-risk pediatric patients: 
a scientific statement from the American Heart Association Expert Panel on Population and Prevention Science; 
the Councils on Cardiovascular Disease in the Young, Epidemiology and Prevention, Nutrition, Physical Activity and 
Metabolism, High Blood Pressure Research, Cardiovascular Nursing, and the Kidney in Heart Disease; and the 
Interdisciplinary Working Group on Quality of Care and Outcomes Research: endorsed by the American Academy 
of Pediatrics. Circulation 114:2710-38, 2006 
 
52. 
Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and 
adolescents: summary report. Pediatrics 128 Suppl 5:S213-S256, 2011 
 
53. 
Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, 
Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 
106:3143-3421, 2002 
 
54. 
Standards of medical care in diabetes--2015: summary of revisions. Diabetes Care 38 Suppl:S4, 
2015 
 
55. 
Spain PD, Oeffinger KC, Candela J, et al: Response to a treatment summary and care plan among 
adult survivors of pediatric and young adult cancer. J Oncol Pract 8:196-202, 2012 
 
56. 
Schwarzer R, Luszczynska A: Self-efficacy, 2015 
 
57. 
Hinds PS, Nuss SL, Ruccione KS, et al: PROMIS pediatric measures in pediatric oncology: valid and 
clinically feasible indicators of patient-reported outcomes. Pediatr. Blood Cancer 60:402-408, 2013 
 
58. 
Cella D, Choi S, Garcia S, et al: Setting standards for severity of common symptoms in oncology 
using the PROMIS item banks and expert judgment. Qual. Life Res, 2014 

Protocol 8543: Version 7/10/20 
Page 40 of 40 
 
59. 
Wallston KA, Wallston BS, DeVellis R: Development of the Multidimensional Health Locus of 
Control (MHLC) Scales. Health Educ. Monogr 6:160-170, 1978 
 
60. 
Morisky DE, Green LW, Levine DM: Concurrent and predictive validity of a self-reported measure 
of medication adherence. Med Care 24:67-74, 1986 
 
61. 
Forsythe LP, Parry C, Alfano CM, et al: Use of survivorship care plans in the United States: 
associations with survivorship care. J Natl. Cancer Inst 105:1579-1587, 2013 
 
62. 
Rosoff PM, Werner C, Clipp EC, et al: Response rates to a mailed survey targeting childhood 
cancer survivors: a comparison of conditional versus unconditional incentives. Cancer Epidemiol. Biomarkers Prev 
14:1330-1332, 2005 
 
63. 
Alexander GL, Divine GW, Couper MP, et al: Effect of incentives and mailing features on online 
health program enrollment. Am. J Prev. Med 34:382-388, 2008 
 
64. 
Baker R, Camosso-Stefinovic J, Gillies C, et al: Tailored interventions to overcome identified 
barriers to change: effects on professional practice and health care outcomes. Cochrane. Database. Syst. 
Rev:CD005470, 2010 
 
65. 
Unverzagt S, Peinemann F, Oemler M, et al: Meta-regression analyses to explain statistical 
heterogeneity in a systematic review of strategies for guideline implementation in primary health care. PLoS. One 
9:e110619, 2014 
 
66. 
Glynn LG, Murphy AW, Smith SM, et al: Interventions used to improve control of blood pressure 
in patients with hypertension. Cochrane. Database. Syst. Rev:CD005182, 2010 
 
67. 
Schedlbauer A, Davies P, Fahey T: Interventions to improve adherence to lipid lowering 
medication. Cochrane. Database. Syst. Rev:CD004371, 2010 
 
68. 
Wens J, Vermeire E, Hearnshaw H, et al: Educational interventions aiming at improving 
adherence to treatment recommendations in type 2 diabetes: A sub-analysis of a systematic review of randomised 
controlled trials. Diabetes Res. Clin Pract 79:377-388, 2008 
 
69. 
Cox CL, Zhu L, Hudson MM, et al: Survivor typologies predict medical surveillance participation: 
the childhood cancer survivor study. Psychooncology 22:1534-1542, 2013 
 
70. 
Kadan-Lottick NS, Robison LL, Gurney JG, et al: Childhood cancer survivors' knowledge about 
their past diagnosis and treatment: Childhood Cancer Survivor Study. JAMA 287:1832-1839, 2002 
 
71. 
Schmittdiel JA, Uratsu CS, Karter AJ, et al: Why don't diabetes patients achieve recommended 
risk factor targets? Poor adherence versus lack of treatment intensification. J Gen. Intern Med 23:588-594, 2008 
 
72. 
Daugherty SL, Powers JD, Magid DJ, et al: The association between medication adherence and 
treatment intensification with blood pressure control in resistant hypertension. Hypertension 60:303-309, 2012