Risk Factors for Cardiovascular Disease Among Thyroid Cancer Survivors: Findings From the Utah Cancer Survivors Study
J Clin Endocrinol Metab, July
Risk Factors for Cardiovascular Disease Among Thyroid Cancer Survivors: Findings From the Utah Cancer Survivors Study
Jihye Park 1 2
Brenna E. Blackburn 1 2
Patricia A. Ganz 3
Kerry Rowe 4
John Snyder 4
Yuan Wan 5
Vikrant Deshmukh 6
Michael Newman 1 6
Alison Fraser 5
Ken Smith 5
Kim Herget 7
Anne C. Kirchhoff 1 8
Dev Abraham 1 9
Jaewhan Kim 10
Marcus Monroe 0 1
Mia Hashibe 1 2
0 Division of Otolaryngology, Department of Surgery, University of Utah School of Medicine , Salt Lake City, Utah 84132 , USA
1 Huntsman Cancer Institute , Salt Lake City, Utah 84112 , USA
2 Division of Public Health, Department of Family and Preventive Medicine, University of Utah School of Medicine , Salt Lake City, Utah 84108 , USA
3 Department of Health Policy and Management, UCLA Fielding School of Public Health , Los Angeles, California 90095- 1772 , USA
4 Intermountain Healthcare , Salt Lake City, Utah 84107 , USA
5 Pedigree and Population Resource, Population Sciences, Huntsman Cancer Institute , Salt Lake City, Utah 84112 , USA
6 University of Utah Health Sciences Center , Salt Lake City, Utah 84132 , USA
7 Utah Cancer Registry, University of Utah , Salt Lake City, Utah 84108 , USA
8 Department of Pediatrics, University of Utah School of Medicine , Salt Lake City, Utah 84108 , USA
9 Division of Endocrinology, Department of Internal Medicine, University of Utah School of Medicine , Salt Lake City, Utah 84112 , USA
10 College of Health, University of Utah , Salt Lake City, Utah 84112 , USA
Context: Thyroid cancer survivors are at high risk of developing multiple cardiac and vascular conditions as consequence of cancer diagnosis and treatment. However, it is still unclear how the baseline and prognostic factors, as well as cancer treatments, play a role in increasing cardiac and vascular disease risk among thyroid cancer survivors. Objective: To investigate the association between potential risk factors, treatment effects, and cardiovascular disease (CVD) outcomes in thyroid cancer survivors. Design, Setting, Patients: Primary thyroid cancer survivors, diagnosed from 1997 to 2012 (n = 3822), were identified using the statewide Utah Population Database. The medical records were used to ascertain information on risk factors and CVD outcomes. Cox proportional hazards models were used to assess the risk of CVD with baseline demographic data and clinical factors. Results: Among thyroid cancer survivors, age and year at cancer diagnosis, cancer stage, sex, baseline body mass index, baseline comorbidities, and TSH suppression therapy were significantly associated with CVD risk 1 to 5 years after cancer diagnosis. Patients who were male, overweight or obese, older at cancer diagnosis, and diagnosed with cancer since 2005 had an increased risk of CVD compared with patients who were female, had a normal body mass index, were younger at cancer diagnosis, and diagnosed with cancer from 1997 to 1999. Administration of TSH suppression therapy, distant metastases at cancer diagnosis, and a higher Charlson comorbidity index score were associated with an increased CVD risk among thyroid cancer survivors. Conclusions: Our findings suggest that examining the effect of thyroid cancer diagnosis, cancer treatment, and demographic characteristics on the risk of CVD is critical. (J Clin Endocrinol Metab 103: 2468-2477, 2018)
Abbreviations: BMI, body mass index; CCI, Charlson comorbidity index; CCS, Clinical
Classification Software; CVD, cardiovascular disease; EMR, electronic medical record; HR,
hazard ratio; RAI, radioactive iodine; UPDB, Utah population database.
Tthe United States, with an estimated 64,300 new cases
hyroid cancer is the eighth most common cancer in
diagnosed in 2016 (
). In the United States, Utah has the
third highest incidence rate of thyroid cancer at 19.03 per
100,000 population (
). The 5-year survival rate of
thyroid cancer was 98.1% from 2006 to 2012 (
with the increasing trend of new cases, thyroid cancer is
expected to surpass other cancers and become the fourth
most common cancer in the United States by 2030 (
The primary treatment of patients with thyroid cancer is
surgery, either total or partial thyroidectomy, with most
undergoing total thyroidectomy (86%) (
). Among the
patients with papillary or follicular thyroid cancer who
received surgery, nearly one-half of them additionally
receive radioactive iodine (RAI) to treat either residual
cancer or ablate the remnant thyroid tissue (
chemotherapy is rarely prescribed for patients with thyroid
cancer, except when metastasis is present, TSH
suppression therapy or TSH replacement therapy is often used to
further reduce the risk of recurrence in select cases (
Given that patients with thyroid cancer are relatively
younger at diagnosis with a higher rate of survival, it is
important to study the long-term effects of cancer treatment
and evaluate the quality of life of thyroid cancer survivors
with a near-normal life expectancy (
). According to
results from previous studies and guidelines, RAI is
associated with an increased risk of cardiovascular diseases
(CVDs), and prolonged thyroxine exposure or TSH
suppressive therapy increases the risk of large artery
impairment and small arterial stiffness (which has been accepted
as a CVD surrogate marker), hypertension, cardiac
arrhythmias, and cardiovascular-specific mortality (
Recently, we reported a study, in which we examined
the risks of circulatory health conditions after thyroid
cancer diagnosis compared with cancer-free
). In that study, we found that thyroid cancer
survivors have an increased risk of several circulatory
conditions compared with the matched cancer-free
population, and these were significantly elevated with
an older age at cancer diagnosis, male sex, obesity, and
higher Charlson comorbidity index (CCI) (
). In an
attempt to further address these associations and better
understand how the baseline and prognostic factors, as
well as cancer treatments, play a role in increasing
cardiac and vascular disease risk among thyroid cancer
survivors, we assessed the risk factors for CVD among
thyroid cancer survivors in the state of Utah.
Materials and Methods
Registry (one of the original nine cancer registries from
National Cancer Institute Surveillance, Epidemiology, and End
Results program), electronic medical records (EMRs), and vital
records from the Utah Department of Health. The EMR data
include statewide inpatient discharge and ambulatory surgery
data and data from University of Utah Health and
Intermountain Healthcare (
). Among the study population, ~97%
had at least one medical record among the listed health care data
sources, 85.6% had statewide hospital discharge/ambulatory
surgery data, and 90.4% had EMR data from University
of Utah Health and/or Intermountain Healthcare. The
University of Utah institutional review board approved the
We used the Utah Cancer Registry records to identify
primary thyroid cancer cases diagnosed from 1997 to 2012 and
linked treatment data. The last follow-up date was identified by
UPDB via various data sources, which included vital records
from the Utah Department of Health, voter registration, driver?s
license division, Utah Cancer Registry records, and Social
Security Death Index (nationwide). We excluded patients with
thyroid cancer if they had had a papillary micro-cancer (n = 18)
or had missing or unknown information on cancer stage (n =
101). Patients were also excluded if they had not been living in
Utah at the time of the diagnosis (n = 128) or if their follow-up
time from the cancer diagnosis was ,1 year (n = 243).
Exposure and outcome of interest
The demographic and clinical data included sex, birth year,
age at thyroid cancer diagnosis, race/ethnicity, body mass index
(BMI), year of cancer diagnosis, cancer stage, cancer histologic
type, number of cancers, cancer treatment, TSH suppression
therapy, and CCI score (
). The CCI score was calculated
using all medical record data before the date of the thyroid
cancer diagnosis and used as a measure of baseline health. We
used a modified CCI score calculation for our analysis. Instead
of including only a few diagnoses categorized within CVD such
as myocardial infarction, peripheral vascular disease,
congestive heart failure, and cerebrovascular disease, we included all
CVD-related diagnoses under investigation in our study for the
CCI score calculation. In addition, two of the variables used to
calculate the score were excluded (any malignancy and
metastatic solid tumor) to avoid double adjustment for cancer (
We used the Clinical Classification Software (CCS) for the
International Classification of Diseases, Ninth Revision,
Clinical Modification (ICD-9-CM), created by the Healthcare Cost
and Utilization Project, to identify CVD outcomes (
CCS is a system that categorizes patient diagnoses and
procedures using ICD-9-CM codes. The CCS categories consist of
four levels, from the broad category (level 1) to more detailed
grouping (level 4) according to clinical meaningfulness (
CVD and five specific cardiovascular categories (hypertension,
heart disease, cerebrovascular disease, diseases of the arteries,
arterioles, and capillaries, and diseases of the veins and
lymphatics) were assessed. If multiple CVD outcomes were
diagnosed after the cancer diagnosis, we used the first primary
CVD case as an individual?s main outcome. The CVD diagnoses
were stratified over three periods: 1 to 5, .5 to 10, and $10 years
after the cancer diagnosis.
The study cohort was developed within the Utah population
database (UPDB), a database using data from the Utah Cancer
The characteristics of thyroid cancer survivors stratified by
the CVD diagnosis were summarized using descriptive statistics.
Cox proportional hazards models were used to calculate the
hazard ratios (HRs) and 95% CIs and to estimate the effect of
each risk factor on the development of CVD. The time-to-event
was defined as the time from the thyroid cancer diagnosis to the
CVD diagnosis or to their last date known to be alive and
residing in Utah. If the proportional hazard assumption was
violated in the Cox model, we used Cox models with cubic
splines to identify nonlinear covariate response relationships in
the Cox model and perform a flexible assessment of the
time-bycovariate interactions (
The BMI at least 1 year before the thyroid cancer diagnosis
was used as the baseline BMI. Given that ~20% of all
participants had missing BMI data at baseline, we used iterative
chained equation imputation, which is a multiple imputation
approach to provide missing BMI data (
). We assessed
whether the BMI was missing at random using the logistic
regression model (1 = missing BMI vs 0 = not missing BMI). In
this regression, we controlled for CVD (i.e., outcome), age at
diagnosis, sex, race, and CCI to assess whether the probability
of the missing BMI depended on the observed covariates and
outcome. Although we observed no differences in missing BMI
data associated with sex, race, and CCI, we did find a difference
in the distribution of mean age at cancer diagnosis between the
missing values and the observed values. Thus, we imputed BMI
for those with missing BMI data at random and adjusted all HR
estimation models for age at diagnosis, sex, race, and CCI with
fully conditional specification methods. To ensure that our
inferences were not biased by the imputed BMI, we compared
Cox regression models estimating HRs with only those with
BMI available in the data vs with the full population after
imputing the BMI for those with missing BMI at random.
We determined the potential confounding factors using
directed acyclic graphs (
) and a review of previous reported
data to assess whether the covariates met three properties of a
confounder both clinically and statistically. Sex, race, age at
diagnosis, cancer diagnosis year, cancer stage, BMI at baseline,
and baseline CCI score were included in the multivariable
adjusted models. The HRs were estimated separately for each
risk factor after adjusting for confounding potentially
associated with that specific risk factor. SAS software, version 9.4
(SAS Institute, Inc., Cary, NC) and Stata software, version
14.1 (StataCorp, College Station, TX) were used for all
Of the 3822 thyroid cancer survivors, 3510 (91.8%)
had a diagnosis of papillary carcinoma (Tables 1 and 2).
The cohort was predominantly white (96.1%) and
female (78.8%). Nearly all had received surgically based
treatment (thyroidectomy and thyroid lobectomy; 99.3%)
and more than one- half (52.6%) had received
postoperative adjuvant RAI treatment. A total of 1719 patients
(45.0%) developed at least one cardiac or vascular disease
1 to 5 years after their cancer diagnosis. The mean 6 SD
follow-up time was 8.4 6 4.1 years for the CVD group and
8.8 6 4.5 years for the non-CVD group.
The proportion of patients who died was significantly
greater among the patients with a diagnosis of CVD
compared with patients without a CVD diagnosis [196
(11.4%) and 56 (2.7%), respectively; P , 0.001] in the 1
to 5 years after the cancer diagnosis. Although most
cancer survivors who did not have a CVD diagnosis had
no baseline comorbidities [1296 (61.6%)], patients
with a CVD diagnosis were more likely to be elderly,
male, and overweight or obese compared with those who
without a CVD diagnosis. No noticeable differences were
found between the patients with and without CVD in the
clinical cancer characteristics.
The risk of CVD was high among the patients with a
diagnosis from 2005 to 2009 and 2010 to 2012
compared with those with a diagnosis from 1997 to 1999
(HR, 1.42; 95% CI, 1.19 to 1.69 and HR, 1.26; 95% CI,
1.05 to 1.51, respectively; Fig. 1). Patients aged 40 to 65
and .65 years at diagnosis had significantly increased
risks for the CVD (HR, 1.66; 95% CI, 1.46 to 1.88 and
HR, 2.84; 95% CI, 2.46 to 3.27, respectively) compared
with those aged ,40 years at cancer diagnosis. The risk
of developing CVD was significantly greater for men
compared with women (HR, 1.46; 95% CI, 1.31 to 1.62)
and was greater for patients who received TSH
suppression therapy compared with those who did not (HR,
1.25; 95% CI, 1.12 to 1.40). Overweight (BMI, 25 to
29.9 kg/m2) and obesity (BMI, $30 kg/m2) were factors
significantly associated with an increased CVD risk (HR,
1.24; 95% CI, 1.11 to 1.39 and HR, 1.41; 95% CI, 1.25
to 1.60). Patients with any comorbidity had more than a
fourfold increased risk of developing CVD compared
with those with no comorbid conditions (HR, 4.47; 95%
CI, 3.87 to 5.15). The presence of distant metastases of
cancer was significantly associated with an elevated CVD
risk compared with a localized cancer stage (HR, 1.35;
95% CI, 1.03 to 1.77). The risk factors for developing
CVD within .5 to 10 years and .10 years were
additionally assessed and summarized in Supplemental Table 1.
Multivariable adjusted HRs for the baseline covariates
and clinical predictors associated with CVD subgroup in
the 1- to 5-year period are summarized in Tables 3 and 4,
respectively. Overall, a diagnosis of cancer at an older age
was significantly associated with elevated risks for
multiple circulatory conditions. Thyroid cancer survivors
with a diagnosis at an age from 40 to 65 years and .65
showed a significantly increased risk of multiple cardiac
and vascular conditions compared with those with a
diagnosis at an age ,40 years after adjusting for
confounders. Furthermore, compared with female thyroid
cancer survivors, male thyroid cancer survivors were
more likely to have multiple CVD conditions. Individuals
with an overweight baseline BMI only had an elevated
risk of hypertension, heart disease, and diseases of the
arteries, arterioles, and capillaries. In contrast, obesity
was associated with an increased risk of all disease
subtypes classified under CVD, except for
cerebrovascular disease (Table 3). The risk factors for the CVD
subgroups of .5- to 10-year and .10-year periods are
summarized in Supplemental Table 2 and Table 3.
The adjusted HRs for the thyroid cancer survivors
who had received TSH suppression therapy were
significantly greater for hypertension and diseases of the
arteries, arterioles, and capillaries (HR, 1.22; 95% CI,
1.06 to 1.41 and HR, 1.27; 95% CI, 1.04 to 1.56,
respectively) compared with those who had not received
TSH suppression therapy. Although the difference was
not statistically significant, the use of radiation therapy
after surgery was marginally associated with an increased
risk of cerebrovascular disease compared with those who
had received surgery only (Table 4). When stratifying the
effect of different types of postoperative radiation
therapy (beam radiation, radioactive implants, and RAI)
on the development of CVD, although only marginally
significant statistically, the use of RAI after surgery was
positively associated with the risk of developing
cerebrovascular disease (HR, 1.42; 95% CI, 0.97 to 2.07; P =
0.07; data not shown) Patients with distant metastases of
cancer had a 58% greater risk of developing diseases of
the arteries, arterioles, and capillaries compared with the
patients with localized thyroid cancer (HR, 1.58; 95%
CI, 1.01 to 2.46). Also, a significantly elevated risk was
found for all 5 CVD subgroups among the patients with
any vs without any pre-existing comorbidities.
In a sensitivity analysis comparing the estimated HRs
of the covariates with only the not missing BMI data
included with the estimated HRs of the covariates with
the imputed BMI included, we found slight changes in the
HRs after the imputation. Among the risk factors for
overall CVD, we found that the estimates for cancer stage
and year at diagnosis have a changed inference owing
to the imputed BMI values. In patients with distant
Surgery and radiation
TSH suppression therapy
CCI score at baseline
No. of cancers
metastases of cancer, the HR was 1.28 (95% CI, 0.95 to
1.73) without imputation vs 1.35 (95% CI, 1.03 to 1.77)
with imputation. In patients with a diagnosis from 2005 to
2009 and 2010 to 2012, the HRs without vs with
imputation were 1.27 (95% CI, 0.96 to 1.69) vs 1.42 (95%
CI, 1.19 to 1.69) and 1.10 (95% CI, 0.83 to 1.47) vs 1.26
(95% CI, 1.05 to 1.51), respectively. However, we did not
observe any notable variation in the overall trends for HRs
after the multiple imputation of the BMI missing values.
In a statewide sample of primary thyroid cancer cases
followed up for .15 years, we found that patient age
and year of cancer diagnosis, cancer stage, sex, baseline
BMI and CCI score, and the use of TSH suppression
therapy were significantly associated with an elevated
CVD risk within 1 to 5 years after the thyroid cancer
diagnosis. Radiation therapy after surgery was
marginally associated with an elevated risk of cerebrovascular
disease compared with surgery only. Additionally, our
findings of increased risks of diseases of the circulatory
system among thyroid cancer survivors treated with TSH
suppression therapy are consistent with previous studies
that assessed the effect of TSH suppression therapy on the
potential risk of long-term adverse CVD outcomes among
patients with thyroid cancer (
). Despite the high
survival rate, thyroid cancer survivors? risk of CVD events
in the first 5 years after the cancer diagnosis suggests that
evaluating, not only patient-specific risk factors, but also
the consequences of the cancer diagnosis and its treatment,
is important to improve the quality of life of thyroid
Similar to the findings from a previous study (
study supports the findings that certain demographic
characteristics of thyroid cancer survivors might have a
considerable effect on cardiac and vascular adverse health
outcomes. Schultz et al. (
) reported, in a cross-sectional
survey of 518 thyroid cancer survivors, that 9.7% had
developed CVD within 10 years of follow-up and that men
were more likely to report cardiovascular effects
compared with women (
). In contrast, Kero et al. (6)
found that thyroid cancer survivors did not have a
significantly greater risk of developing CVD compared with
sibling controls in a recent population-based cohort study
of 1356 early-onset (diagnosis at ,35 years of age) thyroid
cancer survivors. However, our study findings have
improved on these earlier reports, because our sample
included almost 4000 thyroid cancer cases diagnosed in
patients aged $18 years. Also, we used complete EMR
data rather than patient self-report data.
Regarding the late effects of thyroid cancer
treatment, several studies have assessed the potential adverse
effects of postoperative chemotherapy, RAI therapy,
and TSH suppressive therapy (
7, 13?15, 18, 30
Previous findings suggested that RAI therapy might cause,
not only short-term nonfatal complications such as
dry eyes (10), gastrointestinal system disorders (
and salivary dysfunction (
), but also serious
chronic complications, such as pulmonary fibrosis and
permanent bone marrow suppression (8). Furthermore,
long-term TSH suppressive therapy is known to
predispose thyroid cancer survivors to skeletal conditions,
including arthritis, osteoporosis, and bone mineral
density loss (
), and to increase their risk of chronic
cardiovascular outcomes, including tachycardia and
stroke volume decrease (
10, 28, 31
Among the known risks of long-term health
problems related to prolonged cancer treatment, our
findings of an increased CVD risk for patients with thyroid
cancer who received TSH suppression therapy after
thyroidectomy are in agreement with previous research
conducted among thyroid cancer survivors (
6, 13, 15,
). Shargorodsky et al. (15) reported that
postoperative levothyroxine treatment was significantly
associated with large and small artery elasticity, also
known as a proxy marker of CVD, and suggested that
long-term TSH suppressive therapy might alter myocardial
and vascular function impairment. Furthermore, Klein
Hesselink et al. (
) reported that a lower TSH level is
associated with increased cardiovascular mortality, with a
risk of 3.08 (95% CI, 1.32 to 7.21) for each 10-fold
decrease in the geometric mean TSH level. Iatrogenic
hyperthyroidism or thyroid dysfunction has also been known
to increase the risk of atrial fibrillation and subsequent
embolic cerebrovascular accidents (
because our study had limited information on the use
of TSH suppression therapy after surgery, further
investigation is required to evaluate the late effect of
postoperative TSH suppressive therapy exposure on CVD risk.
Although previous studies suggested mixed findings
regarding the linkage between RAI and cerebrovascular
), our findings suggest that thyroid cancer
survivors who received radiation therapy after surgery
have an increased risk of developing cerebrovascular
disease within 1 to 5 years after the cancer diagnosis
compared with those who only underwent surgery.
When we compared the role of different types of
Data presented as HR (95% CI).
aAdjusted for age at diagnosis, BMI at baseline, and CCI score.
bFor the models that violated proportional hazards assumptions, we used Cox models with cubic splines.
cAdjusted for diagnosis y, race, sex, BMI at baseline, and CCI score.
dAdjusted for diagnosis y, age at diagnosis, race, sex, and CCI score.
radiation therapy on cerebrovascular disease, although
the difference was marginally significant statistically,
postoperative RAI usage was the only subtype with an
elevated risk of developing cerebrovascular disease. This
association is biologically plausible, because the carotid
arteries are located immediately adjacent to the thyroid
gland and carotid artery intimal thickening has been
reported after RAI for benign disease (
given that we did not have dosage information, we were
unable to evaluate dose-dependent relationships in our
study population. The most commonly used dosage of
RAI during the study period ranged from 30 mCi for
remnant ablation to 100 to 150 mCi for therapeutic
ablation of locoregional and extensive disease.
Interinstitution and practitioner variation of activities also
ranged from 30 to 150 mCi. Based on these practice
patterns, we estimated that ~50% of subjects had likely
been treated with 30 mCi and the rest with higher
dosages. A rigorous investigation is needed to assess the
role of RAI after surgery on long-term circulatory system
disorders among thyroid cancer survivors.
We observed that patients with thyroid cancer with a
diagnosis from 2005 to 2009 and 2010 to 2012 had an
increased risk of CVD compared with the patients with a
diagnosis from 1997 to 1999. One possible explanation
for these associations might be the increasing proportion
of patients who underwent TSH suppression (P ,
0.0001) and radiation therapy (P = 0.0047) during the
study period owing to changes in treatment strategies.
Future investigation is necessary on the changes in
clinical practices and long-term cardiac and circulatory
conditions among thyroid cancer survivors.
The strengths of our study included the large
populationbased sample and assessment of information on cancer
treatment from the EMRs. The cohort consisted of nearly
4000 thyroid cancer survivors, allowing us to study CVD
morbidity associated with demographic characteristics and
cancer treatment among thyroid cancer survivors.
Furthermore, although previous studies relied on self-reported
survey data, we used EMRs collected from two of the
largest medical care providers in Utah and the hospital
discharge/ambulatory surgery records.
Our study had several limitations. First, although the
state of Utah is becoming more diverse, our study
population was still predominantly white. Thus, the findings
from our study might not be generalizable to other more
diverse populations. Another limitation of our study was
the use of ICD-9-CM codes and medical records for the
disease diagnoses. We could not exclude the possibility of
measurement and/or coding errors. Additionally, we did
not have more detailed treatment-related information
such as the types of TSH suppression therapy or the RAI
Data presented as HR (95% CI).
aAdjusted for diagnosis y, age at diagnosis, race, sex, BMI at baseline, and CCI score.
bAdjusted for diagnosis y, age at diagnosis, race, sex, BMI at baseline, cancer stage at diagnosis, and CCI score.
cFor the models that violated proportional hazards assumptions, we used Cox models with cubic splines.
dAdjusted for diagnosis y, age at diagnosis, race, sex, and BMI at baseline.
treatment, dose, and frequency used, which would have
allowed us further understanding of how various forms
of cancer treatment might affect CVD risk among thyroid
cancer survivors. Also, we were unable to assess other
important potential cofounders (i.e., physical activity,
diet). Hence, further investigation is clearly needed of the
interplay among cancer treatment, demographic traits,
lifestyle, and comorbidity clusters.
To the best of our knowledge, the present study was
one of the first population-based studies to assess the
association between the potential risk factors for CVD
among thyroid cancer survivors. Year and age at cancer
diagnosis, sex, cancer stage, TSH suppression therapy,
baseline BMI, and baseline comorbidity were statistically
significant risk factors for CVD. Our findings suggest that
examining the effect of thyroid cancer diagnosis, cancer
treatment, and demographic and psychosocial
characteristics on the risk of life-threatening conditions is critical.
Thus, for a better quality of life among thyroid cancer
survivors, future research is needed to demonstrate the
long-term health effects after the cancer diagnosis, not
only to provide individualized clinical intervention, but
also to prevent the risk of fatal conditions.
We thank the Pedigree and Population Resource of the Huntsman
Cancer Institute, University of Utah (funded in part by the
Huntsman Cancer Foundation) for its role in the ongoing
collection, maintenance, and support of the UPDB. We also thank
the University of Utah Center for Clinical and Translational
Science (funded by National Institutes of Health Clinical and
Translational Science Awards), and the Pedigree and Population
Resource, University of Utah Information Technology Services
and Biomedical Informatics Core for establishing the Master
Subject Index between the UPDB, the University of Utah Health
Sciences Center, and Intermountain Healthcare.
Financial Support: The present study was supported by the
National Institutes of Health (Grants R21 CA185811 and R03
CA159357; to M.H.,primary investigator), the Huntsman Cancer
Institute, Cancer Control and Population Sciences Program (HCI
Cancer Center Support Grant P30CA042014), and the National
Center for Research Resources grant, ?Sharing Statewide Health
Data for Genetic Research? (Grant R01 RR021746; to G.M.,
primary investigator), with additional support from the Utah
State Department of Health and the University of Utah.
Correspondence and Reprint Requests: Mia Hashibe,
PhD, Division of Public Health, Department of Family and
Preventive Medicine, Huntsman Cancer Institute, 2000 Circle
of Hope Drive, Salt Lake City, Utah 84112. E-mail: mia.
Disclosure Summary: The authors have nothing to
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