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Survival trends and related outcomes of survivors of childhood and young adult cancer
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Content
Survival Trends and Related Outcomes of Survivors of Childhood and Young Adult Cancer
By
Diana J Moke
A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements for the Degree
MASTER OF SCIENCE (CLINICAL AND BIOMEDICAL INVESTIGATIONS)
August 2018
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
2
Table of Contents
Abstract
3
Chapter One: Current Disparities and Trends in Adolescent and Young Adult Cancer
Survival: A California Cancer Registry-based Study
Abstract
5
Introduction
6
Methods
8
Results
11
Discussion
18
Supplemental Materials
24
Chapter Two: Obesity and Risk for Second Malignant Neoplasms in Childhood
Cancer Survivors: A California Cancer Registry-based Case-Control Study
Abstract
32
Introduction
33
Methods
35
Results
39
Discussion
45
References
52
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
3
Abstract
In this thesis, we present novel insights into the contributors and pathophysiology of
important outcomes in child, adolescent, and young adult cancer survivorship using registry-
based data.
Cancer survival has improved dramatically for children and older adults. However,
adolescents and young adults (AYAs, 15-39 years old) were shown in the 1990s to have
plateauing survival improvements. This has been thought to be attributable to a combination of
factors uniquely affecting AYAs, including different disease/host biology, delays in diagnosis
and treatment, increased toxicity to treatment, financial toxicity, and psychosocial factors. In
Chapter 1, we sought to reappraise AYA cancer survival in light of recent data. In this California
Cancer Registry based analysis, cancer site specific survival data was examined from 1988-2014
evaluating for trends in survival over time. In an effort to better understand the stagnating
survival gains once observed in this racially/ethnically and socioeconomically diverse
population, subgroup specific survival over time was assessed, and survival disparities were
defined. We found that, contrary to prior observations in the 1990s of stagnating survival gains,
the time frame from 1988-2014 actually demonstrated the most dramatic survival improvements
for AYAs, especially AYA males, largely due to the improved survival from HIV/AIDS related
cancers after the introduction of effective antiretroviral therapy. However, survival
improvements over the time period were not equally distributed among all AYAs. Not only did
certain cancer sites and stages show no improvement over the time period, all racial/ethnic
groups compared to non-Latino whites and low SES compared to high SES showed growing
survival disparities.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
4
Survival for pediatric cancer has improved greatly over the decades and now reaches
about 80%. With this growing number of cancer survivors, understanding late effects from
cancer therapy has become paramount. A particular late effect causing significant morbidity and
often mortality are treatment related second malignant neoplasms (SMNs), affecting almost 10%
of 30 year survivors of pediatric cancer. While treatment factors and underlying genetic
syndromes have been shown to increase a survivor’s risk of SMN, other risk factors, such as
obesity during time of treatment, have not been described. In this case-control study utilizing the
California Cancer Registry for case and control selection, we performed a retrospective chart
review to test whether obesity at time of cancer treatment increased the risk of SMN. We found
that there is a strong suggestion of an increased risk of SMN associated with obesity at time of
cancer treatment (with an over two-fold odds of SMN for obese patients at diagnosis, and an
over three-fold odds of SMN for patients who are obese at time of diagnosis and at end of
therapy). More research is needed to confirm these findings and identify interventions that can
help control weight during cancer treatment in order to mitigate SMN risk and obesity related
diseases among pediatric cancer survivors.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
5
Chapter One:
Current Disparities and Trends in Adolescent and Young Adult Cancer Survival: A California
Cancer Registry-based Study
ABSTRACT
BACKGROUND: In the 1990s, adolescents and young adults (AYAs, ages 15-39) with cancer
were reported to have lower survival improvement compared to younger and older populations.
OBJECTIVE: To re-evaluate AYA survival trends and disparities using contemporary data.
METHODS: Using California Cancer Registry data from 1988 to 2014, we calculated (1) 5-year
overall survival improvement for AYAs compared to younger and older populations; (2) hazard
ratios of death for AYAs comparing 2001-2014 with 1988-2000, stratified by subgroups (site,
stage, sex, age group, race/ethnicity, socioeconomic status [SES]); and (3) site-specific adjusted
HRs (aHRs) for AYA risk groups and interaction analyses by time period.
RESULTS: For all cancers combined, AYAs had significantly improved survival during the
study period (aHR for later vs. earlier time periods 0.70, 95%CI 0.69-0.71), largely due to lower
mortality in HIV/AIDS-related cancers. Sites showing no improvement were bone/soft tissue
sarcoma, ovary, stomach, testis, thyroid, and uterus. The strongest predictor of survival among
all cancer sites was stage at diagnosis (aHR 6.32 for distant vs. local disease, 95%CI 6.20-6.45).
For all cancers combined, compared to non-Latino whites the aHR for blacks was 1.46 (95%CI
1.42-1.50), for Asian/Pacific Islanders 1.12 (95%CI 1.09-1.15), and for Latino whites 1.06
(95%CI 1.04-1.08). Lower SES was associated with a higher aHR (1.31, 95%CI 1.29-1.34).
Survival disparities by stage, race/ethnicity, and SES increased over the two time periods.
CONCLUSIONS: Cancer survival is improving for AYAs in aggregate, but not for all subsets
including those who have advanced stage disease, are racial/ethnic minorities, and of low SES.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
6
Appropriate interventions should be developed to address these differences, including healthcare
inequities within the AYA population that may exacerbate age-related challenges in cancer care
and delivery.
INTRODUCTION
Recent advances in diagnosis and treatment have resulted in improved survival for most
cancers. However, outcome differences are observed among subgroups of stage, sex, age,
race/ethnicity, and socioeconomic status (SES)(Aizer et al., 2014; Albain, Unger, Crowley,
Coltman, & Hershman, 2009; Albano et al., 2007; Bristow et al., 2015; Bristow et al., 2013;
Chien, Morimoto, Tom, & Li, 2005; Iqbal, Ginsburg, Rochon, Sun, & Narod, 2015; Kadan-
Lottick, Ness, Bhatia, & Gurney, 2003; Kish, Yu, Percy-Laurry, & Altekruse, 2014; Komenaka
et al., 2010; Li, Malone, & Daling, 2003; J. Lin, Qiu, Xu, & Dobs, 2015; S. S. Lin et al., 2002;
Philips, Belasco, Markides, & Gong, 2013; Shariff-Marco et al., 2015; Shariff-Marco et al.,
2014; Yung et al., 2011), indicating that multiple factors determine cancer survival. In the
landmark report, “Closing the Gap,” issued in 2006 by a Progress Review Group of the United
States (US) National Cancer Institute (NCI) (AYA Progress Review Group, 2006), adolescents
and young adults (AYAs, ages 15-39) were reported to have an alarming lack of improvement in
cancer survival compared with other age groups. Based upon Surveillance, Epidemiology and
End Results (SEER) Program data from 1977 to 1997, AYAs experienced lower average annual
percent improvement in cancer survival compared with both children and older adults. Proposed
reasons for this finding included age-related differences in underlying tumor biology, delays in
diagnosis, suboptimal therapy, excess treatment-related toxicity and mortality, poor participation
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
7
in clinical trials, and problems with access and adherence to appropriate therapy (AYA Progress
Review Group, 2006).
With “Closing the Gap” serving as a call to action, numerous efforts were undertaken to
improve outcomes for AYAs with cancer, including more complete characterizations of survival
and toxicity disparities (Freyer, Felgenhauer, Perentesis, & Committee, 2013); elucidation of
tumor biology (Lewis, Seibel, Smith, & Stedman, 2014; Mastrangelo, 2009; Tricoli, Seibel,
Blair, Albritton, & Hayes-Lattin, 2011); introduction of more effective therapy for certain AYA
cancers (Cheung, Pantanowitz, & Dezube, 2005; Orellana-Noia & Douvas, 2018; Wood &
Harrington, 2005); emphasis on improving participation of AYAs in clinical trials (Weiss et al.,
2015); launch of the collaborative National Clinical Trials Network (Weiss et al., 2015);
establishment of an AYA Oncology Discipline Committee in the Children’s Oncology Group
(COG) followed by other NCTN groups (Freyer et al., 2013; Weiss et al., 2015); and emergence
of the discipline of AYA oncology itself (Shaw et al., 2015). However, there is reason to believe
that any potential improvement may not extend to all subgroups within the broad population of
AYAs. Recent data published by the Los Angeles Cancer Surveillance Program (CSP)
documented inferior survival for AYAs who had advanced stage disease, were male, black, or of
low socioeconomic status (SES) (Deapen D, 2015; Liu L, 2017).
In light of these important developments, the availability of more recent data, and access
to uniquely focused resources at our institution, we undertook this study to provide a current and
comprehensive description of AYA cancer survival. Leveraging California’s rich racial, ethnic
and socioeconomic diversity, we used California Cancer Registry (CCR) data from 1988 to 2014
to evaluate overall cancer survival trends for AYAs compared with other age groups, assess
changes in survival over time for each AYA cancer site and subgroup, and delineate socio-
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
8
demographic subgroups at risk for survival disparities. We hypothesized that AYA cancer
survival has improved for certain cancer sites (e.g., Kaposi sarcoma [KS], leukemia, and
lymphoma) and subgroups (e.g., non-Latino whites [NLW] and higher SES), but not for others.
We also postulated that survival disparities persist for at-risk AYA subgroups, including blacks
and those of low SES.
METHODS
Cancer Cases
The state of California requires that all cancer diagnoses among California residents be
reported to the CCR; these data are also included in the NCI’s Surveillance, Epidemiology and
End Results (SEER) Program. We obtained data on all AYA patients diagnosed in California
with invasive cancer, non-invasive cancers in the brain/central nervous system (CNS), and
bladder cancer in situ (defined as not invading the basement membrane of the mucosa of the
bladder wall) from January 1, 1988 through December 31, 2014 and reported to the CCR by
August 1, 2017. Only first primary cancers were included.
AYA Cancer Site Recode
Cancer cases were subdivided by cancer site (as defined by the AYA Site Recode/World
Health Organization [WHO] 2008 definition (Barr, Holowaty, & Birch, 2006; World Health
Organization, 2008)). Twenty-two of the most common cancer sites were included plus an
“other” category comprising all other invasive cancer sites and in situ bladder cancer for a total
of 23 sites. For additional comparisons to the AYA age group, case counts and survival data
from 1988-2014 were provided for all invasive cancers combined for 0-14 and ≥ 40 year olds.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
9
Stage, Sex, Age, Race/ethnicity, and SES
For each cancer case, the following information was obtained: stage at diagnosis
(localized, regional, distant, unknown), sex (male, female, other), age at diagnosis, race/ethnicity
(NLW, black, Latino white [LW], Asian/Pacific Islander [API], other), and SES quintile (high,
mid-high, middle, mid-low, low). Age was divided into 5-year intervals. Race/ethnicity and
Spanish/Latino origin is reported to the CCR by hospitals and physician offices as documented in
medical records. The CCR provides SES based on census results of block level socioeconomic
characteristics from residence at diagnosis which is ranked by quintiles from low (SES=1) to
high (SES=5) (U.S. Census Bureau; American Community Survey). The 1990 census-based SES
was used for cancer cases diagnosed 1988-1995, the 2000 census-based SES was used for cases
during 1996-2005, and the SES based on the American Community Survey 2006-2010 for cases
during 2006-2014.
Time Periods
The period 1988-2014 was divided into two intervals (1988-2000 and 2001-2014) to
allow for observation of trends over time. This demarcation was selected as a chronological
midpoint that corresponded to emergence of an era with increased emphasis on AYA disparities
by the NCI, NCI NCTN groups, and advocacy organizations (Freyer et al., 2013; AYA Progress
Review Group, 2006; Smith et al., 2016; Weiss et al., 2015).
Survival Analyses
We calculated 5-year observed survival by time period and quantified the change
between the two time periods. Vital status was assessed through reporting institutions, and record
linkage with vital statistics, Social Security Administration, driver’s license information, and
credit card records. For deceased patients, survival time was measured in days from the date of
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
10
diagnosis to the date of death from any cause. Patients alive at the end of the study period
(December 31, 2014) were censored as of then or the date of last known previous contact. Five-
year observed survival is defined as the proportion of patients still alive five years after
diagnosis.
Absolute differences in sex-specific 5-year survival between 1988-2000 and 2001-2014
were calculated for all invasive cancers combined for all ages, including bladder cancer in situ
but excluding benign brain/central nervous system [CNS] (as this was not reportable until 2001),
for cases at 5-year age intervals. We then performed this comparison excluding KS (a human
immunodeficiency virus [HIV]/acquired immunodeficiency syndrome [AIDS]-related cancer).
Ratios of 5-year survival between the two time periods (5-year survival for 2001-2014/1988-
2000) were calculated.
Further analyses were performed among AYAs only. Site-specific 5-year survival for
AYAs was calculated using the non-parametric Kaplan-Meier survival function. Crude hazard
ratios (HRs) for death between the two time periods were calculated for each site and further
stratified by stage, sex, age, race/ethnicity, and SES (excluding benign brain/CNS since it was
not reportable until 2001 and thus only present in the second time period). Site-specific crude
HRs by time-period were then calculated within each subgroup, and then adjusted for stage, sex,
age, race/ethnicity and SES (aHRs) and 95%CIs were calculated (Altman & Bland, 2011).
Survival analyses and survival curves were constructed for each site stratified by time-period.
Survival differences between time periods were evaluated using the log-rank test.
Multivariable Cox proportional aHRs for death for the entire 1988-2014 time period were
calculated for each site by risk factors for stage, sex, age, race/ethnicity, and SES (including
benign brain/CNS from 2001-2014). Older and younger AYAs were defined as 25-34 years old
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
11
and 15-24 years old, respectively, for bone/soft tissue sarcoma, ALL, AML, Hodgkin lymphoma,
ovarian germ cell and testis (sites that have higher frequencies in younger AYAs). Older and
younger AYAs were defined as 35-39 years old and 15-34 years old, respectively, for all
remaining sites (with higher frequencies in older AYAs). To test for statistical differences in
aHRs over time, aHRs by site and subgroup were further stratified by time period (1988-2000
and 2001-2014), and interaction analyses by time period were performed. All statistical analyses
were carried out using SAS Version 9.4 (Cary, NC). All p-values were two-sided, with a
significance level set at p<0.05.
RESULTS
For 1988-2000 and 2001-2014, there were a total of 107,747 and 117,746 first cancers
diagnosed among AYAs California residents, respectively (Table 1). In the later time period, a
higher proportion of cases had localized disease (51.6% vs. 46.5%), were female (59.3% vs.
53.1%), LW (33.5% vs. 23.1%), younger (i.e., 15-29 years of age) (35.1% vs. 30.2%), and of
mid-low and low SES quintiles (37.6% vs. 35.1%). Site specific subgroup distribution and
frequency details are shown in Supplemental Table 1. A cancer site list with case counts for
“other” is provided in Supplemental Table 2.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
12
Table 1: Distribution of all AYA cancers by time period, tumor and patient characteristics,
California, 1988-2014.
1988-2000
n=107,747
2001-2014
n=117,746
P value
Cancer Site (%) Bone/Soft Tissue Sarcoma 2·4 2·7 <0·0001
Brain/CNS: Benign - 3·9
Brain/CNS: Invasive 4·2 4·1
Breast 14·1 13·8
Cervix 6·2 4·5
Colorectal 3·7 4·8
Kaposi Sarcoma 8·5 1·0
Kidney 1·1 2·1
Leukemia: ALL 1·3 1·8
Leukemia: AML 1·7 1·9
Leukemia: CML 0·9 0·9
Lip/Oral Cavity/Pharynx 1·6 1·6
Lung 1·8 1·3
Lymphoma: Hodgkin 5·0 5·1
Lymphoma: Non-Hodgkin 7·5 5·8
Melanoma 10·6 9·1
Ovary: Carcinoma 1·6 1·4
Ovary: Germ Cell 0·5 0·6
Stomach 1·1 1·1
Testis 7·5 8·5
Thyroid 7·8 12·4
Uterus 1·1 1·8
Other
a
9·8 9·7
Stage (%) Localized
Regional
Distant
In situ
Unknown
Localized
46·5 51·6 <0·0001
21·6 25·4
21·1
0·2
18·8
0·5
10·7 3·7
46·5 51·6
Sex (%) Male 46·9 40·7 <0·0001
Female 53·1 59·3
Other/Unknown 0·0 0·0
Age Group (%) 15-19 5·1 7·1 <0·0001
20-24 8·5 11·2
25-29 16·6 16·8
30-34 28·5 25·8
35-39 41·2 39·1
Race/Ethnicity
(%)
Asian/Pacific Islander 7·3 9·8 <0·0001
Black 6·9 5·7
Latino white 23·1 33·5
Non-Latino white 59·5 45·9
Other/Unknown 3·2 5·1
Socioeconomic
Status (%)
High 21·3 20·3 <0·0001
Mid-High 22·7 21·7
Middle 20·9 20·4
Mid-Low 18·5 19·4
Low 16·6 18·2
(a) Other indicates all non-categorized invasive cancers and benign intracranial tumors. See Supplemental Table 2 for cancer
sites included in other. 2% and 5·5% of Other cancers are in situ stage in 1988-2000 and 2001-2014, respectively.
CNS=central nervous system, ALL= acute lymphocytic leukemia, AML=acute myeloid leukemia, CML=chronic myeloid
leukemia.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
13
Overall AYA Survival Trends
To gain an overall perspective of survival trends, we first compared 5-year survival
improvements for AYAs to younger and older populations. For all cancers between 1988-2000
and 2001-2014, we found that survival improvement was at least as large among AYAs as in
younger children and older adults. For all cancers combined including KS, AYA males
demonstrated the largest survival improvement (Figure 1A). Among 30-34 year olds, 5-year
survival increased by 20.6% in males but only 4.2% in females, and among 35-39 year olds by
18.9% in males and 4.2% in females. Among males of all ages, survival improvement was
greatest for AYAs. By way of contrast, when KS was excluded, survival also increased for AYA
males, but not as dramatically (9.5% and 10.3% for the 30-34 and 35-39 year olds, respectively).
Excluding KS, between 1988-2000 and 2001-2014, AYAs demonstrated survival improvement
that was larger than younger children, but similar to older adults. Five-year survival rate ratios
for each 5-year age interval are presented in Supplemental Table 3.
Site and Demographic Subgroup-specific AYA Survival Trends
Given the heterogeneity of AYA cancer, we next examined changes in site- and
subgroup-specific AYA survival over time. For each cancer site, Table 2 displays the overall
crude and aHRs for death (adjusted for stage, sex, age, race/ethnicity, SES) comparing 2001-
2014 with 1988-2000. For all cancer sites combined, the overall aHR (0.70, 95%CI 0.69-0.71;
p<0.0001) indicated a lower risk for death in the later time period. We found that survival
improved for 15 of 22 cancer sites. There were no significant differences in survival between the
time periods for bone/STS, ovarian carcinoma, ovarian germ cell tumor, stomach cancer,
testicular cancer, thyroid cancer and uterine cancer. Sites showing the greatest improvement in
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
14
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
15
survival were KS (aHR 0.26, 95%CI 0.24-0.29; p<0.0001), chronic myeloid leukemia (CML,
aHR 0.33, 95%CI 0.28-0.39; p<0.0001), and non-Hodgkin lymphoma (NHL, aHR 0.38, 95%CI
0.36-0.41; p<0.0001) (Table 2, Figure 2).
There were no cancer sites that had significantly worsened survival after adjusting for
cancer and demographic factors. For demographic subgroups of AYAs, Table 2 also summarizes
the subgroup-specific crude HRs for death. Subgroups that showed worsening trends in survival
between the two time periods included black AYAs with bone/STS (HR 1.39, 95%CI 1.07-1.80;
p=0.013), 20-24 year old women with cervical cancer (HR 1.72, 95%CI 1.15-3.15; p=0.009), and
AYAs of low SES with cervical cancer (HR 1.16, 95%CI 1.02-1.33; p=0.027). The improvement
seen in survival of KS and NHL were more evident in those from higher SES groups compared
to the lowest SES group. In addition, survival improvements in invasive brain cancer, colorectal
cancer, melanoma, stomach, and testicular cancer were greater among NLW than among other
racial/ethnic groups (Table 2).
AYA Survival Disparities and Trends
We then evaluated whether tumor and host characteristics were associated with mortality
for each cancer site. Table 3 shows the site-specific aHRs for death (adjusted for stage, sex, age,
race/ethnicity and SES) over the entire 1988-2014 time period for each at-risk subgroup
compared to each indicated reference group. Interaction analyses between the two time periods
(1988-2000 and 2001-2014) are represented by superscripts to indicate if aHRs increased
(designated by
⋀
) or decreased (designated by
⋁
) between the two time periods (Table 3,
Supplemental Table 4).
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
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SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
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SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
18
Stage of disease remained the strongest predictor of mortality among AYAs (aHR distant
to localized disease for all cancers 6.32, 95%CI 6.20-6.45; p<0.0001) for every cancer site
except leukemias, where stage is not applicable. Further, aHRs for distant to localized disease
increased over time for most cancer sites. For all cancers from 1988-2014, males had an elevated
risk of death compared to females (aHR 1.47, 95%CI 1.44-1.49; p<0.0001); however, the aHR
for males decreased over the two time periods. By age, older AYAs had an increased risk of
death compared to younger AYAs (aHR 1.42, 95%CI 1.40-1.44; p<0.0001); this disparity also
decreased over time. For race/ethnicity, compared to NLWs, blacks had the highest risk of death
from all cancers combined (aHR 1.46, 95%CI 1.42-1.50; p<0.0001), a disparity present in almost
every cancer site, followed by APIs (aHR 1.12, 95%CI 1.09-1.15; p<0.0001) and LWs (aHR
1.06, 95%CI 1.06-1.08; p<0.0001). For every racial/ethnic group compared to NLWs, survival
disparities for all cancers combined worsened over time. For all cancers, AYA patients of lower
SES had an increased risk of death compared to higher SES (aHR 1.31, 95%CI 1.29-1.34;
p<0.0001); and like the racial/ethnic disparities, this aHR increased over time.
DISCUSSION
With landmark reports from the 1990s highlighting lower survival improvement for
AYAs relative to younger and older subgroups, the overall objective of this study was to provide
a more current and enriched understanding of AYA cancer survival disparities and trends. Using
California population-based data from 1988-2014, our study shows that AYAs have, in fact,
experienced more dramatic survival improvement than both younger and older patients. While
this improvement held true for multiple AYA cancers, it was particularly striking for HIV/AIDS-
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
19
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
20
related cancers following the introduction of combined anti-retroviral therapy (cART) in 1996
(International Collaboration on HIV and Cancer, 2000). At the same time, our study clearly
indicates that progress in AYA oncology has not been uniformly shared among all AYA subsets,
notably those diagnosed with certain types of cancer and with advanced stage disease, as well as
among racial/ethnic minorities and lower SES groups. Our results are important because they
reflect both gratifying progress resulting from nearly three decades of well-deserved emphasis on
AYA cancer, yet point toward remaining challenges involving cancer biology and therapeutics,
treatment delivery, and healthcare equity.
Our conclusions of recently improved AYA cancer survival are consistent with SEER-17
data from 2000-2009 that showed AYA survival to be equivalent or better to younger children
and older adults in virtually all cancer sites, with the exception of female breast cancer and
leukemias (Lewis et al., 2014). Our findings are also supported by a recent report evaluating
AYA survival trends using SEER-wide data from 1973-2009, which found that after excluding
HIV/AIDS-related cancers and the HIV/AIDS epidemic time-period, AYAs with cancer had (1)
the highest survival compared to other age groups; (2) consistently improving 5-year relative
survival trend over time; and (3) slightly lower survival improvement than in other ages due to a
higher baseline survival for AYAs rather than an absolute failure to improve (Liu et al.).
Compared to that report, our study found that AYAs, especially AYA males, displayed the
largest survival improvement. Rather than being contradictory, these findings reflect the different
years of inclusion for each study (1973-2009 for that study, 1988-2014 for ours) and the
temporal effect of the HIV/AIDS epidemic, including its containment in the later 1990s.
However, our data temper this optimistic picture of recent AYA trends in showing the
improvement in survival has not been shared by all AYAs equally, differentiated by site, stage
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
21
and sociodemographic characteristics. A few cancer sites have demonstrated dramatic survival
improvements over the two time periods. This is exemplified by KS and NHL, which have
benefited from therapeutic advances for HIV, and by CML, where tyrosine-kinase inhibitors
have been highly effective (International Collaboration on HIV and Cancer, 2000; Cheung et al.,
2005; Kantarjian et al., 2003; Wood & Harrington, 2005). In contrast, certain cancer sites have
not shown any survival improvement. While survival for certain sites is excellent and likely
nearing asymptotic levels (e.g., thyroid, testis, ovarian germ cell cancers), other sites (e.g.,
bone/STS, ALL, AML, lung cancer, stomach cancer) have considerable room for improvement.
For each cancer site, the strongest predictor of survival was cancer stage at diagnosis,
associated with up to a 33.9-fold increased risk of death among those with distant versus
localized disease. Of concern, this stage-related survival gap appears to be widening over time.
These findings suggest that research specifically focused on elucidating the tumor biology of
advanced stage disease and development of novel therapies has potential for substantial impact
on AYA survival outcomes. Because delayed diagnosis may account for at least some advanced
stage disease, efforts to improve early detection and timely treatment among AYAs remain
important (Herbert et al., 2018; Martin et al., 2007; Xu et al., 2015).
In addition to disease-specific factors, we also found that host factors contribute to the
likelihood of AYA cancer survival. Sex- and age-specific survival disparities, while present, are
improving over time. In contrast, survival disparities among some racial/ethnic minorities and
those of low SES have stagnated or worsened. These trends hold true in sites with a favorable
prognosis (testicular cancer, Hodgkin lymphoma [HL]) and in sites showing marked survival
gains (KS, NHL). Racial/ethnic- and SES-related survival disparities among AYAs have been
described in many common AYA cancer types, such as HL, NHL, testicular, thyroid, and breast
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
22
cancer (Derouen et al., 2013; DeRouen, Mujahid, Srinivas, & Keegan, 2016; Keegan et al., 2016;
Keegan et al., 2015; Kent et al., 2015). Troubling racial/ethnic survival trends over time have
also been reported for black patients with breast and other cancers, and for Latino children with
ALL (Aizer et al., 2014; Albain et al., 2009; Albano et al., 2007; Bristow et al., 2015; Bristow et
al., 2013; Caggiano, 2015; Chao, Chiu, Xu, & Cooper, 2015; Chien et al., 2005; Derouen et al.,
2013; DeRouen et al., 2016; Iqbal et al., 2015; Kabat, Ginsberg, Sparano, & Rohan, 2016;
Kadan-Lottick et al., 2003; Keegan et al., 2016; Keegan et al., 2015; Kent et al., 2015; Kent et
al., 2010; Kent, Sender, Largent, & Anton-Culver, 2009; Kish et al., 2014; Komenaka et al.,
2010; Li et al., 2003; J. Lin et al., 2015; S. S. Lin et al., 2002; Parise & Caggiano, 2016; Philips
et al., 2013; Shariff-Marco et al., 2015; Shariff-Marco et al., 2014; Tannenbaum, Koru-Sengul,
Zhao, Miao, & Byrne, 2014; Wang, Bhatia, Gomez, & Yasui, 2015). Although survival
differences by race/ethnicity and SES could be explained by differences in disease/host biology,
treatment response, adherence issues, or cultural influences on attitudes towards the medical
system, our study raises an overarching concern about the possibility of a systemic inequality in
cancer care access and delivery for AYAs, a population known to be at risk for lacking adequate
health insurance (Adams, Newacheck, Park, Brindis, & Irwin, 2007).
Our study offers several strengths including the large, robust, and diverse registry-based
dataset of the CCR allowing for site-specific survival adjusted for demographic factors as well as
racial/ethnic and socioeconomic specific analyses; incorporation of differential survival over two
time periods permitting a demonstration of a trajectory of survival disparities; and the ability to
have reliable 5-year vital status in both time-period groups. However, there are also some
weaknesses inherent to registry-based research. These include possible misclassification of stage
or race/ethnicity, which are reported by the site; misclassification of SES, which is a block-level
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
23
measure based on census data using the address provided from medical records; the lack of
cause-specific mortality reporting; and the potential for misclassification of vital status. Despite
these limitations, SEER registries including the CCR data utilized in this study capture high
quality data, adhere to strict quality control standards, and are used as benchmarks for registry-
based data worldwide.
Even though we have demonstrated that the AYA survival improvement gap has
diminished after effective management of HIV/AIDS-related cancers and increased focus on
AYA care and survival, AYAs remain a vulnerable population with unique challenges related to
their life stage (AYA Progress Review Group, 2006). Future directions include in-depth analyses
of site- and subgroup-specific survival trends to explain continued disparities and lack of
survival improvement, and to determine effective interventions for improving outcomes in
certain cancer sites, for late stage disease, and among socio-demographically disadvantaged
subgroups of patients.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
24
SUPPLEMENTAL MATERIALS:
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
25
Supplemental Table 2: “Other” cancer frequency by primary cancer site and time period, AYA,
California, 1988-2014.
Site
Group
Primary Site Number of cases
1988-
2000
2001-2014
1.4 Other and unspecified leukemia 454 551
4.2 Chondrosarcoma 334 314
4.4 Other specified and unspecified bone tumors 148 204
5.1 Fibromatous neoplasms 1,414 1,265
5.2 Rhabdomyosarcoma 211 275
5.3.2 Unspecified soft tissue sarcoma 353 516
6.2.1 Germ cell and trophoblastic neoplasms of nongonadal site -
Intracranial: invasive (behavior code 3) 181 213
6.2.1 Germ cell and trophoblastic neoplasms of nongonadal site -
Intracranial: benign (behavior codes 0,1) - 34
6.2.2 Other nongonadal 662 633
7.2 Skin carcinomas 133 153
8.2.1 Nasopharyngeal carcinoma 494 517
8.2.3 Nasal cavity, mid ear, sinus, larynx, ill-defined head/neck 311 294
8.5.2 Carcinoma of bladder 1,063 893
8.5.5 Carcinoma of other and ill-defined sites, genitourinary tract 481 506
8.6.3 Carcinoma of liver and intrahepatic bile ducts 587 688
8.6.4 Carcinoma of pancreas 456 624
8.6.5 Carcinoma other and ill-defined sites, gastrointestinal tract 500 646
8.7.1 Adrenocortical carcinoma 89 89
8.7.2 Carcinoma of other and ill-defined sites, NOS 1,114 837
9.1.1 Wilms tumor 29 26
9.1.2 Neuroblastoma 27 32
9.1.3 Other pediatric and embryonal tumors, NOS 86 95
9.2.1 Paraganglioma and glomus tumors 60 81
9.2.2 Other specified gonadal tumors 106 160
9.2.3 Myeloma, mast cell, miscellaneous lymphoreticular neoplasm,
NOS 381 508
9.2.4 Other specified neoplasms, NOS 511 725
10 Unspecified Malignant Neoplasms 374 538
99 Unknown 2 3
Total 10,561 11,424
NOS=not otherwise specified.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
26
Supplemental Table 3: Ratio of 5-year survival by age group, California, 2001-2014:1988-2000.
Age
Group
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+
All Invasive Cancer: Male
Ratio of
Survival*
1·07 1·06 1·06 1·08 1·07 1·25 1·37 1·36 1·28 1·24 1·20 1·17 1·16 1·04
Lower
CL
1·06
1·05
1·06
1·07
1·07
1·25
1·37
1·36
1·28
1·24
1·20
1·17
1·16
1·04
Upper
CL
1·09
1·09
1·10
1·11
1·09
1·27
1·39
1·37
1·30
1·26
1·21
1·18
1·17
1·04
All Invasive Cancer: Female
Ratio of
Survival*
1·07 1·08 1·04 1·04 1·02 1·04 1·05 1·05 1·07 1·06 1·08 1·10 1·11 1·02
Lower
CL
1·07 1·08 1·04 1·04 1·02 1·04 1·05 1·05 1·07 1·06 1·08 1·10 1·11 1·02
Upper
CL
1·09 1·11 1·08 1·07 1·04 1·06 1·06 1·06 1·08 1·07 1·09 1·11 1·12 1·02
All Invasive Cancer, Non-KS: Male
Ratio of
Survival*
1·06 1·06 1·06 1·08 1·04 1·07 1·14 1·17 1·18 1·20 1·19 1·17 1·16 1·04
Lower
CL
1·06 1·06 1·06 1·07 1·04 1·07 1·14 1·17 1·18 1·20 1·19 1·17 1·16 1·04
Upper
CL
1·09 1·09 1·10 1·10 1·06 1·09 1·16 1·18 1·20 1·21 1·20 1·18 1·17 1·04
All Invasive Cancer, Non-KS: Female
Ratio of
Survival*
1·07 1·08 1·04 1·04 1·02 1·04 1·05 1·05 1·07 1·06 1·08 1·10 1·11 1·02
Lower
CL
1·07 1·08 1·04 1·04 1·02 1·04 1·05 1·05 1·07 1·06 1·08 1·10 1·11 1·02
Upper
CL
1·09 1·11 1·08 1·07 1·04 1·06 1·06 1·06 1·08 1·07 1·09 1·11 1·12 1·02
CL=confidence limit, upper and lower defined at 95%. Confidence limits calculated using the delta method of variance. KS=Kaposi Sarcoma.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
27
Supplemental Table 4: Adjusted HRs (aHRs) and 95% Confidence Intervals for Risk Groups of AYA Cancer
Diagnosed by Patient and Tumor Characteristics, California, 1988-2014.
Cancer
Site
Year Risk Factor Reference Group Adjusted Model Kaplan Meier Survival Curve*
1988-2000
2001-2014
aHR 95%CI Interaction
p value
All Cancer Combined
1988-2000 Distant Localized 5·51 5·37 5·64 <0·0001
2001-2014 Distant Localized 7·98 7·72 8·26
1988-2000 Male Female 1·53 1·50 1·56 <0·0001
2001-2014 Male Female 1·31 1·27 1·34
1988-2000 35-39 15-34 1·44 1·41 1·47 0·002
2001-2014 35-39 15-34 1·37 1·34 1·41
1988-2000 API NLW 1·09 1·06 1·13 <0·0001
2001-2014 API NLW 1·31 1·26 1·37
1988-2000 Black NLW 1·44 1·39 1·49 0·0005
2001-2014 Black NLW 1·59 1·52 1·67
1988-2000 LW NLW 1·06 1·04 1·09 <0·0001
2001-2014 LW NLW 1·23 1·20 1·27
1988-2000 Low/MidLow SES High/MidHigh SES 1·24 1·21 1·26 <0·0001
2001-2014 Low/MidLow SES High/MidHigh SES 1·47 1·43 1·52
Bone/Soft Tissue Sarcoma
1988-2000 Distant Localized 7·01 6·06 8·11 0·66
2001-2014 Distant Localized 7·34 6·35 8·48
1988-2000 Male Female 1·12 1·00 1·25 0·54
2001-2014 Male Female 1·17 1·05 1·32
1988-2000 25-39 15-24 1·12 1·00 1·25 0·55
2001-2014 25-39 15-24 1·17 1·05 1·31
1988-2000 API NLW 1·15 0·93 1·42 0·22
2001-2014 API NLW 1·38 1·13 1·68
1988-2000 Black NLW 1·24 1·03 1·51 0·09
2001-2014 Black NLW 1·59 1·29 1·95
1988-2000 LW NLW 1·22 1·07 1·39 0·82
2001-2014 LW NLW 1·25 1·09 1·42
1988-2000 Low/MidLow SES High/MidHigh SES 1·07 0·94 1·22 0·56
2001-2014 Low/MidLow SES High/MidHigh SES 1·13 0·99 1·29
Brain and Central Nervous System:
Invasive
1988-2000 Distant Localized 1·88 1·50 2·37 0·44
2001-2014 Distant Localized 2·15 1·69 2·73
1988-2000 Male Female 1·27 1·18 1·37 0·53
2001-2014 Male Female 1·32 1·20 1·45
1988-2000 35-39 15-34 1·40 1·29 1·51 0·60
2001-2014 35-39 15-34 1·35 1·22 1·49
1988-2000 API NLW 1·17 1·01 1·35 0·22
2001-2014 API NLW 1·33 1·13 1·57
1988-2000 Black NLW 1·06 0·89 1·25 0·53
2001-2014 Black NLW 1·15 0·93 1·42
1988-2000 LW NLW 1·00 0·91 1·10 0·046
2001-2014 LW NLW 1·15 1·03 1·28
1988-2000 Low/MidLow SES High/MidHigh SES 1·20 1·10 1·31 0·83
2001-2014 Low/MidLow SES High/MidHigh SES 1·19 1·07 1·32
Breast
1988-2000 Distant Localized 11·29 10·28 12·40 0·005
2001-2014 Distant Localized 13·80 12·42 15·33
1988-2000 Male Female 1·08 0·66 1·77 0·58
2001-2014 Male Female 0·81 0·34 1·96
1988-2000 35-39 15-34 0·93 0·88 0·97 0·70
2001-2014 35-39 15-34 0·94 0·88 1·01
1988-2000 API NLW 0·92 0·84 1·00 0·67
2001-2014 API NLW 0·95 0·84 1·06
1988-2000 Black NLW 1·41 1·31 1·52 0·06
2001-2014 Black NLW 1·60 1·44 1·79
1988-2000 LW NLW 0·99 0·93 1·06 0·10
2001-2014 LW NLW 1·08 0·99 1·17
1988-2000 Low/MidLow SES High/MidHigh SES 1·26 1·19 1·33 <0·0001
2001-2014 Low/MidLow SES High/MidHigh SES 1·55 1·43 1·68
Cervix
1988-2000 Distant Localized 17·26 14·85 20·06 0·02
2001-2014 Distant Localized 22·90 19·22 27·28
1988-2000 Male Female - - - -
2001-2014 Male Female - - -
1988-2000 35-39 15-34 1·14 1·04 1·25 0·29
2001-2014 35-39 15-34 1·05 0·93 1·18
1988-2000 API NLW 1·19 0·98 1·46 0·47
2001-2014 API NLW 1·06 0·82 1·36
1988-2000 Black NLW 1·64 1·40 1·92 0·79
2001-2014 Black NLW 1·70 1·36 2·12
1988-2000 LW NLW 1·01 0·91 1·13 0·99
2001-2014 LW NLW 1·01 0·88 1·17
1988-2000 Low/MidLow SES High/MidHigh SES 1·23 1·09 1·38 0·10
2001-2014 Low/MidLow SES High/MidHigh SES 1·43 1·23 1·66
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
28
Supplemental Table 4 (cont’d): Adjusted HRs (aHRs) and 95% Confidence Intervals for Risk Groups of AYA
Cancer Diagnosed by Patient and Tumor Characteristics, California, 1988-2014.
Cancer
Site
Year Risk Factor Reference Group Adjusted Model Kaplan Meier Survival Curve*
1988-2000
2001-2014
aHR 95%CI Interaction
p value
Colorectal
1988-2000 Distant Localized 12·11 10·59 13·84 0·02
2001-2014 Distant Localized 15·66 13·33 18·39
1988-2000 Male Female 1·36 1·24 1·48 0·72
2001-2014 Male Female 1·33 1·21 1·45
1988-2000 35-39 15-34 1·02 0·94 1·12 0·32
2001-2014 35-39 15-34 0·96 0·88 1·05
1988-2000 API NLW 0·91 0·79 1·05 0·04
2001-2014 API NLW 1·12 0·97 1·28
1988-2000 Black NLW 1·08 0·93 1·24 0·27
2001-2014 Black NLW 1·22 1·03 1·45
1988-2000 LW NLW 0·90 0·81 1·01 0·18
2001-2014 LW NLW 1·00 0·90 1·11
1988-2000 Low/MidLow SES High/MidHigh SES 1·29 1·17 1·43 0·03
2001-2014 Low/MidLow SES High/MidHigh SES 1·51 1·35 1·67
Kaposi Sarcoma
1988-2000 Distant Localized 1·22 1·14 1·31 0·07
2001-2014 Distant Localized 1·88 1·18 2·98
1988-2000 Male Female 1·41 1·11 1·79 0·01
2001-2014 Male Female 0·60 0·33 1·10
1988-2000 35-39 15-34 1·02 0·98 1·07 0·052
2001-2014 35-39 15-34 0·84 0·69 1·02
1988-2000 API NLW 1·07 0·90 1·28 0·48
2001-2014 API NLW 0·84 0·44 1·60
1988-2000 Black NLW 1·14 1·05 1·22 0·008
2001-2014 Black NLW 1·65 1·26 2·15
1988-2000 LW NLW 0·97 0·92 1·03 0·16
2001-2014 LW NLW 1·15 0·91 1·46
1988-2000 Low/MidLow SES High/MidHigh SES 1·07 1·02 1·13 0·002
2001-2014 Low/MidLow SES High/MidHigh SES 1·56 1·23 1·98
Kidney
1988-2000 Distant Localized 27·53 21·78 34·80 0·014
2001-2014 Distant Localized 41·55 32·31 53·43
1988-2000 Male Female 1·36 1·12 1·66 0·56
2001-2014 Male Female 1·24 0·99 1·56
1988-2000 35-39 15-34 1·04 0·86 1·26 0·46
2001-2014 35-39 15-34 0·93 0·76 1·15
1988-2000 API NLW 0·96 0·63 1·47 0·17
2001-2014 API NLW 1·44 0·97 2·12
1988-2000 Black NLW 1·26 0·95 1·66 0·048
2001-2014 Black NLW 1·90 1·39 2·60
1988-2000 LW NLW 1·03 0·81 1·31 0·81
2001-2014 LW NLW 0·99 0·77 1·28
1988-2000 Low/MidLow SES High/MidHigh SES 1·27 1·02 1·58 0·96
2001-2014 Low/MidLow SES High/MidHigh SES 1·28 0·99 1·64
Lip, Oral Cavity, and Pharynx
1988-2000 Distant Localized 6·08 4·63 8·02 0·57
2001-2014 Distant Localized 6·84 5·03 9·31
1988-2000 Male Female 1·56 1·31 1·86 0·26
2001-2014 Male Female 1·33 1·05 1·67
1988-2000 35-39 15-34 1·64 1·39 1·94 0·02
2001-2014 35-39 15-34 1·19 0·95 1·48
1988-2000 API NLW 1·25 0·95 1·65 0·16
2001-2014 API NLW 0·91 0·63 1·30
1988-2000 Black NLW 1·76 1·36 2·27 0·005
2001-2014 Black NLW 0·86 0·55 1·33
1988-2000 LW NLW 0·90 0·70 1·15 0·71
2001-2014 LW NLW 0·84 0·64 1·10
1988-2000 Low/MidLow SES High/MidHigh SES 1·30 1·07 1·56 0·40
2001-2014 Low/MidLow SES High/MidHigh SES 1·48 1·14 1·91
Leukemia: ALL
1988-2000 Distant Localized - - - -
2001-2014 Distant Localized - - -
1988-2000 Male Female 1·11 0·96 1·28 0·81
2001-2014 Male Female 1·08 0·95 1·23
1988-2000 25-39 15-24 1·61 1·40 1·84 0·01
2001-2014 25-39 15-24 2·03 1·79 2·30
1988-2000 API NLW 1·12 0·85 1·47 0·61
2001-2014 API NLW 1·24 0·95 1·62
1988-2000 Black NLW 1·65 1·23 2·22 0·82
2001-2014 Black NLW 1·74 1·25 2·42
1988-2000 LW NLW 1·24 1·06 1·45 0·28
2001-2014 LW NLW 1·40 1·19 1·64
1988-2000 Low/MidLow SES High/MidHigh SES 1·38 1·17 1·62 0·16
2001-2014 Low/MidLow SES High/MidHigh SES 1·18 1·01 1·39
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
29
Supplemental Table 4 (cont’d): Adjusted HRs (aHRs) and 95% Confidence Intervals for Risk Groups of AYA
Cancer Diagnosed by Patient and Tumor Characteristics, California, 1988-2014.
Cancer
Site
Year Risk Factor Reference Group Adjusted Model Kaplan Meier Survival Curve*
1988-2000
2001-2014
aHR 95%CI Interaction
p value
Leukemia: AML
1988-2000 Distant Localized - - - -
2001-2014 Distant Localized - - -
1988-2000 Male Female 1·10 0·98 1·23 0·21
2001-2014 Male Female 1·22 1·08 1·38
1988-2000 25-39 15-24 1·19 1·05 1·35 0·61
2001-2014 25-39 15-24 1·14 1·00 1·31
1988-2000 API NLW 1·05 0·88 1·26 0·56
2001-2014 API NLW 0·97 0·79 1·19
1988-2000 Black NLW 1·19 0·96 1·47 0·82
2001-2014 Black NLW 1·23 0·95 1·60
1988-2000 LW NLW 1·00 0·87 1·14 0·58
2001-2014 LW NLW 1·05 0·91 1·21
1988-2000 Low/MidLow SES High/MidHigh SES 1·01 0·88 1·15 0·009
2001-2014 Low/MidLow SES High/MidHigh SES 1·30 1·12 1·50
Leukemia: CML
1988-2000 Distant Localized - - - -
2001-2014 Distant Localized - - -
1988-2000 Male Female 1·08 0·92 1·28 0·01
2001-2014 Male Female 1·77 1·26 2·50
1988-2000 35-39 15-34 1·00 0·85 1·19 >0.99
2001-2014 35-39 15-34 1·00 0·73 1·37
1988-2000 API NLW 0·90 0·68 1·18 0·43
2001-2014 API NLW 0·70 0·40 1·23
1988-2000 Black NLW 1·13 0·85 1·50 0·09
2001-2014 Black NLW 1·83 1·12 2·99
1988-2000 LW NLW 1·02 0·84 1·23 0·80
2001-2014 LW NLW 1·07 0·75 1·51
1988-2000 Low/MidLow SES High/MidHigh SES 1·52 1·25 1·86 0·85
2001-2014 Low/MidLow SES High/MidHigh SES 1·47 1·05 2·05
Lung
1988-2000 Distant Localized 11·75 9·56 14·43 0·04
2001-2014 Distant Localized 17·37 12·54 24·06
1988-2000 Male Female 1·08 0·98 1·20 0·04
2001-2014 Male Female 1·28 1·13 1·46
1988-2000 35-39 15-34 1·12 1·00 1·26 0·13
2001-2014 35-39 15-34 1·29 1·12 1·48
1988-2000 API NLW 0·90 0·76 1·07 0·72
2001-2014 API NLW 0·86 0·73 1·02
1988-2000 Black NLW 0·96 0·82 1·11 0·70
2001-2014 Black NLW 1·01 0·79 1·30
1988-2000 LW NLW 0·98 0·84 1·14 0·06
2001-2014 LW NLW 0·79 0·67 0·94
1988-2000 Low/MidLow SES High/MidHigh SES 1·17 1·04 1·32 0·06
2001-2014 Low/MidLow SES High/MidHigh SES 1·41 1·21 1·63
Lymphoma: Hodgkin
1988-2000 Distant Localized 1·95 1·63 2·32 0·03
2001-2014 Distant Localized 3·06 2·11 4·45
1988-2000 Male Female 1·46 1·30 1·63 0·67
2001-2014 Male Female 1·39 1·16 1·67
1988-2000 25-39 15-24 1·53 1·35 1·72 0·08
2001-2014 25-39 15-24 1·25 1·04 1·51
1988-2000 API NLW 0·98 0·72 1·33 0·03
2001-2014 API NLW 1·61 1·15 2·26
1988-2000 Black NLW 1·48 1·23 1·79 0·30
2001-2014 Black NLW 1·78 1·33 2·37
1988-2000 LW NLW 1·14 0·98 1·32 0·10
2001-2014 LW NLW 1·40 1·13 1·73
1988-2000 Low/MidLow SES High/MidHigh SES 1·45 1·27 1·65 0·30
2001-2014 Low/MidLow SES High/MidHigh SES 1·65 1·33 2·04
Lymphoma: Non-Hodgkin
1988-2000 Distant Localized 1·42 1·33 1·52 <0·0001
2001-2014 Distant Localized 3·03 2·63 3·48
1988-2000 Male Female 2·47 2·29 2·66 <0·0001
2001-2014 Male Female 1·56 1·40 1·75
1988-2000 35-39 15-34 1·15 1·09 1·22 0·82
2001-2014 35-39 15-34 1·14 1·03 1·26
1988-2000 API NLW 0·67 0·58 0·77 <0·0001
2001-2014 API NLW 1·11 0·92 1·35
1988-2000 Black NLW 1·13 1·02 1·24 0·002
2001-2014 Black NLW 1·54 1·29 1·83
1988-2000 LW NLW 1·09 1·01 1·17 <0·0001
2001-2014 LW NLW 1·47 1·31 1·65
1988-2000 Low/MidLow SES High/MidHigh SES 1·14 1·06 1·22 <0·0001
2001-2014 Low/MidLow SES High/MidHigh SES 1·77 1·57 2·00
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
30
Supplemental Table 4 (cont’d): Adjusted HRs (aHRs) and 95% Confidence Intervals for Risk Groups of AYA
Cancer Diagnosed by Patient and Tumor Characteristics, California, 1988-2014.
Cancer
Site
Year Risk Factor Reference Group Adjusted Model Kaplan Meier Survival Curve*
1988-2000
2001-2014
aHR 95%CI Interaction
p value
Melanoma
1988-2000 Distant Localized 23·75 20·70 27·24 <0·0001
2001-2014 Distant Localized 53·16 44·81 63·06
1988-2000 Male Female 1·67 1·53 1·83 0·61
2001-2014 Male Female 1·74 1·52 2·00
1988-2000 35-39 15-34 1·24 1·13 1·35 0·14
2001-2014 35-39 15-34 1·09 0·96 1·25
1988-2000 API NLW 1·79 1·23 2·60 0·89
2001-2014 API NLW 1·86 1·18 2·94
1988-2000 Black NLW 2·13 1·32 3·46 0·008
2001-2014 Black NLW 0·60 0·27 1·35
1988-2000 LW NLW 0·95 0·81 1·11 0·11
2001-2014 LW NLW 1·16 0·96 1·41
1988-2000 Low/MidLow SES High/MidHigh SES 1·59 1·43 1·76 0·45
2001-2014 Low/MidLow SES High/MidHigh SES 1·71 1·46 2·00
Ovary: Carcinoma
1988-2000 Distant Localized 7·39 5·95 9·18 0·14
2001-2014 Distant Localized 9·70 7·21 13·05
1988-2000 Male Female - - - -
2001-2014 Male Female - - -
1988-2000 35-39 15-34 1·18 1·02 1·37 0·46
2001-2014 35-39 15-34 1·08 0·90 1·29
1988-2000 API NLW 1·21 0·96 1·52 0·90
2001-2014 API NLW 1·18 0·89 1·56
1988-2000 Black NLW 1·36 0·99 1·87 0·74
2001-2014 Black NLW 1·26 0·86 1·83
1988-2000 LW NLW 1·08 0·90 1·31 0·97
2001-2014 LW NLW 1·08 0·87 1·33
1988-2000 Low/MidLow SES High/MidHigh SES 1·13 0·95 1·34 0·88
2001-2014 Low/MidLow SES High/MidHigh SES 1·15 0·93 1·42
Ovary: Germ Cell
1988-2000 Distant Localized 4·43 2·30 8·54 0·53
2001-2014 Distant Localized 6·26 2·69 14·57
1988-2000 Male Female - - - -
2001-2014 Male Female - - -
1988-2000 25-39 15-24 1·59 0·88 2·90 0·32
2001-2014 25-39 15-24 2·64 1·19 5·86
1988-2000 API NLW 1·36 0·52 3·53 0·10
2001-2014 API NLW 0·20 0·02 1·58
1988-2000 Black NLW 1·83 0·72 4·65 0·51
2001-2014 Black NLW 1·00 0·21 4·76
1988-2000 LW NLW 1·19 0·57 2·50 0·68
2001-2014 LW NLW 0·95 0·40 2·24
1988-2000 Low/MidLow SES High/MidHigh SES 1·95 0·91 4·19 0·59
2001-2014 Low/MidLow SES High/MidHigh SES 1·42 0·56 3·61
Stomach
1988-2000 Distant Localized 10·18 7·48 13·84 0·44
2001-2014 Distant Localized 12·17 8·71 17·01
1988-2000 Male Female 1·11 0·98 1·26 0·54
2001-2014 Male Female 1·05 0·92 1·19
1988-2000 35-39 15-34 1·00 0·88 1·14 0·70
2001-2014 35-39 15-34 0·97 0·85 1·10
1988-2000 API NLW 0·92 0·76 1·11 0·52
2001-2014 API NLW 1·01 0·81 1·26
1988-2000 Black NLW 1·18 0·93 1·50 0·95
2001-2014 Black NLW 1·17 0·82 1·65
1988-2000 LW NLW 0·88 0·74 1·04 0·003
2001-2014 LW NLW 1·26 1·05 1·50
1988-2000 Low/MidLow SES High/MidHigh SES 0·99 0·85 1·17 0·27
2001-2014 Low/MidLow SES High/MidHigh SES 1·12 0·96 1·30
Testis
1988-2000 Distant Localized 5·68 4·96 6·50 <0·0001
2001-2014 Distant Localized 13·53 11·20 16·34
1988-2000 Male Female - - - -
2001-2014 Male Female - - -
1988-2000 25-39 15-24 1·47 1·26 1·70 0·001
2001-2014 25-39 15-24 1·01 0·86 1·19
1988-2000 API NLW 1·42 1·00 2·01 0·43
2001-2014 API NLW 1·75 1·19 2·57
1988-2000 Black NLW 1·24 0·87 1·78 0·02
2001-2014 Black NLW 2·32 1·53 3·51
1988-2000 LW NLW 1·15 1·00 1·32 0·003
2001-2014 LW NLW 1·59 1·33 1·89
1988-2000 Low/MidLow SES High/MidHigh SES 1·49 1·30 1·71 0·44
2001-2014 Low/MidLow SES High/MidHigh SES 1·63 1·35 1·97
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
31
Supplemental Table 4 (cont’d): Adjusted HRs (aHRs) and 95% Confidence Intervals for Risk Groups of AYA
Cancer Diagnosed by Patient and Tumor Characteristics, California, 1988-2014.
Cancer
Site
Year Risk Factor Reference Group Adjusted Model Kaplan Meier Survival Curve*
1988-2000
2001-2014
aHR 95%CI Interaction
p value
Thyroid
1988-2000 Distant Localized 4·01 3·01 5·34 0·004
2001-2014 Distant Localized 8·01 5·49 11·69
1988-2000 Male Female 2·30 1·91 2·78 0·21
2001-2014 Male Female 2·85 2·16 3·77
1988-2000 35-39 15-34 1·88 1·57 2·25 0·16
2001-2014 35-39 15-34 1·49 1·13 1·96
1988-2000 API NLW 0·80 0·59 1·10 0·79
2001-2014 API NLW 0·86 0·55 1·35
1988-2000 Black NLW 1·03 0·65 1·63 0·99
2001-2014 Black NLW 1·02 0·50 2·11
1988-2000 LW NLW 0·95 0·76 1·18 >0.99
2001-2014 LW NLW 0·95 0·70 1·29
1988-2000 Low/MidLow SES High/MidHigh SES 1·84 1·49 2·28 0·81
2001-2014 Low/MidLow SES High/MidHigh SES 1·93 1·41 2·64
Uterus
1988-2000 Distant Localized 15·96 11·02 23·13 0·04
2001-2014 Distant Localized 27·62 19·09 39·95
1988-2000 Male Female - - - -
2001-2014 Male Female - - -
1988-2000 35-39 15-34 1·57 1·19 2·08 0·08
2001-2014 35-39 15-34 1·08 0·80 1·47
1988-2000 API NLW 0·94 0·63 1·41 0·14
2001-2014 API NLW 1·47 0·96 2·25
1988-2000 Black NLW 1·72 0·97 3·07 0·81
2001-2014 Black NLW 1·56 0·85 2·84
1988-2000 LW NLW 0·89 0·65 1·22 0·90
2001-2014 LW NLW 0·92 0·62 1·34
1988-2000 Low/MidLow SES High/MidHigh SES 1·27 0·94 1·72 0·68
2001-2014 Low/MidLow SES High/MidHigh SES 1·15 0·80 1·67
Other
1988-2000 Distant Localized 6·03 5·56 6·55 0·81
2001-2014 Distant Localized 5·94 5·38 6·55
1988-2000 Male Female 1·28 1·21 1·35 0·58
2001-2014 Male Female 1·31 1·23 1·40
1988-2000 35-39 15-34 1·46 1·38 1·55 <0·0001
2001-2014 35-39 15-34 1·15 1·08 1·22
1988-2000 API NLW 1·34 1·23 1·46 0·03
2001-2014 API NLW 1·17 1·06 1·29
1988-2000 Black NLW 1·25 1·14 1·37 0·36
2001-2014 Black NLW 1·17 1·04 1·31
1988-2000 LW NLW 1·12 1·04 1·20 0·78
2001-2014 LW NLW 1·14 1·05 1·23
1988-2000 Low/MidLow SES High/MidHigh SES 1·32 1·24 1·41 0·99
2001-2014 Low/MidLow SES High/MidHigh SES 1·32 1·22 1·42
Interaction p value testing for interaction of time period. *All survival curves statistically significant by LRT with alpha set at 0·05 except for the
following sites: cervix, colorectal, lip/oral cavity/pharynx, ovary: carcinoma, ovary: germ cell, stomach, testis, thyroid, uterus. Bolded values
indicate statistically significant values. aHR=adjusted hazard ratio, adjusted for all other factors in the model. 95%CI=95% confidence interval.
API=Asian/Pacific Islander, NLW=non-Latino white, LW=Latino white, SES=socioeconomic status, CNS=central nervous system, ALL= acute
lymphocytic leukemia, AML=acute myeloid leukemia, CML=chronic myeloid leukemia.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
32
Chapter Two:
Obesity and Risk for Second Malignant Neoplasms in Childhood Cancer Survivors: A California
Cancer Registry-based Case-Control Study
ABSTRACT
OBJECTIVE: To determine if obesity during childhood cancer treatment increases risk for
developing second malignant neoplasms (SMNs).
METHODS: In this case-control study, cases (with SMN) and controls were selected from the
Los Angeles Cancer Surveillance Program/California Cancer Registry and had a primary cancer
diagnosis when <21 years old at Children’s Hospital Los Angeles (CHLA) between 1988-2014.
Controls (without SMN) were matched 3:1 to cases (with SMN) at the registry level by sex, age
at diagnosis, primary cancer diagnosis, stage, radiation exposure, and minimum follow-up time.
Medical records were abstracted for cancer treatment exposures, underlying cancer
predisposition syndrome, and height/weight at initial diagnosis, end of therapy (EOT), and
follow-up. BMI, BMI Z-score, and BMI category (normal/underweight <85%, overweight
≥85%, obese≥95%) were determined. Conditional logistic regression was performed to assess
the independent effect of obesity on development of SMN.
RESULTS: 59 cases and 130 matched controls were included. In univariate analysis, obesity and
higher BMI Z-score were associated with development of SMN: obese vs. normal at diagnosis
odds ratio (OR) 2.48, 95%CI 1.05-5.88, p=0.038, BMI Z-score at diagnosis OR 1.29, 95%CI
1.01-1.65, p=0.042, obese at diagnosis and EOT vs. normal at both time points OR 4.26, 95%CI
1.35-13.18). In multivariable analyses after controlling for treatment related exposures, the
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
33
elevated risk persisted, however was statistically significant only for patients who were obese at
both diagnosis and EOT (adjusted OR 3.56, 95%CI 1.03-12.30, p=0.045).
CONCLUSIONS: Obesity during cancer treatment appears to increase the risk of SMNs in
pediatric cancer survivors. More research is needed to confirm these findings and to identify
effective interventions in order to optimize health and prevent secondary health effects, including
SMNs, in cancer survivors.
INTRODUCTION
Because long-term survival for children and adolescents treated for cancer now exceeds
80% (National Cancer Institute, 1975-2004), late effects of cancer treatment have assumed great
importance for this growing population. Among these, subsequent malignant neoplasms (SMNs)
lead to more deaths among 25-year survivors of cancer than any other cause (Mertens et al.,
2008). Compared to development of first cancers among the general population, survivors of
childhood cancer have a six-fold higher risk of developing secondary cancers, with a 30-year
cumulative incidence of up to 9.3% (Curtis et al., 2006; Meadows et al., 2009). Known risk
factors for SMNs include younger age at primary cancer diagnosis, female sex, longer follow-up
time, primary cancer type, genetic predisposition, and exposure to alkylators, anthracyclines,
epipodophyllotoxins, and ionizing radiation (Neglia et al., 2001; Ng, Kenney, Gilbert, & Travis,
2010).
Another potential contributor to SMNs is obesity, a condition that has garnered
substantial attention for increasing the risk for developing primary cancer and certain adverse
outcomes. Among adults, obesity is associated with an increased risk for developing primary
breast, ovarian, endometrial, kidney, and colorectal cancer (Bandera et al., 2016; Brinton et al.,
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
34
2007; Chen et al., 2016; Feola et al., 2016; Golabek et al., 2016; Lee, Keum, & Giovannucci,
2016; Renehan, Tyson, Egger, Heller, & Zwahlen, 2008). Adult and pediatric cancer patients
with increased body mass index (BMI) demonstrate inferior outcomes (including resistance to
treatment, chemotherapy toxicity, cancer relapse, and overall survival) compared to cancer
patients with normal BMI (Amankwah, Saenz, Hale, & Brown, 2016; Karatas et al., 2016; Orgel
et al., 2016; E. Orgel et al., 2014; E Orgel et al., 2014). Several of mechanisms have been
proposed to explain how obesity and adipose dysregulation may create a tumor
microenvironment that confers chemoprotection and promotes cancer cell growth. These include
hormonal changes, pro-inflammatory states, and chemotherapy sequestration (Deng, Lyon,
Bergin, Caligiuri, & Hsueh, 2016; Howe, Subbaramaiah, Hudis, & Dannenberg, 2013; Iyengar,
Hudis, & Dannenberg, 2015; Kolb, Sutterwala, & Zhang, 2016; Sheng & Mittelman, 2014;
Wright & Simone, 2016). These observations suggest biologic plausibility could exist for obesity
influencing the development of SMNs, perhaps in combination with the known oncogenic effects
of some cancer treatments. With obesity affecting up to 15-30% of childhood cancer survivors
(Brown et al., 2016b; M. H. Lin, Wood, Mittelman, & Freyer, 2015; Meacham et al., 2005), it
becomes important to evaluate this as a candidate risk factor for developing SMNs, especially as
one that is potentially modifiable.
In light of the above, we undertook an exploratory study to evaluate the impact of obesity
during cancer treatment on the development of SMN in pediatric cancer survivors. As secondary
aims, we also evaluated obesity at end of therapy and at follow-up to determine whether changes
in weight classification over time impact the risk of SMNs.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
35
METHODS
Case and Control Selection
In this case-control study, cases were defined as patients with pediatric cancer who
developed an SMN; controls were defined as comparable patients who did not develop an SMN.
To identify patients, we utilized longitudinal data from the Los Angeles Cancer Surveillance
Program (CSP) and California Cancer Registry (CCR), which are large, well-established
registries that collect demographic, clinical, treatment, and follow-up data on all incident cancers
among residents of Los Angeles County and California, respectively. Cases were defined as
patients <21 years old who had an initial diagnosis of cancer at Children’s Hospital Los Angeles
(CHLA) between January 1, 1988 and December 31, 2014 and later were diagnosed with a
secondary cancer diagnosed anywhere in California through December 31, 2014.
Controls were then selected via the registry from the entire cohort of all pediatric cancer
patients <21 years old diagnosed at CHLA between January 1, 1988 and December 31, 2014.
Controls were matched using registry variables by the following criteria: age at diagnosis of
primary cancer (exact age if possible, but extended to 0-1, 1-9, 10-20 years old), sex, cancer site,
histology code, radiation exposure (no/yes), stage (localized/regional versus distant), and days of
follow up (controls had to be followed at least as long as the interval between the case’s initial
diagnosis and SMN). The goal was to match three controls to every case with exact matching
criteria. If fewer than three controls were available using the exact matching criteria, some
characteristics (such as age, stage) were relaxed (as described above) to achieve the three
controls. However, in some cases, even with relaxed criteria, three controls could not be
identified, and therefore fewer controls were selected depending on the number of available
matches. There were two cases that did not have any good matches based on the strict matching
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
36
criteria, however they were included with controls that were mismatched on only one of the strict
criteria. We anticipated these pairs would have little impact on treatment exposure (one case, a 3
year old distant primitive neuroectodermal tumor [PNET] was matched to one control, a 12 year
old with regional Ewing sarcoma; and another case, a 15 year old female with olfactory
neuroblastoma was matched to one control, a 10 year old male with neuroblastoma). Based on
similar histology and treatment schema, the following ICD-O-3 histology codes were grouped
when identifying controls: [9835, 9836, 9837, 9811]; [9861, 9891, 9872, 9874]; [9392]; [9400];
[9401]; [9473 Site Brain, 9472]; [9470]; [9421]; [9473 Site Bone and Joint, 9260, 9264, 9364];
[9180, 9183, 9181]; [9500], [9652, 9663, 9664]; [9684, 9680, 9687]; [9727]; [9380]; [9364,
9260]; [8960]; [9510]; [9500]; [8910]; [9071, 9080]; [9061, 9064]; [9801]; [8830]; [9522, 9500].
Chart Abstraction and Definition of Variables
Abstraction of data from medical records for the selected cases and controls was
performed by two physicians (DM and LC) using pre-defined variables of interest and strictly
adhering to a detailed protocol.
Obesity related variables included height (centimeters, cm) and weight (kilograms, kg) at
initial diagnosis, end of therapy (EOT), and at diagnosis of SMN (for cases if diagnosed at
CHLA), or at the clinic visit corresponding to the nearest censor date (for controls). If more than
one height and weight were recorded for the day of question, the second measurements were
collected. If heights and weights were not available in medical notes, they were abstracted from
the patient’s individualized chemotherapy treatment “roadmaps” for the first cycle and/or last of
chemotherapy delivered.
BMI as kg/square meter (m
2
) and corresponding pediatric BMI Z-score (CHOP Research
Institute) were calculated for each patient at each time point. BMI percentile for age and sex for
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
37
patients aged 2 years or older, and weight for length (WFL) for patients <2 years old were
obtained and categorized using the Center for Disease Control pediatric calculator (Center for
Disease Control). Patients were categorized as normal/underweight (BMI <85% or WFL <95%
for age and sex), overweight (BMI=85-94.9% or WFL≥95% for age and sex), or obese (BMI
≥95% for age and sex) (Center for Disease Control). Weight status was categorized for patients
20 years old or older as normal or underweight if BMI <25 kg/m
2
, overweight if BMI=25-29.9
kg/m
2
, and obese if BMI≥30 kg/m
2
. For patients 20 years old or older, BMI Z-score was
estimated as if the collected height and weight were for a patient 19.9 years old. A BMI Z-score
of 1.04 corresponded to the 85% (overweight threshold), and a Z-score of 1.64 corresponded to
the 95% (obese threshold).
Genetic predisposition variables included documentation indicating suspicion or
diagnosis of a cancer predisposition syndrome (Down syndrome, BRCA1 or 2, Li-Fraumeni
syndrome, neurofibromatosis type 1 or type 2, tuberous sclerosis, Beckwith-Wiedemann
syndrome, retinoblastoma, hemihypertrophy, von Hippel Lindau, or other). To minimize
detection bias, patients not suspected of underlying genetic predisposition syndrome until after
SMN was diagnosed were categorized as no underlying syndrome.
Treatment data came from one of the following sources: (1) from cumulative
chemotherapy and radiation exposures available in treatment summaries as part of the CHLA
survivorship clinic; (2) from direct chemotherapy and radiation dosages indicated in
individualized roadmaps; or (3) from total doses administered and controlled for by the patient’s
concurrent body surface area to get the standardized dose of chemotherapy per m
2
. Treatment
related data included date first seen at CHLA; radiation exposure, dose, and field from the
radiation oncology treatment summary; alkylator exposure and cumulative dose [cumulative
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
38
cyclophosphamide equivalent dose (CED, mg/m
2
)= 1.0 (cumulative cyclophosphamide dose
(mg/m
2
)) + 0.244 (cumulative ifosfamide dose (mg/m
2
)) + 0.857 (cumulative procarbazine dose
(mg/m
2
)) + 14.286 (cumulative chlorambucil dose (mg/m
2
)) + 15.0 (cumulative BCNU dose
(mg/m
2
)) + 16.0 (cumulative CCNU dose (mg/m
2
)) + 40 (cumulative melphalan dose (mg/m
2
)) +
50 (cumulative thiotepa dose (mg/m
2
)) + 100 (cumulative nitrogen mustard dose (mg/m
2
)) +
8.823 (cumulative busulfan dose (mg/m
2
))](Green et al., 2014); anthracycline exposure and
cumulative dose [cumulative doxorubicin equivalent dose (mg/m
2
) = 1.0 (cumulative doxorubicin
dose (mg/m
2
)) + 1.0 (cumulative daunorubicin dose (mg/m
2
)) + 0.67 (cumulative epirubicin dose
(mg/m
2
)) + 5 (cumulative idarubicin dose (mg/m
2
)) + 4 (cumulative mitoxantrone dose
(mg/m
2
))](Children's Oncology Group); epipodophyllotoxin exposure and cumulative dose
(cumulative etoposide and etopophosphate dose (mg/m
2
)); platinum exposure and cumulative
dose [cumulative platinum exposure = 1.0 (cumulative cisplatin dose (mg/m
2
)) + 0.25
(cumulative carboplatin dose (mg/m
2
))](Neglia et al., 2001); end of therapy (EOT) date, and date
last seen at CHLA. Treatment doses for controls were censored at follow-up time that the
matched case developed SMN.
Treatment factors were categorized as follows: radiation exposure (dichotomous: no/yes),
cumulative CED (0, 1-4000 mg/m
2
, >4000 mg/m
2
), cumulative anthracycline dose (0, 1-169
mg/m2, >169 mg/m2), cumulative epipodophyllotoxin dose (0, 1-1800 mg/m
2
, >1800 mg/m
2
),
and platinum exposure (dichotomous: no/yes).
Statistical Analysis
Conditional logistic regression was performed for the variable number of controls
matched to each case. Risk factors for development of SMN were assessed by univariate
followed by multivariable analysis for all included patients (n=189), then for matched
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
39
cases/controls that had sufficient EOT data (n=155). The final multivariable model included all
factors with p values <0.10 in univariate analysis. Interaction of sex, follow-up time, and BMI
category with each candidate predictor variable was assessed. All analyses were performed using
pHReg in SAS version 9.4, (Cary, NC). For all analyses, significance was two-sided and set at
p<0.05.
RESULTS
Cases
Seventy-one pediatric cases were initially identified by the registry. Of these, five cases
were excluded: three for the initial cancer and SMN being diagnosed within three weeks’ time
given short interval and likelihood that more likely synchronous cancers and not therapy induced
SMN; one for the initial and second cancers of record (acute monocytic leukemia and acute
granulocytic leukemia, respectively) being diagnosed on the same day suggesting the same
cancer recorded in the registry as two separate cancers; and one for the primary and secondary
cancers of record being myelodysplastic syndrome and acute granulocytic leukemia,
respectively, likely representing disease progression. Sixty-six eligible cases underwent
matching at the registry level (Figure 1). Of these, two additional cases were subsequently
excluded because no appropriate matches could be identified. Thus, a total of 64 case-control
sets underwent chart review.
After chart review, an additional 5 case-control sets were excluded (3 sets for cases for
missing data, 1 set because the case was a testicular relapse misclassified as an SMN in the
registry, and 1 case-control set because all matched controls had incomplete data). Thus, we
arrived at a final sample size of 130 controls matched to 59 cases. Three controls were matched
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
40
per case for 30 cases, two controls per case for 11 cases, and one control per case for 18 cases
(Figure 1).
Figure 1: Consort Diagram
71 Cases
66 Cases
64 Cases
59 Cases
5 cases excluded:
1 with 0 days between first and second malignancy
1 with 12 days between first and second malignancy
2 with 20 days between first and second malignancy
1 with MDS that transformed to AML
2 cases excluded:
2 no appropriate matches
5 case-control sets excluded:
3 sets for cases with missing data
1 set for the case misclassified as SMN
1 set for all matched controls having incomplete data
Matching:
3 controls per case for 40 cases
2 controls per case for 7 cases
1 control per case for 17 cases
Chart Review:
3 controls per case for 30 cases
2 controls per case for 11 cases
1 control per case for 18 cases
130 Controls
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
41
Demographic and Treatment Characteristics
Demographic and treatment data are displayed in Table 1. In aggregate, our sample of
cases and controls was 64.5% were male with a median age of 6.0 years at primary cancer
diagnosis. The most common primary cancer diagnosis was acute lymphocytic leukemia (ALL)
(36.5%), followed by Ewing sarcoma/PNET (11.6%), and brain glioma (WHO Grades I-III)
(11.6%) (Table 1, Table 2). Fifty-six percent had distant stage disease at diagnosis (Table 1). As
a result of our matching criteria, cases and controls had similar distribution by sex, age at
diagnosis, suspected or known underlying predisposition syndrome, year of cancer diagnosis,
cancer diagnosis, and stage of disease (Table 1).
Cases were less likely than controls to be followed at CHLA until censor date than
controls (54.8% versus 70.8%, p=0.026) (Table 1). Though, those that were not followed until
censor date had similar chemo-radiotherapy exposure during their periods of follow-up. Cases
and controls had similar chemotherapy exposure, however cases had a higher proportion of
radiation exposure than controls (57.6% versus 42.3%, p=0.051) (Table 1).
BMI Status
In aggregate, almost 20% of all cases and controls combined were overweight, and
almost 14% were obese (Table 1). For cases compared with controls, BMI Z-score was higher at
time of diagnosis (0.58 versus 0.17, p=0.052) and similar at EOT (0.40 vs. 0.37, p=0.92).
Similarly, for cases compared with controls, a higher proportion were obese at diagnosis (22.0%
versus 10.0%, p=0.082), at EOT only (20.3% versus 9.4%, p=0.026), and at both diagnosis and
EOT (18.4% versus 5.7%, p=0.053) (Table 1).
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
42
Table 1: Description of cases and controls: Demographics, cancer features, treatment factors,
and weight status for cases and controls
All Cases Controls P value
N 189 59 130
Male 120 (63.5%) 35 (59.3%) 85 (65.4%) 0.42
Median age at diagnosis in years
SD [range]
6.0
5.4 [0-20]
5.0
5.7 [0-20]
7.0
5.3 [0-20]
0.54
Age Group
<1 years old
1-9 years old
10-20 years old
15 (7.9%)
109 (57.7%)
65 (34.4%)
4 (6.8%)
37 (62.7%)
18 (30.5%)
11 (8.5%)
72 (55.4%)
47 (36.2%)
0.64
Underlying Syndrome at Primary Cancer
No
Yes
173 (91.5%)
16 (8.5%)
52 (88.1%)
7 (11.9%)
121 (93.1%)
9 (6.9%)
0.26
Syndrome Diagnosis
NF1
Down Syndrome
Li-Fraumeni
Suspected but unconfirmed
7 (3.7%)
3 (1.6%)
1 (0.5%)
4 (2.1%)
4 (6.8%)
0 (0.0%)
1 (1.7%)
2 (3.4%)
3 (2.3%)
3 (2.3%)
0 (0.0%)
3 (2.3%)
0.001*
Year Cancer Diagnosis
1988-1992
1993-1997
1998-2002
2003-2007
2008-2013
35 (18.5%)
50 (26.4%)
41 (21.7%)
41 (21.7%)
22 (11.6%)
20 (33.9%)
11 (18.6%)
10 (16.9%)
12 (20.3%)
6 (10.2%)
15 (11.5%)
39 (30.0%)
31 (23.8%)
29 (22.3%)
16 (12.3%)
0.071
Diagnosis
Acute lymphocytic leukemia
Acute myeloid leukemia
Acute leukemia
Hodgkin lymphoma
Non-Hodgkin lymphoma
Ewing sarcoma/PNET
Osteosarcoma/Malignant fibrous histiosarcoma
Soft tissue sarcoma/Rhabdomyosarcoma
Neuroblastoma
Ovarian germ cell tumor
Retinoblastoma
Wilm’s/Nephroblastoma
Brain glioma
Medulloblastoma/PNET
69 (36.5%)
4 (2.1%)
2 (1.1%)
12 (6.3%)
5 (2.6%)
22 (11.6%)
13 (6.9%)
7 (3.7%)
13 (6.9%)
2 (1.1%)
4 (2.1%)
7 (3.7%)
22 (11.6%)
7 (3.7%)
18 (30.5%)
1 (1.7%)
1 (1.7%)
3 (5.1%)
2 (3.4%)
8 (13.6%)
4 (6.8%)
3 (5.1%)
4 (6.8%)
1 (1.7%)
1 (1.7%)
2 (3.4%)
8 (13.6%)
3 (5.1%)
51 (39.2%)
3 (2.3%)
1 (0.8%)
9 (6.9%)
3 (2.3%)
14 (10.8%)
9 (6.9%)
4 (3.1%)
9 (6.9%)
1 (0.8%)
3 (2.3%)
5 (3.8%)
14 (10.8%)
4 (3.1%)
0.99*
Stage
Localized/Regional
Distant
Unknown
79 (41.8%)
105 (55.6%)
5 (2.6%)
23 (39.0%)
32 (54.2%)
4 (6.8%)
56 (43.1%)
73 (56.2%)
1 (0.8%)
0.057
Records Available at CHLA until Censored
No
Yes
65 (34.4%)
124 (65.6%)
27 (45.8%)
32 (54.2%)
38 (29.2%)
92 (70.8%)
0.027
Radiation Exposure
No
Yes
100 (52.9%)
89 (47.1%)
25 (42.4%)
34 (57.6%)
75 (57.7%)
55 (42.3%)
0.051
Cumulative Cyclophosphamide Equivalent Dose:
0
1-4000
4001+
34 (18.0%)
64 (33.9%)
91 (48.1%)
13 (22.0%)
14 (23.7%)
32 (54.2%)
21 (16.2%)
50 (38.5%)
59 (45.4%)
0.13
Cumulative Anthracycline Dose:
0
1-169
170+
41 (21.7%)
56 (29.6%)
92 (48.7%)
14 (23.7%)
15 (25.4%)
30 (50.8%)
27 (20.8%)
41 (31.5%)
62 (47.7%)
0.68
Cumulative Epipodophyllotoxin Dose:
0
119 (63.0%)
30 (50.8%)
89 (68.5%)
0.063
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
43
1-1800
1801+
25 (13.2%)
45 (23.8%)
11 (18.6%)
18 (30.5%)
14 (10.8%)
27 (20.8%)
Platinum Exposure
No
Yes
139 (73.5%)
50 (26.5%)
41 (69.5%)
18 (30.5%)
98 (75.4%)
32 (24.6%)
0.39
Completed therapy at CHLA
No
Yes
34 (18.0%)
155 (82.0%)
10 (16.9%)
49 (83.0%)
24 (18.5%)
106 (81.5%)
0.80
N 189 59 130
Mean BMI Z-Score Diagnosis (SD) 0.30 (1.34) 0.58 (1.32) 0.17 (1.34) 0.052
Weight Status at Diagnosis
Not overweight/obese
Overweight
Obese
126 (66.7%)
37 (19.6%)
26 (13.8%)
35 (59.3%)
11 (18.6%)
13 (22.0%)
91 (70.0%)
26 (20.0%)
13 (10.0%)
0.082
N 155 49 106
Mean BMI Z-Score End of Therapy (SD) 0.38 (1.56) 0.40 (1.69) 0.37 (1.51) 0.92
Weight Status at End of Therapy
Not overweight/obese
Overweight
Obese
102 (65.8%)
31 (20.0%)
22 (14.2%)
26 (53.1%)
11 (22.4%)
12 (20.3%)
76 (71.7%)
20 (18.9%)
10 (9.4%)
0.026
Weight Status Change Diagnosis to End of Therapy
Normal/Overweight to Normal/Overweight
Normal/Overweight to Obese
Obese to Normal/Overweight
Obese to Obese
117 (75.5%)
16 (10.3%)
7 (4.5%)
15 (9.7%)
31 (63.3%)
6 (12.2%)
3 (6.1%)
9 (18.4%)
86 (81.1%)
10 (9.4%)
4 (3.8%)
6 (5.7%)
0.053
P values for categorical variables were calculated using Pearson chi square, p values for continuous variables derived from
Wilcoxon rank sum. *Fisher’s exact test. SD= standard deviation, CHLA=Children’s Hospital Los Angeles, PNET=primitive
neuroectodermal tumor, NF1=neurofibromatosis type 1, BMI=body mass index (kg/m
2
).
Characteristics of SMNs
The median time from primary cancer diagnosis to SMN was 7.5 years (standard
deviation [SD] 5.6 years, range 0.5-25.3 years). Among the 59 cases who developed SMN, the
SMNs were acute myeloid leukemia (AML, n=15), thyroid (n=10), brain glioma (n=9),
osteosarcoma (n=6), Ewing sarcoma/PNET (n=4), soft tissue sarcoma (n=4), salivary gland
(n=2), ALL (n=2), kidney and renal pelvis (n=2), and lymphoblastic lymphoma, testicular germ
cell tumor, melanoma, breast ductal carcinoma, and rectal adenocarcinoma (n=1 for each) (Table
2).
Relationship of BMI and Obesity with Development of SMN
Using conditional logistic regression, on univariate analysis we found statistically
significant associations between SMN and obesity at diagnosis (compared to
normal/underweight at diagnosis, OR 2.48, 95%CI 1.05-5.88, p=0.038), pediatric BMI Z-score at
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
44
Table 2: Distribution of cancer site/histology by cancer sequence
Cancer Site/Histology, n=59 % of Primary Cancer (n) % of Secondary Cancer
(n)
Acute lymphocytic leukemia 30.5 (18) 3.3 (2)
Acute myeloid leukemia 1.7 (1) 25.4 (15)
Acute leukemia, mixed phenotypic 1.7 (1) 0.0 (0)
Hodgkin lymphoma 5.1 (3) 0.0 (0)
Non-Hodgkin lymphoma 3.3 (2) 1.7 (1)
Brain glioma 13.6 (8) 15.2 (9)
Medulloblastoma/PNET 5.1 (3) 0.0 (0)
Neuroblastoma 6.8 (4) 0.0 (0)
Ewing sarcoma/PNET 13.6 (8) 6.8 (4)
Osteosarcoma/Malignant fibrous histiosarcoma 6.8 (4) 10.1 (6)
Soft tissue sarcoma/Rhabdomyosarcoma 5.1 (3) 6.8 (4)
Wilm’s/Nephroblastoma 3.3 (2) 0.0 (0)
Renal cancer 0.0 (0) 3.3 (2)
Ovarian germ cell tumor 1.7 (1) 0.0 (0)
Testicular germ cell tumor 0.0 (0) 1.7 (1)
Retinoblastoma 1.7 (1) 0.0 (0)
Thyroid 0.0 (0) 16.9 (10)
Salivary gland 0.0 (0) 3.3 (2)
Melanoma 0.0 (0) 1.7 (1)
Rectal adenocarcinoma 0.0 (0) 1.7 (1)
Breast 0.0 (0) 1.7 (1)
PNET=primitive neuroectodermal tumor
diagnosis (OR 1.29, 95%CI 1.01-1.65, p=0.042, such that for every 1 point increase in Z-score
correlated with a 29% increased risk of SMN), year of diagnosis 1993-2013 (compared to 1988-
1992, OR 0.17, 95%CI 0.05-0.60, p=0.006), radiation exposure (compared to no radiation
exposure, OR 3.84, 95%CI 1.11-13.29, p=0.034), and moderate epipodophyllotoxin exposure (1-
1800 mg/m
2
compared to 0 mg/m
2
, OR 3.73 95%CI 1.16-11.98, p=0.027) (Table 3). There were
no associations between SMN and stage of cancer at diagnosis, cumulative CED, cumulative
anthracycline dose, or platinum exposure. For the subset who had completed treatment at CHLA
and had heights and weights recorded at EOT (n=155), there was also an association between
weight status over time: for patients who were obese at diagnosis and EOT compared with those
who were normal/underweight at both time points, the OR for SMN was 4.26 (95%CI 1.35-
13.38, p=0.013) (Table 3).
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
45
On multivariable analysis, after controlling for year of diagnosis, radiation exposure, and
epipodophyllotoxin dose, there were dose-dependent relationships between weight status and
SMN, and between BMI Z-score at diagnosis and SMN, however these were not significant
(adjusted OR [aOR] for obesity 2.38, 95%CI 0.93-6.10, p=0.10, aOR for Z-score 1.27, 95%CI
0.96-1.67, p=0.09) (Table 4). In a multivariable model that included only patients for whom EOT
BMI data were available, patients who were obese at diagnosis and EOT compared to those who
were not had a significantly increased risk of SMN after controlling for year of diagnosis,
radiation exposure, and epipodophyllotoxin dose (aOR 3.56, 95%CI 1.03-12.30, p=0.045) (Table
5). Patients who started therapy in the obese category and ended therapy not obese appeared to
have mitigated their risk of SMN (aOR 1.21, 95%CI 0.18-8.14, p=0.84). Those that started
therapy not obese and became obese at EOT had an elevated risk of SMN, however it was not
significant (aOR 3.44, 95%CI 0.84-14.22, p=0.09) (Table 5). Interaction analyses revealed no
significant interactions between the candidate predictors.
DISCUSSION
In this case-control study we found evidence that obesity at time of cancer treatment may
be associated with an increased risk of developing SMN. While the association did not meet
statistical significance in multivariable analysis, the elevated OR was consistently elevated
among all the models with an over two-fold increased risk of SMN among obese patients. In
addition, evidence of a dose-response was present. Among the subjects that had BMI data at
EOT, this association between obesity and SMN was especially evident among patients who both
started and completed therapy in the obese state, with an over 3-fold statistically significant
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
46
Table 3: Univariate analysis using conditional logistic regression for predictive factors on
development of SMN: all patients, n=189 (59 cases, 130 controls)
Univariate Analysis
N OR 95% CI P value
BMI Z-Score at Diagnosis 189 1.29 1.01-1.65 0.042
Weight Status at Diagnosis
Normal/Underweight
Overweight
Obese
Global Null Hypothesis Test
189
1.00
1.21
2.48
-
Ref
0.55-2.66
1.05-5.88
-
-
0.64
0.038
0.12
BMI Z-Score End of Therapy 155 1.06 0.82-1.37 0.64
Weight Status at End of Therapy
Normal/Underweight
Overweight
Obese
Global Null Hypothesis Test
155
1.00
0.40
2.37
-
Ref
0.11-1.46
0.93-6.06
-
-
0.16
0.071
0.033
Weight Status Change Diagnosis to End of Therapy
Normal/Overweight to Normal/Overweight
Normal/Overweight to Obese
Obese to Normal/Overweight
Obese to Obese
Global Null Hypothesis Test
155
1.00
1.99
1.45
4.26
-
Ref
0.60-6.59
0.30-7.01
1.35-13.38
-
-
0.26
0.65
0.013
0.086
Confirmed/Suspected Syndrome
No
Yes
189
1.00
2.86
Ref
0.75-10.98
-
0.12
Year of Diagnosis
1988-1992
1993-2013
189
1.00
0.17
Ref
0.05-0.60
-
0.006
Stage of Cancer at Diagnosis
Localized/Regional
Distant
Unknown
Global Null Hypothesis Test
189
1.00
1.82
7.44
Ref
0.47-7.03
0.79-70.28
-
0.38
0.08
0.17
Radiation Exposure
No
Yes
189
1.00
3.84
Ref
1.11-13.29
-
0.034
Cumulative Cyclophosphamide Equivalent Dose
0
1-4000 mg/m
2
4001+ mg/m
2
Global Null Hypothesis Test
189
1.00
0.23
0.62
-
Ref
0.05-1.11
0.20-1.90
-
-
0.07
0.40
0.18
Cumulative Anthracycline Dose
0
1-169 mg/m
2
170+ mg/m
2
Global Null Hypothesis Test
189
1.00
1.75
2.24
-
Ref
0.27-11.28
0.32-15.70
-
-
0.55
0.42
0.69
Cumulative Epipodophyllotoxin Dose
0
1-1800 mg/m
2
1801+ mg/m
2
Global Null Hypothesis Test
189
1.00
3.73
2.46
-
Ref
1.16-11.98
0.78-7.80
-
-
0.027
0.12
0.075
Platinum Exposure
No
Yes
189
1.00
1.23
Ref
0.38-4.01
-
0.73
BMI=body mass index (kg/m
2
)
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
47
Table 4: Multivariable analyses using conditional logistic regression for predictive factors on
development of SMN: all patients, n=189 (59 cases, 130 controls)
Multivariate Model 1 Multivariate Model 2
OR 95% CI P
value
OR 95%CI P value
BMI Z-score at Diagnosis 1.27 0.96-1.67 0.09
Weight Status at Diagnosis
Normal/Underweight
Overweight
Obese
Global Null Hypothesis Test
1.00
1.23
2.38
-
Ref
0.52-2.90
0.93-6.10
-
-
0.63
0.07
0.19
Year of Diagnosis
1988-1992
1993-2013
1.00
0.15
Ref
0.04-0.57
-
0.005
1.00
0.15
Ref
0.04-0.55
-
0.004
Radiation Exposure
No
Yes
1.00
3.81
Ref
0.90-
16.02
-
0.07
1.00
3.88
Ref
0.93-16.18
-
0.06
Cumulative Epipodophyllotoxin Dose
0
1-1800 mg/m
2
1801+ mg/m
2
Global Null Hypothesis Test
1.00
1.84
2.15
-
Ref
0.44-7.62
0.56-8.19
-
-
0.40
0.26
0.50
1.00
1.68
2.07
-
Ref
0.40-7.08
0.54-7.96
-
-
0.48
0.29
0.55
Factors with p <0.10 in univariate analysis included in multivariate model.
Table 5: Multivariable analysis using conditional logistic regression for predictive factors on
development of SMN: all patients who completed therapy at CHLA, n=155 (49 cases, 106
controls)
Multivariate Model 3
OR 95% CI P value
Weight Status Change Diagnosis to End of Therapy
Normal/Overweight to Normal/Overweight
Normal/Overweight to Obese
Obese to Normal/Overweight
Obese to Obese
Testing Global Null Hypothesis
1.00
3.44
1.21
3.56
Ref
0.84-14.22
0.18-8.14
1.03-12.30
-
0.09
0.84
0.045
0.11
Year of Diagnosis
1988-1992
1993-2013
1.00
0.16
Ref
0.04-0.62
-
0.008
Radiation Exposure
No
Yes
1.00
14.49
Ref
0.95-221.15
-
0.056
Cumulative Epipodophyllotoxin Dose
0
1-1800 mg/m
2
1801+ mg/m
2
Testing Global Null Hypothesis
1.00
1.91
1.59
-
Ref
0.34-10.87
0.33-7.70
-
-
0.47
0.56
0.75
Factors with p <0.10 in univariate analysis included in multivariate model.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
48
increased risk of SMN compared to those who were non-obese at start and EOT, after controlling
for treatment factors. While these findings are concerning, the small number of patients that
started therapy obese but who became non-obese by the EOT (n=7), the elevated risk of SMN
was alleviated. This highlights the need for further studies and the subsequent potential for
effective intervention to reduce weight or maintain normal weight during treatment exposures.
Our findings add to the existing literature suggesting that obesity in childhood cancer is
associated with poor outcomes. Other than a single study that showed no association between
BMI and response to treatment or relapse in childhood leukemia patients (Eissa et al., 2017), the
majority of the literature supports our finding. For example, higher weight status was found to be
associated with increased toxicity and decreased survival in children with the most common
childhood cancer, ALL, when compared to patients with normal BMI (Amankwah et al., 2016;
Eissa et al., 2017; Orgel et al., 2016; E. Orgel et al., 2014). In addition, in a cohort of pediatric
leukemia patients, those with higher BMI had increased risk of residual leukemia after induction
chemotherapy than their counterparts with normal BMI (E Orgel et al., 2014). Similar to the
increased risk of residual disease in obese patients, being overweight or obese has also been
associated with increased relapse rates in children after treatment for leukemia (Amankwah et
al., 2016; E Orgel et al., 2014).
In this study, the most common SMN diagnosed was AML, followed by thyroid and
brain glioma. This is in contrast to the Childhood Cancer Survivorship Study cohort which
observed that the most frequent SMN was breast cancer, followed by thyroid, then central
nervous system tumors (Meadows et al., 2009). This is likely due to a combination of the
treatment era differences, the follow-up time differential between the two study samples, and the
known time sensitivity for incidence of secondary leukemias (Leone, Mele, Pulsoni, Equitani, &
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
49
Pagano, 1999). Our study is unique in its inclusivity of patients who develop a secondary cancer
at any time after first cancer diagnosis, compared to the CCSS cohort which includes only
survivors that are alive at 5 years after their initial cancer diagnosis.
Known risk factors for SMN, such as earlier treatment era (Schaapveld et al., 2015),
epipodophyllotoxin exposure, and radiation exposure (Neglia et al., 2001; Ng et al., 2010) were
also found to be predictive of SMN. Although we attempted to match controls to cases at the
registry level based on radiation exposure, it was evident that radiation exposure was sometimes
misclassified in the registry and, thus, needed to be adjusted for in the statistical analysis.
Alkylator therapy, conversely, was not found to be associated with SMN. While it is unclear why
this association was opposite than expected, this discrepancy may be explained by the cancer
types and respective standard therapies that were represented in this sample. In addition, the role
of underlying syndrome in the development of SMN was surprisingly undetectable. The overall
prevalence of genetic predisposition syndromes has been reported to be about 8.5% of pediatric
cancer patients (Zhang et al., 2015). In our study, in order to minimize detection bias, patients
were categorized as having a suspected or known underlying syndrome only if it was suspected
during the first cancer (thus, based on syndromic physical features, known genetic disorders,
type of primary cancer [for example, retinoblastoma], or strong family history of cancer), and not
if it was only suspected as a result of an SMN. Thus, there were four cases that were later found
to have an underlying syndrome after the SMN was diagnosed, which would have strengthened
the association if they had been categorized as having an underlying syndrome at the time of
initial diagnosis. We have a high suspicion that the true association between SMN and
underlying genetic syndrome, if systematically evaluated, is much more pronounced than what
was found in our study.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
50
Excess weight is an important health factor affecting a large proportion of pediatric
cancer patients and survivors (Brown et al., 2016b; Garmey et al., 2008; M. H. Lin et al., 2015).
In our study which included all invasive cancer diagnoses, one-third of patients were overweight
or obese. This proportion, while lower than a multi-ethnic study of 400 childhood leukemia
survivors that found almost half of all the patients at 11 years of follow-up were either
overweight or obese (Brown et al., 2016a), is still considerable. Since higher BMI is known to
increase the risk for multiple serious late effects and potentially life-limiting comorbidities, such
as heart disease, metabolic syndrome, and diabetes (Gunn, Emilsson, Gabriel, Maguire, &
Steinbeck, 2016; Hudspeth, Gold, & Clemmons, 2017; Meacham et al., 2005), our study
suggests that increased risk of SMN should also be considered as an obesity related late-effect.
This study illuminates that SMN is another possible adverse outcome that may associated
with obesity, a risk factor affecting substantial proportion of pediatric cancer patients and
survivors. Our study has many strengths, including ability to comparably ascertain cases and
controls at the registry level, ability to match well to at least one control on multiple factors,
incorporation of accurate chemotherapy and radiation data into the analysis, absence of recall
bias given chart abstraction of an objective exposure variable, minimizing detection bias by
following a strict protocol of chart review so that efforts to collect treatment and height/weight
data were standardized among all cases and controls, and evaluation of weight class over time.
Weaknesses include a heterogeneous group of primary and subsequent malignancies, relatively
small numbers, misclassification of radiation status at the registry level, exclusion of
cases/controls for incomplete data, and inability to infer causality. Given the current study’s
limitations, it is important that these preliminary data demonstrating the elevated risk of SMN in
obese patients be replicated in a larger sample of survivors. Regardless, cancer patients would
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
51
likely benefit from the study of interventions to control BMI during treatment which would
certainly improve survival and overall health for survivors of childhood and adolescent cancer,
and may in turn reduce risk for SMNs.
SURVIVAL TRENDS AND OUTCOMES IN CHILD AND YA CANCER SURVIVORS
52
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Abstract (if available)
Abstract
In this thesis, we present novel insights into the contributors and pathophysiology of important outcomes in child, adolescent, and young adult cancer survivorship using registry-based data. ❧ Cancer survival has improved dramatically for children and older adults. However, adolescents and young adults (AYAs, 15-39 years old) were shown in the 1990s to have plateauing survival improvements. This has been thought to be attributable to a combination of factors uniquely affecting AYAs, including different disease/host biology, delays in diagnosis and treatment, increased toxicity to treatment, financial toxicity, and psychosocial factors. In Chapter 1, we sought to reappraise AYA cancer survival in light of recent data. In this California Cancer Registry based analysis, cancer site specific survival data was examined from 1988-2014 evaluating for trends in survival over time. In an effort to better understand the stagnating survival gains once observed in this racially/ethnically and socioeconomically diverse population, subgroup specific survival over time was assessed, and survival disparities were defined. We found that, contrary to prior observations in the 1990s of stagnating survival gains, the time frame from 1988-2014 actually demonstrated the most dramatic survival improvements for AYAs, especially AYA males, largely due to the improved survival from HIV/AIDS related cancers after the introduction of effective antiretroviral therapy. However, survival improvements over the time period were not equally distributed among all AYAs. Not only did certain cancer sites and stages show no improvement over the time period, all racial/ethnic groups compared to non-Latino whites and low SES compared to high SES showed growing survival disparities. ❧ Survival for pediatric cancer has improved greatly over the decades and now reaches about 80%. With this growing number of cancer survivors, understanding late effects from cancer therapy has become paramount. A particular late effect causing significant morbidity and often mortality are treatment related second malignant neoplasms (SMNs), affecting almost 10% of 30 year survivors of pediatric cancer. While treatment factors and underlying genetic syndromes have been shown to increase a survivor’s risk of SMN, other risk factors, such as obesity during time of treatment, have not been described. In this case-control study utilizing the California Cancer Registry for case and control selection, we performed a retrospective chart review to test whether obesity at time of cancer treatment increased the risk of SMN. We found that there is a strong suggestion of an increased risk of SMN associated with obesity at time of cancer treatment (with an over two-fold odds of SMN for obese patients at diagnosis, and an over three-fold odds of SMN for patients who are obese at time of diagnosis and at end of therapy). More research is needed to confirm these findings and identify interventions that can help control weight during cancer treatment in order to mitigate SMN risk and obesity related diseases among pediatric cancer survivors.
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Moke, Diana Jean
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Survival trends and related outcomes of survivors of childhood and young adult cancer
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Clinical and Biomedical Investigations
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