Download final research paper TOP

Introduction
Obesity has been known to cause many systemic illnesses within
numerous body systems; including the cardiovascular, reproductive, digestive,
and respiratory system [1-4]. Studies have shown the relationship between body
mass index (BMI) and risk for most health outcomes is highest for people with
excessively low (BMI < 18.5 kg/m2) or high BMI levels (BMI ≥ 25 kg/m2) ;
however, among people with normal BMI values (BMI in the range of 18.5 to
24.9 kg/m2) the relationship between BMI and risk for chronic diseases is not
significant [3]. One study found the strongest association with disease mortality
among those who were obese and had a high waist-to-hip ratio (WHR), compared
with women with normal BMI and WHR. A significantly worse mortality rate
was observed only among postmenopausal women with high WHR.[5]
Meta-analyses have found that obesity is associated with increased risk for
most cancers including cancers of the breast, colon, and genitalia [1-4]. With
respect to breast cancer, obese patients are more likely to be diagnosed at a later
stage, have larger sized tumors, and experience lymph node metastases [6].
Obesity among survivors is also associated with elevated risk for cancer
recurrence, and overall mortality[7]. Increasing evidence indicates that being
overweight not only increases the risk for recurrence, but reduces the likelihood
of survival for many cancers [8].
In addition, studies have shown that obesity increases the risk for ovarian
cancer and plays a role in ovarian cancer survival [9]. A recent meta-analysis
found that obesity was associated with a 30% increased risk of ovarian cancer
when compared with p a t i e n t s o f normal weight [10]. Similarly, obese
ovarian cancer survivors are 1.68 time more likely than non-obese women to die
from ovarian cancer [11]. The study revealed that overweight or obesity during
early adulthood is associated with worse prognosis of patients with invasive
EOC. In addition, premorbid obesity was associated with higher mortality
among patients with advanced-stage ovarian cancer [9].
Physical activity is associated with a number of benefits throughout the
cancer continuum [12]. A high status of physical activity has been known to
decrease the risk of cancers occurrence by 27% among compared with those in
the lowest level [13]. This was shown when intense physical activity between
ages 18 and 30 was associated with a decreased risk of death among women with
early ovarian cancer stage. Additionally, women in the highest category of
physical activity during young adult life had a decreased mortality risk if they
were diagnosed with early stage ovarian cancer [14]. There is also found evidence
of improved survival for women who engaged in greater than 2 hours of activity
per week as compared to those who reported less than 1 hour per week [15]. In
addition, physical activity is associated with improvements in body mass index,
physical function, cancer-related fatigue, and mood [12]. Among ovarian cancer
survivors physical activity was inversely associated with fatigue, peripheral
neuropathy, depression, anxiety, sleep latency, use of sleep medication, and
daytime dysfunction, and was positively associated with happiness, sleep quality,
and sleep efficiency [16].
There are gaps in the literature that connects body size, quality of life, and
recurrence with ovarian cancer survivors. The Ovarian Nutrition Education
(ONE) Study was a randomized dietary intervention for stage 11- N ovarian
cancer survivors. The aims of the ONE Study were to (a) examine the feasibility
of a telephone-based dietary intervention for stages 11-N ovarian cancer survivors
who had completed treatment at least 6 months prior to the intervention; and (b)
determine the differences between a low fat, high fiber (LFHF) diet and a
standard National Cancer Institute (NCI) diet supplemented with a soy-based
beverage and encapsulated F\0Cs with respect to serum carotenoid and tocopherol
levels, dietary intake, anthropometry, and health- related quality of life (HRQOL)
[17]. We used this study to examine the affect body size and physical activity has
on HRQOL and disease recurrence in ovarian cancer survivors. To best of our
knowledge no previous studies have compared effectiveness of maintaining a
normal body size and level of physical activity in this way. Investigating such
aims may help to reveal the benefits associated with these behaviors among
ovarian cancer survivors. We hypothesized that an ovarian Cancer survivors that
meet current guidelines for physical activity (30 minutes/day ≥ days/week) will be
associated with better HRQOL scores. Also women with larger waist
circumferences (WC) (> 88 centimeters) and obesity status (BMI ≥ 30 kg/m2)
will be associated with worse HRQOL scores. Lastly, we believe lifestyle
behaviors will be associated with recurrence-free survival.
Methods
Ovarian cancer survivors were identified between 2003 and 2009 from
The University of Texas MD Anderson Cancer Center patient database. Survivors
were eligible if they (a) were 21 years of age or older; (b) were diagnosed with
epithelial ovarian cancer ≥ stage IIA; (c) had no evidence of recurrent or
progressive disease at the time of recruitment; (d) were in their first clinical
remission (cancer antigen [CA]-125 levels≤35.0 units/mL) and computed
tomography scans of the abdomen/pelvis or second-look surgery showed no
evidence of ovarian cancer for the duration of the study; (e) were able to speak or
read English; (f) were ambulatory/mobile and able to eat whole foods; (g) had a
life expectancy of ≥6 months; (h) had a body mass index (BMI)≥19.5; and (i) had
completed treatment ≥6 months before the intervention. Women were excluded
from the study if they (a) were pregnant or lactating; (b) had been diagnosed with
a comorbidity that necessitated a restricted diet or medication for which a highfiber diet was a contraindication; or (c) had evidence of bowel obstruction. Data
was obtained from the tumor registry regarding ethnicity, age at diagnosis, time
since diagnosis, age at randomization, and disease stage at diagnosis of the
eligible participants. This study was approved by the Institutional Review Board
at MD Anderson Cancer Center.
Anthropometric indicators and medical characteristics (i.e., height,
weight, and waist and hip circumferences) were assessed at baseline and 6 months
by trained staff. To minimize variability in the measurements, one trained staff
member measured all study participants. For the purposes of this study, we
focused on weight and waist-to-hip ratios. Medical characteristics (i.e., age, stage,
race, and data of diagnosis) were ascertained using the MD Anderson clinical
database.
PA was assessed with a self-administered instrument designed for the
Women’s Health Initiative. PA was calculated separately for light (metabolic
equivalent tasks [MET] level < 3.0), moderate (MET level 3.0-5.9), and vigorous
(MET level _ 6.0) activities. A variable was also created for moderate-to-vigorous
PA (MET level _ 3.0), which was then used to create a dichotomous variable
(‘‘meeting PA guidelines’’) based on a cutoff of 10.0 MET hours/week, which
equaled approximately 150 minutes/week of moderate-paced walking or the
equivalent of other exercise durations and/or intensities. The cutoff used here was
consistent with the current recommendations of the Centers for Disease Control
and Prevention for PA24 and has been validated in previous studies.[18]
HRQOL was assessed at baseline and 6 months using the SF-36Health
Survey [19]. The SF-36 measures levels of health by asking questions pertaining
to physical and mental well-being. It includes a total of four subscales each for
mental (emotional well-being, vitality, role limitations due to emotional problems,
and social functioning) and physical (physical functioning, general health
perceptions, bodily pain, and role limitations due to physical health problems)
wellbeing.
Subscale scores range from 0 to 100, with higher scores indicating better
health. The reliability and validity of the SF-36 have been established, and the
instrument has been used in various populations of cancer survivors [20].
The study participants were characterized with simple descriptive
statistics. We then used Analysis of Covariance (ANCOVA) to examine the
associations between lifestyle behaviors (i.e., PA, BS, and obesity status) and
health related quality of life. For the purposes of the ANCOVA we focused on
overall quality of life and the physical and mental health summary scores. Cox
proportional hazard models were used to examine the association between
lifestyle characteristics. Covariates in the ANCOVA models included age at
randomization, years out from diagnosis, stage at diagnosis, and either LTPA
METS (for WC and BMI categories) or BMI (for LTPA categories). All Cox
proportional hazard models were adjusted for stage at diagnosis, and either LTPA
METS (for WC and BMI categories) or BMI (for LTPA categories). All statistical
tests were two sides and statistical significance was determined at alpha < 0.05.
Results
Descriptive characteristics of study participants by intervention condition
Table 1. Descriptive characteristics of study participants by intervention condition
FVJC Group
LFHF Group
(N=27)
(N=24)
P-value
Age, in years
Mean ±SD
51.7±9.4
55.7±10.1
30-49, n (%)
11 (40.7)
6 (25.0)
50-69
14 (51.9)
15 (62.5)
70+
2 (7.4)
3 (12.5)
0.154
0.672
Years since diagnosis
Median (5%, 75%)
1.6 (1.1 – 4.5)
1.5 (1.1 – 3.5)
0.542
0.389
Stage at diagnosis
II
4 (14.8)
8 (33.3)
III
23 (85.2)
16 (66.6)
IV
0 (0.0)
1 (4.1)
Race/ethnicity
White
24 (88.9%)
20 (83.3%)
0.217
600 (180, 1020)
630 (221, 1253)
0.999
28.8±7.0
27.1±6.1
0.381
MET-minutes of PA/week
Median (5%, 75%)
BMI (kg/m2)
Mean ±SD
Obese (>30 kg/m2)
8 (29.6%)
8 (33.3%)
LFHF = low-fat and high-fiber condition; FVJC = fruit, vegetable, and juice concentrate condition;
SD=standard deviation, MET=metabolic equivalent; PA=physical activity; BMI=body mass index.
Descriptive Characteristics
We identified 206 ovarian cancer survivors who were eligible to
participate in the ONE Study; however, only 51 (25%) survivors opted to
participate and provided written informed consent. No differences were observed
between the intervention groups in terms of medical and demographic
characteristics. On average, participants were 50-59 years old, 1.6 years out from
diagnosis, diagnosed with stage III disease, white, and overweight (60% had BMI
≥ 25) at baseline (Table 1).
Lifestyle Behaviors
Because there were no differences between intervention conditions we
collapsed our data. Half (49%) of the women participating in the ONE Study were
meeting current guidelines for physical activity (150 minutes of moderate to
vigorous physical activity per week). In addition, more than half (59%) of our
women were obese (BMI ≥ 30 kg/m2) and approximately 29% were found to
display characteristics of abdominal obesity (waist circumference > 88
centimeters).
Associations between lifestyle behaviors and health related quality of life
Table 2. Associations between lifestyle behaviors and health related quality of life
Waist Circumference
Obesity Status
Physical Activity
< 88 cm
≥ 88 cm
p
value
Not
Obese
Obese
p
value
Meeting
Guidelines
Not
Meeting
Guidelines
P
value
Overall
Quality
of Life
79.6(2.9)
70.8(5.9)
0.171
83.9
(3.8)
73.1
(3.5)
0.049
76.5 (19.4)
79.4 (17.0)
0.884
Mental
Health
78.9
(3.3)
73.2
(6.2)
0.423
84.7
(4.1)
72.3
(3.8)
0.039
77.3 (4.1)
78.8 (3.8)
0.802
Physical
Health
80.3
(3.3)
68.5
(6.2)
0.102
83.0
(4.4)
73.8
(4.1)
0.142
78.1 (4.0)
78.1 (3.8)
0.999
Adjusted associations between lifestyle characteristics and HRQOL
outcomes are reported in Table 2. The results show participants whose waist
circumferences were below 88 cm had a 8.8 point higher overall HRQOL score; a
5.7 point higher mental health score; and a 11.8 point physical health score than
those whose WC was ≥88 cm (all P < 0.05). Those with a BMI below obesity
(BMI ≥ 30 kg/m2) had 10.8-point higher overall HRQOL score; a 12.4 point
higher mental health (MH) score; and a 9.2 point higher physical health score than
those whose BMI was ≥ 30 kg/m2 (all P < 0.05).
Associations between lifestyle behaviors and ovarian cancer recurrence
Table 3. Associations between lifestyle behaviors and ovarian cancer
recurrence
No of Disease
Recurrences/Total No.
Hazard Ratio
Normal
Group
At risk
95% CI
Waist Circumference
12/24
6/9
0.71 (0.25 – 2.04)
Median time to recurrence
4.36 years
3.12 years
Body Mass Index
11/24
7/9
Median time to recurrence
4.57 years
2.94 years
Physical Activity
9/16
9/15
Median time to recurrence
3.79 years
4.46 years
0.59 (0.19 – 1.73)
0.92 (0.35 – 2.41)
Engaging in physical activity and maintaining a normal body size (i.e.,
WC or normal weight) was not significantly associated with recurrence free
survival (See Table 3). Recurrence free survival was greater for the non-obese,
women who with smaller waist circumferences and women who were not meeting
guidelines for physical activity when compared to women who did not display
these characteristics. All hazard ratios were statistically nonsignificant (all P >
0.05).
Discussion
In this study, we found that ovarian cancer survivors with a normal BMI
and WC are shown to have a higher overall quality of life and mental health than
those survivors who were obese or those with a waist circumference above 88 cm.
Similarly, these women had better recurrence free survival, albeit not statistically
significant. On the other hand, our research showed physical activity was not
associated with any of our study outcomes. To our knowledge, this is one of the
first studies conducted among ovarian cancer patients to demonstrate associations
between physical activity, body size, and health outcomes. Overall, these data
support previous studies suggesting that having a larger body size may contribute
to adverse health outcomes among ovarian cancer survivors.
Few published data have examined the association between weight related
measures and HRQOL outcomes in either women or men. Previous studies show
men with a high waist circumference have a poor quality of life with symptoms of
impaired physical and psychological [21]. These similar results prove the
consequences an unhealthy weight can affect adversely ovarian cancer survivors.
More research is needed to validate the clinical significance of healthy body
conditions among ovarian cancer survivors. Previous studies have shown that
obesity is associated with poor physical and mental health status as well as their
individual indicators, independent of self-reported PA [22-23].
We are not sure why meeting guidelines for physical activity was not
associated with HRQOL among our study participants. It could be that the 600minute Metabolic Equivalent threshold may be too high for this population given
the severity of treatment. Distal stage at diagnosis for this population is associated
with dismal survival and HRQOL outcomes. It could be that the majority of the
women in this sample participated in mild to moderate activity and may be well
below the 600-minute Metabolic Equivalent threshold. More research is needed to
determine what types of physical activity are associated with HRQOL in this
vulnerable population of cancer survivors.
Limited data exist on the associations between lifestyle characteristics and
ovarian cancer prognosis. Previous studies examining these associations have
focused primarily on dietary intake, but few studies have reported on weight
status or PA. Our small sample size limited us for identifying associations
between lifestyle characteristics and recurrence-free survival. Larger sample sizes
are needed to adequately assess these relationships. In view of the significant
associations we observed between body size and HRQOL, we believe that these
indicators may increase recurrence rates in this population. Although our
associations between PA and HRQOL were not promising, we believe that
physical activity will improve ovarian cancer prognosis.
The limitations of this study are its small sample size and use of selfreported measures. Despite these inherent limitations, this study had a number of
notable strengths, including being among the first studies to assess the association
between lifestyle characteristics and health outcomes among ovarian cancer
survivors. Other notable strengths include validated measures for PA and HRQOL
and objective assessments of weight status.
In conclusion, this study provided evidence that distal stage ovarian cancer
survivors with normal body size tend to have a healthier overall quality of life,
mental, and physical health. These data as well as others suggest that ovarian
cancer survivors displaying characteristics of obesity might benefit from
interventions designed to reduce weight. Future studies are needed in larger
populations to characterize adequately the association between lifestyle behaviors
and health outcomes in this population.
Acknowledgements
The authors thank the participants in this intervention, especially those
who were not able to see this study come to fruition. We would like to thank
NSA, the developers of Juice Plus. We also express our gratitude to Maria Rocio
Moguel for her technical assistance.
References
1.
Skirnisdottir, I. and B. Sorbe, Prognostic impact of body mass index and effect of
overweight and obesity on surgical and adjuvant treatment in early-stage epithelial
ovarian cancer. Int J Gynecol Cancer, 2008. 18(2): p. 345-51.
2.
Santamaria, F., S. Montella, and A. Pietrobelli, Obesity and pulmonary disease:
unanswered questions. Obes Rev, 2012.
3.
Katzmarzyk, P.T., et al., Body mass index and risk of cardiovascular disease, cancer and
all-cause mortality. Can J Public Health, 2012. 103(2): p. 147-51.
4.
Maruthur, N.M., et al., Body mass index and colon cancer screening: a systematic review
and meta-analysis. Cancer Epidemiol Biomarkers Prev, 2012. 21(5): p. 737-46.
5.
Parekh, N., U. Chandran, and E.V. Bandera, Obesity in Cancer Survival. Annu Rev Nutr,
2012.
6.
Haakinson, D.J., et al., The Impact of Obesity on Breast Cancer: A Retrospective Review.
Ann Surg Oncol, 2012.
7.
Ligibel, J., Obesity and breast cancer. Oncology (Williston Park), 2011. 25(11): p. 9941000.
8.
Anderson, A.S. and S. Caswell, Obesity management--an opportunity for cancer
prevention. Surgeon, 2009. 7(5): p. 282-5.
9.
Yang, H.S., et al., Effect of obesity on survival of women with epithelial ovarian cancer:
a systematic review and meta-analysis of observational studies. Int J Gynecol Cancer,
2011. 21(9): p. 1525-32.
10.
Lahmann, P.H., et al., Anthropometric measures and epithelial ovarian cancer risk in the
European Prospective Investigation into Cancer and Nutrition. Int J Cancer, 2010.
126(10): p. 2404-15.
11.
Protani, M.M., C.M. Nagle, and P.M. Webb, Obesity and Ovarian Cancer Survival: A
Systematic Review and Meta-analysis. Cancer Prev Res (Phila), 2012. 5(7): p. 901-10.
12.
Fong, D.Y., et al., Physical activity for cancer survivors: meta-analysis of randomised
controlled trials. BMJ, 2012. 344: p. e70.
13.
Cottreau, C.M., R.B. Ness, and A.M. Kriska, Physical activity and reduced risk of
ovarian cancer. Obstet Gynecol, 2000. 96(4): p. 609-14.
14.
Yang, L., et al., Predictors of ovarian cancer survival: a population-based prospective
study in Sweden. Int J Cancer, 2008. 123(3): p. 672-9.
15.
Moorman, P.G., et al., Recreational physical activity and ovarian cancer risk and
survival. Ann Epidemiol, 2011. 21(3): p. 178-87.
16.
Stevinson, C., et al., Physical activity in ovarian cancer survivors: associations with
fatigue, sleep, and psychosocial functioning. Int J Gynecol Cancer, 2009. 19(1): p. 73
17.
Paxton, Raheem J., et al., Randomized Parallel-Group Dietary Study for Stages II-IV
Ovarian Cancer Survivors. elsevier, 2012
18.
Kolahdooz F, lbiebele Tl, van der PolsJC, Webb PM. Dietary patterns and ovarian
cancer risk. Amj Clin Nutr 2009;89:297-304.
19.
Ware Jr JE. Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I.
Conceptual framework and item selection. Med Care 1992;30:473-83.
20.
Goodwin PJ, Black JT, Bordeleau LJ, Ganz PA. Health-related quality-of-life mea
surement in randomized clinical trials in breast cancer-taking stock] Nat!Cancer Inst
2003;95:263-81.
21.
Bandura A. Self-efficacy: toward a unifYing theory of behavioral change. Psycho! Rev
1977;84:191-215.
22.
Han, T.S., et al., Impaired quality of life and sexual function in overweight and obese
men: the European Male Ageing Study. Eur J Endocrinol, 2011. 164(6): p. 1003-11.
23.
Mosher, Catherine E., et al,, Assocations between lifestyle factors and quality of life
among older long term breast, prostate, and colorectal cancer survivors. Cancer, 2009