Received: 13 September 2018
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Revised: 19 August 2019
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Accepted: 14 October 2019
DOI: 10.1111/ecc.13186
ORIGINAL ARTICLE
The effects of exercise on insulin, glucose, IGF-axis and CRP
in cancer survivors: Meta-analysis and meta-regression of
randomised controlled trials
Yafeng Wang1 | Ben Jin2 | Raheem J. Paxton3 | Weili Yang4 | Xirui Wang5 |
Yurui Jiao6 | Chuanhua Yu1 | Xiong Chen7
1
Department of Epidemiology and
Biostatistics, School of Health Sciences,
Wuhan University, Wuhan, China
2
Department of Urology, The First Affiliated
Hospital of Xi'an Jiaotong University, Xi'an,
China
3
Department of Community Medicine
and Population Health, The University of
Alabama, Tuscaloosa, AL, USA
4
Department of Pediatric Surgery, The
Second Affiliated Hospital of Xi'an Jiaotong
University, Xi'an, China
5
Department of Epidemiology and
Biostatistics, Xi'an Jiaotong University, Xi'an,
China
6
Department of endocrinology, The Second
Hospital of Shanxi Medical University,
Taiyuan, China
7
Department of Endocrinology, The First
Affiliated Hospital of Wenzhou Medical
University, Wenzhou, China
Correspondence
Chuanhua Yu, School of Health Sciences,
Wuhan University, Wuhan, Hubei, China.
Email: YuCHua@whu.edu.cn
Abstract
Background: The purpose of this study was to investigate the relationship between
physical activity and biological mediators of cancer recurrence and survival.
Methods: We conducted a comprehensive literature search of PubMed, ScienceDirect
and Web of Science for randomised controlled trials examining the association between physical activity and C-reactive protein (CRP), glucose, insulin, insulin resistance and insulin growth factor-one (IGF-1) up to December 2017. Standardised mean
difference (SMD) scores were calculated, and meta-regression was performed.
Results: The meta-analysis indicated that survivors randomised to physical activity conditions experienced greater improvements in Insulin (SMD = −0.59; 95%
CI, −1.05 to −0.14), CRP (SMD = −0.52; 95% CI, −0.87 to −0.17), insulin resistance
(SMD = −0.20; 95% CI, −0.41 to −0.003) and glucose (SMD = −0.19; 95% CI, −0.35 to
−0.02) than survivors randomised to control conditions. The meta-regression showed
that study duration was positively, albeit marginally related (p = .056) to change in
CRP levels among survivors in the physical activity conditions. Furthermore, higher
baseline insulin levels in the physical activity conditions were associated with improving insulin levels throughout the intervention (p = .007).
Conclusions: Promoting physical activity throughout the survivorship continuum is
an effective intervention strategy for improving levels of insulin, glucose control, in-
Xiong Chen, Department of Endocrinology,
The First Affiliated Hospital of Wenzhou
Medical University, Wenzhou, Zhejiang,
China.
Email: chasecx@126.com
sulin resistance and CRP among cancer survivors.
KEYWORDS
cancer survivors, CRP, exercise, meta-analysis, glucose, IGF-axis, insulin, meta-regression
1 | I NTRO D U C TI O N
completion (Hill et al., 2014; Schover et al., 2014; Seth, Singh, Seth, &
Sapra, 2017). Encouragingly, engaging in healthy lifestyle behaviours
Scientific advancements in cancer treatment during the past 30 years
my shield survivors from late effects and improve their overall health
have resulted in improvements in cancer-specific and overall survival
and well-being (Pierce et al., 2007; Turner et al., 2018).
rates (Torre et al., 2015). Despite significant improvements, survivors
Despite the benefits of a healthy lifestyle, many fail to meet the
experience significant deficits in overall health and well-being (Brown
health guidelines proposed by the American Cancer Society (Rock
et al., 2003). In fact, many experiences late effects (e.g., infertility, car-
et al., 2012). Of all the guidelines, the health benefits of physical
diovascular injury and fatigue) persist for years following treatment
activity have been the most consistently documented (US Cancer
Eur J Cancer Care. 2019;00:e13186.
https://doi.org/10.1111/ecc.13186
wileyonlinelibrary.com/journal/ecc
© 2019 John Wiley & Sons Ltd
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WANG et Al.
Statistics Working Group, 2007). In particular, several meta-analytic
cancer; the outcomes included HOMA, glucose, insulin, IGF-1 or CRP
studies have confirmed the relationship between physical activity
with corresponding mean and standard deviations for each condition.
and improved survival (Spei et al., 2019; Wu et al., 2016; Yeganeh,
The exclusion criteria included participants were ≤18 years at study
Harrison, Vincent, Teede, & Boyle, 2018). Studies have speculated
enrolment; the outcome reported only median and range values;
that the same biological mediators that escalated one's risk for cancer
and whether multiple studies reported results from the same study
initiations and metastasis (i.e., glucose tolerance, insulin sensitivity
population. Two reviewers independently carried out the literature
and inflammation) may be the same culprits in determining cancer
search and study selection. Any disagreements on the inclusion of
recurrence and survival rates (Bastard et al., 2000; Frank et al., 2005).
studies were resolved by a third reviewer.
However, limited data exist on the biological mechanisms underlying
the relationship between physical activity, recurrence and survival. In
cancer survivors, several studies have investigated the exercise-in-
2.3 | Data extraction and quality assessment
duced changes in physiological biomarkers. However, the results
have been inconsistent and the exercise-induced changes appear to
A standardised form was used to extract data from each study. The
differ among cancer sites (Fong et al., 2012; Kang et al., 2017).
following extracted information included characteristics of the
The purpose of this study was to address the gaps in the literature
study (first author, year of publication, study location, sample size,
by conducting a meta-analysis to evaluate the effect of physical activ-
the mean age, gender, mean body mass index (BMI), %body fat, the
ity interventions on insulin, insulin resistance, glucose, insulin growth
baseline insulin level, cancer type and cancer stage), characteristic of
factors (IGF) and related binding proteins (BP), and C-reactive protein
the physical activity intervention and control condition (i.e., exercise
(CRP) in cancer survivors. The proposed study expands upon prior me-
type, duration, frequency, intensity and treatment for the control
ta-analyses by addressing some of the methodological limitations that
group) and results (changes in insulin, HOMA, glucose, IGF-axis and
may have contributed to inconsistent findings (Fong et al., 2012; Kang
CRP). Two researchers independently extracted relevant data using a
et al., 2017; Meneses-Echávez et al., 2016). In particular, we propose
standardised excel template. Any discrepancies between two reviewers
to adjust for potential confounding factors such as lifestyle and study
were discussed, and a consensus was achieved. The two reviewers also
characteristics, which may influence the results. In addition, we pro-
assessed risk of bias by using Cochrane Collaboration risk assessment
pose to conduct a meta-regression model to comprehend the indepen-
tools for randomised controlled trials (Higgins & Green, 2011).
dent effects of physical activity on each individual biological marker.
2 | M E TH O DS
2.4 | Statistical analysis
Given that different measurements were used for each outcome,
2.1 | Search strategy
we calculated standardised mean difference (SMD) scores with 95%
confidence intervals (CIs). Statistical heterogeneity was assessed using
The meta-analysis was performed in accordance with the preferred
the I2 test and Cochran's Q statistic (I2 values > 50% indicated the
reporting items for systematic reviews and meta-analyses criteria
existence of heterogeneity and p < .10 indicated a statistical significance).
described elsewhere (Moher, Liberati, Tetzlaff, & Altman, 2010). A
When there was no significant heterogeneity, a fixed-effects model
comprehensive literature search was conducted for all relevant stud-
was used; otherwise, a random-effects model was used. To explore the
ies published in PubMed, ScienceDirect and Web of Science before
potential for heterogeneity, meta-regression and subgroup analyses
January 2017 using the following keywords: “cancer OR neoplasm
were carried out. Subgroup analysis was also performed according to
OR tumor” AND “physical activity OR exercise OR resistance OR
cancer type. In addition, we conducted a sensitivity analysis to assess
strength OR stretching” AND “randomized controlled trial OR con-
the stability of the pooled results by removing one study at a time.
trolled clinical trial OR randomized OR trial.” A detailed description of
Publication bias was evaluated with the Begg's and Egger's tests. All
the Boolean Search criteria was included in Appendix S1. To ensure
statistical analyses were performed with Stata version 11.0 (STATA). A
that we captured additional articles, we expanded the comprehen-
two-sided p value of ≤.05 was considered statistically significant.
sive literature search to December 2017. Furthermore, no language
restrictions were imposed, and the reference list of retrieved articles
was also searched for relevant studies.
2.2 | Selection criteria
3 | R E S U LT S
3.1 | Characteristics of included studies
A total of 11,057 potentially eligible articles were identified via
The included studies fulfilled the following inclusion criteria: study
our online search. After eliminating duplicates, 9,960 articles were
design was limited to RCT; the study compared a physical activity
selected for further screening, with 123 articles being thoroughly
intervention with a control group; adults were diagnosed with any
assessed for potential eligibility. After reviewing the full text of these
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articles, only 15 articles were deemed eligible for our meta-analysis
when compared to the control condition (SMD = −0.59; 95% CI,
(Bower et al., 2014; Cormie et al., 2015; Fairey et al., 2003; Galvão,
−1.05 to −0.14; p = .011; see Figure 2a). The analysis also indicated
Taaffe, Spry, Joseph, & Newton, 2010; Guinan et al., 2013; Irwin et
significant between-study heterogeneity (I2 = 86.0%; see Table 2),
al., 2009; Janelsins et al., 2011; Jones et al., 2013; Lahart, Metsios,
but no publication bias. We also observed greater reductions in
Nevill, Kitas, & Carmichael, 2016; Ligibel et al., 2008; Nuri et al.,
glucose (SMD = −0.19; 95% CI, −0.35 to −0.02; p = .024) and insulin
2012; Nuri, Moghaddasi, Darvishi, & Izadpanah, 2016; Schmitz,
resistance (HOMA: SMD = −0.20; 95% CI, −0.41 to −0.003; p = .046)
Ahmed, Hannan, & Yee, 2005; Sprod et al., 2012; Thomas, Alvarez-
among survivors in the intervention conditions when compared
Reeves, Lu, Yu, & Irwin, 2013) (Figure 1).
to the control groups. No between-study heterogeneity or bias
The characteristics of the included studies are summarised
was observed for glucose (I2 = 33.8%; see Figure 2b) nor insulin
in Table 1. Among the included studies, there were a total of 793
resistance (I2 = 46.7%; see Figure 2c). Clinically and statistically
participants distributed roughly proportional in the intervention
significant mean differences in CRP (SMD = −0.52; 95% CI, −0.87 to
(n = 403) and control (n = 390) conditions. Studies were conducted
−0.17; Figure 2d) were observed between intervention and control
in United States (n = 8), Australia (n = 2), Iran (n = 2), the United
conditions, with significant between-study heterogeneity. However,
Kingdom (n = 1), Canada (n = 1) and Ireland (n = 1). The studies fo-
it should be noted that survivors in the physical activity conditions
cused primarily on breast cancer survivors (n = 12), with few focus-
did not differ from the control conditions with respect to IGF-1
ing on prostate (n = 2) or colorectal cancer (n = 1) survivors. The
(SMD = −0.09; 95% CI, −1.34 to 1.16; p = .89) with no evidence of
age of survivors in the intervention conditions ranged from 52.4 to
heterogeneity (I2 = 94.9%; see Table 2) or bias.
69.6 years old, whereas the age range of survivors in the control conditions ranged from 52.7 to 70.1 years old. Study duration varied
widely from 6 weeks to 12 months.
3.3 | Exploratory heterogeneity analysis
The meta-regression showed that baseline insulin levels may be the
3.2 | Changes in insulin, HOMA, glucose, CRP and
IGF-1
main source of heterogeneity in the meta-analysis (Figure 3b). In
particular, higher baseline insulin levels in physical activity conditions
were associated with a greater decrease in insulin levels throughout
The results of the meta-analysis indicated that survivors in the
the study (slope = −0.12, 95% CI, −0.20 to −0.04; p = .007; Figure 3b).
physical activity condition experienced greater reductions in insulin
Body size (i.e., body fat and BMI) and intervention duration were not
F I G U R E 1 Flow chart for the selection
of eligible studies
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TA B L E 1
Characteristics of 15 randomised controlled trials included in meta-analysis of effect of exercise in cancer survivors
Sample
Age
Intervention
|
Author
Cancer type
Country
Janelsins et al.
(2011)
Breast cancer
USA
Lahart et al. (2016)
Breast cancer
UK
Exercise
group
Control
group
Exercise
group
Control
group
9
10
54.3 ± 10.6
40
40
52.4 ± 10.3
Study
quality
Exercise group
Control group
Duration
Outcome
52.7 ± 6.7
Tai chi chuan
exercise
Non-physical activity control
3 months
Insulin, IGF−1,
HOMA
A
54.7 ± 8.3
Home-based PA
intervention
Usual care
6 months
Insulin
A
Irwin et al. (2009)
Breast cancer
USA
37
38
56.4 ± 9.5
55.6 ± 7.7
Aerobic exercise
Usual care
6 months
Insulin, IGF−1
A
Fairey et al. (2003)
Breast cancer
Canada
25
28
59 ± 5
58 ± 6
The exercise group
The delayed control group
15 weeks
Insulin, Glucose,
IGF−1
A
Schmitz et al.
(2005)
Breast cancer
USA
39
40
53.3 ± 8.7
52.8 ± 7.6
Weight training
The delayed control group
6 months
Insulin, Glucose,
IGF−1, HOMA
A
Ligibel et al. (2008)
Breast cancer
USA
51
49
52 ± 9
53 ± 9
Strength training
exercise
intervention
Usual care
4 months
Insulin, Glucose,
HOMA
A
Jones et al. (2013)
Breast cancer
USA
36
31
56.4 ± 9.6
55.4 ± 7.6
Aerobic exercise
intervention
Usual care
6 months
CRP
A
Guinan et al. (2013)
Breast cancer
Ireland
16
10
50.1 ± 8.3
45.1 ± 9.0
Aerobic programme
Control group
3 months
Insulin, Glucose,
CRP, HOMA
A
Nuri et al. (2012)
Breast cancer
Iran
14
15
NA
NA
Combined training
Control group
15 weeks
Insulin, Glucose,
HOMA
A
Sprod et al. (2012)
Breast cancer
USA
9
10
54.3 ± 3.6
52.7 ± 2.1
Tai chi chuan
exercise
Control group
3 months
Insulin, Glucose,
IGF−1
A
Bower et al. (2014)
Breast cancer
USA
16
15
NA
NA
Yoga
Control group
3 months
CRP
A
Thomas et al. (2013)
Breast cancer
USA
35
30
56.5 ± 9.8
55.1 ± 7.6
Moderate-intensity
aerobic exercise
Usual care
6 months
Glucose
A
Nuri et al. (2016)
Colorectal
cancer
Iran
15
15
NA
NA
Training group
Control group
2 months
Insulin, Glucose,
HOMA
A
Cormie et al. (2015)
Prostate
cancer
Australia
32
31
69.6 ± 6.5
67.1 ± 7.5
Supervised exercise
Usual care
3 months
Insulin, Glucose,
CRP
A
Galvão et al. (2010)
Prostate
cancer
Australia
29
28
69.5 ± 7.3
70.1 ± 7.3
The exercise group
Usual care
3 months
Insulin, Glucose,
CRP
A
Abbreviations: CRP, c-reactive protein; HOMA, homeostasis model assessment; IGF-1, insulin-like growth factor-1; NA, not available.
WANG et Al.
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significantly related to changes in insulin, HOMA, glucose and IGF-1
compared to survivors in controlled conditions. In our subgroup
Figure 3a, c, and d). Results of the sensitivity analysis indicated that
analysis, it appeared that changes in CRP were more pronounced
insulin level change remained stable (Figure 4). In addition, we found
in breast and prostate cancer survivors. The sensitivity analysis
that the Schmitz et al. study was a primary source of heterogeneity
indicated that caution is warranted when interpreting the impact of
and excluding this study resulted in stabilising the results (see
physical activity intervention on levels IGF-1, HOMA and glucose
Figure 5). The meta-regression indicated that the duration of the
in cancer survivors. Furthermore, our meta-regression analysis
intervention was marginally accounted for the relationship between
indicated that having high baseline insulin levels and study duration
the physical activity and change in CRP levels (slope = 0.26, 95% CI,
influenced the impact of the intervention on insulin and CRP levels,
−0.01 to 0.53; p = .056; Figure 6). The subgroup analysis showed
respectively. Overall, these data provide evidence compelling
that significant mean changes in CRP levels were more pronounced
evidence physical activity intervention may influence markers
in prostate cancer survivors (SMD = −0.63; 95% CI, −1.00 to −0.26;
associated with the IGF-axis and inflammatory pathways.
p = .004) than it was for breast cancer survivors (SMD = −0.49; 95%
CI, −1.04 to 0.07; p = .087; see Table 2).
In our study, we observed that survivors enrolled in physical
activity interventions experienced greater improvements in insulin,
glucose and insulin resistance than participants in the control conditions and that many of these changes may be related to having
4 | D I S CU S S I O N
high insulin levels at baseline. We were somewhat surprised that null
findings were observed with IGF-1. These findings add to the un-
The present meta-analysis evaluated the role that participating in
certainty of using plasm and serum levels of IGF-1 as an indicative
physical activity intervention had on biological mediators of cancer
marker (Fong et al., 2012; Kang et al., 2017; Meneses-Echávez et al.,
recurrence and survival. Results indicated that survivors who
2016; Zhu et al., 2016). In addition, significant heterogeneity was
participated in physical activity intervention experienced greater
observed for IGF-1, which was minimised after removing a study.
improvements in insulin, glucose, insulin resistance and CRP when
Therefore, exercise might improve IGF-1 in breast cancer survivors,
FIGURE 2
CRP
Meta-analysis for the effect estimate of exercise on insulin, glucose, HOMA and CRP. (a) insulin; (b) glucose; (c) HOMA; (d)
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TA B L E 2
WANG et Al.
Subgroup analysis in meta-analysis of effect of exercise in cancer survivors
Subgroup
N
SMD
Lower
Upper
PSMD
Q
I2
PH
HOMA
All
7
−0.20
−0.41
0.00
0.046
11.26
46.70%
0.081
Breast cancer
6
−0.19
−0.40
0.02
0.073
11.06
54.80%
0.050
Colorectal cancer
1
−0.36
−1.08
0.36
0.328
11
−0.19
−0.35
−0.02
0.024
15.10
33.80%
0.128
0
Glucose
All
Breast cancer
8
−0.15
−0.34
0.04
0.119
14.17
50.60%
0.048
Prostate cancer
2
−0.33
−0.69
0.03
0.075
0.19
0.00%
0.663
Colorectal cancer
1
−0.17
−0.89
0.54
0.635
0
Insulin
All
Breast cancer
12
−0.59
−1.05
−0.14
0.011
78.80
86.00%
<0.001
9
−0.81
−1.41
−0.21
0.008
71.04
88.70%
<0.001
0.29
0.00%
0.591
Prostate cancer
2
0.09
−0.27
0.45
0.628
Colorectal cancer
1
−0.31
−1.03
0.41
0.396
All
5
−0.09
−1.34
1.16
0.89
77.68
94.90%
<0.001
Excluding one study
4
−0.76
−1.08
−0.44
<0.001
4.31
30.40%
0.230
IGF-I
CRP
All
6
−0.52
−0.87
−0.17
0.004
10.71
53.30%
0.058
Breast cancer
4
−0.49
−1.04
0.07
0.087
9.00
66.70%
0.029
Prostate cancer
2
−0.63
−1.00
−0.26
0.001
0.47
0.00%
0.493
Abbreviations: CRP, c-reactive protein; HOMA, homeostasis model assessment; IGF-1, insulin-like growth factor-1.
but further studies were required to draw a definitive conclusion.
Prior systematic review and meta-analytic studies have indicated
The results we observed with markers associated with the IGF-
that participating in regular physical activity is associated with a re-
axis resemble those observed in non-cancer populations (Kasapis
duction in CRP (Fedewa, Hathaway, & Ward-Ritacco, 2017; Kasapis
& Thompson, 2005) and a recent study promoting aerobic and re-
& Thompson, 2005), which correspond with reduction in body size.
sistance training (Kang et al., 2017; Ligibel et al., 2008; Meneses-
Similarly, Kang et al. (2017) observed a meaningful reduction of CRP
Echávez et al., 2016). It should be noted that our data differs from
levels in response to the exercise interventions. The results of our
that of a prior meta-analysis performed in breast cancer survivors
meta-analysis confirm the results of prior review and meta-analytic
(Löf, Bergström, & Weiderpass, 2012). Some have suggested that
studies with respect to reduction in CRP. Importantly, the results
physical activity-induced changes in biological markers are depen-
appeared to be more pronounced in prostate cancer survivors. In ad-
dent on changes in body size or high baseline insulin levels (Gunter
dition, longer duration will weaken the effect of physical activity on
et al., 2009; Ligibel et al., 2008; Pasanisi et al., 2006). However, our
CRP levels throughout the study. Unfortunately, we were not able
meta-regression only partially confirmed these suggestions, with
to perform the meta-regression of effect of body size in the physical
greater support for the higher baseline insulin levels, but not for
activity and CRP relationships because no more than three studies
higher baseline body size (i.e., BMI and per cent body fat). Overall,
provided sufficient data on change in body size. Therefore, the fur-
results of the meta-analysis, subsequent meta-regression and test
ther RCTs investigating these associations are required to confirm,
for heterogeneity provide strong evidence indicating that physi-
whether these relationships differ by body size.
cal activity intervention may improve markers associated with the
There were a number of limitations that should be discussed.
IGF-axis and that survivors with high insulin levels may receive the
First, heterogeneity between intervention and control groups was
greatest benefits from these types of interventions. Subsequent me-
observed, which may affect the robustness of our results. In par-
ta-analyses with a larger variety of studies with relevant variables
ticular, there was significant heterogeneity between groups for
are required to confirm our results. Inconsistent with a previous
certain biomarkers, preventing us from moving further with the me-
meta-analysis, our results showed that physical activity can improve
ta-analysis for these variables. To minimise this limitation with the
insulin resistance (Fong et al., 2012). In our study, we included three
remaining variables, we performed the subgroup, sensitivity and me-
additional included studies, and smaller sample size in their study
ta-regression analyses to explore factors associated with heteroge-
can lead to the wider CIs.
neity. Secondly, our analysis was based on unadjusted data, without
WANG et Al.
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F I G U R E 3 Meta-regression of the BMI change, %body fat change, baseline insulin levels and intervention duration and insulin. (a) change
of the BMI; (b) baseline insulin levels; (c) %Body Fat change; (d) intervention duration
F I G U R E 4 Sensitivity analysis for the
effect estimate of exercise on insulin
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WANG et Al.
F I G U R E 5 Sensitivity analysis for the
effect estimate of exercise on IGF-1
adjusting for the confounding factors that might influence outcome
and duration, as well as baseline health characteristics are sources of
variables. Lastly, we were unable to examine the impact of exercise
heterogeneity in future meta-analyses. Furthermore, future meta-
type, intensity and duration of the results due to limitations of the
analytic work should consider adopting our analytic framework to
included studies. Despite these limitations, we were able to conduct
increase the robustness of their findings.
a number of statistical analyses to identify sources of heterogeneity
and bias resulting in a robust analytic framework that can be repli-
AC K N OW L E D G E M E N T S
cated in future studies.
None.
5 | CO N C LU S I O N
C O N FL I C T O F I N T E R E S T
The authors declare no conflict of interest.
In conclusion, physical activity is an effective intervention for
AU T H O R C O N T R I B U T I O N S
improving levels of insulin, insulin resistance, glucose and CRP
Conception and design of the study: YFW and CHY. Acquisition of
among cancer survivors. The results of our meta-analyses support
data and analysis: BJ, WLY, XRW and YRJ. Writing and revision of the
strong and consistent relationships between these variables, but
manuscript: YFW, RJP, CHY and XC. All authors read and approved
also identify variables that should be consistently reported on and
the final manuscript.
explored further. For example, more data are needed to determine
whether factors such as cancer treatment, exercise type, intensity
E T H I C A L A P P R OVA L
Every study included in the meta-analysis has been published after
the approval of an ethics committee, and each patient enrolled
signed a written consent. For this reason, the present meta-analysis
did not require further ethics committee approval.
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S U P P O R T I N G I N FO R M AT I O N
Additional supporting information may be found online in the
Supporting Information section.
How to cite this article: Wang Y, Jin B, Paxton RJ, et al. The
effects of exercise on insulin, glucose, IGF-axis and CRP in
cancer survivors: meta-analysis and meta-regression of
randomised controlled trials. Eur J Cancer Care.
2019;00:e13186. https://doi.org/10.1111/ecc.13186