PLoS ONE
Home Optimising weight-loss interventions in cancer patients—A systematic review and network meta-analysis
Optimising weight-loss interventions in cancer patients—A systematic review and network meta-analysis
Optimising weight-loss interventions in cancer patients—A systematic review and network meta-analysis

Competing Interests: BH has previously received honoraria from Eversana Incorporated for provision of methodologic advice related to the conduct of systematic reviews and meta-analysis. NL has previously received honoraria for participation in advisory boards from Lilly, Novartis, Pfizer, Roche, TerSera and research funds from Abbvie, Exact Sciences, Genomic Health and Lilly. All other authors have no conflicts to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Article Type: research-article Article History
Abstract

Background

Excess weight has been associated with increased morbidity and a worse prognosis in adult patients with early-stage cancer. The optimal lifestyle interventions to optimize anthropometric measures amongst cancer patients and survivors remain inconsistent.

Objective

To conduct a systematic review and network meta-analysis (NMA) of randomized controlled trials (RCTs) comparing the effects of exercise and dietary interventions alone or in combination on anthropometric measures of adult cancer patients and survivors.

Methods

A systematic search of Medline, Embase and the Cochrane Trials Registry was performed. Outcomes of interest included changes in weight, body mass index (BMI), and waist circumference. Screening and data collection were performed by two reviewers. Bayesian NMAs were performed.

Results

Overall, 98 RCTs were included; 75 were incorporated in NMAs (n = 12,199). Groups of intervention strategies included: 3 exercise interventions, 8 dietary interventions, 7 combination interventions of diet and exercise and standard care. Median intervention duration was 26 weeks. NMA suggested that diet alone (mean difference [MD] -2.25kg, 95% CrI -3.43 to -0.91kg) and combination strategies (MD -2.52kg, 95% CrI -3.54 to -1.62kg) were associated with more weight loss compared to standard care. All dietary interventions achieved a similar magnitude of weight loss (MD range from -2.03kg to -2.52kg). Both diet alone and combination strategies demonstrated greater BMI reductions versus standard care, and each of diet alone, exercise alone and combination strategies demonstrated greater reductions in waist circumference than standard care.

Conclusion

Diet and exercise alone or in combination are effective lifestyle interventions to improve anthropometric measures in cancer patients and survivors. All reputable diets appear to be similarly effective to achieve weight loss.

LeVasseur,Cheng,Mazzarello,Clemons,Vandermeer,Jones,Joy,Barbeau,Wolfe,Ahmadzai,Hersi,Stober,Shorr,Hilton,Hutton,and Ehlers: Optimising weight-loss interventions in cancer patients—A systematic review and network meta-analysis

Background

Being either overweight (body mass index (BMI) between 25–29.9 kg/m2) or obese (BMI >30 kg/m2) contributes to increased cancer-related mortality [14]. In addition, excessive energy intake and suboptimal levels of physical activity may influence the course of the disease, treatment efficacy and toxicity, as well as overall health, well-being and overall survival [512]. The importance of addressing obesity in cancer patients was demonstrated by the 2014 American Society of Clinical Oncology (ASCO) position statement outlining their commitment to promoting research delineating the relationship between obesity and cancer, as well as educating oncology care providers about best practices for weight control [13]. Subsequently, a summit on Advancing Obesity Clinical Trials in Cancer Survivors was convened to provide recommendations and highlighted the need to further evaluate the impact of energy balance on cancer outcomes and define the degree of benefit in various cancer survivor subgroups [14].

Studies in cancer patients and survivors have demonstrated that lifestyle changes such as increased physical activity and improved dietary quality can lead to weight control and weight loss [1518]. However, these interventions include a broad range of dietary interventions (e.g. low-fat, hypocaloric, and Mediterranean) and physical activity (e.g. aerobic and resistance training). Despite the rapidly increasing number of trials supporting the safety of exercise and dietary interventions in the adjuvant and post-treatment settings [1929], the optimal method to mitigate weight gain during cancer treatment and to achieve weight loss after treatment, across various early-stage cancers, has yet to be identified [14, 15]. While systemic reviews looking at the role of diet and exercise on weight in specific cancer subgroups have been undertaken [17, 18, 3033], no such reviews have directly compared the effect of various diet and exercise interventions to each other, alone or in combination, on anthropometric measures across various cancer types [3436]. Additionally, guidelines regarding weight management strategies have not focused on cancer patients and survivors [13].

The purpose of this systematic review was to explore and synthesize the available evidence evaluating the optimization of anthropometric measures through various diet, exercise and combination interventions, during and after cancer treatment, in adult patients with early stage cancer. In turn, this will allow for the identification of optimal intervention recommendations to address obesity in cancer patients and survivors, as well as determining gaps in the evidence that should be addressed by future research.

Methods

A protocol for the study was prepared a priori and followed throughout the review process; this protocol is provided in S1 Text. The PRISMA Extension Statement for Network Meta-Analysis was used to guide the reporting of this study [37].

Study question and inclusion criteria

This systematic review was designed to identify and synthesize the available data addressing the following research question framed in the Population-Intervention-Comparator-Outcome-Study Design (PICOS) framework: “Based on data from randomized controlled trials, what are the relative effects of competing weight loss strategies in terms of changes in anthropometric measures for patients with early stage cancer? The population of interest was adult cancer patients included in trials during and after treatment for early stage cancer of any type. Studies aiming to mitigate weight-loss or cachexia during cancer treatment were excluded. Studies including patients with advanced cancer were also excluded. The interventions of interest were lifestyle intervention strategies in the form of dietary interventions, exercise interventions and combinations thereof. All diet and exercise plans and comparisons versus standard of care were of interest. Interventions primarily leveraging counselling or behavioural therapy, and interventions comparing the method of intervention delivery were only included in the qualitative analysis. Outcomes of interest included change in body weight (in kilograms), body mass index (BMI), and waist circumference (WC). Only randomized studies were sought, with no restrictions on duration of intervention or patient follow-up. The longest available follow-up data while enrolled was used for data extraction.

Literature search

An information specialist (RS) designed and performed an electronic literature search to identify relevant articles. Ovid Medline (1946-September 2019), EMBASE (1947-September 2019) and the Cochrane Central Register of Controlled Trials (1993–September 2019) were searched to identify relevant citations. The search consisted of key terms (e.g. weight management, weight loss, energy intake, diet, exercise), related text word searches and was limited to English language studies. The reference sections of included papers were reviewed to identify additional relevant citations. The full literature search strategy is provided in S2 Text and was peer-reviewed using the PRESS framework by a second information specialist [38].

Study screening and study selection

Pairs of reviewers from the authorship team (NL, SM, MC, LV, CS, JH, AAJ) screened all citations independently. Stage 1 review consisted of screening titles and abstracts only. Stage 2 review consisted of screening the full texts of citations that were considered potentially relevant. After each stage reviewers (NL, SM, MC, LV, CS, JH, AAJ) resolved discrepancies through a third party if needed. The process of study selection is presented in a flow diagram [39].

Data collection and risk of bias assessment

Data collection from the included studies was performed by two reviewers (NL, SM) using a standardized data extraction template implemented in Microsoft Excel (version 10, Microsoft Corporation, Seattle, Washington, USA). A pilot test of the data collection form was performed on the first 5 studies and refined accordingly. Data items collected included the following: study design, patient eligibility criteria, patient demographics (e.g. type of malignancy, performance status, age distribution, menopausal status, and baseline measures of weight, BMI and waist circumference), intervention details (diet, exercise or combination regimen, along with corresponding details of each intervention), and outcome data (final values and/or changes in body weight, BMI, waist circumference). After data collection, the reviewers resolved any discrepancies and consulted a third party when needed.

Full text articles were independently assessed for risk of bias by 2 reviewers. The Cochrane Collaboration’s tool for assessing risk of bias in randomized trials was used [40]. The tool assessed potential areas of bias including selection bias, performance/detection bias, attrition bias and reporting bias. Discrepancies in the initial independent assessments were resolved by discussion. A narrative summary of findings from these assessments is provided in the main text, while a tabular summary of all assessments is provided in the review supplement.

Structuring the evidence networks for meta-analysis

There was interest to compare the effects of specific interventions to each other (e.g. to compare different types of diets head-to-head, or against different exercise or combination strategies) and to compare groups of clinical relevance (i.e. standard care therapy versus exercise interventions versus dietary interventions versus combined interventions). An NMA model allowing for comparisons at both levels (intervention level and group level) in the same analysis was implemented [41]. For the more granular level of comparisons, in addition to standard care, there were 18 interventions, including those of dietary interventions (including low calorie diet, low carbohydrate diet, low fat diet, Mediterranean diet, NCI diet, phyto-rich/plant-based diet, low fat + low calorie diet, and low fat + phyto-rich diet), exercise interventions (aerobic exercise, resistance exercise, combined program of aerobic and resistance exercise), and combined diet and exercise; the number of interventions compared per analysis varied according to the number of studies with available outcome data. Group level comparisons involved estimated measures of effect between standard care, diet interventions, exercise interventions and combined diet and exercise interventions. An expert in exercise science and nutrition (LJ) established the optimal categorizations of therapies into the dietary, exercise and combination groups and at the individual intervention level. A practical approach was utilized to focus on the nature of the intervention without details about the specific restrictions or parameters of the intervention (e.g., exercise programs were grouped in terms of activity such as aerobic exercise or resistance training, but variations in frequency and duration were not modeled).

Methods for evidence synthesis

NMA is an extension of traditional pairwise meta-analysis which enables the comparison of multiple interventions in a single analysis, and which allows for incorporation of both direct and indirect evidence of relevance [34, 35]. NMAs of the changes from baseline in body weight, body mass index and waist circumference were performed. The nature of reporting these endpoints varied across included studies, with some reporting changes from baseline while others reported mean values of each endpoint at baseline and follow-up, with standard deviations for each. For the latter, we calculated the mean changes from baseline and imputed the standard errors of the mean changes (for details, see S3 Text). We fit random effects (RE), three-level hierarchical models with a Normal likelihood and identity link [41] based on the mean changes from baseline and corresponding standard errors, with clustering of the interventions into 4 groups (standard care, diet interventions, exercise interventions and combined interventions); the main text focuses upon group level comparisons, while the intervention level comparisons are reported in detail in the report appendices. All mean differences (MD) of interventions versus standard care were reported along with corresponding 95% credible intervals. Forest plots are presented to summarize findings versus the standard care group, while all possible pairwise comparisons between interventions are summarized using league tables provided in this review’s online supplement. Details regarding our approach to model selection and fit assessment are also provided in the review supplement. The assumption of consistency between direct and indirect evidence was assessed by plotting the posterior mean deviance contributions from the consistency model against those from the unrelated means model to see if they aligned. All NMAs were performed using OpenBUGS software version 3.2.3 [42] and the R package R2OpenBUGS [43]. Model convergence was assessed using established methods including Gelman-Rubin diagnostics and the Potential Scale Reduction Factor [42, 44]. Findings reported within the main text of the review focus upon results from NMAs, while author conclusions of the remaining studies that did not appropriately fit into the NMAs (due to the types of comparisons made or lack of sufficient data) are summarized in the appendices. The Comparison-adjusted funnel plots were applied to assess for small-study effects as signals of publication bias. Following presentation of detailed supporting information for all results from the review (S4S7 Text), the OpenBUGS code for data analyses is provided in S8 Text, while raw data used for NMAs for the outcome measures of weight change, BMI change and waist circumference change are provided in S1, S2 and S3 Data, respectively. A completed PRISMA NMA Checklist is provided in S9 Text.

Results

Quantity of evidence identified

The initial search identified 7,812 articles. Duplicates were removed (n = 1,595), leaving 6,217 unique citations for review. Stage 1 screening of titles and abstracts identified 493 potentially relevant citations, which were subsequently reviewed in full text. Of these citations, 98 met the a priori inclusion criteria [20, 24, 45142], representing 75 studies that were included for analysis [20, 24, 4551, 5398, 100108, 110112, 114121] (Table 1). Reasons for study exclusion are listed in the flow diagram presented in Fig 1. A list of studies identified as meeting eligibility criteria but not included in NMAs is provided in S4 Text, with supporting rationale for their exclusion from syntheses of the data. For reasons related to network structure, the research was not planned to consider differences in method of delivery (n = 4) [123, 130, 132, 136] or intensity (n = 2) [125, 127]. Behavioral and counselling therapies were included in the qualitative analyses, but not considered of interest for the NMAs (n = 6) [122, 124, 131, 133, 139, 141]. Interventions used in only 1 study were excluded from the network (n = 7) [52, 113, 128, 134, 135, 137, 138]. Studies missing data also precluded NMA and were excluded (n = 3) [109, 129, 142].

Process of study selection.
Fig 1

Process of study selection.

A flow diagram is shown which depicts the process of study selection.

Table 1
Overview of study characteristics included in NMAs (n = 75).
CharacteristicSummary Measure
Year of publication
2010>59 (78.7%)
2001–200916 (21.3%)
1991–20000 (0%)
<19900 (0%)
Study sample size
<50 patients33 (44.0%)
51–100 patients27 (36.0%)
101–500 patients13 (17.3%)
501–1000 patients0 (0%)
>1000 patients2 (2.7%)
Time of Study Intervention
Pre-operative3 (4.0%)
During chemotherapy9 (12.0%)
During adjuvant hormone therapy/androgen deprivation9 (12.0%)
After treatment54 (72.0%)
Type of cancer patients enrolled
Breast48 (64.0%)
Prostate13 (17.3%)
Colorectal3 (4.0%)
Mixed sites8 (10.6%)
Other sites3 (4.0%)
Median of average patient ages (range)57 (42–73)
Median of average patient body weights (range kg)80 (49–98)
Median of average patient BMI (range kg/m2)29 (23–35)
Duration of study intervention
<3 months14 (18.7%)
3–6 months44 (58.7%)
7–12 months11 (14.7%)
>12 months5 (6.7%)
Not reported1 (1.3%)
# studies involving a treatment group of:
Standard care72 (96.0%)
Dietary Intervention16 (21.3%)
Exercise Therapy45 (60.0%)
Combination Intervention26 (34.7%)

Study characteristics, patient characteristics and risk of bias

Amongst data from a total of 14,378 patients in the included studies, 12,199 were included in NMAs. Study characteristics including year of publication, study size, duration, type of malignancy, median age, weight and BMI are summarized in Table 1, while a detailed intervention-level description is provided in S5 Text. Individual study sizes ranged from 10 [64] to 3,088 [76]. The studies enrolled patients with a range of tumour types including breast cancer (48 studies, 9,513 patients) [20, 24, 56, 58, 59, 61, 62, 6471, 7380, 82, 88, 89, 91, 9397, 102, 103, 105, 106, 108, 110, 112, 114, 115, 117, 119, 143], prostate cancer (9 studies, 521 patients) [8385, 90, 92, 101, 107, 111, 118], colorectal cancer (3 studies, 301 patients) [104, 116, 120], mixed tumour sites (primarily breast, prostate and colorectal) (8 studies, 1,812 patients) [60, 63, 72, 81, 100, 121] and other sites including endometrial and lung cancer (3 studies, 181 patients) [86, 87, 98]. Risk of bias assessment of the included studies showed that few of the studies concealed treatment allocation and many had an unknown risk for blinding to outcome (detailed assessments are provided in S5 Text).

Intervention characteristics and outcomes reported

Overall, studies included in NMAs evaluated dietary interventions (n = 11) [20, 56, 65, 68, 69, 76, 77, 80, 84, 106, 115], exercise interventions (n = 36) [25, 57, 60, 64, 66, 67, 70, 71, 7375, 78, 8183, 89, 92, 93, 95, 97, 98, 100, 101, 103, 104, 107, 110112, 114, 116, 118, 120, 129, 140, 144] or a combination of both dietary and exercise interventions (n = 21) [58, 59, 6163, 72, 74, 8588, 90, 91, 94, 96, 102, 105, 108, 117, 119, 121]. Change in body weight was reported by 65 studies (n = 11,267), while changes in BMI and waist circumference were reported by totals of 47 studies (n = 6,875) and 31 studies (n = 1,835), respectively (S5 Text). Figs 24 present network diagrams displaying the patterns of comparisons and numbers of patients per intervention for each endpoint assessed using NMA. The majority of comparisons in the included studies used standard care as the control group; standard care across studies generally consisted of information handouts related to food intake, while small numbers of studies involved waitlist controls or were lacking description. The number of interventions per NMA varied from a maximum of 18 for the weight loss endpoint to 15 for waist circumference. The total numbers of studies (minimum 31 for waist circumference to maximum 65 for body weight) and patients (from minimum 1,835 for waist circumference to maximum 11,267 for body weight) also varied notably across analyses based on availability of data.

Network diagram for change in body weight (kg): 18 interventions and standard care, 11,267 patients.
Fig 2

Network diagram for change in body weight (kg): 18 interventions and standard care, 11,267 patients.

The evidence network of the available studies and interventions for change in body weight is shown. Joining lines denote intervention comparisons where one or more trials were available. Nodes are proportionally sized to reflect the numbers of patients studied with each intervention. Edge width reflects the number of RCTs for each comparison. Nodes coloured green represent interventions considered to belong to the exercise group, while red nodes reflect the dietary group and the blue node denotes the diet/exercise combination group.

Network diagram for change in BMI: 16 interventions and standard care, 6,857 patients.
Fig 3

Network diagram for change in BMI: 16 interventions and standard care, 6,857 patients.

The evidence network of the available studies and interventions for change in BMI is shown. Joining lines denote intervention comparisons where one or more trials were available. Nodes are proportionally sized to reflect the numbers of patients studied with each intervention. Edge width reflects the number of RCTs for each comparison. Nodes coloured green represent interventions considered to belong to the exercise group, while red nodes reflect the dietary group and the blue node denotes the diet/exercise combination group.

Network diagram for change in waist circumference: 15 interventions and standard care, 1,835 patients.
Fig 4

Network diagram for change in waist circumference: 15 interventions and standard care, 1,835 patients.

The evidence network of the available studies and interventions for change in waist circumference is shown. Joining lines denote intervention comparisons where one or more trials were available. Nodes are proportionally sized to reflect the numbers of patients studied with each intervention. Edge width reflects the number of RCTs for each comparison. Nodes coloured green represent interventions considered to belong to the exercise group, while red nodes reflect the dietary group and the blue node denotes the diet/exercise combination group.

NMA model fit evaluation for analyses of body weight, BMI and waist circumference

For all three endpoints, comparison of posterior residual deviance values with the numbers of unconstrained data points indicated adequate model fit of random effects models, which were found to be preferred to fixed effects analyses based on comparison of DIC values (see review supplement, S6 Text for details). Inspection of DIC values and posterior mean deviance contributions did not identify evidence that the consistency assumption for NMA was violated for any of the RE NMAs, and thus results from RE consistency models are the focus of the report. There was no evidence of publication bias based on comparison adjusted funnel plots (see S7 Text).

Findings from NMA: Weight change

A total of 80 studies (13,069 patients) reporting weight change were identified [20, 24, 45, 4750, 5254, 56, 5863, 65, 66, 6872, 7489, 9196, 99, 101112, 115121, 123, 125, 127, 128, 130, 131, 134136, 138, 140143]. A total of 65 studies (11,267 patients) comprising 18 interventions (and standard care) were included in the NMAs of changes in weight from baseline measured in kilograms [20, 24, 45, 4751, 53, 54, 56, 5863, 65, 66, 6872, 7489, 9196, 101108, 110112, 115121, 145]. Fig 5 summarizes the estimates from NMA for group comparisons versus standard care, while the online supplement provides numerical details of pairwise comparisons.

Estimated differences in weight change (kg) compared to standard care from NMA (18 interventions and standard care, 65 studies, 11,267 patients).
Fig 5

Estimated differences in weight change (kg) compared to standard care from NMA (18 interventions and standard care, 65 studies, 11,267 patients).

The estimated differences (2.5% and 97.5% quantiles) of interventions versus standard care from random effects consistency model are displayed. Colored summary estimates represent estimated treatment effects of the groups of interventions versus standard care.

For comparisons at the group level, pairwise comparisons versus standard care found dietary interventions (MD -2.25kg, 95% CrI –3.43 to -0.91kg) and combination interventions (MD -2.52kg, 95% CrI -3.54 to -1.62kg) to be associated with statistically significantly greater weight reductions, while exercise interventions (MD -0.69kg, 95% CrI -1.75 to +0.49kg) were not (Fig 5). Comparisons between the different groups found both dietary interventions (MD -1.56kg, 95% CrI -3.12 to +0.17kg) and combination interventions (MD -1.82kg, 95% CrI -3.43 to -0.50kg) to be associated with greater weight loss than exercise interventions. Changes with dietary and combination interventions were similar (MD -0.26kg, 95% CrI -2.04kg to +1.19kg).

For comparisons at the intervention level, all 8 dietary interventions were associated with greater reductions in body weight when compared to standard care with all differences being of similar magnitude (range -2.03 to -2.52kg; Fig 5). Most combined interventions demonstrated a comparable difference in weight change versus standard care (range -2.13 to -2.92kg).

Findings from NMA: BMI change

A total of 58 studies (7967 patients) were identified [20, 24, 4548, 50, 5356, 58, 60, 6265, 6974, 77, 79, 80, 84, 85, 88, 90, 92102, 106, 108, 110, 111, 113116, 122, 131134, 136140] and a total of 39 studies comprising 15 interventions (and standard care) and 6,265 patients were included in for analysis [20, 24, 4548, 50, 51, 5356, 58, 60, 6265, 6974, 77, 79, 80, 84, 85, 88, 90, 9298, 100102, 106, 108, 110, 111, 114116]. Two interventions that were included in the previous analysis of weight change had no available data for change in BMI (NCI diet, and low calorie / low fat diet combined with aerobic exercise). Comparisons at the group level found that dietary interventions (MD -0.87 kg/m2, 95% CrI -1.47 kg/m2 to -0.22 kg/m2) and the combination of diet with exercise interventions (MD -0.91 kg/m2, 95% CI -1.56 kg/m2 to -0.36 kg/m2) were associated with a greater BMI reduction compared to standard care, while exercise interventions were not (MD -0.23 kg/m2, 95% CrI -0.95 kg/m2 to 0.49 kg/m2) (Fig 6). Comparisons between dietary, exercise and combination of diet with exercise interventions revealed no significant differences (see S7 Text for numeric details).

Estimated differences in BMI change compared to standard care from NMA (16 interventions and standard care, 47 studies, 6,824 patients).
Fig 6

Estimated differences in BMI change compared to standard care from NMA (16 interventions and standard care, 47 studies, 6,824 patients).

The estimated differences (2.5% and 97.5% quantiles) of interventions versus standard care from random effects consistency model are displayed. Colored summary estimates represent estimated treatment effects of the groups of interventions versus standard care.

Comparisons at the intervention level of the analysis found that aerobic exercise and aerobic exercise combined with resistance training showed significant differences in BMI reduction relative to standard care, but resistance training alone did not. All dietary interventions in the network were associated with BMI reductions (ranged -0.56 kg/m2 to -1.17 kg/m2), and differences were statistically significant for low calorie diet, low fat diet, low carbohydrate diet, and Mediterranean diet (Fig 6). Most combination interventions were also associated with statistically significant BMI reduction (except for aerobic exercise combined with Mediterranean diet).

Findings from NMA, waist circumference change

A total of 39 studies included (2,616 patients) reported data on changes in waist circumference [56, 58, 60, 61, 65, 67, 68, 70, 71, 74, 79, 85, 86, 88, 89, 91, 94, 99, 102, 106, 108, 109, 112, 115, 116, 119, 120, 123, 127, 130, 131, 134, 136, 139, 140]. A total of 31 studies involving 15 interventions (and standard care) and 1,835 patients were included for analysis [46, 4951, 53, 56, 58, 60, 61, 65, 6771, 74, 79, 85, 86, 88, 89, 91, 94, 102, 106, 108, 112, 115, 116, 119, 120]; in comparison to the set interventions that were evaluated earlier for their effects on weight loss, no data were available for low calorie diet, NCI diet or low carbohydrate/low fat diet.

At the group level of the analysis, the groups of exercise interventions (MD -1.78cm, 95% CrI -2.89cm to -0.64cm), dietary interventions (MD -2.32cm, 95% CrI -4.02cm to -0.69cm) and combination interventions (MD -2.51cm, 95% CrI -3.81cm to -1.34cm) were all associated with greater reductions in waist circumference compared to standard care (Fig 7). Comparisons between the different active groups suggested that there was no evidence of important differences between combination interventions and exercise interventions (MD -0.72cm, 95% CrI -2.45 to 0.82cm), between dietary interventions and exercise interventions (MD -0.53cm, 95% CrI -2.53cm to 1.44cm) or between combination interventions and dietary interventions (MD -0.19cm, 95% CrI -2.30cm to 1.85cm).

Estimated differences in waist circumference change (cm) compared to standard care from NMA (15 interventions and standard care, 32 studies, 1,875 patients).
Fig 7

Estimated differences in waist circumference change (cm) compared to standard care from NMA (15 interventions and standard care, 32 studies, 1,875 patients).

The estimated differences (2.5% and 97.5% quantiles) of interventions versus standard care from random effects consistency model are displayed. Coloured summary estimates represent estimated treatment effects of the groups of interventions versus standard care.

At the intervention level of the analysis, all interventions demonstrated larger reductions than standard care (Fig 7; range of differences from -1.54cm to -2.86cm).

Fig 8 (panels A, B and C) present league tables that summarize comparisons between intervention classes for each endpoint.

League tables, comparisons between group.
Fig 8

League tables, comparisons between group.

League tables of estimated posterior median pairwise differences in weight change (kg) with credible intervals / 2.5% and 97.5% quantiles (lower triangle), and the pairwise probabilities that a treatment is better than another (upper triangle) are presented. A complete summary of estimates for efficacy from the RE consistency model assuming vague priors is displayed. Statistically significant differences between intervention categories are shown in bold, underlined font. The lower/right-most comparison for each comparison is the reference treatment.

Discussion

Our analyses reveal that dietary and combination regimens of diet and exercise during and after cancer treatment achieved greater weight, BMI and waist circumference reduction when compared to standard care in overweight and obese patients with early stage cancer. Moreover, changes in weight between eight different dietary interventions were of similar magnitude, highlighting the fact that dietary interventions with different macronutrient profiles achieve similar results. In addition, weight and BMI losses achieved with combination interventions were similar to dietary interventions alone, underlining the fact that dietary change has a significant effect on anthropometric measures. With regard to waist circumference, at the group level of analysis, exercise, dietary and combination interventions were all associated with significant reductions compared to standard care. However, the magnitude of change in waist circumference was most meaningful with combination interventions of diet and exercise.

There is increasing evidence of the negative impact of obesity in patients with breast [3, 7, 16, 146150], ovarian [151], pancreatic [152], endometrial [153], prostate [154, 155] and colon cancer [156, 157]. It is clear that the obesity epidemic needs to be addressed with effective management strategies [13].

Oncology health care providers have not traditionally taken an active role in weight control management for their patients and resources directed at cancer patients and survivors seeking weight control and weight loss are limited [13]. This study highlights the fact that optimization of anthropometric measures in patients with early stage cancer is best achieved by dietary and combination interventions, but more importantly, that the improvement of anthropometric measures was similar, regardless of the specific lifestyle intervention used.

To our knowledge, this is the first systematic review comprising data from dietary, exercise and combination regimens together and comparing them at the group level and at the intervention level. An advantage of performing an NMA in this setting is that it is an extension of traditional pairwise meta-analysis, thus enabling the comparison of multiple interventions in a single analysis. It also permits the incorporation of both direct and indirect evidence of relevance [34, 35]. To proceed with analyses, pragmatic pooling of data into groups was performed in order to translate the findings of this study to clinical practice. Similar to previous meta-analyses on this topic, “standard care” arms were grouped together in order to facilitate the comparison.

While the results of our analyses have consistently identified dietary and combination regimens as having the greatest effect on weight, BMI and waist circumference, it is important to note that many of the studies included in this meta-analysis were not specifically designed to improve anthropometric measures, particularly for the studies comprising exercise interventions. It is therefore unclear if clinically meaningful results would be achieved if exercise studies were designed to improve anthropometric measures with exercise only. Further, gains in muscle mass are associated with an increase in lean body mass and decreased body fat, which may result in cumulative weight gain [158]. Body composition may therefore be a more meaningful endpoint to identify the benefits of lifestyle interventions. This endpoint was not included as part of this analysis as it is scarcely included in pragmatic lifestyle intervention trials and is of little use in the clinical oncology practice and survivorship care. Furthermore, ideal weight loss targets of clinical significance in the cancer population remain unknown. Many targets suggested have been derived from the Diabetes Prevention Programs [159] which recommend a 10% reduction in body weight, although this target is seldom achieved in lifestyle studies involving cancer patients. Additionally, although the evidence linking obesity to poor outcomes in observational studies is evident, the impact of changes in anthropometric measures on long-term outcomes remains uncertain [160]. Therefore, clinical trials attempting to identify achievable and sustainable targets for change in anthropometric measures which translate into improved outcomes are needed.

Amongst the limitations of this study, it should be noted that a practical approach to treatment classification was utilized which did not take into consideration granular details of interventions such as caloric or fat restrictions or intensity and frequency of exercise. This strategy was taken given that, while there were often minor differences in such details across studies, these differences were generally small. The interventions were not sufficiently well-connected in the evidence networks of weight, BMI and waist circumference. Therefore, our reporting of the results was focused on the group level rather the intervention level. It should also be noted that different intervention designs of efficacy, effectiveness or direct comparisons of the two may not necessarily translate into comparable clinically meaningful benefits. Variability existed in the definition of standard of care across studies and definitions of the standard of care arm was often limited or unclear. The median BMI of patients included in the studies was 29, with a range between 23 to 35. While this indicates that patients with a normal BMI were included in the studies utilized for meta-analyses, the majority of studies enrolled overweight or obese patients, limiting generalizability to patients with a BMI in the normal range. Finally, patients with early stage cancer of all types were included in this analysis to allow generalizability, but it should be noted that most patients enrolled in the presented studies had early stage breast, prostate and colorectal cancer. This study does not recognize the needs of specific patient populations that were not represented in the included studies, for whom losses could be detrimental, and should be interpreted with caution.

Conclusions

This analysis reveals that dietary and combination interventions of diet and exercise targeted to overweight and obese patients with early-stage cancer significantly improved anthropometric measures compared to standard care. Prior to this work, there was no clear consensus regarding optimal lifestyle interventions for patients with early stage cancer. However, after performing direct comparisons of multiple dietary strategies, our research suggests that all reputable diets appear to be equally effective to achieve weight loss, BMI loss and reduced weight circumference. Additionally, combinations of diet and exercise appear to be associated with a larger probability of achieving a decrease in waist circumference when compared to dietary interventions alone. While body composition may be a more meaningful endpoint, the utility of this in routine oncological practice is limited. Larger studies incorporating interventions specifically designed to alter anthropometric measures and body composition with longer intervention periods and follow-up are warranted, to better define the role of lifestyle strategies in the management of patients with early stage cancer during and after treatment.

References

National Cancer Institute. NCI: Fact sheet: Obesity and cancer risk. 2017; https://www.cancer.gov/about-cancer/causes-prevention/risk/obesity/obesity-fact-sheet.

DSChan, ARVieira, DAune, EVBandera, DCGreenwood, AMcTiernan, et al Body mass index and survival in women with breast cancer-systematic literature review and meta-analysis of 82 follow-up studies. Ann Oncol 2014 10;25(10):19011914. 10.1093/annonc/mdu042

MProtani, MCoory, JHMartin. Effect of obesity on survival of women with breast cancer: systematic review and meta-analysis. Breast Cancer Res Treat 2010 10;123(3):627635. 10.1007/s10549-010-0990-0

NRShah, ERBraverman. Measuring adiposity in patients: the utility of body mass index (BMI), percent body fat, and leptin. PLoS One 2012;7(4):e33308 10.1371/journal.pone.0033308

EECalle, CRodriguez, KWalker-Thurmond, MJThun. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N Engl J Med 2003 4 24;348(17):16251638. 10.1056/NEJMoa021423

WDemark-Wahnefried, EAPlatz, JALigibel, CKBlair, KSCourneya, JAMeyerhardt, et al The role of obesity in cancer survival and recurrence. Cancer Epidemiol Biomarkers Prev 2012 8;21(8):12441259. 10.1158/1055-9965.EPI-12-0485

DSChan, ARVieira, DAune, EVBandera, DCGreenwood, AMcTiernan, et al Body mass index and survival in women with breast cancer-systematic literature review and meta-analysis of 82 follow-up studies. Ann Oncol 2014 10;25(10):19011914. 10.1093/annonc/mdu042

AELohmann, PJGoodwin, RTChlebowski, KPan, VStambolic, RJDowling. Association of Obesity-Related Metabolic Disruptions With Cancer Risk and Outcome. J Clin Oncol 2016 12 10;34(35):42494255. 10.1200/JCO.2016.69.6187

BDHopkins, MDGoncalves, LCCantley. Obesity and Cancer Mechanisms: Cancer Metabolism. J Clin Oncol 2016 12 10;34(35):42774283. 10.1200/JCO.2016.67.9712

10 

CDuggan, JdeDTapsoba, CYWang, AMcTiernan. Dietary Weight Loss and Exercise Effects on Serum Biomarkers of Angiogenesis in Overweight Postmenopausal Women: A Randomized Controlled Trial. Cancer Res 2016 7 15;76(14):42264235. 10.1158/0008-5472.CAN-16-0399

11 

HGreenlee, ZShi, CLSardo Molmenti, ARundle, WYTsai. Trends in Obesity Prevalence in Adults With a History of Cancer: Results From the US National Health Interview Survey, 1997 to 2014. J Clin Oncol 2016 9 10;34(26):31333140. 10.1200/JCO.2016.66.4391

12 

MCPlaydon, MBBracken, TBSanft, JALigibel, MHarrigan, MLIrwin. Weight Gain After Breast Cancer Diagnosis and All-Cause Mortality: Systematic Review and Meta-Analysis. J Natl Cancer Inst 2015 9 30;107(12):djv275 10.1093/jnci/djv275

13 

JALigibel, CMAlfano, KSCourneya, WDemark-Wahnefried, RABurger, RTChlebowski, et al American Society of Clinical Oncology position statement on obesity and cancer. J Clin Oncol 2014 11 1;32(31):35683574. 10.1200/JCO.2014.58.4680

14 

JALigibel, CMAlfano, DHershman, RMBallard, SSBruinooge, KSCourneya, et al Recommendations for Obesity Clinical Trials in Cancer Survivors: American Society of Clinical Oncology Statement. J Clin Oncol 2015 11 20;33(33):39613967. 10.1200/JCO.2015.63.1440

15 

KHSchmitz, KSCourneya, CMatthews, WDemark-Wahnefried, DAGalvao, BMPinto, et al American College of Sports Medicine roundtable on exercise guidelines for cancer survivors. Med Sci Sports Exerc 2010 7;42(7):14091426. 10.1249/MSS.0b013e3181e0c112

16 

JLigibel. Obesity and breast cancer. Oncology (Williston Park) 2011 10;25(11):9941000.

17 

DAGalvao, RUNewton. Review of exercise intervention studies in cancer patients. J Clin Oncol 2005 2 1;23(4):899909. 10.1200/JCO.2005.06.085

18 

RTChlebowski, MMReeves. Weight Loss Randomized Intervention Trials in Female Cancer Survivors. J Clin Oncol 2016 12 10;34(35):42384248. 10.1200/JCO.2016.69.4026

19 

JPark, TSMorley, MKim, DJClegg, PEScherer. Obesity and cancer—mechanisms underlying tumour progression and recurrence. Nat Rev Endocrinol 2014 8;10(8):455465. 10.1038/nrendo.2014.94

20 

RTChlebowski, GLBlackburn, CAThomson, DWNixon, AShapiro, MKHoy, et al Dietary fat reduction and breast cancer outcome: interim efficacy results from the Women’s Intervention Nutrition Study. J Natl Cancer Inst 2006 12 20;98(24):17671776. 10.1093/jnci/djj494

21 

MDHolmes, WYChen, DFeskanich, CHKroenke, GAColditz. Physical activity and survival after breast cancer diagnosis. JAMA 2005 5 25;293(20):24792486. 10.1001/jama.293.20.2479

22 

CNHolick, PANewcomb, ATrentham-Dietz, LTitus-Ernstoff, AJBersch, MJStampfer, et al Physical activity and survival after diagnosis of invasive breast cancer. Cancer Epidemiol Biomarkers Prev 2008 2;17(2):379386. 10.1158/1055-9965.EPI-07-0771

23 

BSternfeld, EWeltzien, CPQuesenberryJr, ALCastillo, MKwan, MLSlattery, et al Physical activity and risk of recurrence and mortality in breast cancer survivors: findings from the LACE study. Cancer Epidemiol Biomarkers Prev 2009 1;18(1):8795. 10.1158/1055-9965.EPI-08-0595

24 

KSCourneya, JRMackey, GJBell, LWJones, CJField, ASFairey. Randomized controlled trial of exercise training in postmenopausal breast cancer survivors: cardiopulmonary and quality of life outcomes. J Clin Oncol 2003 5 1;21(9):16601668. 10.1200/JCO.2003.04.093

25 

KCourneya, CFriedenreich, HQuinney, AFields, LJones, AFairey. A randomized trial of exercise and quality of life in colorectal cancer survivors. European journal of cancer care 2003;12(4):347357. 10.1046/j.1365-2354.2003.00437.x

26 

JAMeyerhardt, DHeseltine, DNiedzwiecki, DHollis, LBSaltz, RJMayer, et al Impact of physical activity on cancer recurrence and survival in patients with stage III colon cancer: findings from CALGB 89803. J Clin Oncol 2006 8 1;24(22):35353541. 10.1200/JCO.2006.06.0863

27 

JAMeyerhardt, ELGiovannucci, SOgino, GJKirkner, ATChan, WWillett, et al Physical activity and male colorectal cancer survival. Arch Intern Med 2009 12 14;169(22):21022108. 10.1001/archinternmed.2009.412

28 

JAMeyerhardt, ELGiovannucci, MDHolmes, ATChan, JAChan, GAColditz, et al Physical activity and survival after colorectal cancer diagnosis. J Clin Oncol 2006 8 1;24(22):35273534. 10.1200/JCO.2006.06.0855

29 

ELRichman, SAKenfield, MJStampfer, APaciorek, PRCarroll, JMChan. Physical activity after diagnosis and risk of prostate cancer progression: data from the cancer of the prostate strategic urologic research endeavor. Cancer Res 2011 6 1;71(11):38893895. 10.1158/0008-5472.CAN-10-3932

30 

CLVan Patten, JGde Boer, ESTomlinson Guns. Diet and dietary supplement intervention trials for the prevention of prostate cancer recurrence: a review of the randomized controlled trial evidence. J Urol 2008 12;180(6):231421; discussion 2721–2. 10.1016/j.juro.2008.08.078

31 

MPlaydon, GThomas, TSanft, MHarrigan, JLigibel, MIrwin. Weight Loss Intervention for Breast Cancer Survivors: A Systematic Review. Curr Breast Cancer Rep 2013 9;5(3):222246. 10.1007/s12609-013-0113-0

32 

WDemark-Wahnefried, KLCampbell, SCHayes. Weight management and its role in breast cancer rehabilitation. Cancer 2012 4 15;118(8 Suppl):22772287. 10.1002/cncr.27466

33 

World Cancer Research Fund / American Institute for Cancer Research. Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective.: Washington DC: AICR; 2007.

34 

GLu, AEAdes. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 2004 10 30;23(20):31053124. 10.1002/sim.1875

35 

FCatala-Lopez, ATobias, CCameron, DMoher, BHutton. Network meta-analysis for comparing treatment effects of multiple interventions: an introduction. Rheumatol Int 2014 11;34(11):14891496. 10.1007/s00296-014-2994-2

36 

GSalanti. Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool. Res Synth Methods 2012 6;3(2):8097. 10.1002/jrsm.1037

37 

BHutton, GSalanti, DMCaldwell, AChaimani, CHSchmid, CCameron, et al The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med 2015 6 2;162(11):777784. 10.7326/M14-2385

38 

MSampson, JMcGowan, ECogo, JGrimshaw, DMoher, CLefebvre. An evidence-based practice guideline for the peer review of electronic search strategies. J Clin Epidemiol 2009 9;62(9):944952. 10.1016/j.jclinepi.2008.10.012

39 

DMoher, ALiberati, JTetzlaff, DGAltman, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 2009 10;62(10):10061012. 10.1016/j.jclinepi.2009.06.005

40 

JPHiggins, DGAltman, PCGotzsche, PJuni, DMoher, ADOxman, et al The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011 10 18;343:d5928 10.1136/bmj.d5928

41 

RKOwen, DGTincello, RAKeith. Network meta-analysis: development of a three-level hierarchical modeling approach incorporating dose-related constraints. Value Health 2015 1;18(1):116126. 10.1016/j.jval.2014.10.006

42 

DSpiegelhalter, AThomas, NBest, DLunn. OpenBUGS user manual, version 3.2.3 Cambridge, UK: MRC Biostatistics Unit; 2014.

43 

SSturtz, ULigges, AGelman. R2WinBUGS: A Package for Running WinBUGS. Journal of Statistical Software 2005;12(3):116.

44 

The Evidence Synthesis TSD Series. Technical Support Document 2 (TSD-2). NICE Decision Support Unit.

45 

SJFreedland, LHoward, JAllen, JSmith, JStout, WAronson, et al A lifestyle intervention of weight loss via a low-carbohydrate diet plus walking to reduce metabolic disturbances caused by androgen deprivation therapy among prostate cancer patients: carbohydrate and prostate study 1 (CAPS1) randomized controlled trial. Prostate Cancer Prostatic Dis 2019 9;22(3):428437. 10.1038/s41391-019-0126-5

46 

JMcNeil, DRBrenner, CRStone, RO’Reilly, YRuan, JKVallance, et al Activity Tracker to Prescribe Various Exercise Intensities in Breast Cancer Survivors. Med Sci Sports Exerc 2019 5;51(5):930940. 10.1249/MSS.0000000000001890

47 

SMijwel, AJervaeus, KABolam, JNorrbom, JBergh, HRundqvist, et al High-intensity exercise during chemotherapy induces beneficial effects 12 months into breast cancer survivorship. J Cancer Surviv 2019 4;13(2):244256. 10.1007/s11764-019-00747-z

48 

LBourke, RStevenson, RTurner, RHooper, PSasieni, RGreasley, et al Exercise training as a novel primary treatment for localised prostate cancer: a multi-site randomised controlled phase II study. Sci Rep 2018 5 30;8(1):8374-018-26682-0. 10.1038/s41598-018-26682-0

49 

CMDieli-Conwright, JHParmentier, NSami, KLee, DSpicer, WJMack, et al Adipose tissue inflammation in breast cancer survivors: effects of a 16-week combined aerobic and resistance exercise training intervention. Breast Cancer Res Treat 2018 2;168(1):147157. 10.1007/s10549-017-4576-y

50 

SMHenning, CGalet, KGollapudi, JBByrd, PLiang, ZLi, et al Phase II prospective randomized trial of weight loss prior to radical prostatectomy. Prostate Cancer Prostatic Dis 2018 6;21(2):212220. 10.1038/s41391-017-0001-1

51 

KToohey, KPumpa, AMcKune, JCooke, KDDuBose, DYip, et al Does low volume high-intensity interval training elicit superior benefits to continuous low to moderate-intensity training in cancer survivors? World J Clin Oncol 2018 2 10;9(1):112. 10.5306/wjco.v9.i1.1

52 

DVArtene, CIBordea, ABlidaru. Results of 1-year Diet and Exercise Interventions for ER+/PR+/-/HER2- Breast Cancer Patients Correlated with Treatment Type. Chirurgia (Bucur) 2017 Jul-Aug;112(4):457468.

53 

ABraakhuis, PCampion, KBishop. The Effects of Dietary Nutrition Education on Weight and Health Biomarkers in Breast Cancer Survivors. Med Sci (Basel) 2017 6 2;5(2): 10.3390/medsci5020012

54 

WDemark-Wahnefried, SRais-Bahrami, RADesmond, JBGordetsky, GRHunter, ESYang, et al Presurgical weight loss affects tumour traits and circulating biomarkers in men with prostate cancer. Br J Cancer 2017 10 24;117(9):13031313. 10.1038/bjc.2017.303

55 

MLIrwin, BCartmel, MHarrigan, FLi, TSanft, LShockro, et al Effect of the LIVESTRONG at the YMCA exercise program on physical activity, fitness, quality of life, and fatigue in cancer survivors. Cancer 2017 4 1;123(7):12491258. 10.1002/cncr.30456

56 

SWCho, JHKim, SMLee, SMLee, EJChoi, JJeong, et al Effect of 8-week nutrition counseling to increase phytochemical rich fruit and vegetable consumption in korean breast cancer patients: a randomized controlled trial. Clin Nutr Res 2014 1;3(1):3947. 10.7762/cnr.2014.3.1.39

57 

KSCourneya, DCMcKenzie, KGelmon, JRMackey, RDReid, YYasui, et al A multicenter randomized trial of the effects of exercise dose and type on psychosocial distress in breast cancer patients undergoing chemotherapy. Cancer Epidemiol Biomarkers Prev 2014 5;23(5):857864. 10.1158/1055-9965.EPI-13-1163

58 

WDemark-Wahnefried, LWJones, DCSnyder, RJSloane, GGKimmick, DCHughes, et al Daughters and Mothers Against Breast Cancer (DAMES): main outcomes of a randomized controlled trial of weight loss in overweight mothers with breast cancer and their overweight daughters. Cancer 2014 8 15;120(16):25222534. 10.1002/cncr.28761

59 

PJGoodwin, RJSegal, MVallis, JALigibel, GRPond, ARobidoux, et al Randomized trial of a telephone-based weight loss intervention in postmenopausal women with breast cancer receiving letrozole: the LISA trial. J Clin Oncol 2014 7 20;32(21):22312239. 10.1200/JCO.2013.53.1517

60 

MBackman, YWengstrom, BJohansson, ISkoldengen, SBorjesson, STarnbro, et al A randomized pilot study with daily walking during adjuvant chemotherapy for patients with breast and colorectal cancer. Acta Oncol 2014 4;53(4):510520. 10.3109/0284186X.2013.873820

61 

HAGreenlee, KDCrew, JMMata, PSMcKinley, AGRundle, WZhang, et al A pilot randomized controlled trial of a commercial diet and exercise weight loss program in minority breast cancer survivors. Obesity (Silver Spring) 2013 1;21(1):6576. 10.1002/oby.20245

62 

EScott, AJDaley, HDoll, NWoodroofe, REColeman, NMutrie, et al Effects of an exercise and hypocaloric healthy eating program on biomarkers associated with long-term prognosis after early-stage breast cancer: a randomized controlled trial. Cancer Causes Control 2013 1;24(1):181191. 10.1007/s10552-012-0104-x

63 

WDemark-Wahnefried, MCMorey, RSloane, DCSnyder, PEMiller, TJHartman, et al Reach out to enhance wellness home-based diet-exercise intervention promotes reproducible and sustainable long-term improvements in health behaviors, body weight, and physical functioning in older, overweight/obese cancer survivors. J Clin Oncol 2012 7 1;30(19):23542361. 10.1200/JCO.2011.40.0895

64 

RRao, VCruz, YPeng, AHarker-Murray, BBHaley, HZhao, et al Bootcamp during neoadjuvant chemotherapy for breast cancer: a randomized pilot trial. Breast Cancer (Auckl) 2012;6:3946. 10.4137/BCBCR.S9221

65 

AVillarini, PPasanisi, MRaimondi, GGargano, EBruno, DMorelli, et al Preventing weight gain during adjuvant chemotherapy for breast cancer: a dietary intervention study. Breast Cancer Res Treat 2012 9;135(2):581589. 10.1007/s10549-012-2184-4

66 

CADeNysschen, JKBrown, MHCho, MJDodd. Nutritional symptom and body composition outcomes of aerobic exercise in women with breast cancer. Clin Nurs Res 2011 2;20(1):2946. 10.1177/1054773810379402

67 

EMGuinan, JMHussey, JMWalsh, MJKennedy, EMConnolly. The effect of aerobic exercise on the metabolic risk profile of breast cancer survivors 2–6 months post chemotherapy. J Clin Oncol 2011 9 20;29(27_suppl):244.

68 

MMFlynn, SEReinert. Comparing an olive oil-enriched diet to a standard lower-fat diet for weight loss in breast cancer survivors: a pilot study. J Womens Health (Larchmt) 2010 6;19(6):11551161. 10.1089/jwh.2009.1759

69 

CAThomson, ATStopeck, JWBea, ECussler, ENardi, GFrey, et al Changes in body weight and metabolic indexes in overweight breast cancer survivors enrolled in a randomized trial of low-fat vs. reduced carbohydrate diets. Nutr Cancer 2010;62(8):11421152. 10.1080/01635581.2010.513803

70 

MLIrwin, MAlvarez-Reeves, LCadmus, EMierzejewski, STMayne, HYu, et al Exercise improves body fat, lean mass, and bone mass in breast cancer survivors. Obesity (Silver Spring) 2009 8;17(8):15341541.

71 

JALigibel, AGiobbie-Hurder, DOlenczuk, NCampbell, TSalinardi, EPWiner, et al Impact of a mixed strength and endurance exercise intervention on levels of adiponectin, high molecular weight adiponectin and leptin in breast cancer survivors. Cancer Causes Control 2009 10;20(8):15231528. 10.1007/s10552-009-9358-3

72 

MCMorey, DCSnyder, RSloane, HJCohen, BPeterson, TJHartman, et al Effects of home-based diet and exercise on functional outcomes among older, overweight long-term cancer survivors: RENEW: a randomized controlled trial. JAMA 2009 5 13;301(18):18831891. 10.1001/jama.2009.643

73 

LQRogers, PHopkins-Price, SVicari, RPamenter, KSCourneya, SMarkwell, et al A randomized trial to increase physical activity in breast cancer survivors. Med Sci Sports Exerc 2009 4;41(4):935946. 10.1249/MSS.0b013e31818e0e1b

74 

WDemark-Wahnefried, LDCase, KBlackwell, PKMarcom, WKraus, NAziz, et al Results of a diet/exercise feasibility trial to prevent adverse body composition change in breast cancer patients on adjuvant chemotherapy. Clin Breast Cancer 2008 2;8(1):7079. 10.3816/CBC.2008.n.005

75 

CEMatthews, SWilcox, CLHanby, CDer Ananian, SPHeiney, TGebretsadik, et al Evaluation of a 12-week home-based walking intervention for breast cancer survivors. Support Care Cancer 2007 2;15(2):203211. 10.1007/s00520-006-0122-x

76 

JPPierce, LNatarajan, BJCaan, BAParker, ERGreenberg, SWFlatt, et al Influence of a diet very high in vegetables, fruit, and fiber and low in fat on prognosis following treatment for breast cancer: the Women’s Healthy Eating and Living (WHEL) randomized trial. JAMA 2007 7 18;298(3):289298. 10.1001/jama.298.3.289

77 

CShaw, PMortimer, PAJudd. Randomized controlled trial comparing a low-fat diet with a weight-reduction diet in breast cancer-related lymphedema. Cancer 2007 5 15;109(10):19491956. 10.1002/cncr.22638

78 

FHerrero, AFSan Juan, SJFleck, JBalmer, MPerez, SCanete, et al Combined aerobic and resistance training in breast cancer survivors: A randomized, controlled pilot trial. Int J Sports Med 2006 7;27(7):573580. 10.1055/s-2005-865848

79 

KHSchmitz, RLAhmed, PJHannan, DYee. Safety and efficacy of weight training in recent breast cancer survivors to alter body composition, insulin, and insulin-like growth factor axis proteins. Cancer Epidemiol Biomarkers Prev 2005 7;14(7):16721680. 10.1158/1055-9965.EPI-04-0736

80 

KLJen, ZDjuric, NMDiLaura, ABuison, JNRedd, VMaranci, et al Improvement of metabolism among obese breast cancer survivors in differing weight loss regimens. Obes Res 2004 2;12(2):306312. 10.1038/oby.2004.38

81 

TRBurnham, AWilcox. Effects of exercise on physiological and psychological variables in cancer survivors. Med Sci Sports Exerc 2002 12;34(12):18631867. 10.1097/00005768-200212000-00001

82 

RSegal, WEvans, DJohnson, JSmith, SColletta, JGayton, et al Structured exercise improves physical functioning in women with stages I and II breast cancer: results of a randomized controlled trial. J Clin Oncol 2001 2 1;19(3):657665. 10.1200/JCO.2001.19.3.657

83 

PCormie, DAGalvao, NSpry, DJoseph, RChee, DRTaaffe, et al Can supervised exercise prevent treatment toxicity in patients with prostate cancer initiating androgen-deprivation therapy: a randomised controlled trial. BJU Int 2015 2;115(2):256266. 10.1111/bju.12646

84 

JLWright, SPlymate, AD’Oria-Cameron, CBain, KHaugk, LXiao, et al A study of caloric restriction versus standard diet in overweight men with newly diagnosed prostate cancer: a randomized controlled trial. Prostate 2013 9;73(12):13451351. 10.1002/pros.22682

85 

RFO’Neill, FHaseen, LJMurray, JMO’Sullivan, MMCantwell. A randomised controlled trial to evaluate the efficacy of a 6-month dietary and physical activity intervention for patients receiving androgen deprivation therapy for prostate cancer. J Cancer Surviv 2015 9;9(3):431440. 10.1007/s11764-014-0417-8

86 

Vvon Gruenigen, HFrasure, MBKavanagh, JJanata, SWaggoner, PRose, et al Survivors of uterine cancer empowered by exercise and healthy diet (SUCCEED): a randomized controlled trial. Gynecol Oncol 2012 6;125(3):699704. 10.1016/j.ygyno.2012.03.042

87 

VEvon Gruenigen, KSCourneya, HEGibbons, MBKavanagh, SEWaggoner, ELerner. Feasibility and effectiveness of a lifestyle intervention program in obese endometrial cancer patients: a randomized trial. Gynecol Oncol 2008 4;109(1):1926. 10.1016/j.ygyno.2007.12.026

88 

BPakiz, SWFlatt, WABardwell, CLRock, PJMills. Effects of a weight loss intervention on body mass, fitness, and inflammatory biomarkers in overweight or obese breast cancer survivors. Int J Behav Med 2011 12;18(4):333341. 10.1007/s12529-010-9079-8

89 

LBDolan, KCampbell, KGelmon, SNeil-Sztramko, DHolmes, DCMcKenzie. Interval versus continuous aerobic exercise training in breast cancer survivors—a pilot RCT. Support Care Cancer 2016 1;24(1):119127. 10.1007/s00520-015-2749-y

90 

SEGilbert, GATew, CFairhurst, LBourke, JMSaxton, EMWinter, et al Effects of a lifestyle intervention on endothelial function in men on long-term androgen deprivation therapy for prostate cancer. Br J Cancer 2016 2 16;114(4):401408. 10.1038/bjc.2015.479

91 

MHarrigan, BCartmel, ELoftfield, TSanft, ABChagpar, YZhou, et al Randomized Trial Comparing Telephone Versus In-Person Weight Loss Counseling on Body Composition and Circulating Biomarkers in Women Treated for Breast Cancer: The Lifestyle, Exercise, and Nutrition (LEAN) Study. J Clin Oncol 2016 3 1;34(7):669676. 10.1200/JCO.2015.61.6375

92 

THvid, BLindegaard, KWinding, PIversen, KBrasso, TPSolomon, et al Effect of a 2-year home-based endurance training intervention on physiological function and PSA doubling time in prostate cancer patients. Cancer Causes Control 2016 2;27(2):165174. 10.1007/s10552-015-0694-1

93 

IMLahart, GSMetsios, AMNevill, GDKitas, ARCarmichael. Randomised controlled trial of a home-based physical activity intervention in breast cancer survivors. BMC Cancer 2016 3 17;16:234-016-2258-5. 10.1186/s12885-016-2258-5

94 

VBSheppard, JHicks, KMakambi, AHurtado-de-Mendoza, WDemark-Wahnefried, LAdams-Campbell. The feasibility and acceptability of a diet and exercise trial in overweight and obese black breast cancer survivors: The Stepping STONE study. Contemp Clin Trials 2016 1;46:106113. 10.1016/j.cct.2015.12.005

95 

JCBrown, KHSchmitz. Weight lifting and appendicular skeletal muscle mass among breast cancer survivors: a randomized controlled trial. Breast Cancer Res Treat 2015 6;151(2):385392. 10.1007/s10549-015-3409-0

96 

SCasla, SLopez-Tarruella, YJerez, IMarquez-Rodas, DAGalvao, RUNewton, et al Supervised physical exercise improves VO2max, quality of life, and health in early stage breast cancer patients: a randomized controlled trial. Breast Cancer Res Treat 2015 9;153(2):371382. 10.1007/s10549-015-3541-x

97 

TCornette, FVincent, SMandigout, MTAntonini, SLeobon, ALabrunie, et al Effects of home-based exercise training on VO2 in breast cancer patients under adjuvant or neoadjuvant chemotherapy (SAPA): a randomized controlled trial. Eur J Phys Rehabil Med 2016 4;52(2):223232.

98 

EEdvardsen, OHSkjonsberg, IHolme, LNordsletten, FBorchsenius, SAAnderssen. High-intensity training following lung cancer surgery: a randomised controlled trial. Thorax 2015 3;70(3):244250. 10.1136/thoraxjnl-2014-205944

99 

HGreenlee, AOGaffney, ACAycinena, PKoch, IContento, WKarmally, et al inverted exclamation markCocinar Para Su Salud!: Randomized Controlled Trial of a Culturally Based Dietary Intervention among Hispanic Breast Cancer Survivors. J Acad Nutr Diet 2015 5;115(5):709723.e3. 10.1016/j.jand.2014.11.002

100 

CSKampshoff, MJChinapaw, JBrug, JWTwisk, GSchep, MRNijziel, et al Randomized controlled trial of the effects of high intensity and low-to-moderate intensity exercise on physical fitness and fatigue in cancer survivors: results of the Resistance and Endurance exercise After ChemoTherapy (REACT) study. BMC Med 2015 10 29;13:275-015-0513-2. 10.1186/s12916-015-0513-2

101 

TSNilsen, TRaastad, ESkovlund, KSCourneya, CWLangberg, WLilleby, et al Effects of strength training on body composition, physical functioning, and quality of life in prostate cancer patients during androgen deprivation therapy. Acta Oncol 2015 11;54(10):18051813. 10.3109/0284186X.2015.1037008

102 

AKSwisher, JAbraham, DBonner, DGilleland, GHobbs, SKurian, et al Exercise and dietary advice intervention for survivors of triple-negative breast cancer: effects on body fat, physical function, quality of life, and adipokine profile. Support Care Cancer 2015 10;23(10):29953003. 10.1007/s00520-015-2667-z

103 

NTravier, MJVelthuis, CNSteins Bisschop, Bvan den Buijs, EMMonninkhof, FBackx, et al Effects of an 18-week exercise programme started early during breast cancer treatment: a randomised controlled trial. BMC Med 2015 6 8;13:121-015-0362-z. 10.1186/s12916-015-0362-z

104 

JKVan Vulpen, MJVelthuis, CNSteins Bisschop, NTravier, BJVan Den Buijs, FJBackx, et al Effects of an Exercise Program in Colon Cancer Patients undergoing Chemotherapy. Med Sci Sports Exerc 2016 5;48(5):767775. 10.1249/MSS.0000000000000855

105 

AYArikawa, BCKaufman, SKRaatz, MSKurzer. Effects of a parallel-arm randomized controlled weight loss pilot study on biological and psychosocial parameters of overweight and obese breast cancer survivors. Pilot Feasibility Stud 2017 7 10;4:17-017-0160-9. eCollection 2018. 10.1186/s40814-017-0160-9

106 

MSkouroliakou, DGrosomanidis, PMassara, CKostara, PPapandreou, DNtountaniotis, et al Serum antioxidant capacity, biochemical profile and body composition of breast cancer survivors in a randomized Mediterranean dietary intervention study. Eur J Nutr 2018 9;57(6):21332145. 10.1007/s00394-017-1489-9

107 

BAWall, DAGALVaO, NFatehee, DRTaaffe, NSpry, DJoseph, et al Exercise Improves V O2max and Body Composition in Androgen Deprivation Therapy-treated Prostate Cancer Patients. Med Sci Sports Exerc 2017 8;49(8):15031510. 10.1249/MSS.0000000000001277

108 

ERoveda, JAVitale, EBruno, AMontaruli, PPasanisi, AVillarini, et al Protective Effect of Aerobic Physical Activity on Sleep Behavior in Breast Cancer Survivors. Integr Cancer Ther 2017 3;16(1):2131. 10.1177/1534735416651719

109 

FKwiatkowski, MAMouret-Reynier, MDuclos, FBridon, THanh, IVan Praagh-Doreau, et al Long-term improvement of breast cancer survivors’ quality of life by a 2-week group physical and educational intervention: 5-year update of the ’PACThe’ trial. Br J Cancer 2017 5 23;116(11):13891393. 10.1038/bjc.2017.112

110 

GAThomas, BCartmel, MHarrigan, MFiellin, SCapozza, YZhou, et al The effect of exercise on body composition and bone mineral density in breast cancer survivors taking aromatase inhibitors. Obesity (Silver Spring) 2017 2;25(2):346351. 10.1002/oby.21729

111 

KHojan, EKwiatkowska-Borowczyk, ELeporowska, PMilecki. Inflammation, cardiometabolic markers, and functional changes in men with prostate cancer. A randomized controlled trial of a 12month exercise program. Pol Arch Intern Med 2017 1 10;127(1):2535. 10.20452/pamw.3888

112 

THKim, JSChang, KSPark, JPark, NKim, JILee, et al Effects of exercise training on circulating levels of Dickkpof-1 and secreted frizzled-related protein-1 in breast cancer survivors: A pilot single-blind randomized controlled trial. PLoS One 2017 2 8;12(2):e0171771 10.1371/journal.pone.0171771

113 

HGhavami, NAkyolcu. The impact of lifestyle interventions in breast cancer women after completion of primary therapy: A randomized study. J Breast Health 2017;13(2):9499.

114 

LQRogers, KSCourneya, PMAnton, PHopkins-Price, SVerhulst, RSRobbs, et al Social Cognitive Constructs Did Not Mediate the BEAT Cancer Intervention Effects on Objective Physical Activity Behavior Based on Multivariable Path Analysis. Ann Behav Med 2017 4;51(2):321326. 10.1007/s12160-016-9840-6

115 

HGreenlee, AOgden Gaffney, ACAycinena, PKoch, IContento, WKarmally, et al Long-term Diet and Biomarker Changes after a Short-term Intervention among Hispanic Breast Cancer Survivors: The inverted exclamation markCocinar Para Su Salud! Randomized Controlled Trial. Cancer Epidemiol Biomarkers Prev 2016 11;25(11):14911502. 10.1158/1055-9965.EPI-15-1334

116 

ICantarero-Villanueva, ASanchez-Jimenez, NGaliano-Castillo, LDiaz-Rodriguez, LMartin-Martin, MArroyo-Morales. Effectiveness of Lumbopelvic Exercise in Colon Cancer Survivors: A Randomized Controlled Clinical Trial. Med Sci Sports Exerc 2016 8;48(8):14381446. 10.1249/MSS.0000000000000917

117 

CBefort, JKlemp, DSullivan, FDiaz, KSchmitz, MPerri, et al Comparison of strategies for weight loss maintenance among rural breast cancer survivors: The rural women connecting for better health randomized controlled trial. Cancer Res 2016;76((4 SUPPL. 1)).

118 

KMWinters-Stone, KSLyons, JDobek, NFDieckmann, JABennett, LNail, et al Benefits of partnered strength training for prostate cancer survivors and spouses: results from a randomized controlled trial of the Exercising Together project. J Cancer Surviv 2016 8;10(4):633644. 10.1007/s11764-015-0509-0

119 

MMReeves, COTerranova, JMErickson, JRJob, DSBrookes, NMcCarthy, et al Living well after breast cancer randomized controlled trial protocol: evaluating a telephone-delivered weight loss intervention versus usual care in women following treatment for breast cancer. BMC Cancer 2016 10 28;16(1):830-016-2858-0. 10.1186/s12885-016-2858-0

120 

KSCourneya, JLVardy, CJO’Callaghan, CMFriedenreich, KLCampbell, HPrapavessis, et al Effects of a Structured Exercise Program on Physical Activity and Fitness in Colon Cancer Survivors: One Year Feasibility Results from the CHALLENGE Trial. Cancer Epidemiol Biomarkers Prev 2016 6;25(6):969977. 10.1158/1055-9965.EPI-15-1267

121 

JCBrown, RLYung, AGobbie-Hurder, LShockro, KO’Connor, NCampbell, et al Randomized trial of a clinic-based weight loss intervention in cancer survivors. J Cancer Surviv 2018 4;12(2):186195. 10.1007/s11764-017-0657-5

122 

IMLahart, ARCarmichael, AMNevill, GDKitas, GSMetsios. The effects of a home-based physical activity intervention on cardiorespiratory fitness in breast cancer survivors; a randomised controlled trial. J Sports Sci 2018 5;36(10):10771086. 10.1080/02640414.2017.1356025

123 

MStolley, PSheean, BGerber, CArroyo, LSchiffer, ABanerjee, et al Efficacy of a Weight Loss Intervention for African American Breast Cancer Survivors. J Clin Oncol 2017 8 20;35(24):28202828. 10.1200/JCO.2016.71.9856

124 

RLSedjo, SWFlatt, TByers, GAColditz, WDemark-Wahnefried, PAGanz, et al Impact of a behavioral weight loss intervention on comorbidities in overweight and obese breast cancer survivors. Support Care Cancer 2016 8;24(8):32853293. 10.1007/s00520-016-3141-2

125 

JLDevin, ATSax, GIHughes, DGJenkins, JFAitken, SKChambers, et al The influence of high-intensity compared with moderate-intensity exercise training on cardiorespiratory fitness and body composition in colorectal cancer survivors: a randomised controlled trial. J Cancer Surviv 2016 6;10(3):467479. 10.1007/s11764-015-0490-7

126 

CAnderson, MHarrigan, SMGeorge, LMFerrucci, TSanft, MLIrwin, et al Changes in diet quality in a randomized weight loss trial in breast cancer survivors: the lifestyle, exercise, and nutrition (LEAN) study. NPJ Breast Cancer 2016 8 24;2:16026 10.1038/npjbcancer.2016.26

127 

KToohey, SSemple, KPumpa, JCooke, Larnold, PCraft, et al High-intensity interval training versus continuous moderate intensity training: Effects on health outcomes and cardiometabolic disease risk factors in cancer survivors: A pilot study. J Sci Med Sport 2015;19:e94.

128 

KMWinters-Stone, NDieckmann, GFMaddalozzo, JABennett, CWRyan, TMBeer. Resistance Exercise Reduces Body Fat and Insulin During Androgen-Deprivation Therapy for Prostate Cancer. Oncol Nurs Forum 2015 7;42(4):348356. 10.1188/15.ONF.348-356

129 

KSCourneya, CMFriedenreich, CFranco-Villalobos, JJCrawford, NChua, SBasi, et al Effects of supervised exercise on progression-free survival in lymphoma patients: an exploratory follow-up of the HELP Trial. Cancer Causes Control 2015 2;26(2):269276. 10.1007/s10552-014-0508-x

130 

DAGalvao, NSpry, JDenham, DRTaaffe, PCormie, DJoseph, et al A multicentre year-long randomised controlled trial of exercise training targeting physical functioning in men with prostate cancer previously treated with androgen suppression and radiation from TROG 03.04 RADAR. Eur Urol 2014 5;65(5):856864. 10.1016/j.eururo.2013.09.041

131 

LTrinh, RCPlotnikoff, RERhodes, SNorth, KSCourneya. Feasibility and preliminary efficacy of adding behavioral counseling to supervised physical activity in kidney cancer survivors: a randomized controlled trial. Cancer Nurs 2014 Sep-Oct;37(5):E822. 10.1097/NCC.0b013e3182a40fb6

132 

ALHawkes, SKChambers, KIPakenham, TAPatrao, PDBaade, BMLynch, et al Effects of a telephone-delivered multiple health behavior change intervention (CanChange) on health and behavioral outcomes in survivors of colorectal cancer: a randomized controlled trial. J Clin Oncol 2013 6 20;31(18):23132321. 10.1200/JCO.2012.45.5873

133 

JRHebert, TGHurley, BEHarmon, SHeiney, CJHebert, SESteck. A diet, physical activity, and stress reduction intervention in men with rising prostate-specific antigen after treatment for prostate cancer. Cancer Epidemiol 2012 4;36(2):e12836. 10.1016/j.canep.2011.09.008

134 

AJLittman, LCBertram, RCeballos, CMUlrich, JRamaprasad, BMcGregor, et al Randomized controlled pilot trial of yoga in overweight and obese breast cancer survivors: effects on quality of life and anthropometric measures. Support Care Cancer 2012 2;20(2):267277. 10.1007/s00520-010-1066-8

135 

KMWinters-Stone, JDobek, LNail, JABennett, MCLeo, ANaik, et al Strength training stops bone loss and builds muscle in postmenopausal breast cancer survivors: a randomized, controlled trial. Breast Cancer Res Treat 2011 6;127(2):447456. 10.1007/s10549-011-1444-z

136 

ZDjuric, JSEllsworth, ALWeldon, JRen, CRRichardson, KResnicow, et al A Diet and Exercise Intervention during Chemotherapy for Breast Cancer. Open Obes J 2011;3:8797. 10.2174/1876823701103010087

137 

WDemark-Wahnefried, TJPolascik, SLGeorge, BRSwitzer, JFMadden, MTRuffin4th, et al Flaxseed supplementation (not dietary fat restriction) reduces prostate cancer proliferation rates in men presurgery. Cancer Epidemiol Biomarkers Prev 2008 12;17(12):35773587. 10.1158/1055-9965.EPI-08-0008

138 

ZLi, WJAronson, JRArteaga, KHong, GThames, SMHenning, et al Feasibility of a low-fat/high-fiber diet intervention with soy supplementation in prostate cancer patients after prostatectomy. Eur J Clin Nutr 2008 4;62(4):526536. 10.1038/sj.ejcn.1602743

139 

CLCarmack Taylor, CDemoor, MASmith, ALDunn, KBasen-Engquist, INielsen, et al Active for Life After Cancer: a randomized trial examining a lifestyle physical activity program for prostate cancer patients. Psychooncology 2006 10;15(10):847862. 10.1002/pon.1023

140 

TOhira, KHSchmitz, RLAhmed, DYee. Effects of weight training on quality of life in recent breast cancer survivors: the Weight Training for Breast Cancer Survivors (WTBS) study. Cancer 2006 5 1;106(9):20762083. 10.1002/cncr.21829

141 

CLLoprinzi, LMAthmann, CGKardinal, JRO’Fallon, JASee, BKBruce, et al Randomized trial of dietician counseling to try to prevent weight gain associated with breast cancer adjuvant chemotherapy. Oncology 1996 May-Jun;53(3):228232. 10.1159/000227565

142 

Fde Waard, RRamlau, YMulders, Tde Vries, Svan Waveren. A feasibility study on weight reduction in obese postmenopausal breast cancer patients. Eur J Cancer Prev 1993 5;2(3):233238. 10.1097/00008469-199305000-00007

143 

KSCourneya, RJSegal, DCMcKenzie, HDong, KGelmon, CMFriedenreich, et al Effects of exercise during adjuvant chemotherapy on breast cancer outcomes. Med Sci Sports Exerc 2014 9;46(9):17441751. 10.1249/MSS.0000000000000297

144 

JSchmitt, NLindner, MReuss-Borst, HCHolmberg, BSperlich. A 3-week multimodal intervention involving high-intensity interval training in female cancer survivors: a randomized controlled trial. Physiol Rep 2016 2;4(3):10.14814/phy2.12693. 10.14814/phy2.12693

145 

KSCourneya, RJSegal, JRMackey, KGelmon, RDReid, CMFriedenreich, et al Effects of aerobic and resistance exercise in breast cancer patients receiving adjuvant chemotherapy: a multicenter randomized controlled trial. J Clin Oncol 2007 10 1;25(28):43964404. 10.1200/JCO.2006.08.2024

146 

DPGuh, WZhang, NBansback, ZAmarsi, CLBirmingham, AHAnis. The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health 2009 3 25;9:88-2458-9-88. 10.1186/1471-2458-9-88

147 

EMCespedes Feliciano, MLKwan, LHKushi, EKWeltzien, ALCastillo, BJCaan. Adiposity, post-diagnosis weight change, and risk of cardiovascular events among early-stage breast cancer survivors. Breast Cancer Res Treat 2017 4;162(3):549557. 10.1007/s10549-017-4133-8

148 

GPfeiler, RKonigsberg, CFesl, BMlineritsch, HStoeger, CFSinger, et al Impact of body mass index on the efficacy of endocrine therapy in premenopausal patients with breast cancer: an analysis of the prospective ABCSG-12 trial. J Clin Oncol 2011 7 1;29(19):26532659. 10.1200/JCO.2010.33.2585

149 

Ede Azambuja, WMcCaskill-Stevens, PFrancis, EQuinaux, JPCrown, MVicente, et al The effect of body mass index on overall and disease-free survival in node-positive breast cancer patients treated with docetaxel and doxorubicin-containing adjuvant chemotherapy: the experience of the BIG 02–98 trial. Breast Cancer Res Treat 2010 1;119(1):145153. 10.1007/s10549-009-0512-0

150 

NDruesne-Pecollo, MTouvier, EBarrandon, DSChan, TNorat, LZelek, et al Excess body weight and second primary cancer risk after breast cancer: a systematic review and meta-analysis of prospective studies. Breast Cancer Res Treat 2012 10;135(3):647654. 10.1007/s10549-012-2187-1

151 

MMProtani, CMNagle, PMWebb. Obesity and ovarian cancer survival: a systematic review and meta-analysis. Cancer Prev Res (Phila) 2012 7;5(7):901910. 10.1158/1940-6207.CAPR-12-0048

152 

DLi, JSMorris, JLiu, MMHassan, RSDay, MLBondy, et al Body mass index and risk, age of onset, and survival in patients with pancreatic cancer. JAMA 2009 6 24;301(24):25532562. 10.1001/jama.2009.886

153 

HArem, MLIrwin. Obesity and endometrial cancer survival: a systematic review. Int J Obes (Lond) 2013 5;37(5):634639. 10.1038/ijo.2012.94

154 

YCao, JMa. Body mass index, prostate cancer-specific mortality, and biochemical recurrence: a systematic review and meta-analysis. Cancer Prev Res (Phila) 2011 4;4(4):486501.

155 

ADiscacciati, NOrsini, AWolk. Body mass index and incidence of localized and advanced prostate cancer—a dose-response meta-analysis of prospective studies. Ann Oncol 2012 7;23(7):16651671. 10.1093/annonc/mdr603

156 

JAMeyerhardt, PJCatalano, DGHaller, RJMayer, ABBenson3rd, JSMacdonald, et al Influence of body mass index on outcomes and treatment-related toxicity in patients with colon carcinoma. Cancer 2003 8 1;98(3):484495. 10.1002/cncr.11544

157 

JJDignam, BNPolite, GYothers, PRaich, LColangelo, MJO’Connell, et al Body mass index and outcomes in patients who receive adjuvant chemotherapy for colon cancer. J Natl Cancer Inst 2006 11 15;98(22):16471654. 10.1093/jnci/djj442

158 

CSPadilha, PCMarinello, DAGalvao, RUNewton, FHBorges, FFrajacomo, et al Evaluation of resistance training to improve muscular strength and body composition in cancer patients undergoing neoadjuvant and adjuvant therapy: a meta-analysis. J Cancer Surviv 2017 1 4 10.1007/s11764-016-0592-x

159 

Diabetes Prevention Program Research Group. Long-term effects of lifestyle intervention or metformin on diabetes development and microvascular complications over 15-year follow-up: the Diabetes Prevention Program Outcomes Study. Lancet Diabetes Endocrinol 2015 11;3(11):866875. 10.1016/S2213-8587(15)00291-0

160 

PJGoodwin, RTChlebowski. Obesity and Cancer: Insights for Clinicians. J Clin Oncol 2016 12 10;34(35):41974202. 10.1200/JCO.2016.70.5327