https://orcid.org/0000-0003-1582-5593
Figures
Abstract
Background
Breast (BCa) and prostate (PCa) cancer are two of the most common but survivable cancers. One important component of survivorship that is impacted by treatment long term is diminished quality of life (QoL). Supervised exercise improves QoL and subsequent outcomes but is not accessible for all survivors. Additionally, many factors influence QoL including physical activity (PA), cardiorespiratory fitness (CRF), physical function, and fatigue. However, the COVID-19 pandemic has highlighted the need to increase access to exercise beyond supervised exercise facilities. Home-based exercise may provide a feasible alternative for cancer survivors especially for those living in rural communities.
Objectives
The primary aim is to investigate the effects of home-based exercise training (Pre-training vs. Post-training) on QoL in BCa/PCa. A secondary aim is to investigate PA, CRF, physical function, and fatigue and potential moderators (age, cancer-type, intervention duration and type). Home-based exercise trials (randomized crossover or quasi-experimental design) with adults (aged 18 years and over) breast or prostate cancer survivors (not currently undergoing chemotherapy or radiation treatment) were eligible for inclusion.
Data sources
Electronic databases were searched (inception-December 2022) for studies which included adult BCa or PCa survivors (not currently on chemotherapy/radiation), at least measured QoL, and undergoing unsupervised, home-based exercise training.
Appraisal and synthesis methods
Initially, 819 studies were identified, from which 17 studies (20 effects) involving 692 participants were extracted. Effect sizes were calculated as standardized mean differences (SMD). Data were pooled using a 3-level model with restricted maximum likelihood estimation. Pooled SMD was used to assess the magnitude of effect, where <0.2, 0.2, 0.5, and 0.8 was defined as trivial, small, moderate, and large respectively.
Results
Home-based exercise resulted in small improvements in QoL (SMD = 0.30, 95% CI 0.01, 0.60, p = 0.042), PA (SMD = 0.49, 95% CI 0.26, 0.75, p<0.001) and CRF (SMD = 0.45, 95% CI -0.01, 0.91, p = 0.056). Physical function (SMD = 0.00, 95% CI -0.21, 0.21, p = 1.000) and fatigue (SMD = -0.61, 95%CI -1.53, 0.32, p = 0.198) did not change.
Conclusions
Home-based exercise results in small improves QoL in BCa/PCa survivors, independent of cancer type, intervention duration and type, or age. Home-based exercise also improves PA and CRF enhancing survivorship. Therefore, home-based exercise is an efficacious alternative option to improve QoL for BCa and PCa survivors especially for those who live in rural communities or lack access to exercise facilities.
Citation: Bates-Fraser LC, Riley S, Stopforth C, Moertl K, Edgar K, Stoner L, et al. (2023) Home-based exercise improves quality of life in breast and prostate cancer survivors: A meta-analysis. PLoS ONE 18(4): e0284427. https://doi.org/10.1371/journal.pone.0284427
Editor: Ronald Chow, University of Toronto Temerty Faculty of Medicine, CANADA
Received: March 1, 2022; Accepted: March 20, 2023; Published: April 20, 2023
Copyright: © 2023 Bates-Fraser et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
The survival rates for breast (BCa) and prostate (PCa), the two most common non-dermatological cancers, are high at 98 and 90% [1], respectively. However, of the estimated 7.5 million BCa and PCa survivors [2], many are burdened by diminished quality of life (QoL). Evidence demonstrates that declines in QoL [3–8] can be attributed to the cancer- and cancer treatment- related side effects [9–11], including increased fatigue [11,12] and subsequent reductions in physical activity [13,14] (PA), cardiorespiratory function [15] (CRF), and physical function [16]. One approach to combat reduced QoL is supervised exercise training. Further, it is known that supervised exercise decreases fatigue [11,12], can potentially increase PA [13,14], CRF [15] and physical function [16], and improves QoL [5–8]. However, supervised exercise is not always feasible due to many challenges at the environmental and behavioral levels [17–19]. Commonly reported barriers to exercise engagement include lack of access to exercise facilities, time to commute to exercise facilities around work or treatment schedules, health disparities (lack of resources in low socioeconomic areas) and residing in a rural community [17–19]. The importance of these barriers have become particularly emphasized in the wake of the COVID-19 pandemic [20]. Alternatively, home-based, unsupervised exercise may minimize the likelihood of the aforementioned barriers impeding exercise initiation and adherence in BCa and Pca survivors. However, the effect of home-based unsupervised exercise on QoL and other outcomes such as PA, CRF, physical function, and fatigue remain unknown.
The strongest form of evidence for guiding policy development, including exercise prescription, are meta-analytical findings [21,22]. While previous meta-analyses do support the use of supervised exercise for improving QoL in BCa and PCa survivors [23–25], such support is unavailable for unsupervised exercise. Home-based unsupervised exercise is a potentially advantageous strategy for BCa/PCa survivors who live in rural communities or lack access to supervised training. There are several important considerations in conducting such a meta-analysis, including the need to account for effect size dependencies and potential effect moderators. With respect to the former consideration, a range of instruments have been used to quantify QoL, including FACT-B [26], FACT-G [27], FACT-P [28], SF-36 [29], IBCSG [30], EORTC [31], PORPUS [32], PFS [33]. Some studies have used more than one of these tools, meaning that there is a need to account for multiple effects nested within a given study. No standardized exercise prescription exists for BCa/PCa survivors leading to studies with a variety of exercise training durations and types of exercise further complicating between study comparisons. Adjustments can be made for the nested effects using 3-level meta-analysis, which calculates the overall effect size while accounting for variance between studies (Level 3 tau2), variance between effect sizes extracted from the same study (Level 2 tau2), and sampling variance (Level 1 tau2) [34]. The 3-level model can also assess whether the QoL instruments moderates the effect, and thereby account for both level 2 and level 3 variance, and test additional moderators that may help to explain level 3 variance. Important potential moderators include the duration of the intervention and the form of exercise prescriptions (frequency, intensity, time, and type). Examination of the control groups were outside the scope of this meta-analysis. However, taking a 3-level meta-analytic approach will allow us to consolidate the existing literature most effectively to guide exercise recommendations for BCa/PCa survivors. Furthermore, in a 3-level model we can also account for variance due to potential moderators such as age or cancer type.
Finally, current American College of Sports Medicine Guidelines recommend engaging in 150 minutes of moderate-to-vigorous aerobic physical activity and resistance training at least 2 days per week [35,36]. Therefore, when comparing the effects of home-based unsupervised exercise, consideration for the exercise prescription is also key to inform subsequent recommendations and current practice. We must consider the type (i.e., aerobic, resistance training, or combined), frequency (i.e., days per week), and duration of the exercise intervention (i.e., number of weeks) when comparing the effect of exercise in BCa/PCa survivors.
1.1 Objective
The primary objective of this study was to examine the effect of home-based exercise on QoL in BCa/PCa survivors. Secondary objectives were to examine the effect of home-based exercise on PA, CRF, physical function, and fatigue. Additionally, exploratory analyses were conducted to examine potential differences in cancer type (BCa vs. PCa), study duration (≤ 12 weeks or ≥ 13 weeks), age (≤ 59 years old or ≥ 60 years old), exercise type (aerobic, resistance training, combined, or other), and assessment type.
2. Methods
This meta-analysis was carried out in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and registered with PROSPERO.
2.1 Data sources and searches
Electronic databases (PubMed, Embase, Scopus, SPORTDiscus, and Google Scholar) were searched by two authors (LB, KM) utilizing the search: (prostate cancer OR prostate tumor OR prostate neoplasm OR prostate malignancy OR breast cancer OR breast tumor OR breast malignancy OR hormonal cancer) AND (quality of life OR functional movement OR activities of daily living OR timed up and go OR 6 minute walk test OR gait OR balance OR physical function OR physical activity OR fatigue) AND (home based exercise OR home exercise training OR exercise at home OR unsupervised exercise OR home exercise OR walking). The reference lists of all identified trials and relevant reviews or editorials were also examined. The search was limited to English language studies published between inception and December 2022.
2.2 Article selection
For the purpose of this meta-analysis, the term ‘article’ is used synonymously with ‘study’, and ‘trial’ is the unit included in the meta-analysis. A given article may have resulted in more than one eligible ‘trial’ if the article included more than one intervention group. Initially, article titles and abstracts were screened for relevance. The full-text of potentially eligible articles were obtained to review eligibility for inclusion. The following criteria were used to select trials for inclusion in the review: i) Participants Inclusion: Adults (aged 18 years and over), ii) cancer survivors (i.e., not currently undergoing chemotherapy or radiation treatment), iii) breast or prostate cancer survivors (we will define survivorship as post-surgery and/or no longer undergoing chemotherapy or radiation treatment) and exclusion: i) Under the age of 18, ii) supervised exercise training and/or group-based exercise training, iii) cancer patient currently undergoing chemotherapy or radiation treatment.
In trials with multiple treatment arms and a single control group, the sample size of the control group was divided by the number of treatment groups to avoid over-inflation of the sample size. Repeated publications for the same studies were excluded. Two researchers (LB, KM) completed the study selection independently.
2.3 Data extraction and quality assessment
Data extracted for each eligible trial included bibliographic information (author, publication year), baseline participant characteristics, details of intervention(s), and results of reported outcomes. Study quality was assessed using the NIH Study Quality Assessment Tool [37] and RoB2: revised Cochrane risk-of-bias tool for randomized trials (range 1–3), which includes items related to randomization, deviations from intended interventions, missing data, measurement of the outcome, selection of the reported result, and overall bias [38]. Because it is difficult (if not impossible) to blind participants to an exercise intervention, we considered the blinding of the operator to the outcome assessment as a quality criterion. Data extraction, quality assessment, and scrutiny of the exercise interventions were completed by two authors (LB, SR).
2.4 Data synthesis
For each outcome of interest, the pre- and post-intervention values (mean and standard deviation) were entered into a spreadsheet. When mean differences and associated standard deviations were not published, they were estimated from the pre- and post-intervention values based on methods from the Cochrane Handbook for Systematic Reviews of Interventions. For studies reporting multiple time points, only the final time point was used in analyses. Primary study outcomes were QoL, PA, CRF (VO2), physical function, and fatigue variables. Two authors independently gathered data by reviewing literature, and then results were compared (LB and SR or KE or CS). Aggregation and calculation of final results was conducted by one author (LS).
2.5 Data analysis
A single author (LS) conducted statistical analysis using the metafor-package [39] for the R statistical environment (RKWard version 0.7.1). Considering the QoL measures are expressed using different units and scales, standardized mean differences (SMD) were calculated. Data were pooled using a 3-level model with restricted maximum likelihood estimation [40,41]. The pooled SMD was used to assess the magnitude of effect, where <0.2, 0.2, 0.5, and 0.8 was defined as trivial, small, moderate, and large respectively [42]. A 3-level meta-analysis model was used to account for effect size dependency when a given study reported more than one effect size (i.e., multiple QoL measures) [34]. These models permit calculation of a summary (or average/overall) effect size (SMD) estimate while accounting for variance between studies (Level 3 tau2), variance between effect sizes extracted from the same study (Level 2 tau2), and sampling variance (Level 1 tau2). Subsequent to running the 3-level models, we examined the robustness of the pooled results, the potential for publication bias, and heterogeneity. In the event of significant heterogeneity, moderator analysis was conducted. The α level was set a priori at α = 0.05 for the pooled SMD estimate and α = 0.10 for moderator analysis.
Robustness was examined at each level of the model using Studentized residuals and Cook’s distances. Studies with a studentized residual larger than the 100 x (1–0.05/(2 X k)) were considered potential outliers. Studies with a Cook’s distance larger than the median plus six times the interquartile range of the Cook’s distances were considered to be influential. Publication bias was qualitatively examined through inspection of Begg’s funnel plot, and funnel plot asymmetry was quantitively tested using the regression intercept test, with the standard error of the observed outcomes specified as a moderator in the 3-level model [43]. Last, heterogeneity was assessed the Q-test [44] and the I2 statistic [45], where <25%, 25%-75%, >75% indicate low, moderate and considerate risk, respectively. Significant heterogeneity indicated that effect sizes could not be treated as estimates of one common effect size. The level of variance (tau2) was examined using log-likelihood ratio tests, where the full model was compared to separate models excluding level-2 (within-study, e.g., multiple QoL outcomes) and level-3 (between-study) variance parameters. Subsequently, the model was extended with a priori determined moderator analysis (cancer type, assessment type, age, exercise duration, or exercise type). The amount of variance explained through the specific of moderator(s) was examined by calculating the percentage reduction in the tau2 at each level of the model. In the event of a significant moderator, subgroup analysis was performed through use of dichotomous dummy coded variables.
3. Results
3.1 Literature search and selection
Fig 1 outlines the literature search strategy. A total of 949 potentially eligible articles were identified. Following screening of titles and abstracts, 914 articles were excluded because they did not meet selection criteria. Of these, 35 randomized cross-over trials underwent full text review and 18 were excluded due to i) supervised exercise component [46–51], ii) participants undergoing cancer treatment [52–56], iii) or outcome of interest [57–63]. The final analysis included 17 studies (20 trials) [64–80] with 17 studies reporting QoL, 10 PA, 6 CRF, 7 physical function, and 14 fatigue.
3.2 Description of the included studies
3.2.1 Study setting and participants.
Included trial characteristics are summarized in Table 1. The trials were carried out in the US (n = 9), Canada (n = 4), Italy (n = 1), Turkey (n = 1), Netherlands (n = 1), UK (n = 1), India (n = 1), Germany (n = 1), and Denmark (n = 1). The number of participants in each trial ranged from 7 to 249 (median = 20, mean = 28.6). Fourteen trials included only BCa survivors and five trials only PCa survivors. The mean age of the participants ranged from 51 to 72 years (60 (7)). Only thirteen trials reported baseline body mass index (kg/m2). The mean body mass index was 28.8 (1.4).
3.2.2 Interventions.
A brief description of the exercise interventions is given in Table 1. The duration of interventions varied in length from 2 weeks to 52 weeks, with a median of 12 weeks. The trials included aerobic exercise only, resistance exercise only, aerobic and resistance training combined, walking, or other (yoga, exergaming, or gardening).
3.2.3 Methodological quality assessment.
The methodological assessment of included trials is summarized in Table 1. The quality of the included studies ranged from 1–3 (1 being poor and 3 being high quality), with a median quality score of 2 and a mean score of 2.1. Fourteen of the studies were randomized but only six stated that the allocation process was concealed, and outcome assessors were blinded. Ten studies adequately described withdrawal rates and reason for withdrawal, whereas only eight studies described adherence and two mentioned compliance to the intervention. Five studies were given a score of 3 and considered high quality because they reported a randomized design, measured PA at the beginning and end of study, included adherence/compliance/drop-out data, and the exercise prescribed met ACSM guidelines. Twelve studies were given a score of 2 and considered fair quality and three studies were given a score of 1 and considered poor quality.
3.3 Synthesis of results
3.3.1 Quality of life.
The pooled SMD was used to assess the magnitude of effect, where <0.2, 0.2, 0.5, and 0.8 was defined as trivial, small, moderate, and large respectively [42]. The pooled SMD effect from the 3-level model is presented initially, and then discussion of heterogeneity and effect measure modification follow.
In total k = 17 studies were included, from which u = 23 effect sizes were extracted with a total sample of n = 657. The adjudicated mean quality of the articles was 2 (out of 3), with a range of 1 to 3. The observed SMDs ranged from -1.1 to 1.9, with the majority of estimates (74%) being positive/beneficial.
The pooled SMD effect is presented in Fig 2, which contained the significant effect moderator assessment type. Data are presented by moderator. Based on the 3-level model, there was a small but significant effect (SMD = 0.30, 95% CI: 0.01 to 0.60, p = 0.042). Examination of the studentized residuals and Cook’s distance revealed that one study [71] may be an outlier and could be considered influential. Removal of Malem [71] decreased the size of the estimated effect, which remained small and significant (SMD = 0.21, 95% CI: 0.02 to 0.40, p = 0.030). No asymmetry (p = 0.174) was revealed following inspection of the funnel plot and regression test.
(k = 17, u = 23, n = 508). Based on the 3-level model, there was a small but significant effect (SMD = 0.30, 95% CI: 0.01 to 0.60, p = 0.042). Abbreviations: CI, confidence interval; SMD, standardized mean differences.
According to the Q-test, the true outcomes appear to be heterogeneous (Q = 65, p<0.001, tau2 = 0.26, I2 = 63%). The majority of the variance was at level-3 (77%), with the remainder of the variance at level-1 (23%). Neither cancer type (p = 0.483), study duration (p = 0.148), participant age (p = 0.279) or exercise prescription type (p = 0.795) were significant effect moderators. However, QoL measurement method was a significant moderator (p = 0.002), decreasing the level-3 variance by 52% and the overall variance by 40%. The subgroup analysis for QoL method is presented in Fig 2. There was a moderate significant increase (beneficial) for EORTC (p = <0.001), trivial to small non-significant increases for FACT (p = 0.498), SF-36 (p = 0.434) and IBCSG (p = 0.834), and a significant large decrease (beneficial) for PIPER (p = 0.044). The Malem study, which was identified as potential outlier/influential, utilized the EORTC method. With the removal of this study the effect for the EORTC method was reduced to small-moderate effect, but remained significant (SMD = 0.48, 95% CI: 0.24 to 0.73, p<0.001).
3.3.2 Physical activity.
In total of k = 10 studies were included, from which u = 14 effect sizes were extracted with a total sample of n = 630. The adjudicated mean quality of the articles was 2 (out of 3), with a range of 2 to 3. The observed SMD ranged from -0.2 to 1.7, with the majority of estimates being positive/beneficial (86%).
The pooled effect is reported in in Fig 3 by moderator assessment type. Based on the 3-level model, there was a small but significant effect (SMD = 0.49, 95% CI: 0.22 to 0.75, p<0.001). Examination of the studentized residuals and Cook’s distance revealed no outliers or potentially influential studies or effects. Inspection of the funnel plot nor the regression test indicated asymmetry (p = 1.000).
Based on the 3-level model, there was a small but significant effect (SMD = 0.49, 95% CI: 0.22 to 0.75, p<0.001). Abbreviations: CI, confidence interval; SMD, standardized mean differences.
According to the Q-test, the true outcomes appear to be moderately heterogeneous (Q = 34, p = 0.001, tau2 = 0.11, I2 = 56%). The majority of the variance was at level-3 (66%), followed by level-1 (28%) and level-2 (6%). Neither cancer type (p = 0.133), study duration (p = 0.109), participant age (p = 0.130) or exercise prescription type (p = 0.245) were significant effect moderators. However, PA measurement method was a significant moderator (p = 0.069), decreasing the level-3 variance by 5%, and the overall variance by 9%. The subgroup analysis for PA measurement method is presented in Fig 3. There was a moderate (SMD = 0.54) increase (beneficial) for self-reported PA (p<0.001), and a small (SMD = 0.28), non-significant increase for objectively measured PA (p = 0.113). With the removal of Nyrop [73] and Spector [75] (due to the potential of these studies being outliers) the pooled effect size was reduced for both self-reported PA (SMD = 0.38, 95% CI: 0.22 to 0.55, p<0.001) and for objectively measured PA (SMD = 0.16, 95% CI: -0.10 to 0.23, p = 0.230).
3.3.3 Cardiorespiratory fitness.
In total of k = 7 studies were included, from which u = 14 effect sizes were extracted with a total sample of n = 312. The adjudicated mean quality of the articles was 2 (out of 3), with a range of 2 to 3. The observed SMD ranged from -0.2 to 1.9, with the majority of estimates being positive/beneficial (86%).
The pooled effect is reported in in Fig 4 on moderator exercise type. Based on the 3-level model, there was a small effect (SMD = 0.45, 95% CI: -0.01 to 0.91) which approached significance (p = 0.056). Examination of the studentized residuals and Cook’s distance revealed that one study (Santa Mina) may be an outlier and could be considered influential. Removal of Santa Mina due to the chance of it being an outlier decreased the size of the estimated effect (SMD = 0.20, 95% CI: -0.01 to 0.40, p = 0.067). Inspection of the funnel plot and the regression test indicated likely asymmetry (p = 0.067).
Based on the 3-level model, there was a small effect (SMD = 0.45, 95% CI: -0.01 to 0.91) which approached significance (p = 0.056). Abbreviations: CI, confidence interval; SMD, standardized mean differences.
According to the Q-test, the true outcomes appear to be considerably heterogeneous (Q = 68, p<0.001, tau2 = 0.44, I2 = 78). The majority of the variance was at level-3 (75%), with the remainder of the variance at level-1 (25%). Neither measurement type (p = 0.212), cancer type (p = 0.852), study duration (p = 0.213), participant age (p = 0.852) or VO2max unit expression (p = 0.403) were significant effect moderators. However, exercise prescription modality was approached being a significant moderator (p = 0.101), decreasing the level-3 variance by 39% and the overall variance by 29%. The subgroup analysis for exercise prescription modality is presented in Fig 4. There was a large, significant increase (beneficial) for aerobic (p = 0.001) or strength (p = 0.018) exercise prescription, a small, non-significant increase for combined (p = 0.286), and a trivial, non-significant decrease for other (p = 0.966). The Santa Mina [72] study included both aerobic and strength arms. Removal of this study decreased the pooled effect size for both aerobic (SMD = 0.33, 95%CI: -0.73 to 1.38, p = 0.541) and strength (SMD = 0.17, 95%CI: -0.81 to 1.15, p = 0.736), and combined became significant (SMD = 0.27, 95%CI: 0.01 to 0.53, p = 0.039).
3.3.4 Physical function.
In total of k = 7 studies were included, from which u = 12 effect sizes were extracted with a total sample of n = 285. The adjudicated mean quality of the articles was 2 (out of 3), with a range of 2 to 3. The observed SMD ranged from -0.6 to 0.5. An increase in 6-minute walk, 1-minute chair stands, 30 second chair stands, grip strength, and questionnaires (FACT) indicate a beneficial change. A decrease in timed-up-and-go also indicates a positive/beneficial change.
The pooled effect is reported in Fig 5 on moderator assessment type. Based on the 3-level model, there was no discernable effect (SMD = 0.00, 95% CI: -0.21 to 0.21, p = 1.000). Examination of the studentized residuals and Cook’s distance revealed no outliers or potentially influential studies or effects. Inspection of the funnel plot nor the regression test indicated asymmetry (p = 0.174).
Based on the 3-level model, there was no discernable effect (SMD = 0.00, 95% CI: -0.21 to 0.21, p = 1.000). Abbreviations: CI, confidence interval; SMD, standardized mean differences.
According to the Q-test, the true outcome has a low risk of being heterogeneous (Q = 15, p<0.165, tau2 = 0.036, I2 = 29%). The majority of the variance was at level-1 (66%), followed by level-2 (34%). Neither cancer type (p = 0.738), study duration (p = 0.936), participant age (p = 0.888) or exercise prescription type (p = 0.575) were significant effect moderators. However, physical function measurement method was a significant moderator (p = 0.012), decreasing the overall variance by 34%. The subgroup analysis for physical function method is presented in Fig 5. There was a small increase for Stand30 (p = 0.036) and a moderate decrease for self-report (p = 0.018). There were trivial-small, non-significant increases for 6MWT (p = 0.093) and Stand1 (p = 0.570), and negligible-small, non-significant decreases for grip strength (p = 0.729) and TUG (p = 0.243).
3.3.5 Fatigue.
In total of k = 14 studies were included, from which u = 18 effect sizes were extracted with a total sample of n = 407. The adjudicated mean quality of the articles was 2 (out of 3), with a range of 1 to 3. The observed SMD ranged from –7.3 to 0.5, with the majority of estimates (67%) being negative (beneficial), such that a smaller number represents less fatigue.
The pooled effect is reported in Fig 6 on moderator age. Based on the 3-level model, there was a moderate but non-significant effect (SMD = -0.61, 95% CI: -1.53 to 0.32, p = 0.198). Examination of the studentized residuals and Cook’s distance revealed that one study (Melam [71]) may be an outlier and could be considered influential. Removal of Malem decreased the size of the estimated effect (SMD = -0.18, 95% CI: -0.44 to 0.07, p = 0.163). Inspection of the funnel and the regression test likely indicated funnel plot asymmetry (p<0.001).
Based on the 3-level model, there was a moderate but non-significant effect (SMD = -0.61, 95% CI: -1.53 to 0.32, p = 0.198). Abbreviations: CI, confidence interval; SMD, standardized mean differences.
According to the Q-test, the true outcomes appear to be heterogeneous (Q = 132, p<0.001, tau2 = 0.55, I2 = 87%). The majority of the variance was at level-3 (97%), with the remainder of the variance at level-1 (3%). Neither cancer fatigue measurement method (p = 0.913), cancer type (p = 0.410), study duration (p = 0.432), participant age (p = 0.167) or exercise prescription type (p = 0.894) were significant effect moderators.
4. Discussion
The aim of this meta-analysis was to investigate the effects of home-based exercise interventions on BCa and PCa survivors. The main findings were that home-based exercise leads to a small, but significant (SMD = 0.30, p = 0.042) increase in QoL. Additionally, small increases were found in PA (SMD = 0.49, p<0.001) and CRF (SMD = 0.45, p = 0.056). Home-based exercise did not affect physical function SMD = 0.00, p = 0.100) and there were moderate but non-significant (SMD = -0.61, p = 0.198) improvements reported in fatigue.
4.1 Limitations
Several limitations should be borne in mind when considering the findings of this meta-analysis. First, the sample size of included trials was generally small, and a limited number of trials reported all variables of interest. Second, the small number of trials limits the conclusions drawn from the sub-group analysis; further trials are required to delineate the interactions more clearly between home-based exercise interventions. Third, the quality of the included trials was generally fair (median quality score of 2 and a mean score of 2.1 on a scale of 1 (poor) to 3 (high) quality) and lacked information on intervention adherence and compliance.
4.2 Quality of life
Our findings suggest that home-based exercise results in a small but improvement in QoL regardless of the exercise type, intervention duration, age, or cancer (BCa or PCa) type. These data expand on the recent systematic review [20] which established that home-based exercise is feasible in a variety of cancer survivors. Arguably any improvement in QoL is meaningful as enhanced QoL is critical in survivorship. Interestingly, it appears that the questionnaire used may impact the magnitude of QoL quantified. EORTC may be more sensitive to physical changes and FACT may be more sensitive to psychosocial changes [81]. For example, every study that assessed QoL using the EORTC reported some degree of improvement (positive or beneficial change) whereas studies that assessed QoL using the FACT reported mixed findings. Investigators utilizing exercise training to improve QoL may wish to consider EORTC as it may better detect physical changes initiated by PA. Both the EORTC and FACT are valid and reliable questionnaires, but investigators should consider the purpose of their evaluation (physical or psychosocial) when selecting which measurement tool to use [81,82].
These data suggest that home-based exercise improves physical outcomes (function, CRF) contributing to an enhanced QoL but may not improve psychosocial outcomes [83]. Since home-based exercise is completed without supervision or a community it may not confer the same social benefit as supervised or group exercise training [84–86]. There is a significant positive association between social support and PA [87]. In wake of the COVID-19 pandemic and a shift to the virtual delivery of exercise programs [84], we must consider ways to increase social support for cancer survivors. Furthermore, qualitative data investigating psychosocial benefits from PA in breast and prostate cancer survivors suggest that despite facing many barriers to PA engagement, support from other cancer survivors or family/friends should be considered in exercise prescription [88,89].
Our hypothesis that home-based exercise training improves QoL in BCa and PCa survivors was confirmed which is meaningful for survivors, especially those living in rural communities. There was no asymmetry, and the data was heterogenous. When comparing these data to meta-analyses investigating supervised exercise training, we see improvements in QoL of similar magnitude. QoL increased following supervised exercise training in two BCa (SMD = 0.35; 95% CI: 0.15–0.54 [90] and SMD = 0.45, 95% CI 0.20–0.69 [91]) and one PCa (SMD = 0.29; 95% CI = 0.10–0.49 [5]) meta-analysis. Home-based exercise in this study resulted in a highly comparable significant increase in QoL (SMD = 0.30, 95% CI: 0.01 to 0.60). Therefore, unsupervised home-based exercise training is an advantageous strategy for BCa/PCa survivors since it requires far less resources (e.g., supervised exercise facility, commuting time, etc.) than supervised exercise training and results in comparable increases in QoL so long as the goals set are reasonable [92].
When comparing our findings to supervised exercise training, improvements in QoL between the training strategies is of similar magnitude. Supervised exercise training increased QoL in two BCa (SMD = 0.35; 95% CI: 0.15–0.54 [90] and SMD = 0.45, 95% CI 0.20–0.69 [91]) and one PCa (SMD = 0.29; 95% CI = 0.10–0.49 [5]) meta-analyses, which is comparable to increase in QoL shown in the current study using home-based exercise (SMD = 0.30, 95% CI: 0.01 to 0.60). Additionally, although the studies included in this investigation explored different types of exercise [i.e., aerobic exercise only, resistance exercise only, aerobic and resistance training combined, walking, or other (yoga, exergaming, or gardening)] the exercise prescription type did not significantly impact the results. Therefore, for older cancer survivors the type of exercise prescribed should be based on feasibility and potential enjoyment. Further, the majority of studies (N = 15) prescribed an exercise frequency in line with the current American College of Sports Medicine (ACSM) guidelines of achieving 150 minutes of moderate-to-vigorous physical activity on 3–5 days per week. Therefore, unsupervised home-based exercise training is an advantageous strategy for BCa/PCa survivors since it requires far less resources (e.g., supervised exercise facility, commuting time, etc.) than supervised exercise training and results in highly comparable increases in QoL.
4.3 Physical activity, cardiorespiratory fitness, physical function, and fatigue
Secondary aims of this meta-analysis were to investigate the effect of home-based exercise training on PA, CRF, physical function, and fatigue. Engaging in PA throughout the day is important in mitigating sedentary behavior and engaging in healthy lifestyle behaviors to prevent chronic disease risk. Due to a high prevalence of cardiometabolic disease in BCa/PCa survivors [93,94], PA engagement is very important to survivorship as it contributes to CRF and helps prevent secondary disease [13,14]. Overall, there is a moderate improvement (SMD = 0.49, p<0.001) in PA reported following home-based exercise training. Our hypothesis that home-based exercise would improve PA was confirmed. However, despite no asymmetry our data had moderate heterogeneity. The heterogeneity could be due to variation in baseline PA levels between studies or variation in PA assessment type (self-report vs. accelerometry). In this meta-analysis, approximately half of the included studies reported BCa/PCa survivors that were physically active [64,67,69,72,77] (meeting ACSM guidelines of 150 minutes of moderate intensity PA per week) at baseline. It is also important to note that only 3 studies objectively measured PA using accelerometry [69,75,80], with the majority of studies using self-reported PA measurements. Studies that utilized accelerometry reported small improvements in PA (SMD = 0.28), whereas self-reported PA was reported to be larger (SMD = 0.54). This suggesting that BCa/PCa survivors over-estimate their physical activity levels. Investigators should keep this in mind when designing future interventions and use accelerometry to measure PA whenever possible to ensure objective accurate measurements [95].
Following home-based exercise training there were also small improvements in CRF that approached significance (SMD = 0.49, p = 0.056). The data had asymmetry likely due to one outlier and considerable heterogeneity which could also be due to variance in baseline CRF similar to PA. Aerobic exercise training resulted in the largest (SMD = 1.27) improvements in CRF, followed by strength training (SMD = 0.89) and then combined (SMD = 0.28). Both aerobic and strength training can benefit CRF, so the participants goals should be considered when designing exercise prescription.
Interestingly physical function did not improve following home-based exercise training (SMD = 0.00, p = 1.00) with no asymmetry or heterogeneity. Physical function is typically considered a key determinant in predicting QoL [16,96]. For example, if someone lacks physical function, then they likely also have a reduced QoL. Therefore, we were surprised that QoL increased despite no improvement in physical function. We postulate that perhaps physical function does not seem to improve because i) we do not have a universal means of assessment in the field or across the studies included in this meta-analysis; or ii) upon further examination of the participants in the study physical function was relatively average at baseline compared to older adults without BCa/PCa. Grip strength and 6-minute walk reported were average for participants and timed stand tests/TUG were just below average indicating that the participants in this meta-analysis may have not had the expected physical function determinants usually expected in BCa/PCa survivors.
Fatigue is one of the most common side effects for BCa/PCa survivors, yet we found only a moderate, non-significant (SMD = -0.61, p = 0.198) decrease in fatigue with asymmetry likely from one outlier and heterogeneity in the data. However, only three studies included in this meta-analysis reported severe fatigue at baseline [65,66,73]. The remaining studies reported only moderate or mild fatigue. The variation in baseline levels of fatigue may be why there was heterogeneity and non-significant findings. Furthermore, the result of exercise training on fatigue was highly varied. A meta-analysis of the effects of supervised exercise on fatigue in BCa found a clear significant improvement in fatigue after both aerobic (SMD = -0.51) and resistance training (SMD = -0.41) [97]. Therefore, we hypothesized that home-based exercise would elicit similar findings. At first, we were surprised by the non-significant improvement in fatigue, especially considering the large effect. However, upon further investigation, the majority of BCa/PCa survivors included in this meta-analysis do no report severe fatigue at baseline. Currently undergoing chemotherapy or radiation was an exclusion criterion which may explain why participants were not suffering from severe fatigue at baseline. Since many of the participants included in this study were not suffering from severe fatigue at baseline is it not surprising that exercise training did not improve fatigue since it was not actually a problem at baseline. Additionally, there is no standardized procedure for assessing fatigue which could explain some of the variation in these data. Further research is needed to design a robust tool to assess fatigue.
5. Conclusions
Cancer survivorship is a dynamic process which evolves over time for BCa/PCa survivors. Health outcomes such as QoL, PA, CRF, physical function, and fatigue contribute towards the life of a BCa/PCa survivor after cancer. Unsupervised, home-based exercise training may be a good alternative for survivors who do not have access or interest in participating in supervised or group-based programs (Table 2). However, we must consider limitations of the current literature (e.g., limited number of high-quality trials, small sample sizes) along with the long-term sustainability of this approach [84]. Engaging in home-based exercise results in small improvements in QoL, which is arguably the most important outcome investigated by this current study because it is critical in survivorship. Therefore, clinicians and caregivers should encourage BCa/PCa survivors to engage in exercise to improve QoL, PA and CRF. Future research is needed to continue refining exercise prescription/guidelines for BCa/PCa survivors and additional research is needed to effectively target the needs of various cancer types and exercise delivery to other timepoints among the cancer care continuum.
Supporting information
S1 Fig. Funnel plot of observed outcomes (standardized mean difference) for quality of life.
Description. Funnel plot constructed using 3-level model. Includes k = 17 studies, u = 23 effect sizes, and total sample of n = 657. Regression intercept test constructed by specifying the standard error of the observed outcomes as a moderator in a 3-level model. Interpretation. No asymmetry (p = 0.174) was revealed following inspection of the funnel plot and regression test.
https://doi.org/10.1371/journal.pone.0284427.s001
(DOCX)
S2 Fig. Funnel plot of observed outcomes (standardized mean difference) for physical activity.
Description. Funnel plot constructed using 3-level model. Includes k = 10 studies, u = 14 effect sizes, and total sample of n = 630. Regression intercept test constructed by specifying the standard error of the observed outcomes as a moderator in a 3-level model. Interpretation. Inspection of the funnel plot nor the regression test indicated asymmetry (p = 1.000).
https://doi.org/10.1371/journal.pone.0284427.s002
(DOCX)
S3 Fig. Funnel plot of observed outcomes (standardized mean difference) for cardiorespiratory fitness.
Description. Funnel plot constructed using 3-level model. Includes k = 7 studies, u = 14 effect sizes, and total sample of n = 312. Regression intercept test constructed by specifying the standard error of the observed outcomes as a moderator in a 3-level model. Interpretation. Inspection of the funnel plot and the regression test indicated likely asymmetry (p = 0.067).
https://doi.org/10.1371/journal.pone.0284427.s003
(DOCX)
S4 Fig. Funnel plot of observed outcomes (standardized mean difference) for physical function.
Description. Funnel plot constructed using 3-level model. Includes k = 7, studies, u = 12, effect sizes, and total sample of n = 285. Regression intercept test constructed by specifying the standard error of the observed outcomes as a moderator in a 3-level model. Interpretation. Inspection of the funnel plot nor the regression test indicated asymmetry (p = 0.174).
https://doi.org/10.1371/journal.pone.0284427.s004
(DOCX)
S5 Fig. Funnel plot of observed outcomes (standardized mean difference) for fatigue.
Description. Funnel plot constructed using 3-level model. Includes k = 14, studies, u = 18 effect sizes, and total sample of n = 407. Regression intercept test constructed by specifying the standard error of the observed outcomes as a moderator in a 3-level model. Interpretation. Inspection of the funnel and the regression test likely indicated funnel plot asymmetry (p< 0.001).
https://doi.org/10.1371/journal.pone.0284427.s005
(DOCX)
References
- 1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2022. CA Cancer J Clin. 2022 Jan 1;71(1):7–33.
- 2. Miller KD, Nogueira L, Mariotto AB, Rowland JH, Yabroff KR, Alfano CM, et al. Cancer treatment and survivorship statistics, 2019. CA Cancer J Clin. 2019 Sep 1;69(5):363–85. pmid:31184787
- 3. Arndt V, Koch-Gallenkamp L, Jansen L, Bertram H, Eberle A, Holleczek B, et al. Quality of life in long-term and very long-term cancer survivors versus population controls in Germany. Acta Oncol (Madr). 2017;56(2):190–7. pmid:28055266
- 4. Jarrett N, Scott I, Addington-Hall J, Amir Z, Brearley S, Hodges L, et al. Informing future research priorities into the psychological and social problems faced by cancer survivors: a rapid review and synthesis of the literature. European Journal of Oncology Nursing. 2013;17(5):510–20. pmid:23619278
- 5. Teleni L, Chan RJ, Chan A, Isenring EA, Vela I, Inder WJ, et al. Exercise improves quality of life in androgen deprivation therapy-treated prostate cancer: systematic review of randomised controlled trials. Endocr Relat Cancer. 2016;23(2):101–12. pmid:26584972
- 6. Valenti M, Porzio G, Aielli F, Verna L, Cannita K, Manno R, et al. Physical exercise and quality of life in breast cancer survivors. Int J Med Sci. 2008;5(1):24. pmid:18219372
- 7. Buffart LM, Kalter J, Sweegers MG, Courneya KS, Newton RU, Aaronson NK, et al. Effects and moderators of exercise on quality of life and physical function in patients with cancer: An individual patient data meta-analysis of 34 RCTs. Cancer Treat Rev. 2017;52:91–104. pmid:28006694
- 8. Zhang X, Li Y, Liu D. Effects of exercise on the quality of life in breast cancer patients: a systematic review of randomized controlled trials. Supportive Care in Cancer. 2019;27(1):9–21. pmid:30032399
- 9. Campbell KL, Winters-Stone KM, Patel AV, Gerber LH, Matthews CE, May AM, et al. An Executive Summary of Reports From an International Multidisciplinary Roundtable on Exercise and Cancer: Evidence, Guidelines, and Implementation. Rehabilitation Oncology. 2019;37(4).
- 10. Ndjavera W, Orange S, O’Doherty A, Leicht AS, Rochester M, Mills R, et al. Exercise‐induced attenuation of treatment side‐effects in patients with newly diagnosed prostate cancer beginning androgen‐deprivation therapy: a randomised controlled trial. BJU Int. 2020;125(1):28–37. pmid:31605663
- 11. Wagoner CW, Lee JT, Battaglini CL. Community-based exercise programs and cancer-related fatigue: a systematic review and meta-analysis. Supportive Care in Cancer. 2021. pmid:33751225
- 12. Taaffe DR, Newton RU, Spry N, Joseph D, Chambers SK, Gardiner RA, et al. Effects of different exercise modalities on fatigue in prostate cancer patients undergoing androgen deprivation therapy: a year-long randomised controlled trial. Eur Urol. 2017;72(2):293–9. pmid:28249801
- 13. Finlay A, Wittert G, Short CE. A systematic review of physical activity-based behaviour change interventions reaching men with prostate cancer. Journal of Cancer Survivorship. 2018;12(4):571–91. pmid:29770953
- 14. Peterson LL, Ligibel JA. Physical activity and breast cancer: an opportunity to improve outcomes. Curr Oncol Rep. 2018;20(7):1–10. pmid:29713835
- 15. Scott JM, Zabor EC, Schwitzer E, Koelwyn GJ, Adams SC, Nilsen TS, et al. Efficacy of exercise therapy on cardiorespiratory fitness in patients with cancer: a systematic review and meta-analysis. Journal of Clinical Oncology. 2018;36(22):2297. pmid:29894274
- 16. Sweegers MG, Altenburg TM, Chinapaw MJ, Kalter J, Verdonck-de Leeuw IM, Courneya KS, et al. Which exercise prescriptions improve quality of life and physical function in patients with cancer during and following treatment? A systematic review and meta-analysis of randomised controlled trials. Br J Sports Med. 2018;52(8):505–13. pmid:28954800
- 17. Knowlton SE O’Donnell EK, Horick N, Perez GK, Park E, Rabin J, et al. Moving forward on all fronts: impact, patterns, and barriers to exercise in cancer survivors and patients living with advanced disease. Supportive Care in Cancer. 2020;28(10):4979–88. pmid:32034513
- 18. Weller S, Oliffe JL, Campbell KL. Factors associated with exercise preferences, barriers and facilitators of prostate cancer survivors. Eur J Cancer Care (Engl). 2019;28(5):e13135. pmid:31332891
- 19. Jones LM, Reinhoudt LL, Hilverda F, Rutjes C, Hayes SC. Using the integrative model of behavioral prediction to understand female breast cancer survivors’ barriers and facilitators for adherence to a community-based group-exercise program. In: Seminars in Oncology Nursing. Elsevier; 2020. p. 151071. pmid:33008683
- 20. Batalik L, Winnige P, Dosbaba F, Vlazna D, Janikova A. Home-Based Aerobic and Resistance Exercise Interventions in Cancer Patients and Survivors: A Systematic Review. Cancers (Basel). 2021;13(8):1915. pmid:33921141
- 21. Stoner L, Barone Gibbs B, Meyer ML, Fryer S, Credeur D, Paterson C, et al. A Primer on Repeated Sitting Exposure and the Cardiovascular System: Considerations for Study Design, Analysis, Interpretation, and Translation. Vol. 8, Frontiers in Cardiovascular Medicine. 2021. p. 894. pmid:34485414
- 22. Harris RP, Helfand M, Woolf SH, Lohr KN, Mulrow CD, Teutsch SM, et al. Current methods of the US Preventive Services Task Force: a review of the process. Am J Prev Med. 2001 Apr;20(3 Suppl):21–35. pmid:11306229
- 23. Bourke L, Smith D, Steed L, Hooper R, Carter A, Catto J, et al. Exercise for men with prostate cancer: a systematic review and meta-analysis. Eur Urol. 2016;69(4):693–703. pmid:26632144
- 24. Ferrer RA, Huedo-Medina TB, Johnson BT, Ryan S, Pescatello LS. Exercise interventions for cancer survivors: a meta-analysis of quality of life outcomes. Annals of behavioral medicine. 2011;41(1):32–47. pmid:20931309
- 25. Gerritsen JKW, Vincent AJPE. Exercise improves quality of life in patients with cancer: a systematic review and meta-analysis of randomised controlled trials. Br J Sports Med. 2016;50(13):796–803. pmid:26719503
- 26. Brady MJ, Cella DF, Mo F, Bonomi AE, Tulsky DS, Lloyd SR, et al. Reliability and validity of the Functional Assessment of Cancer Therapy-Breast quality-of-life instrument. Journal of clinical oncology. 1997;15(3):974–86. pmid:9060536
- 27. Cella DF, Tulsky DS, Gray G, Sarafian B, Linn E, Bonomi A, et al. The Functional Assessment of Cancer Therapy scale: development and validation of the general measure. J Clin Oncol. 1993;11(3):570–9. pmid:8445433
- 28. Esper P, Mo FEI, Chodak G, Sinner M, Cella D, Pienta KJ. Measuring quality of life in men with prostate cancer using the functional assessment of cancer therapy-prostate instrument. Urology. 1997;50(6):920–8. pmid:9426724
- 29. Ware JE Jr, Gandek B. Overview of the SF-36 health survey and the international quality of life assessment (IQOLA) project. J Clin Epidemiol. 1998;51(11):903–12. pmid:9817107
- 30. Bernhard J, Hürny C, Coates AS, Peterson HF, Castiglione-Gertsch M, Gelber RD, et al. Quality of life assessment in patients receiving adjuvant therapy for breast cancer: The IBCSG approach. Annals of Oncology. 1997;8(9):825–35.
- 31. Aaronson NK, Cull A, Kaasa S, Sprangers MAG. The EORTC modular approach to quality of life assessment in oncology. Int J Ment Health. 1994;23(2):75–96.
- 32. Ritvo P, Irvine J, Naglie G, Tomlinson G, Bezjak A, Matthew A, et al. Reliability and validity of the PORPUS, a combined psychometric and utility-based quality-of-life instrument for prostate cancer. J Clin Epidemiol. 2005;58(5):466–74. pmid:15845333
- 33. Piper BF, Dibble SL, Dodd MJ, Weiss MC, Slaughter RE, Paul SM. The revised Piper Fatigue Scale: psychometric evaluation in women with breast cancer. In: Oncology nursing forum. Oncology Nursing Society; 1998.
- 34. Leckie G. Module 11: Three-Level Multilevel Models. Bristol: Centre for Multilevel Modelling. 2013.
- 35. Patel AV, Friedenreich CM, Moore SC, Hayes SC, Silver JK, Campbell KL, et al. American College of Sports Medicine roundtable report on physical activity, sedentary behavior, and cancer prevention and control. Med Sci Sports Exerc. 2019;51(11):2391. pmid:31626056
- 36. Campbell KL, Winters-Stone KM, Wisemann J, May AM, Schwartz AL, Courneya KS, et al. Exercise Guidelines for Cancer Survivors: Consensus Statement from International Multidisciplinary Roundtable. Med Sci Sports Exerc [Internet]. 2019;51(11). Available from: https://journals.lww.com/acsm-msse/Fulltext/2019/11000/Exercise_Guidelines_for_Cancer_Survivors_.23.aspx. pmid:31626055
- 37. NIH: National Heart L and BI. Study Quality Assessment Tools. 2021.
- 38. Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. bmj. 2019;366. pmid:31462531
- 39. Assink M, Wibbelink CJM. Fitting three-level meta-analytic models in R: A step-by-step tutorial. Quant Method Psychol. 2016;12(3):154–74.
- 40. Assink M, Wibbelink CJM. Fitting three-level meta-analytic models in R: A step-by-step tutorial. Quant Method Psychol. 2016;12(3):154–74.
- 41. Cheung MWL. A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes. Neuropsychol Rev. 2019;29(4):387–96. pmid:31446547
- 42.
Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale NJ: Erlbaum; 1988.
- 43. Sterne JAC, Sutton AJ, Ioannidis JPA, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ (Online). 2011;343(7818):1–8. pmid:21784880
- 44. Cochran WG. The Combination of Estimates from Different Experiments. Biometrics. 1954 Mar;10(1):101.
- 45. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Bmj. 2003;327(7414):557–60. pmid:12958120
- 46. Pasyar N, Barshan Tashnizi N, Mansouri P, Tahmasebi S. Effect of yoga exercise on the quality of life and upper extremity volume among women with breast cancer related lymphedema: A pilot study. European Journal of Oncology Nursing. 2019;42(August):103–9. pmid:31479846
- 47. Rogers LQ, Fogleman A, Trammell R, Hopkins‐Price P, Spenner A, Vicari S, et al. Inflammation and psychosocial factors mediate exercise effects on sleep quality in breast cancer survivors: pilot randomized controlled trial. Psychooncology. 2015;24(3):302–10. pmid:24916951
- 48. Buffart LM, Ros WJG, Chinapaw MJM, Brug J, Knol DL, Korstjens I, et al. Mediators of physical exercise for improvement in cancer survivors’ quality of life. Psychooncology. 2014;23(3):330–8. pmid:24123482
- 49. Cenik F, Keilani M, Galid A, Crevenna R. First exercise group for Turkish breast cancer patients in Vienna–a pilot project to include Turkish migrants. Disabil Rehabil. 2020 Jan 2;42(1):20–5. pmid:30688115
- 50. Ochi E, Tsuji K, Narisawa T, Shimizu Y, Kuchiba A, Suto A, et al. Cardiorespiratory fitness in breast cancer survivors: a randomised controlled trial of home-based smartphone supported high intensity interval training. BMJ Support Palliat Care. 2022;12(1):33–7. pmid:34389552
- 51. Aydin M, Kose E, Odabas I, Bingul BM, Demirci D, Aydin Z. The effect of exercise on life quality and depression levels of breast cancer patients. Asian Pac J Cancer Prev. 2021;22(3):725. pmid:33773535
- 52. Cadmus LA, Salovey P, Yu H, Chung G, Kasl S, Irwin ML. Exercise and quality of life during and after treatment for breast cancer: results of two randomized controlled trials. Psycho‐Oncology: Journal of the Psychological, Social and Behavioral Dimensions of Cancer. 2009;18(4):343–52.
- 53. Wang YJ, Boehmke M, Wu YWB, Dickerson SS, Fisher N. Effects of a 6-Week Walking Program on Taiwanese Women Newly Diagnosed With Early-Stage Breast Cancer. Cancer Nurs. 2011;34(2). pmid:20697267
- 54. Gordon LG, Battistutta D, Scuffham P, Tweeddale M, Newman B. The Impact of Rehabilitation Support Services on Health-related Quality of Life for Women with Breast Cancer. Breast Cancer Res Treat. 2005;93(3):217–26. pmid:16136270
- 55. Sagarra-Romero L, Butragueño J, Gomez-Bruton A, Lozano-Berges G, Vicente-Rodríguez G, Morales JS. Effects of an online home-based exercise intervention on breast cancer survivors during COVID-19 lockdown: a feasibility study. Supportive Care in Cancer. 2022;30(7):6287–97. pmid:35471614
- 56. Moon C, Gallegos AM, Sheikh B, Kumar P, Liss M, Patel DI. Pilot Study on the Impact of a Home-Based Exercise Program on Inflammatory Cytokines and Quality of Life in Men with Prostate Cancer Under Active Surveillance. Cancer Control. 2022;29:10732748221130964. pmid:36200522
- 57. Gautam AP, Maiya AG, Vidyasagar MS. Effect of home-based exercise program on lymphedema and quality of life in female postmastectomy patients: Pre-post intervention study. J Rehabil Res Dev. 2011;48(10):1261–8. pmid:22234669
- 58. Jeffs E, Wiseman T. Randomised controlled trial to determine the benefit of daily home-based exercise in addition to self-care in the management of breast cancer-related lymphoedema: A feasibility study. Supportive Care in Cancer. 2013;21(4):1013–23. pmid:23073712
- 59. Payne JK, Held J, Thorpe J, Shaw H. Effect of exercise on biomarkers, fatigue, sleep disturbances, and depressive symptoms in older women with breast cancer receiving hormonal therapy. Oncol Nurs Forum. 2008;35(4):635–42. pmid:18591167
- 60. Sajid S, Dale W, Mustian K, Kotwal A, Heckler C, Porto M, et al. Novel physical activity interventions for older patients with prostate cancer on hormone therapy: A pilot randomized study. J Geriatr Oncol. 2016/02/23. 2016 Mar;7(2):71–80. pmid:26916611
- 61. Tsuji K, Ochi E, Okubo R, Shimizu Y, Kuchiba A, Ueno T, et al. Effect of home-based high-intensity interval training and behavioural modification using information and communication technology on cardiorespiratory fitness and exercise habits among sedentary breast cancer survivors: habit-B study protocol for a random. BMJ Open. 2019;9(8):e030911.
- 62. Reis AD, Lima LS de, Barros ÊA da C, Bertoli J, Gobbo LA, Silva CB da, et al. Impact of home-based aerobic training combined with food orientation on food consumption, daily physical activity and cardiorespiratory fitness among breast cancer survivors: six-month clinical trial. Sao Paulo Medical Journal. 2021;139:259–68. pmid:33978132
- 63. Winters-Stone KM, Torgrimson-Ojerio B, Dieckmann NF, Stoyles S, Mitri Z, Luoh SW. A randomized-controlled trial comparing supervised aerobic training to resistance training followed by unsupervised exercise on physical functioning in older breast cancer survivors. J Geriatr Oncol. 2022;13(2):152–60. pmid:34426142
- 64. Alibhai SMH, Santa Mina D, Ritvo P, Tomlinson G, Sabiston C, Krahn M, et al. A phase II randomized controlled trial of three exercise delivery methods in men with prostate cancer on androgen deprivation therapy. BMC Cancer. 2019;19(1):1–11.
- 65. Baruth M, Wilcox S, Der Ananian C, Heiney S. Effects of Home-Based Walking on Quality of Life and Fatigue Outcomes in Early Stage Breast Cancer Survivors: A 12-Week Pilot Study. J Phys Act Health. 2015;12(Suppl 1):S110–8.
- 66. Corrado B, Ciardi G, Iammarrone CS, Arpino G. Home Exercise Program is an effective tool in improving upper limb function and quality of life in breast cancer survivors: A retrospective observational study. Journal of Human Sport and Exercise. 2018;13(4):926–39.
- 67. Culos-Reed SN, Robinson JL, Lau H, O’Connor K, Keats MR. Benefits of a physical activity intervention for men with prostate cancer. J Sport Exerc Psychol. 2007;29(1):118–27. pmid:17556779
- 68. Ergun M, Eyigor S, Karaca B, Kisim A, Uslu R. Effects of exercise on angiogenesis and apoptosis-related molecules, quality of life, fatigue and depression in breast cancer patients. Eur J Cancer Care (Engl). 2013;22(5):626–37. pmid:23731173
- 69. Golsteijn RHJ, Bolman C, Volders E, Peels DA, De Vries H, Lechner L. Short-term efficacy of a computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: A randomized controlled trial. International Journal of Behavioral Nutrition and Physical Activity. 2018;15(1):1–14.
- 70. Lahart IM, Metsios GS, Nevill AM, Kitas GD, Carmichael AR. Randomised controlled trial of a home-based physical activity intervention in breast cancer survivors. BMC Cancer. 2016;16(1):1–14. pmid:26988367
- 71. Melam GR, Buragadda S, Alhusaini AA, Arora N. Effect of complete decongestive therapy and home program on health- related quality of life in post mastectomy lymphedema patients. BMC Womens Health. 2016;16(1):1–9. pmid:27145867
- 72. Santa Mina D, Alibhai SMH, Matthew AG, Guglietti CL, Pirbaglou M, Trachtenberg J, et al. A randomized trial of aerobic versus resistance exercise in prostate cancer survivors. J Aging Phys Act. 2013;21(4):455–78. pmid:23238110
- 73. Nyrop KA, Callahan LF, Cleveland RJ, Arbeeva LL, Hackney BS, Muss HB. Randomized Controlled Trial of a Home‐Based Walking Program to Reduce Moderate to Severe Aromatase Inhibitor‐Associated Arthralgia in Breast Cancer Survivors. Oncologist. 2017;22(10):1238–49. pmid:28698390
- 74. Spahn G, Choi KE, Kennemann C, Lüdtke R, Franken U, Langhorst J, et al. Can a multimodal mind-body program enhance the treatment effects of physical activity in breast cancer survivors with chronic tumor-associated fatigue? a randomized controlled trial. Integr Cancer Ther. 2013;12(4):291–300. pmid:23766391
- 75. Spector D, Deal AM, Amos KD, Yang H, Battaglini CL. A pilot study of a home-based motivational exercise program for African American breast cancer survivors: Clinical and quality-of-life outcomes. Integr Cancer Ther. 2014;13(2):121–32. pmid:24105359
- 76. Stan DL, Croghan KA, Croghan IT, Jenkins SM, Sutherland SJ, Cheville AL, et al. Randomized pilot trial of yoga versus strengthening exercises in breast cancer survivors with cancer-related fatigue. Supportive Care in Cancer. 2016;24(9):4005–15. pmid:27129840
- 77. Villumsen BR, Jorgensen MG, Frystyk J, Hørdam B, Borre M. Home-based ‘exergaming’ was safe and significantly improved 6-min walking distance in patients with prostate cancer: a single-blinded randomised controlled trial. BJU Int. 2019;124(4):600–8. pmid:31012238
- 78. Yuen HK, Sword D. Home-based exercise to alleviate fatigue and improve functional capacity among breast cancer survivors. J Allied Health. 2007;36(4):257–75. pmid:19759996
- 79. Portela ALM, Santaella CLC, Gómez CC, Burch A. Feasibility of an exercise program for Puerto Rican women who are breast cancer survivors. Rehabilitation oncology. 2008;26(2):20. pmid:20664723
- 80. Bail JR, Frugé AD, Cases MG, De Los Santos JF, Locher JL, Smith KP, et al. A home-based mentored vegetable gardening intervention demonstrates feasibility and improvements in physical activity and performance among breast cancer survivors. Cancer. 2018;124(16):3427–35. pmid:29932460
- 81. Nguyen J, Popovic M, Chow E, Cella D, Beaumont JL, Chu D, et al. EORTC QLQ-BR23 and FACT-B for the assessment of quality of life in patients with breast cancer: a literature review. J Comp Eff Res. 2015;4(2):157–66. pmid:25825844
- 82. Chu D, Popovic M, Chow E, Cella D, Beaumont JL, Lam H, et al. Development, characteristics and validity of the EORTC QLQ-PR25 and the FACT-P for assessment of quality of life in prostate cancer patients. J Comp Eff Res. 2014;3(5):523–31. pmid:25350803
- 83. Toohey K, Hunter M, Paterson C, Mortazavi R, Singh B. Exercise Adherence in Men with Prostate Cancer Undergoing Androgen Deprivation Therapy: A Systematic Review and Meta-Analysis. Vol. 14, Cancers. 2022.
- 84. Gonzalo-Encabo P, Wilson RL, Kang DW, Normann AJ, Dieli-Conwright CM. Exercise oncology during and beyond the COVID-19 pandemic: Are virtually supervised exercise interventions a sustainable alternative? Crit Rev Oncol Hematol. 2022;174:103699. pmid:35526668
- 85. Catt S, Sheward J, Sheward E, Harder H. Cancer survivors’ experiences of a community-based cancer-specific exercise programme: results of an exploratory survey. Supportive Care in Cancer. 2018;26(9):3209–16. pmid:29623420
- 86. Fang YY, Lee YH, Chan JC, Chiou PY, Chou XY, Chiu WT, et al. Effects of exercise interventions on social and cognitive functioning of men with prostate cancer: a meta-analysis. Supportive Care in Cancer. 2020;28(5):2043–57. pmid:31907651
- 87. Trost SG, Owen N, Bauman AE, Sallis JF, Brown W. Correlates of adults’ participation in physical activity: review and update. Med Sci Sports Exerc. 2002;34(12):1996–2001. pmid:12471307
- 88. Sheill G, Guinan E, Neill LO, Hevey D, Hussey J. The views of patients with metastatic prostate cancer towards physical activity: a qualitative exploration. Supportive Care in Cancer. 2018;26(6):1747–54. pmid:29243168
- 89. Milton K, Poole K, Cross A, Gasson S, Gokal K, Lyons K, et al. ‘People don’t get cancer, families do’: Co‐development of a social physical activity intervention for people recently affected by a cancer diagnosis. Eur J Cancer Care (Engl). 2022. pmid:35285105
- 90. Hong F, Ye W, Kuo CH, Zhang Y, Qian Y, Korivi M. Exercise intervention improves clinical outcomes, but the “time of session” is crucial for better quality of life in breast cancer survivors: a systematic review and meta-analysis. Cancers (Basel). 2019;11(5):706. pmid:31121916
- 91. Falcetta FS, Träsel H de AV, de Almeida FK, Falcetta MRR, Falavigna M, Rosa DD. Effects of physical exercise after treatment of early breast cancer: systematic review and meta-analysis. Breast Cancer Res Treat. 2018;170(3):455–76. pmid:29654416
- 92. Sheeran P, Maki A, Montanaro E, Avishai-Yitshak A, Bryan A, Klein WMP, et al. The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: A meta-analysis. Health psychology. 2016;35(11):1178. pmid:27280365
- 93. Coughlin SS, Ayyala D, Majeed B, Cortes L, Kapuku G. Cardiovascular disease among breast cancer survivors. Cardiovasc Disord Med. 2020;2(1). pmid:32661518
- 94. Tsai HK D’Amico AVSadetsky N, Chen MH, Carroll PR. Androgen deprivation therapy for localized prostate cancer and the risk of cardiovascular mortality. J Natl Cancer Inst. 2007;99(20):1516–24. pmid:17925537
- 95. Sheeran P, Abraham C, Jones K, Villegas ME, Avishai A, Symes YR, et al. Promoting physical activity among cancer survivors: Meta-analysis and meta-CART analysis of randomized controlled trials. Vol. 38, Health Psychology. Sheeran, Paschal: Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, 323B Davie Hall, Chapel Hill, NC, US, 27599, psheeran@unc.edu: American Psychological Association; 2019. p. 467–82.
- 96. Hanson ED, Sheaff AK, Sood S, Ma L, Francis JD, Goldberg AP, et al. Strength training induces muscle hypertrophy and functional gains in black prostate cancer patients despite androgen deprivation therapy. Journals of Gerontology—Series A Biological Sciences and Medical Sciences. 2013;68(4):490–8. pmid:23089339
- 97. Meneses-Echávez JF, González-Jiménez E, Ramírez-Vélez R. Effects of supervised exercise on cancer-related fatigue in breast cancer survivors: a systematic review and meta-analysis. BMC Cancer. 2015;15(1):1–13. pmid:25885168