Abstract
Background: Breast cancer patients report high levels of psychosocial maladjustment after hospital discharge. Peer support may play an important role in improving anxiety and quality of life in breast cancer patients. This study aimed to assess the effect of peer support on quality of life and anxiety in breast cancer patients. Method: A systematic review and meta-analysis of randomized controlled studies were conducted, using data sourced from PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, SinoMed, China Science and Technology Periodical Database, China National Knowledge Infrastructure, and Wanfang Data for randomized controlled trials (RCTs) from inception to October 15, 2021. The RCTs reporting the effect of peer support intervention on quality of life and anxiety in breast cancer patients were included. The quality of evidence was assessed using the Cochrane risk of bias tool, that is, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated for the pooled effect size. Results: A total of 14 studies were included in the systematic review and 11 in the meta-analysis. The pooled results revealed that peer support significantly improved quality of life (SMD = 0.69, 95% CI = 0.28–1.11) and anxiety (SMD = −0.45, 95% CI = −0.88 to −0.02) in breast cancer patients. The quality of evidence was low as all studies showed the risk of bias and inconsistency. Conclusion: Peer support intervention has the potential to effectively improve psychosocial adaptations in breast cancer patients. Future studies with a robust design and larger sample size are needed to investigate the potential factors associated with the beneficial effects of peer support.
Introduction
Breast cancer has become the leading cause of cancer-related deaths in women globally [1]. Data from the National Central Cancer Registry (NCCR) show that there are 4.292 million new cancer cases in China every year, of which breast cancer accounts for 15% of the total [2]. With the improvement of breast cancer screening awareness and the advancement of medical technology, the survival rate of breast cancer patients has improved and the survival period has been prolonged [1]. However, survivors are not only at risk of disease recurrence but also suffer from multiple problems such as postoperative body image disorder, marital relationship damage, and degeneration of social roles [3]. More than 60% of breast cancer patients experience symptoms of psychosocial maladaptation such as anxiety, depression, and social barriers during treatment. Ultimately, it will affect the overall rehabilitation of patients [4, 5], so it is urgent to improve the level of psychosocial adaptation of patients.
As one of the important ways of psychosocial adaptation intervention, peer support has been widely used in many fields [6‒8]. Peer support refers to a form of education in which individuals with the same diseases or conditions meet to exchange information, share experiences, and encourage or help each other overcome difficulties [9] and is controlled by professionals who do not share the common situation which is different from self-help groups [10]. Peer support as one of the coping measures for breast cancer patients can buffer stress and promote the individual’s psychosocial adaptation by reconstructing threat assessment and improving the coping response [11]. Peer supporters share their experiences in managing disease and returning to family and society. Patients gain a sense of identity and belonging through peers sharing experiences and information, which has a positive impact on the psychological adaptation of cancer diagnosis and treatment. Peer support can also help patients reassess themselves and improve their coping styles [12]. Both the Patient Survivor Advocate Program developed by the University of Wisconsin Breast Center [13] and National Basic Plan for promoting measures to cope with cancer published by Japan’s health ministry [14] agreed that peer support should be provided to breast cancer patients.
Recently, peer support has been used as an effective way to improve the psychosocial adaptation of patients, and related research about breast cancer patients has gradually increased [15, 16]. There are different tools to measure the effect of peer support on improving psychosocial adaptation. Some studies have used indicators such as quality of life, emotional distress, anxiety, and body image to measure patients’ psychosocial adaptation [17‒19]. However, some recent studies have found that peer support is not effective in improving the psychosocial adaptation of breast cancer patients [20, 21]. Thus far, to our best knowledge, there is no systematic review conducted to examine the effect of peer support intervention on psychosocial adaptation in breast cancer patients. To address this knowledge gap, a systematic review is needed to test the effectiveness of peer support on psychosocial adaptation among women with breast cancer.
By reviewing existing research, we found limited publications on the effectiveness of peer support for psychosocial adjustment in breast cancer patients. Therefore, this review chooses to use two indicators of quality of life and anxiety to reflect the level of psychosocial adaptation of patients. This review aimed to determine the effect of different types of peer support on improving psychosocial adaptation in breast cancer patients and to provide guidance and reference for health workers who wish to design and implement such programmes for these patients in the future.
Methods and Materials
Aim and Design
A systematic review and meta-analysis of randomized controlled trials (RCTs) were performed to assess the effect of peer support intervention on quality of life and anxiety in breast cancer patients. The review and meta-analysis were performed according to the Cochrane Handbook for Systematic Reviews of Interventions [22]. This study has been registered in the PROSPERO database (CRD42021285812).
Search Methods
A systematic literature search was performed across four English (PubMed, Embase, Cochrane Central Register of Controlled Trials, and Web of Science) and four Chinese databases (Chinese Biomedical Literature Database (SinoMed), China Science and Technology Periodical Database, China National Knowledge Infrastructure, and Wanfang Data) from inception to October 15, 2021. The search terms included the synonyms of “breast cancer,” “peer support,” and “randomised controlled trial.” Additional eligible articles identified from reference lists of relevant reviews and studies were also included.
The inclusion criteria were as follows: (1) types of patients: adult participants diagnosed with breast cancer (including metastatic breast cancer and recurrent breast cancer); (2) types of interventions: peer support – peer support providers were people with breast cancer but not health professionals; (3) types of controls: usual care – both the intervention group and control group received similar baseline care; (4) types of outcome measures: quality of life or anxiety assessed by validated measures; the outcome was compared at baseline and a predefined follow-up time point; and (5) types of studies: RCTs. The exclusion criteria were as follows: (1) participants below 18 years of age; (2) studies without baseline values; and (3) use of additional interventions provided by health professionals that could influence outcomes.
Quality Appraisal
Two reviewers assessed the risk of bias in the selected studies according to the Cochrane Handbook for Systematic Review of Interventions. Any discrepancies were resolved by discussion and consulting a third reviewer. The criteria were as follows: sequence generation, allocation concealment, blinding procedures, selective outcome reporting, incomplete outcome data, and other potential biases. Each domain was rated as having a low, high, or unclear risk of bias. Discrepancies were resolved through a discussion between the two reviewers.
The overall quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria of risk of bias, inconsistency, indirectness, imprecision, and publication bias. The quality assessment was classified into high, moderate, low, or very low.
Data Abstraction
The data for this study were extracted by two reviewers. Extracted information included the first author’s name, year of publication, country, sample size, participants’ characteristics, peer support providers’ characteristics, intervention duration, outcome measures, and follow-up period. To ensure accuracy, the information extracted by the two researchers was compared, and any disagreement was resolved by the third reviewer.
Data Analysis
Review Manager 5.3 and Stata 14.0 software was used to perform a meta-analysis for the valid data included in the study. As all outcomes were continuous, standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated as pooled effect estimates. Cochrane’s Q test and I2 were used to quantitatively analyse heterogeneity across the included studies in each analysis. The fixed-effects model is used if p ≥ 0.1 or I2 ≤ 50%, whereas when p < 0.1 or I2 ≥ 50%, substantial heterogeneity between the studies is indicated and possible reasons are investigated. Sensitivity analysis and subgroup analysis can be used to identify the source of the heterogeneity. If there is no obvious methodological or clinical heterogeneity, the random-effects model is used for meta-analysis. The publication bias is judged by whether the funnel chart is symmetrical or not and Egger’s test. If a publication bias exists, the trim-and-fill method is used to estimate the number of corresponding missing studies [23].
Results
Search Outcome
A total of 1,503 titles were identified through the database searches and other sources, from which 262 duplicates were removed. A further 1,162 articles were excluded by screening the titles and abstracts. Next, 79 relevant full-text articles were assessed for eligibility and 65 articles were excluded according to the selection criteria. Thus, 14 studies were included in this systematic review. Of these, 3 studies were excluded from the meta-analysis as they contained comments on changes in quality of life and/or anxiety but did not provide the data used to calculate these changes. Therefore, 11 studies were included in the meta-analysis. The selection process is presented in Figure 1.
Descriptions of the Selected Studies
The 14 studies included in the systematic review were published between 2010 and 2021. These studies were conducted in four countries: China (k = 6) [24‒29], the USA (k = 5) [20, 30‒32], South Korea (k = 1) [33], and Iran (k = 2) [34, 35]. All studies were RCTs. The characteristics of these studies are described in Table 1.
Patient Characteristics
Overall, the 14 studies included 1,455 breast cancer patients, with sample sizes ranging from 26 to 103. The mean age of the patients ranged from 38.8 to 62.8 years, with an average age of 51.1 years. Six studies did not provide the average of the participants [21, 25, 26, 28, 33, 35].
Intervention Characteristics
The peer support interventions in the studies varied widely in terms of intervention mode, duration, follow-up period, and peer support providers. Six studies provided single-mode and the others provided mixed-mode peer support interventions [20, 21, 24, 26‒28, 34]. Eight studies used online-based support (e-mail, telephone, message, WeChat) [20, 21, 24, 29‒33].
The intervention duration ranged from 1 to 6 months. The follow-up duration ranged from 6 weeks to 12 months. Three studies did not report the duration of intervention [21, 27, 28], and two studies did not report the follow-up period [25, 27].
The number of peer support providers ranged from 3 to 30; four studies did not report the number of support providers [21, 27, 29, 31]. The training period for peer support providers ranged from 4 h to 7 days. The ratio of support providers to breast cancer patients ranged from 1:1 to 1:18.
Comparative Interventions
Eleven studies provided usual nursing (usual care, usual education, and usual consultation) to a control group for comparison. One study did not provide any intervention [35], and three studies did not report the intervention provided to the control group.
Outcome Characteristics
In this review, six studies assessed the quality of life by using the Functional Assessment of Cancer Therapy-Breast (FACT-B), two studies used the Quality of Life Questionnaire-Core (QLQ-C30), one study used the Quality of Life Questionnaire for Breast Cancer (QLQ-BR23) and the Short Form 36 Health Survey (SF-36). Two studies assessed the level of anxiety using the Hospital Anxiety and Depression Scale (HADS), three studies used the Self-Rating Anxiety Scale (SAS), and two studies used the Brief Symptom Inventory (BSI). Detailed information is presented in Table 1.
Summary of Risk of Bias
The risk of bias is presented in Figure 2 (and online suppl. Fig. S1; see www.karger.com/doi/10.1159/000527849 for all online suppl. material). Most studies showed a low risk of selection bias. All studies had an unclear risk of performance bias, and the majority had an unclear risk of detection bias. Most of the studies showed a low risk of attrition and reporting bias. Five studies had a high risk of other bias because participants withdrew before the study was completed.
Pooled Analysis
Quality of Life
Seven studies with 775 participants (peer support group = 387, control group = 388) provided data for changes in quality of life. Further, the heterogeneity analysis revealed significant heterogeneity between the studies (Q = 47.90, p < 0.01, I2 = 87%); therefore, the random-effects model was used. From Figure 3, the result of the pooled analysis showed that the intervention group scored significantly higher than the control group on measures of quality of life (SMD = 0.69, 95% CI = 0.28–1.11, p = 0.001), and the differences were statistically significant. Three studies with no available data were not included in the meta-analysis [21, 29, 34].
Due to substantial heterogeneity in the pooled result, a subgroup analysis was performed to elucidate the relevant factors associated with the potentially beneficial effects of peer support intervention (online suppl. Table S1). The results showed that the subgroup-estimated effect sizes were not significantly correlated. Due to the lack of information in the primary studies, some factors were not included in the subgroup analysis.
In the sensitivity analysis, the pooled results showed no significant changes after excluding any single study. Based on the shape of the funnel plot shown in online supplementary Figure S2 and the results of the Egger’s test (p = 0.04), a slight publication bias was found in the meta-analysis. Therefore, the trim-and-fill method was used to evaluate the impact of potential studies with missing values on the results of the meta-analysis. After twice iteration, the results showed that there were no missing studies or significant changes in the effect size, suggesting that the pooled result was stable and the potential publication bias did not exist.
Anxiety
Seven studies with 845 participants (peer support group = 457, control group = 388) reported anxiety scores. Based on the heterogeneity test, the random-effects model was used for the pooled analysis (Q = 53.86, p < 0.01, I2 = 89%). Shown in Figure 4, compared with the control group, the peer support intervention group showed significantly reduced anxiety (SMD = −0.45, 95% CI = −0.88 to −0.02, p = 0.04).
Subgroup analyses were performed on the mode of intervention (single or mixed; online or offline) to clarify the potentially beneficial effects of peer support intervention on anxiety (online suppl. Table S2). All subgroup-estimated effect sizes showed no significant correlation (p > 0.05). Some factors were not included in the subgroup analysis due to a lack of information in the original studies.
Based on the shape of the inverted-funnel plots shown in online supplementary Figure S3 and Egger’s test (p = 0.23), there was no significant publication bias in the seven studies included in the meta-analysis. The sensitivity analysis showed that the pooled results did not significantly change after excluding any single study, indicating that the results were stable.
Quality of Evidence
The quality-of-evidence profiles for the outcomes are provided in online supplementary Table S3. All the studies that provided peer support intervention for breast cancer showed a risk of bias and inconsistency. Quality of evidence was low for the analyses of both quality of life and anxiety.
Discussion
This study systematically reviewed the effectiveness of peer support interventions for improving quality of life and reducing anxiety in breast cancer patients. Fourteen RCTs were included in the systematic review, and 11 of them were selected for the meta-analysis. The comprehensive results showed that peer support can effectively enhance quality of life (SMD = 0.69, 95% CI: 0.28–1.11, p < 0.01) and reduce anxiety (SMD = −0.45, 95% CI: −0.88 to −0.22, p = 0.04) in breast cancer patients.
It is noteworthy that all of the selected studies had limitations in the blinding process due to the interactions between patients and peer support providers during the intervention. Furthermore, substantial heterogeneity across the studies was revealed in the pooled analysis. Therefore, a random-effects model was used to obtain conservative results, and a subgroup analysis was performed to explore the factors that caused the heterogeneity. There was a slight publication bias in the meta-analysis of the studies examining the effect of peer support on quality of life. The trim-and-fill method proved that the pooled result was stable, and the potential publication bias had no significant impact. There was no publication bias in the meta-analysis of the studies examining the effect of peer support on anxiety. Sensitivity analyses verified the reliability of the results for both quality of life and anxiety.
Similar to previous studies [36], the two meta-analyses in this study showed significant heterogeneity, indicating a variety of factors that affect the relationship between peer support intervention and quality of life and anxiety in breast cancer patients. Therefore, a subgroup analysis was conducted to clarify the potential factors leading to this heterogeneity. The subgroup analysis included factors such as the region of publication, sample size, type of peer support intervention, and follow-up duration. However, none of these factors had a significant impact on heterogeneity. Other factors (e.g., training courses for peer support providers, length of training, ratio of peer support providers to patients, duration and frequency of peer support interventions) may have led to the inconsistent effects of peer support interventions [37]. For example, peer supporters received training on breast cancer diagnosis, treatment, and symptom management for part of the original studies included [33, 35, 38], but health information privacy and mental health confidentiality training were only involved in Crane-Okada et al.’s research [38]. Another study suggested that peer support intervention should be conducted at a certain period of time after diagnosis (such as 4–6 weeks) because women who have just been diagnosed with breast cancer may feel very distressed and be reluctant to contact non-professionals [33]. However, the above-mentioned factors were either unavailable in the primary studies or too diverse to make comparisons. Considering that this review included a relatively small number of studies, in the future, more studies are required to identify the factors that affect heterogeneity.
This review suggests that peer support intervention can effectively improve the quality of life of breast cancer patients, which is consistent with the study by Kong et al. [39]. As a form of social support, peer support can increase patients’ adaptive behaviours and encourage them to adopt positive coping strategies that can reduce physical and psychological symptoms and improve their quality of life [40]. For instance, in the studies included here, breast cancer patients sought help from well-trained peer educators on the challenges they faced throughout the treatment. Furthermore, the peer educators shared effective self-management strategies with the patients and corrected any inappropriate nursing methods and treatment concepts; this exchange helped reduce the patients’ physical symptoms and psychological burden, thereby improving their quality of life [26]. Due to the risk of bias and heterogeneity, the quality of evidence assessed by the GRADE profiler Guideline Development Tool was very low. Therefore, the estimated effect cannot be confidently stated.
Furthermore, this review found that peer support interventions can reduce anxiety in breast cancer patients. This can be explained by the characteristics of peer support, which consist of three parts: information, assessment, and emotional support [9], where emotional support can help patients restore self-esteem and confidence in treatment and recovery, thereby reducing their anxiety [41]. However, in the study by Crane-Okada et al. [20], peer support intervention failed to significantly improve anxiety in breast cancer patients. This inconsistency may be ascribed to the fact that the telemedicine model (employed by Crane-Okada et al. [20]) is not as effective as face-to-face intervention for older people who tend to opt not to use mobile devices or lack the skills to use communication technologies to virtually connect with people [42, 43]. The quality of the evidence included in this study is very low, implying little confidence in the estimated effect. Therefore, further research is necessary to establish effective modes of peer support intervention.
Strengths and Limitations
The key strength of this work is that this is the first systematic review and meta-analysis to evaluate the impact of peer support interventions on the quality of life and anxiety in breast cancer patients. It is important to note that rigorous methods were used to determine eligible studies and to conduct the systematic review and meta-analysis. In addition, the risk of bias and the quality of the evidence were assessed, and the trim-and-fill method was used to further evaluate the impact of publication bias on the results of the meta-analysis.
However, the review was also subject to several limitations. Firstly, the number of articles included in this study was relatively small. Due to the lack of blinding methods for participants, experimenters, and outcome evaluators, most of the studies showed implementation and detection biases. Secondly, the heterogeneity observed in the two meta-analyses indicated the existence of potential mediating factors, such as the form of peer support intervention, duration, frequency, and follow-up period. Although subgroup and sensitivity analyses were performed, the source of heterogeneity was not fully explained. Thirdly, about 35% of the risk assessment had a high degree of risk of bias due to the uneven baseline data or small sample size in some studies. As revealed by the GRADE profiler Guideline Development Tool, these restrictions may have led to a decrease in the overall quality of evidence.
Implications for Clinical Practice and Future Research
The current results provide significant implications for clinical application. Firstly, it is essential to popularize peer support interventions because these interventions have been proven to improve quality of life and anxiety in breast cancer patients [31, 32]. Peer support interventions are a potentially effective strategy in the medical resource plan to relieve global tension [14]. In particular, this method has high economic benefits for low- and middle-income regions as a long-term support strategy [44].
This study also offers important directions for future research. Firstly, only two studies included in the review showed a low risk of bias. Most of the studies contained flaws in the research method, such as an unclear random allocation process, lack of information on blinding, results evaluation, and incomplete data. Therefore, carefully designed RCTs are required to accurately evaluate the impact of peer support interventions on breast cancer survivors. Moreover, peer support interventions are complex and integrated interventions with different components. Thus, an important goal for future research is to determine the best method to provide peer support intervention for breast cancer patients. In addition, it is difficult to maintain the fidelity of the intervention for a large sample of participants; future studies should necessarily attend to this aspect.
Conclusions
Peer support as a complement to traditional health care services is widely used, and the effects are controversial. This systematic review shows that breast cancer patients may benefit from peer support intervention to improve psychosocial adaptations such as quality of life and anxiety, which indicates that peer support may potentially introduce another cost-effective type of human resource to address the shortage of mental health care providers for breast cancer patients. Future studies with better design and larger sample size are needed to explore potential mediating factors associated with the effectiveness of peer support intervention on breast cancer patients and issues on what training peer supporters receive prior to the peer support intervention; how to guide older people with breast cancer to access or provide peer support by telemedicine; and when is the most appropriate time to provide peer support.
Statement of Ethics
An ethics statement is not applicable because this study is based exclusively on the published literature.
Conflict of Interest Statement
The authors have no conflicts of interest to declare.
Funding Sources
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author Contributions
Yingyao Tan and Meijiao Qin: data curation, investigation, methodology, writing – original draft, and writing – review and editing. Bing Liao, Lixia Wang, and Guangting Chang: visualization. Fengxiang Wei: supervision and writing – original draft. Shu Cai: supervision, writing – original draft, and writing – review and editing.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.