Introduction

Breast cancer is one of the most common malignancies among women worldwide [1]. As the prognosis of breast cancer continues to improve and breast cancer is becoming more of a chronic disease, the attention given to health-related quality of life (HRQoL) during and after diagnosis and treatment becomes more important [2, 3]. This focus is crucial as breast cancer patients experience many different physical and psychological symptoms either directly related to the disease or the treatment of the disease (surgery, systemic therapy, radiotherapy). These symptoms occur not only during treatment but also years after completion of treatment, significantly impairing the (long-term) HRQoL of these patients [4,5,6]. Given the association between HRQoL and healthcare utilization, enhancing HRQoL is not only crucial for the well-being of patients but can also lead to more efficient utilization of healthcare resources in the future [7].

Previously published literature demonstrated the positive effects of patient-reported symptom monitoring on HRQoL in various tumor types [8,9,10,11]. Patient-reported symptom monitoring is defined as the process of active and systematic reporting of symptoms initiated by the patient either at home or in the hospital [12]. Various other advantages of patient-reported symptom monitoring have been reported in the literature and encompass survival benefits, reduced anxiety, enhanced physical well-being, improved treatment adherence, fewer emergency room visits, and greater patient empowerment [11,12,13,14,15,16,17,18,19]. In addition, patients experience enhanced self-control and improved communication with healthcare professionals (HCPs). Moreover, HCPs can modify treatment regimens when necessary and respond more timely and effectively to prevent worsening and escalation of symptoms [9, 12, 15, 20,21,22].

Despite the proven benefits of symptom monitoring in enhancing health outcomes across various cancer types, its specific advantages for breast cancer patients remain underexplored in the current literature [8,9,10]. While breast cancer patients share common symptoms with other cancer types, they also experience unique challenges related to their disease. Breast cancer patients differ significantly from other cancer cohorts in aspects such as their age distribution and treatment regimens that for example can extend over years, like hormonal therapy. Moreover, the impact of breast cancer on HRQoL is distinct compared to other cancer types due to the significance of the breast in female identity and sexuality [8,9,10, 23,24,25,26]. Additionally, symptom monitoring and the importance of HRQoL domains will differ between breast cancer patients treated with curative or palliative treatment, but this distinction is also not established in the existing literature, which underscores the need for more research in this area [27, 28]. Therefore, this review aims to investigate the effect of patient-reported symptom monitoring on the HRQoL of breast cancer patients. By identifying critical research gaps and highlighting areas needing further exploration, this review aims to provide the scientific community with foundational insights that future studies could utilize to enhance both the efficiency of breast cancer healthcare and the HRQoL of breast cancer patients.

Methods

Literature Search

The methodology of this study was guided by the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) [29]. A comprehensive literature search was conducted with the help of a biomedical information specialist from inception to November 14, 2023, in multiple databases including Medline, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, CINAHL, and PsycINFO. Search terms related to symptom monitoring and HRQoL were used. The full search strings can be found in Appendix A. The snowball method was used to identify articles that were not found in the literature search. This involved examining the reference list of included studies as well as conducting citation searches of included articles.

Eligibility Criteria

The retrieved papers were screened by two independent reviewers (NJMCVP and CJGVDH) on title and abstract. Inclusion criteria were articles that had the intervention of patient-reported symptom monitoring (online or in hard copy), focused on HRQoL as an outcome, using patient-reported validated questionnaires, and articles that described results specified for breast cancer patients aged 18 years and older. Studies focusing on extensive interventions on symptoms (e.g., coaching following severe tiredness, extensive symptom self-management programs, nurse-led telephone decision models for the management of moderate to severe toxicities) were excluded because they could confound the direct effects of patient-reported symptom monitoring alone on HRQoL. Similarly, studies with mixed cancer samples were excluded unless they reported HRQoL outcomes separately for each cancer type, to ensure the specificity of the findings to breast cancer patients. Other exclusion criteria were systematic reviews and meta-analyses, non-English language studies, animal studies, case reports, and cross-sectional studies. Discrepancies in selected articles between the two reviewers were resolved through discussion and consensus was found in all cases.

Data Extraction

Two independent researchers (NJMCVP and CJGVDH) extracted methodological and baseline characteristics of the included studies such as year of publication, country, study design, sample size, patients’ description, primary study aim, frequency of symptom monitoring, follow-up period, type of symptom monitoring (intervention), control group and HRQoL assessment. Additionally, data on HRQoL were extracted from the studies included.

Quality Assessment

The risk of bias (RoB) in the included studies was assessed independently by both authors (NJMCVP and CJGVDH) using the Cochrane tool for randomized controlled trials (RCTs) and the Newcastle–Ottawa Scale (NOS) for nonrandomized studies [30, 31]. In the Cochrane tool bias in RCTs is assessed as a judgment (high, low, or unclear) for individual elements from five domains (selection, performance, attrition, reporting, and other) [30]. Cohort studies are rated with the NOS on three items: the selection of the study groups, the comparability of the study groups, and the ascertainment of either the outcome or exposure of interest. Scores can range from zero to nine. The NOS can be converted to Agency for Healthcare Research and Quality (AHRQ) standards, namely; good, fair, and poor [31].

Results

Literature Search

A total of 5573 articles were identified through the literature search of which 2603 were duplicates (Fig. 1). From the remaining 2970 articles, 2941 articles were excluded based on their title and/ or abstract, leaving 29 articles for full-text evaluation. Of the 29 articles, 25 were excluded due to several reasons including the absence of HRQoL outcomes and/ or symptom monitoring, or studies with mixed samples without results specified for breast cancer patients. Finally, four articles were included in this review [32,33,34,35]. No additional articles were identified with the snowball method.

Fig. 1
figure 1

Flowchart study selection

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Study Characteristics

An overview of the key characteristics of the studies included can be found in Table 1. Studies were conducted in Turkey, Japan, Sweden, and Slovenia. Two studies were RCTs, and two were prospective cohort studies. Sample sizes ranged from 14 to 149 patients. All studies examined daily patient-reported symptom monitoring through electronic devices and focused solely on breast cancer patients with no distant metastasis (M0) who received systemic therapy. The primary study aim of the four studies was to evaluate the effect of using a mobile app for symptom monitoring on global HRQoL or domains of HRQoL. Three studies examined patients receiving chemotherapy and one study examined patients receiving anti-hormonal therapy [32,33,34,35]. Three studies compared patients receiving standard care (control group) to patients who reported their symptoms online over time [32, 34, 35]. One study did not make a comparison and only examined the effect of online symptom monitoring on HRQoL over time [33].

Table 1 Study characteristics
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Quality Assessment

The methodological quality of the included studies using the Cochrane tool and the NOS are displayed in Fig. 2 and Table 2, respectively [30, 31]. The included RCTs had a high risk of bias, and the included cohort studies had poor quality based on AHRQ standards (Fig. 2, Table 2).

Fig. 2
figure 2

Quality assessment of RCTs based on Cochrane tool. In the color-coded ranking, green color represents low risk of bias, yellow unclear, and red high risk of bias

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Table 2 Quality Assessment of non-randomized studies based on the NOS and AHRQ
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HRQoL Assessment

The frequency and methods of the HRQoL assessment differed between the included studies (Table 1). Three of the studies measured HRQoL at two time points; before treatment and during or after the treatment [32,33,34]. Grasic et al. measured HRQoL domains at 4 time points; before systemic treatment, after the first week, after the first cycle, and at the end of systemic treatment [35]. Three of the included studies used the European Organization for Research and Treatment of Cancer (EORTC QLQ-C30) and/ or EORTC QLQ-BR23 to assess HRQoL and one study used the Functional Assessment of Cancer Therapy – Breast (FACT-B) [32,33,34,35].

HRQoL Results and Conclusions of the Studies

The key findings regarding global HRQoL or domains of HRQoL are provided for each included study (Table 1).

The results of the RCT conducted by Öztürk et al. showed that after using Msemptom, a mobile application for symptom monitoring, median scores of the EORTC QLQ-C30 symptom (p = 0.004) and nausea-vomiting domains (p = 0.012) of patients in the control group were significantly higher than median scores of patients in the intervention group. However, EORTC QLQ-BR23 sexual function (p = 0.024) and sexual pleasure scores (p = 0.026) were significantly higher for patients in the control group compared to patients in the intervention group. Öztürk et al. conclude that symptom monitoring is only effective in controlling physical symptoms and suggest that additional research (including studies with longer follow-up durations) is needed to examine the effect of symptom monitoring on symptom control and HRQoL of breast cancer patients more clearly. Öztürk et al. recommend expanding the use of symptom monitoring in breast cancer patients [32].

Takada et al. used the Personal Health Record (PHR) app. The app was an electronic tool that allowed patients to record their diagnoses, symptoms, and medications during therapy, facilitating the sharing and communication of medical information with HCPs. They demonstrated that physical well-being scores measured with the FACT-B were significantly higher after using the PHR app (one month after initiation of hormonal therapy) compared to before using the PHR app (before initiation of hormonal therapy) (p = 0.035). However, there were no significant differences in the social well-being, emotional well-being, functional well-being, and breast cancer domain before and after the use of the PHR app. Takada et al. conclude that the use of PHR did not negatively affect HRQoL measured with the FACT-B in breast cancer patients and could be used as a communication tool between breast cancer patients and HCPs [33, 36].

Similarly, Fjell et al. utilized the Interaktor app, specifically developed for research in neo-adjuvant chemotherapy (NACT) patients. This app allows for self-reporting of 14 common chemotherapy symptoms, immediate data transfer to HCPs for real-time monitoring, access to evidence-based self-care advice and relevant websites related to assessed symptoms, and features a built-in risk assessment model that triggers alerts for severe symptoms. Fjell et al. concluded that the Interaktor app reduced symptom burden and improved HRQoL measured with the EORTC QLQ-C30 in patients with NACT. Patients receiving symptom monitoring had significantly higher emotional functioning scores (p = 0.008) and significantly lower nausea and vomiting (p = 0.007), appetite loss (p = 0.027), and constipation scores (p = 0.007) compared to patients in the control group. The corresponding effect sizes ranged from 0.30 to 0.43. Fjell et al. conclude that further research on both user experience and healthcare costs is necessary before clinical implementation [34, 37].

Grasic et al. used the PRO Mamma mobile app, designed for breast cancer patients to record, and report 50 specific symptoms relevant to the expected adverse effects for patients during neoadjuvant or adjuvant treatments. The app categorizes symptom severity into mild, moderate, or severe and offers corresponding self-management advice. The study found that using the PRO Mamma mobile app, improved overall HRQoL. After the first week of treatment, the adjusted mean differences between the intervention and control group were significant for the global quality of life score (10.1, 95% CI 1.8 to 18.5, p = 0.02) and the summary score (8.9, 95% CI 3.1 to 14.7, p = 0.003) of the EORTC QLQ-C30. At the end of treatment, only the mean difference for the summary score was significant (10.6, 95% CI 3.9 to 17.3, p = 0.002). An exploratory analysis on other EORTC QLQ-C30 and EORTC QLQ-BR23 domains was performed and demonstrated various improvements; social, physical, role, and cognitive function were increased, and pain, appetite loss, and systemic therapy side effects were reduced. The difference between the groups in social functioning after the first week could be generalized to the population after adjusting for multiple testing (adjusted p = 0.04). The authors concluded that using this app enabled patients to better manage their symptoms, leading to improved HRQoL [35].

In summary, these findings showed that while the specific methods of monitoring varied among the included studies, all consistently used online platforms, either web or app-based, for symptom monitoring. Additionally, the results showed that online patient-reported symptom monitoring may have a positive effect on certain aspects of HRQoL, such as physical well-being, emotional well-being, social functioning, and symptom control, while potentially impacting sexual function and pleasure differently. Although the studies collectively demonstrated potential benefits, they also highlighted areas requiring further research, including the extension to measure all HRQoL domains, the long-term effects, and the cost-effectiveness.

Discussion

This systematic review aimed to examine the effect of symptom monitoring by breast cancer patients on their HRQoL. The results suggest that online patient-reported symptom monitoring may improve (domains of) HRQoL of M0 breast cancer patients undergoing systemic therapy. Additionally, some positive effects on symptom control were found.

The findings of the current study are in line with previous reviews conducted in metastatic (M1) and M0 cancer patients, including various cancer types such as breast cancer. However, those results were analyzed as a combined group and not separately for breast cancer patients and/ or M0 and M1 cancer patients. Additionally, relatively few of the included studies in those reviews focused on HRQoL as a health outcome, highlighting the need for more focused research in this area [8,9,10]. A recent RCT demonstrated that weekly symptom monitoring leads to statistically significant and clinically meaningful improvements in HRQoL of lung cancer patients. Interestingly, both patient-centered and healthcare provider-centered approaches to monitoring were equally effective on HRQoL. Given the increasing pressure on healthcare systems, the authors conclude that a patient-centered approach to symptom monitoring is more sustainable [19].

Unfortunately, no studies were identified in the literature search of the current study that investigated the effect of symptom monitoring on HRQoL of M1 breast cancer patients. Considering the crucial role of palliative care in the management of M1 cancer patients, which is defined as improving HRQoL by preventing and relieving suffering through early detection, correct assessment and treatment of pain and other symptoms (physical, psychosocial, and spiritual), symptom monitoring is by definition important in this group [38]. Moreover, most M1 breast cancer patients tend to have somewhat longer survival compared to other M1 cancer types, making symptom monitoring and HRQoL even more important in this particular subgroup [39, 40]. Barbera et al. conducted a comprehensive study on symptom monitoring which also included M1 patients with various cancer types. Their large, matched cohort study with real-world data, demonstrated an improved availability of palliative care services [41]. This promising finding highlights the potential benefits of symptom monitoring in M1 patients, again underlining the need for more research in this area to optimize patient-centered healthcare and -support in the future.

Strengths and Limitations

One of the key strengths of this review is the comprehensive literature search and snowball method that was conducted to minimize the risk of evidence selection bias. Additionally, all included studies used validated and standardized HRQoL outcomes, which contributes to reliable and accurate data.

One major limitation of this review was the low number of studies included (n = 4), all of which focused on patients receiving systemic treatment, showing that little attention has been paid to studying the potential positive effects on HRQoL during other phases in the disease trajectory, including radiotherapy and/ or different types of surgery [32,33,34,35]. Moreover, in the four articles, HRQoL was measured using three different questionnaires (EORTC QLQ-BR23, EORTC QLQ-C30, and FACT-B) [32,33,34,35]. For daily practice the several methodologies are adequate, however, for research purposes, they can introduce loss of information [42]. While some questionnaires can be mapped to one other, this has not been done for the FACT-B, which limits comparison across studies and hinders the pooling of results in the current study [43,44,45]. Additionally, it was not possible to calculate the outcome impact, such as effect sizes, for two of the four studies, which further complicated the comparison of outcomes. Another limitation was the fact that the included studies had relatively small sample sizes (ranging from 14 to 149 patients) and the limited number of measurements of HRQoL (2–4 time points) may not fully capture the changes of HRQoL during systemic treatment. Lastly, the RoB observed in the included studies was high, which affects the validity of the study findings and highlights the need for more research.

Future Perspective

The results of this review demonstrated that there is limited literature on the effect of symptom monitoring on HRQoL of M0 breast cancer patients, and no literature specified for M1 breast cancer patients. Additionally, all studies included in this review only monitored symptoms during (systemic) treatment, while symptoms are experienced from diagnosis and onwards, so in the future symptom monitoring should be examined during the whole patient journey, including the diagnostic phase, all treatment interventions, and including time windows without active treatment. Monitoring should also continue during follow-up as it is well known that the majority of patients experience long-term and late symptoms after completion of breast cancer treatment, which affects their daily functioning and therefore their HRQoL [6, 46].

Clinical Implications

Despite the proven benefits of symptom monitoring in other cancer types and the availability of implementation frameworks, symptom monitoring is currently not widely implemented in routine clinical practice for breast cancer patients [12,13,14,15,16,17, 47,48,49]. This is partly due to the significant commitment from both patients and HCPs. For effective implementation, it is essential to involve HCPs actively and boost patients’ digital and health literacy [50]. Furthermore, successful usage and adherence of symptom monitoring tools depend on the benefits experienced by patients, which in return incentivizes HCPs to recommend symptom monitoring to a wider patient population. Symptom monitoring is intended to lead to more personalized consultations and care, directly addressing patient-reported problems. Implementing symptom monitoring can potentially reduce pressure on healthcare systems and workload for HCPs first because there are fewer ad hoc interventions required for patients contacting the HCP because of severe or worsening symptoms. Secondly, in the future, the number of consultations might be reduced for patients in whom symptoms are absent and HRQoL is satisfactory [50,51,52]. Validated questionnaires and current implementation frameworks should be used to accelerate knowledge development about symptom monitoring for breast cancer patients and their HCPs, ultimately enhancing symptom self-management and the efficiency of breast cancer healthcare in the future.

Conclusion

Online patient-reported symptom monitoring has the potential to positively impact the HRQoL of M0 breast cancer patients undergoing systemic therapy, yet the available evidence remains limited. Additional research on symptom monitoring and HRQoL during all phases in the disease trajectory, including its impact on personalized treatment, is needed before integration into routine care for M0 breast cancer patients can be considered. Notably, there is a lack of literature specifically addressing patient-reported symptom monitoring and HRQoL in M1 breast cancer patients. This M1 subgroup experiences specific treatment- and cancer-related symptoms, underscoring the significance of symptom monitoring and HRQoL, especially in the final phase of their life. In future research in this patient group, using common validated measures is essential.