Adjuvant hormone therapy can affect the quality of life of postmenopausal breast cancer patients with the estrogen receptor (ER+). This study aimed to measure the outcomes of health-related quality of life (HRQoL) in postmenopausal women with ER+ breast cancer receiving non-steroidal aromatase inhibitors (NSAI), steroidal aromatase inhibitors (SAI), and hormone change therapy (Switch). This cross-sectional study was conducted by interviewing women with postmenopausal ER+ breast cancer. The EQ-5D-5L instrument was used to measure and compare utility scores among patients who received NSAI, SAI, and switch therapy. As a result, the average utility score EQ-5D-5L for NSAI is 0.864 (SD = 0.117), significantly different (p = 0.025) from SAI 0.777 (SD = 0.211) and switch 0.776 (SD = 0.071). The conclusion is that NSAI, SAI, and Switch significantly affected HRQoL in postmenopausal breast cancer patients with ER+. NSAI has a better quality of life compared to SAI and Switch.

aromatase inhibitors, breast cancer, EQ-5D-5L, ER+, HRQoL

The fifth leading cause of death in the world is breast cancer. Breast cancer is diagnosed in more than 1.1 million women annually, accounting for 1.6% of fatalities (Belete et al. 2022). According to the World Health Organization (WHO), there will be 24 million more cancer deaths in 2035 (Moradinazar et al. 2019). Breast cancer is the leading cause of cancer death in the Republic of Indonesia, with a mortality rate of 17.1 per 100,000 people, according to data from the Indonesian Ministry of Health for 2021. Most cancer patients in Indonesia are diagnosed at the age of 55 or older. However, about 19.22% and 0.79% of cancer cases occurred in patients aged 45 years and 18 years, respectively (Solikhah et al. 2022).

Numerous endocrine therapies are available, including progestins, luteinizing hormone-releasing hormone (LHRH) agonists, pure ER antagonists, non-steroidal and steroidal aromatase inhibitors, and selective estrogen receptor modulators (SERMs). These therapies are crucial in the treatment of breast cancer. With longer treatment durations, a growing number of breast cancer survivors, and an increase in the number of young women receiving this kind of care, the long-term effects of endocrine therapy are becoming more and more significant (Buijs et al. 2008).

In patients with hormone receptor-positive breast cancer, which represents 70% of total breast cancer, one of the mainstays of treatment is adjuvant hormone therapy (AHT), which can suppress hormone production (non-steroid aromatase inhibitors and steroid aromatase inhibitors) or interfere with hormone receptor signaling (selective estrogen receptor modulators) (Andreu et al. 2022). Hormone therapy reduces the chance of breast cancer recurrence by up to 40% and death by one-third. (Marschner et al. 2019) Aromatase inhibitor treatment lasts 5 to 10 years, so patients must deal with long-term medical interventions, potential side effects, and accompanying psychological discomfort, all of which can significantly impact the quality of life (QoL) (Marschner et al. 2019, Andreu et al. 2022). However, previous studies have focused more on breast cancer patients with HR+/HER2- (Mitra et al. 2016; Wood et al. 2017b; Criscitiello et al. 2021; Cardoso et al. 2024).

The primary goals of treatment for all breast cancer patients are tumor elimination and prevention of metastatic recurrence while maintaining quality of life (Criscitiello et al. 2021). Measuring patient quality of life is needed to improve health outcomes and evaluate therapeutic management (Setyowibowo et al. 2018a; Koboto et al. 2020b). This is done to contextualize the impact of the disease and the treatment given to the patient, which can make it easier to find information on problems affecting patient treatment, improve the healing process, determine treatment decisions, and serve as an economic evaluation of long-term research and the cost-effectiveness of new health technologies (Stefanovic et al. 2017; Riis et al. 2019). Furthermore, there is evidence that patient symptoms can affect HRQOL during treatment (Reed et al. 2012; Shin et al. 2016; Wood et al. 2017a, 2017b; Lazarewicz et al. 2019; Avis et al. 2020).

EuroQol-5 dimensions (EQ-5D-5L) were used in this study to evaluate the quality of life of breast cancer patients. The EQ-5D-5L questionnaire is a generic questionnaire that uses the utility of the set of values to determine the patient’s health state. This questionnaire was created in Europe (developed by The EuroQol Group) and has since been used in many nations worldwide, including Indonesia. EQ-5D-5L comprises five domains and five patient condition levels (Devlin and Krabbe 2013). This questionnaire can also be used to assess the quality of life of breast cancer patients (Devlin and Krabbe 2013). An individual’s response to components of his life, particularly bodily, mental, activity, and sociocultural, is referred to as his quality of life (Devlin and Krabbe 2013; Di Maio et al. 2020). Data on health-related quality of life (HRQoL) can help with treatment recommendations in the future (Buijs et al. 2007). However, to date, real-world HRQOL data have typically focused on patients with advanced or metastatic breast cancer or included a limited cohort of patients with early-stage breast cancer (Reed et al. 2012; Shin et al. 2016; Hamer et al. 2017; Wood et al. 2017a, 2017b; Lazarewicz et al. 2019; Avis et al. 2020). Therefore, more extensive studies are needed in patients with early- and late-stage ER+ breast cancer. In particular, it is essential to evaluate HRQOL in disease-free patients who have undergone ER+ breast cancer surgery to better understand HRQOL at this critical stage of their treatment and to provide context for future evaluations. This study aimed to compare the quality of life of postmenopausal women with ER+ breast cancer who received NSAI, SAI, or Switch in Indonesia using the instrument of the EQ-5D-5L questionnaire.

This is the first study using EQ-5D-5L to evaluate HRQoL of patients with breast cancer + ER in postmenopausal women in one of the national referral hospitals in Indonesia. These results provide insight into the differences in the quality of life of postmenopausal patients with ER+ breast cancer who received NSAI, SAI, or switch. Previous studies have shown that EQ-5D-5L is an acceptable instrument for health status in Indonesia (Purba et al. 2017, Setyowibowo et al. 2018b). As we all know, using non-Indonesian preference weights can lead to biased estimates when conducting Indonesian cost-utility analysis, possibly due to cultural differences (Su et al. 2019). The availability of Indonesian preferences made the EQ-5D-5L a perfect fit for this study. Valid health utility values of postmenopausal women with ER+ breast cancer can provide essential baseline data for the cost-utility analysis of ER+ breast cancer in postmenopausal women in a referral hospital in Indonesia.

This study found that the majority of patients with ER+ breast cancer (44.2%) were between the ages of 50 and 55, which is consistent with a study that found that the incidence of breast cancer increases with age and peaks between the ages of 50 and 55 (Widodo et al. 2017; Cheng et al. 2018; Anwar et al. 2019). According to one study, the average age of patients diagnosed with breast cancer was 55.52 years (Leong et al. 2010; Ou et al. 2019). In this study, the highest degree of education among patients with ER+ breast cancer was high school (50.0%). Patients’ level of education is related to their knowledge about a condition and health behavior, both in terms of applying a healthy lifestyle to prevent health risks (breast cancer) and knowledge activities in detecting breast cancer (Toulasik et al. 2019). Most patients (48.8%) were at stage IIIa of the disease. This is because people tend to seek health facilities after experiencing disturbing health complaints; ignorance is the main reason for delay and noncompliance with treatment; and the government does not have an organized screening program, so breast cancer has entered the category of advanced-stage breast cancer (Toulasik et al. 2019; Nsaful et al. 2022; Fernandes et al. 2023).

Descriptive statistics show that the differences in the number or percentage of patients who did not have problems with the self-care dimension of adjuvant hormone therapy were NSAI 42 (95.5%), SAI 23 (88.5%), and Switch 16 (100%). This study aligns with a study that reported the highest number in the self-care dimension (62.5%), with the answer being no problem (Wallwiener et al. 2016). The proportion of patients who reported having the highest problem was in the anxiety or depression dimension. The difference in the number or percentage level of small anxious or depressed patients on adjuvant hormone therapy was NSAI 21 (47.7%), SAI 14 (53.8%), and Switch 3 (18.8%). A study reported that 81 (47.6%) had problems in the anxiety or depression dimension (Abu Farha et al. 2017), and another study reported that 58% said they had mild to moderate anxiety or depression (Wallwiener et al. 2016). The EQ-5D-5L questionnaire identifies pain and anxiety or depression as significant stressors. This condition is caused by the side effects of therapy and hair loss (Wallwiener et al. 2016). There is one patient (1.2%) who was unable to walk in the mobility dimension, namely on adjuvant hormone therapy with SAI 1 (3.8%). Pain and insomnia are the domains of quality of life most affected in patients with breast cancer (Yusoff et al. 2022).

NSAI has an average utility score of EQ-5D-5L of 0.864, significantly (0.025), making it the highest average utility score compared to the average utility score in SAI of 0.777 and Switch of 0.776. Likewise, the average VAS score of 83.11 for NSAI is significantly higher (0.007) than the average VAS score of 76.35 for SAI and 76.25 for Switch. A study says the NSAI has a QALY value of 11.12, higher than the SAI of 9.9124 (Hind et al. 2007). Research with different results states that NSAI has a QALY value of 1,447 for letrozole and 1,496 for anastrozole, less than the SAI QALY value of 1,608 for exemestane (Sabale et al. 2017).

The utility score EQ-5D-5L with age 50–55 has a higher average utility score and VAS than age 56–60 and age >60, but it is not significantly different (p = 0.257). In a study, the results showed that patients aged 50 to 59 had a utility value of 0.91 and a VAS value of 89.35, higher than patients who were younger (aged 30–39) and older (aged 60–69 and > 70) (Yusoff et al. 2022). Patients with a university education level had significantly the highest mean utility score of 0.856 (p = 0.000) and an average VAS score of 83.21 (p = 0.040). This research is supported by research that shows a significant difference between patients with high levels of education who have a better quality of life than patients with low levels of education because they have better access to information sources (Liu et al. 2017; Park et al. 2011). Breast cancer patients with elementary to high school education levels showed lower quality of life results than patients with higher education than high school (p = 0.012) (Mursyid et al. 2019). Patients with clinical stage I at diagnosis had the highest mean utility and VAS scores but were not significantly different (p = 0.215). The results of this study are supported by research results that state that patients with stage 1 breast cancer have a utility value of 0.72 (0.55–0.85), which is better compared to patients with advanced stages, who have a utility value of 0.67 (0.51–0.81) (Abu Farha et al. 2017). The cancer stage is directly related to the patient’s quality of life. Patients with advanced-stage cancer will have more physically severe problems compared to patients with early-stage cancer. These problems can then affect the psychological aspects of the patient, causing the patient’s quality of life to decrease (Rudiyo et al. 2012). This study produced an average utility score for disease-free survival of 0.844 (SD = 0.176), which aligns with a study that obtained an average utility score for disease-free survival of 0.850 (Djalalov et al. 2015). This study’s average utility score for recurrence was 0.784 (SD = 0.087), in line with a study that produced an average utility score for locoregional, including contralateral recurrence, of 0.72530 (Djalalov et al. 2015). Based on group representation: 1) NSAI has a group with a majority of medium- to high-utility scores; 2) SAI has a group with a majority of medium- to low-utility scores; 3) Switch has groups with lower middle and upper middle utility scores. Based on this, NSAI has higher uniformity in the middle group. Thus, boxplots can better visualize the majority group.

The relationship of all variables (age, education, clinical stage, health status, and adjuvant hormone therapy) with the statistics-based health utility score shows a significant value (Sig. Change in F Change = 0.001), which means that there is a correlation between all variables simultaneously on the utility score. The Pearson correlation value is R = 0.465, which means that the level of correlation between all variables simultaneously on the utility score has a moderate correlation category.

There is no significant correlation (0.247) between age and utility score for breast cancer patients. This result is consistent with research that shows that age has no significant correlation with quality of life (p = 0.826) (Park et al. 2011). The strength of the correlation between age and utility score is weak (-0.126), and the relationship between age and utility score is not unidirectional. There is a significant correlation (0.000) between education and utility scores for people with breast cancer. The strength of the correlation between education and utility scores is sufficient (0.421), and the relationship between education and utility scores is unidirectional. Different results stated that education was not significantly correlated with quality of life (p = 0.81) (Yusoff et al. 2022). There is a significant correlation (0.007, 0.002, and 0.000) between clinical stage, health state, and adjuvant hormone therapy and the utility scores of breast cancer patients. The correlation coefficients are -0.291, -0.330, and -0.385, respectively, meaning that the strength of the correlation between clinical stage, health state, and the adjuvant of hormone therapy to the utility score is sufficient, and the correlation is not unidirectional. Different results state that the cancer stage does not correlate significantly with quality of life (p = 0.125) (Abu Farha et al. 2017).

One limitation of the evaluation is that while the EQ-5D-5L is a reliable instrument for assessing HRQoL, it may lack the sensitivity needed to fully capture all the nuances of HRQoL that are specific to breast cancer patients, especially regarding the particular side effects of hormone therapy. This study may only measure health-related quality of life (HRQoL) at a specific time, so it does not capture the long-term changes in HRQoL that may occur during and after hormone therapy.

The findings of this study indicate that many patients with breast cancer do not have problems in the self-care dimension. However, there are the most significant problems on the anxiety or depression dimension, especially in SAI with a slightly anxious or depressed level. The results of this study provide data on NSAI, which has significantly the highest average utility score of EQ-5D-5L and EQ-VAS compared to SAI and switch hormone therapy.

Conflict of interest

The authors have declared that no competing interests exist.

Ethical statements

The authors declared that no clinical trials were used in the present study.

The authors declared that no experiments on humans or human tissues were performed for the present study.

The authors declared that no informed consent was obtained from the humans, donors or donors’ representatives participating in the study.

The authors declared that no experiments on animals were performed for the present study.

The authors declared that no commercially available immortalised human and animal cell lines were used in the present study.

Funding

No funding was reported.

Author contributions

All authors have contributed equally.

Author ORCIDs

Wawang Anwarudin https://orcid.org/0000-0002-3597-1769

Auliya A. Suwantika https://orcid.org/0000-0001-8671-2065

Data availability

All of the data that support the findings of this study are available in the main text.