Breast cancer (BC) is prevalent in low and middle-income countries (LMICs) where the majority of cases are diagnosed in late stages. The aims of this study were: (1) to assess quality of life (QOL) and health status of Indonesian women with BC symptoms before definitive diagnosis; (2) to compare QOL and health status between women with BC symptoms before definitive diagnosis and Indonesian women in general; (3) to evaluate the association between demographic variables (age, residence, social economic status and education level) and QOL within the Indonesian women with BC symptoms before definitive diagnosis.
We used WHOQOL-BREF to measure QOL and EQ-5D-5L for health status. Multivariate analysis of covariance (MANCOVA) was used to compare QOL and health status between women with BC symptoms and women from the general Indonesian population in order to control for confounders. Regression analyses were used for testing the association between the demographic variables, QOL, and health status.
In comparison with the data from the women from the general population (n = 471), the women with BC symptoms (n = 132) reported lower QOL, especially in physical and psychological domains. They also reported more problems in all dimensions of health status. Higher education and monthly income were positively associated with QOL and health status among the women with BC symptoms.
Citation: Setyowibowo H, Purba FD, Hunfeld JAM, Iskandarsyah A, Sadarjoen SS, Passchier J, et al. (2018) Quality of life and health status of Indonesian women with breast cancer symptoms before the definitive diagnosis: A comparison with Indonesian women in general. PLoS ONE 13(7): e0200966. https://doi.org/10.1371/journal.pone.0200966
Editor: Chung-Ying Lin, Hong Kong Polytechnic University, HONG KONG
Received: April 12, 2018; Accepted: July 5, 2018; Published: July 19, 2018
Copyright: © 2018 Setyowibowo 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 data files are available at https://dataverse.nl/dataset.xhtml?persistentId=hdl:10411/PTQG6C.
Funding: This study was financed by the KWF Kankerbestrijding (the Dutch Cancer Society: number VU 2012-5572 to JP) and the EuroQol Group (EQ Project number: 2013240 to JP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: BC, Breast cancer; EQ-5D-5L, European Quality of Life-5 Dimensions-5 Levels; HICs, High-income countries; LMICs, Low-middle income countries; QOL, Quality of life; WHOQOL-BREF, World health organization Quality of life BREF
Breast cancer (BC) is the most frequently diagnosed malignant tumor among women in both high-income countries (HICs) and low and middle-income countries (LMICs) . The incidence of BC in LMICs is lower than for HICs, but mortality rates in LMICs are higher than in HICs because of advanced-staged diagnosis and inadequate access to care . The mortality rates have been decreasing in many HICs since around 1990 due to early detection and improved treatment . In Indonesia, BC continues to be the most common malignancy in women with an incidence rate of 40.3 percent and a mortality rate of 16.6 percent per 100,000 people .
The diagnostic process of BC and its treatments are often associated with negative effects that can lead to lower quality of life (QOL) [4, 5]. Consequently, the current intervention of BC should not only focus on illness control but also to maintain and improve QOL of women with BC. Throughout the process of hospital care, from diagnosis to treatment, the BC examinations and treatments affect the physical, psychological and social aspects of the life of a woman, which can significantly reduce her QOL, increase psychological distress , and uncertainty , negatively affect her body image and sexuality , illness perception , and increase unmet health needs . Therefore, the information about QOL is crucial at every stage of the BC trajectory. However, most investigations explore various issues after definitive diagnosis, e.g., QOL in women with BC during treatment [9, 11, 12] and QOL in BC survivors [13–15].
To our knowledge, no previous investigation was conducted among the women before the definitive diagnosis in Indonesian women. This stage is essential because some psychosocial problems might already occur when women find abnormalities in their breasts. One of the issues may be the uncertainty about having or not having the disease and the future treatment process. The diagnosis of BC may have many consequences, not only related to life expectancy but also to QOL. Some women with BC in Indonesia have a belief that BC is an incurable and deadly disease . On the other hand, despite having discovered the symptoms of BC, some women may assume that they have no severe health problems. Given the interrelation between demographic characteristics, QOL and health status in general [17–20], we also evaluated which demographic attributes might contribute to a lower QOL and health status in the women with BC symptoms.
No studies have yet been published that compared QOL and health status between undiagnosed women with BC symptoms and women in the general population in Indonesia. Therefore, the aims of this study were: (1) to assess QOL and health status of Indonesian women with BC symptoms before receiving a definitive diagnosis; (2) to compare QOL and health status between women with BC symptoms and Indonesian women in general; (3) to evaluate the association of socio-demographic factors with QOL and health status of Indonesian women with BC symptoms before the definitive diagnosis. The current study that investigated QoL and health status for women with BC symptoms before definite diagnosis may serve as a bridge for future studies to explore whether psychosocial concerns such as impaired body image and unmet needs should be taken into account for women with BC symptoms before definitive diagnosis.
This study consisted of two groups of participants: 1) Indonesian women with BC symptoms who already consulted the hospital but yet without a definitive diagnosis (BC Symptoms Group) and (2) Indonesian women from the general population (General Population Group).
BC symptoms group.
Participants were recruited from four district hospitals in West Java, Indonesia. They were new patients (outpatients) who visit the hospital with breast symptoms, which make them suspects of having BC, but yet without a definitive diagnosis. The following inclusion criteria were used: women with age 18 years and above, an adequate command of the Indonesian language (Bahasa Indonesia) and no major psychiatric disorder. The last criterion was determined by checking the medical record on a consultation history/record with the Psychiatric Department. Patients who have been seen by a psychiatrist were excluded from the study.
General population group.
The data of the comparison group (which will be referred to as "general population" in this manuscript) were women selected from a larger study focused upon the Indonesian general population, in which several questionnaires were tested in a face-to-face setting at the home/office of the interviewer or at the homes of the subjects .This study implemented a multi-stage stratified quota sampling method to ensure representativeness with the Indonesian general population, which resulted in 1054 participants being interviewed. Only the female participants with the age of 18 years and above from the aforementioned study were included in the analysis of the present study.
A standard socio-demographic questionnaire was used to collect participants' background data on residence, age, education level and income level.
QOL was measured using the Indonesian version of the WHOQOL-BREF, with a four weeks-time retrospection. WHOQOL-BREF has been utilized in several investigations in the BC populations in Asian countries , including Indonesia . This instrument is a self-report questionnaire that consists of 26 items. The internal consistency of the WHOQOL BREF’s domains in the present sample were 0.70, 0.78, 0.57, and 0.75 for physical, psychological, social, and environmental domain respectively. Two items measure QOL and health satisfaction in general. Twenty-four items measure four broad domains: (i) physical health (7 items), e.g., "Do you have enough energy for everyday life?”, (ii) psychological health (6 items), e.g., "How much do you enjoy life?”, (iii) social relationships (3 items), e.g., "How satisfied are you with your personal relationships?” and (iv) environmental (8 items), e.g., "How satisfied are you with the conditions of your living place?” Each item is rated using a 5-point Likert scale with varied wording on each scale depending on the item (for example 1 = very dissatisfied to 5 = very satisfied) . The internal consistency of the WHOQOL BREF domains in the present sample were 0.70, 0.78, 0.57, and 0.75 for physical, psychological, social, and environmental domain respectively.
The health status of the participants was measured by the EQ-5D-5L . This instrument has been used in several BC patient populations around the world . EQ-5D-5L is a generic health-related QOL instrument based on a descriptive system that defines health in terms of five dimensions: mobility (MO), self-care (SC), usual activities (UA), pain/discomfort (PD), and anxiety/depression (AD).
Each dimension has five levels: (1) no problems, (2) slight problems, (3) moderate problems, (4) severe problems, and (5) extreme problems/unable. Therefore, the EQ-5D-5L instrument describes 3125 (55) unique health states. A 1-digit number expresses the level selected for that specific dimension. A specific health state then consisted of a combination of a 5-digit number for the five dimensions. For example, state ‘11111’ indicates ‘no problems on any of the five dimensions’, while state ‘34512’ indicates ‘moderate problems in walking about, severe problems washing or dressing, extreme problems doing usual activities, no pain or discomfort, and slight anxiety or depression’. This descriptive system is followed by a self-rating of overall health status on a visual analogue scale (EQ-VAS) ranging from 0 ("the worst health you can imagine") to 100 ("the best health you can imagine"). EQ-5D-5L has been proven as a valid and reliable questionnaire to be used in Indonesia .
Data collection procedures
BC symptoms group.
The study was approved by the Health Research Ethics Committee of Dr. Hasan Sadikin General Hospital Bandung. Participants who agreed to participate by means of oral or written consent were asked to complete the following instruments in the hospital: (1) the socio-demographic and medical history form, (2) the WHOQOL-BREF, and (3) the EQ-5D-5L. If they had difficulties in completing the instruments, the interviewers helped them by reading the items out loud and asking the participants to indicate the answers.
General population group.
The study was approved by the Health Research Ethics Committee, Faculty of Medicine, Universitas Padjadjaran, Indonesia . A representative sample from the Indonesian general population was recruited using multi-stage stratified quota sampling. The interviewers explained the objectives of the study, followed by filling in the informed consent when the participants agreed to participate. Three instruments completed by the participants were: (1) the socio-demographic form: age, sex, income, and education, (2) the WHOQOL-BREF, (3) the EQ-5D-5L. The participants were helped by the interviewers whenever they had problems completing the questionnaires.
Demographic characteristics were summarized using descriptive statistics, including percentages for categorical data, and means and standard deviations for continuous data. The self-reported health problems obtained from the EQ-5D-5L were presented in percentages of each level of each dimension that was answered positively and then compared between the groups with the Chi-square test. Each participant’s EQ-5D-5L responses then were transformed to a single index score based on the preference of the Indonesian general population, a so-called ‘value set’. For instance, the health state of ‘11111’ corresponds to an EQ-5D-5L index score of 1.00, and ‘22211’, which means ‘slight problems in mobility, self-care and usual activities and no problems in pain/discomfort and anxiety/depression’ leads to a value of 0.69. Mean and standard deviation were calculated for the EQ-VAS, EQ-5D-5L index score and each domain of the WHOQOL-BREF.
For the comparison of the QOL between the two groups, we applied an independent t-test if the data were normally distributed or the Wilcoxon rank-sum test if not normally distributed. Normality was tested using the Shapiro-Wilk test and visual inspection of the histograms. For determining the magnitude of the differences, we calculated the effect size using Cohen's d, and we applied the criteria from Cohen for the interpretation: 0.2–0.5 = small, 0.5–0.8 = medium, >0.8 = large difference .
We also applied multivariate analysis of covariance (MANCOVA) with the QOL (WHOQOL-BREF: physical, psychological, social, and environment domain scores) and health status (EQ-5D-5L: EQ-VAS and index score) scores as outcomes and a variable ‘group’ (BC symptoms group vs. general population group) as the predictor in the MANCOVA. Further multiple linear regression analysis was carried out to evaluate whether and if so which socio-demographic variables were significantly affect the QOL and health status scores in the BC symptom group only. Beforehand, a Spearman correlation analysis was done to check whether any significant correlation(s) between each sociodemographic variable with other demographic variables and the outcomes (QOL and health status). We found that ethnicity and religion had no significant correlation to any other variables, therefore they were excluded from the analysis. The following sociodemographic variables: residence (urban/rural), age, level of education (basic: primary school and below/middle: high school/high: all others), and monthly income (below 2 million IDR/2-4 million IDR/above 4 million IDR) were included in the multiple linear regression analysis. Statistical analyses were performed using SPSS-IBM version 21; p-values < .05 were considered statistically significant.
Characteristics of participants
The demographic characteristics of women with BC symptoms and the general population are presented in Table 1. The proportion of age and residence subgroups were similar between the two groups. The BC symptom group had a significantly higher level of education and monthly income than the general population group.
QoL and health status in BC symptoms group and general population group
The mean scores of the QOL domains: measured by the WHOQOL-BREF and health status: measured by the EQ-5D-5L are summarized in Table 2. Concerning the QOL, the BC symptoms group showed significantly lower scores (less favorable) on physical and psychological domains than the general population. The effect sizes for these differences were considered as small. For health status, the EQ-VAS and index score of women with BC symptoms were significantly lower than the general population with medium effect sizes for both scores.
Table 3 presents the comparison of the EQ-5D-5L self-reported health status of the BC symptom and the general population samples. The proportions of responses for each severity level of problems were significantly different for all dimensions between the two samples. It can be seen that the percentage of the BC symptoms group which reported no problems in four dimensions: self-care, usual activity, pain/discomfort and anxiety/depression was lower than that of the general population. In addition, no participants from the general population group reported the worst level of problems in any dimensions, while 1.5%, 3.8%, and 6.8% of the BC symptoms group indicated unable/severe problems in usual activity, pain/discomfort, and anxiety/depression, respectively.
For the MANCOVA analysis, we included the educational level and monthly income as covariates because only these two characteristics differed significantly between the two groups. The results still showed significant overall differences in the QOL between women with BC symptoms and the general population (Wilks’ lambda of 0.85; p-value<0.001). A MANCOVA conducted on the health status yielded similar results (Wilks’ lambda of 0.82; p-value<0.001).
Further multiple linear regression analysis conducted only in the BC symptoms group showed that participants who lived in a rural area demonstrated higher social domain scores than they who did not live in a rural area. Concerning education, participants with the lowest educational levels (i.e. primary school and below) demonstrated lower scores (less favorable) on physical, social, and environmental QOL domains than participants who had college/university level of education, while only physical health scores were significantly different between the middle and the lowest levels of education. Participants in the lowest monthly income group demonstrated less favorable scores in physical, psychological, and environment QOL domains than participants in the highest monthly income group, while only the social domain score was significantly different between the middle and lowest-income groups. With respect to health status (EQ-5D-5L), participants who had the lowest educational level demonstrated significantly lower EQ-5D-5L index scores than participants who achieved higher educational level. We found that age had no significant association with QOL and health status of women with BC symptoms. Details can be seen in Table 4.
To our knowledge, this is the first study that compared the QOL between Indonesian women with BC symptoms before the definitive diagnosis and Indonesian women in general. We found that the QOL of Indonesian women with BC symptoms was significantly lower than in the general Indonesian population, especially in the physical and psychological domain. They also reported more problems across all dimensions, namely mobility, self-care, usual activity, pain/discomfort and anxiety/depression. These findings were also maintained after correction for demographic differences. In addition, we found that education and monthly income were positively associated with the QOL and health status among the women with BC symptoms.
Previous studies among patients with BC reported that pain/discomfort and anxiety/depression are the most common symptoms reported. This might be associated with lower level of HRQOL among patients across different states of BC: after primary BC, during recurrence, and metastases [28–30]. Our study extended these previous results by adding that in the phase of pre-definite diagnosis, the similar results occurred: a higher percentage of reported problems in pain/discomfort and anxiety/depression. Note that because of the EQ-5D wording in the two aforementioned dimensions, we don’t know yet whether the women felt pain or discomfort and anxiety or depression. Further explorations might be needed to investigate whether participants have problems on only one or both conditions, e.g. pain or discomfort.
Concerning the group of women with BC symptoms, we found that higher levels of education and income were associated with more favorable physical, social, and environmental dimensions of QOL compared to those with lower levels of education. This finding is consistent with previous studies in other populations which demonstrated that both income [15, 31, 32] and education  level have a significant impact on QOL: the lower, the worse. It may be hypothesized that higher socio-economic and educational level of patients may lead to better access to information and health services; as a result, these individuals may have fewer problems and feel less uncertain.
Certain limitations of the current study should be considered. First, the sample of women with BC symptoms was obtained from only one area in Indonesia, West Java, that might not be a representative for the whole Indonesian archipelago. Second, the participants of the present study were women with BC symptoms who visited the hospital. It could be argued that these women were anxious enough about the symptoms they observed to enable them to visit the hospital, compared to the women who did not visit the hospital although they probably observed some BC symptoms. This might have biased the results. Third, the comparison group consisting of adult women from the general population, was not screened for the presence of any diseases. Therefore, it is possible that this group included a few participants with BC symptoms, a BC diagnosis, or BC survivors. This might have influenced the results, leading to an underestimation of the actual differences between the groups. Fourth, the choice of generic instruments: WHQOL-BREF and EQ-5D-5L, might be not sensitive enough to measure the QOL and health status of the patients compared to disease-specific instruments such as the European Organization for Research and Treatment of Cancer QOL Questionnaire-C30 (EORTC QLQ-C30)  and the Functional Assessment of Cancer Therapy-General (FACT-G) . However, since the aim of the present study was to compare QOL of women with BC symptoms to women from the general population, which are less likely to have any BC symptoms, generic QOL instruments were considered as the best tool to serve this aim. Nevertheless, there are significant differences between the groups, which indicate worse QOL and health status in the group with BC symptoms. Fifth, although the EQ-5D-5L had been validated and used in breast cancer patients’ population in different countries across the world , this was not the case for Indonesia. So, it is not known for certain that the psychometric properties are supported accurately in the context of this study.
Future research might investigate other factors that may contribute to the QOL of women with BC symptoms, such as social support or physical activities, and find and evaluate effective ways to promote and improve their QOL. Studies might evaluate strategies carried out by healthcare providers and professionals, e.g., physicians, nurses, psychologists, or community health workers to increase their compliance and reduce physical and psychological problems, such as provision of individualized information, symptom management, counseling, or psychosocial interventions.
Our study showed that Indonesian women with BC symptoms before the definitive diagnosis reported lower physical and psychological QOL and more pain/discomfort and anxiety/depression compared to the Indonesian women in general. Awareness and support for them from the medical field might improve these aspects of QOL.
- 1. Torre LA, Islami F, Siegel RL, Ward EM, Jemal A. Global Cancer in Women: Burden and Trends. Cancer Epidemiol Biomarkers Prev. 2017. pmid:28223433.
- 2. Torre LA, Siegel RL, Ward EM, Jemal A. Global Cancer Incidence and Mortality Rates and Trends—An Update. Cancer Epidemiol Biomarkers Prev. 2016;25(1):16–27. pmid:26667886.
- 3. Ferlay JS, I; Ervik M; Forman D; Bray F. GLOBOCAN 2012: Estimated Cancer Incidence, Mortality and Prevalence Worldwide in 2012. 2012.
- 4. Jones SM, LaCroix AZ, Li W, Zaslavsky O, Wassertheil-Smoller S, Weitlauf J, et al. Depression and quality of life before and after breast cancer diagnosis in older women from the Women's Health Initiative. J Cancer Surviv. 2015;9(4):620–9. pmid:25708515; PubMed Central PMCID: PMCPMC4547920.
- 5. Karlsen RV, Frederiksen K, Larsen MB, von Heymann-Horan AB, Appel CW, Christensen J, et al. The impact of a breast cancer diagnosis on health-related quality of life. A prospective comparison among middle-aged to elderly women with and without breast cancer. Acta Oncol. 2016;55(6):720–7. Epub 2016/03/05. pmid:26942569.
- 6. Ng CG, Mohamed S, Kaur K, Sulaiman AH, Zainal NZ, Taib NA, et al. Perceived distress and its association with depression and anxiety in breast cancer patients. PLoS One. 2017;12(3):e0172975. Epub 2017/03/16. pmid:28296921; PubMed Central PMCID: PMCPMC5351853.
- 7. Ahadzadeh AS, Sharif SP. Uncertainty and Quality of Life in Women With Breast Cancer: Moderating Role of Coping Styles. Cancer Nurs. 2018. pmid:29489477.
- 8. Fang SY, Lin YC, Chen TC, Lin CY. Impact of marital coping on the relationship between body image and sexuality among breast cancer survivors. Support Care Cancer. 2015;23(9):2551–9. Epub 2015/01/27. pmid:25617071.
- 9. Iskandarsyah A, de Klerk C, Suardi DR, Soemitro MP, Sadarjoen SS, Passchier J. Satisfaction with information and its association with illness perception and quality of life in Indonesian breast cancer patients. Support Care Cancer. 2013;21(11):2999–3007. pmid:23775157.
- 10. Fang SY, Cheng HR, Lin CY. Validation of the modified Chinese Cancer Survivor's Unmet Needs (CaSUN-C) for women with breast cancer. Psychooncology. 2018;27(1):236–42. Epub 2017/07/13. pmid:28699657.
- 11. Kim SY, Kim SW, Shin IS, Park MH, Yoon JH, Yoon JS, et al. Changes in depression status during the year after breast cancer surgery and impact on quality of life and functioning. Gen Hosp Psychiatry. 2018;50:33–7. pmid:28987920.
- 12. Hawley ST, Janz NK, Griffith KA, Jagsi R, Friese CR, Kurian AW, et al. Recurrence risk perception and quality of life following treatment of breast cancer. Breast Cancer Res Treat. 2017;161(3):557–65. pmid:28004220; PubMed Central PMCID: PMCPMC5310669.
- 13. Shin WK, Song S, Jung SY, Lee E, Kim Z, Moon HG, et al. The association between physical activity and health-related quality of life among breast cancer survivors. Health Qual Life Outcomes. 2017;15(1):132. pmid:28666465; PubMed Central PMCID: PMCPMC5493872.
- 14. Keim-Malpass J, Levine B, Danhauer SC, Avis NE. Work-related perceptions and quality of life among breast cancer survivors. Psychooncology. 2016;25(7):873–6. Epub 2015/09/01. pmid:26315583; PubMed Central PMCID: PMCPMC4769689.
- 15. Yan B, Yang LM, Hao LP, Yang C, Quan L, Wang LH, et al. Determinants of Quality of Life for Breast Cancer Patients in Shanghai, China. PLoS One. 2016;11(4):e0153714. pmid:27082440; PubMed Central PMCID: PMCPMC4833339.
- 16. Iskandarsyah A, de Klerk C, Suardi DR, Soemitro MP, Sadarjoen SS, Passchier J. Psychosocial and cultural reasons for delay in seeking help and nonadherence to treatment in Indonesian women with breast cancer: a qualitative study. Health Psychol. 2014;33(3):214–21. Epub 2013/01/24. pmid:23339645.
- 17. McCaffrey N, Kaambwa B, Currow DC, Ratcliffe J. Health-related quality of life measured using the EQ-5D-5L: South Australian population norms. Health Qual Life Outcomes. 2016;14(1):133. pmid:27644755; PubMed Central PMCID: PMCPMC5028927.
- 18. Garcia-Gordillo MA, Adsuar JC, Olivares PR. Normative values of EQ-5D-5L: in a Spanish representative population sample from Spanish Health Survey, 2011. Qual Life Res. 2016;25(5):1313–21. pmid:26482825.
- 19. Cruz LN, Polanczyk CA, Camey SA, Hoffmann JF, Fleck MP. Quality of life in Brazil: normative values for the WHOQOL-bref in a southern general population sample. Qual Life Res. 2011;20(7):1123–9. pmid:21279448.
- 20. Xia P, Li N, Hau KT, Liu C, Lu Y. Quality of life of Chinese urban community residents: a psychometric study of the mainland Chinese version of the WHOQOL-BREF. BMC Med Res Methodol. 2012;12:37. pmid:22452994; PubMed Central PMCID: PMCPMC3364902.
- 21. Purba FD, Hunfeld JAM, Iskandarsyah A, Fitriana TS, Sadarjoen SS, Ramos-Goni JM, et al. The Indonesian EQ-5D-5L Value Set. Pharmacoeconomics. 2017. Epub 2017/07/12. pmid:28695543.
- 22. Lin CY, Hwang JS, Wang WC, Lai WW, Su WC, Wu TY, et al. Psychometric evaluation of the WHOQOL-BREF, Taiwan version, across five kinds of Taiwanese cancer survivors: Rasch analysis and confirmatory factor analysis. J Formos Med Assoc. 2018. Epub 2018/04/18. pmid:29661488.
- 23. Skevington SM, Lotfy M, O'Connell KA, Group W. The World Health Organization's WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. A report from the WHOQOL group. Qual Life Res. 2004;13(2):299–310. pmid:15085902.
- 24. Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36. pmid:21479777; PubMed Central PMCID: PMCPMC3220807.
- 25. Luo N, Cheung YB, Ng R, Lee CF. Mapping and direct valuation: do they give equivalent EQ-5D-5L index scores? Health Qual Life Outcomes. 2015;13:166. Epub 2015/10/07. pmid:26438167; PubMed Central PMCID: PMCPMC4595246.
- 26. Setiawan D, Dusafitri A, Galistiani GF, van Asselt AD, Postma MJ. Health-Related Quality of Life of Patients with HPV-Related Cancers in Indonesia. Value in Health Regional Issues. 2018;15:63–9. pmid:29474181
- 27. Cohen J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed: Lawrence Erlbaum Associates; 1988.
- 28. Lidgren M, Wilking N, Jonsson B, Rehnberg C. Health related quality of life in different states of breast cancer. Qual Life Res. 2007;16(6):1073–81. pmid:17468943.
- 29. Matalqah LM, Radaideh KM, Yusoff ZM, Awaisu A. Health-related quality of life using EQ-5D among breast cancer survivors in comparison with age-matched peers from the general population in the state of Penang, Malaysia. Journal of Public Health. 2011;19(5):475.
- 30. Rabin EG, Heldt E, Hirakata VN, Fleck MP. Quality of life predictors in breast cancer women. Eur J Oncol Nurs. 2008;12(1):53–7. pmid:17884731.
- 31. Gangane N, Khairkar P, Hurtig AK, San Sebastian M. Quality of Life Determinants in Breast Cancer Patients in Central Rural India. Asian Pac J Cancer Prev. 2017;18(12):3325–32. pmid:29286227.
- 32. Homaee Shandiz F, Karimi FZ, Khosravi Anbaran Z, Abdollahi M, Rahimi N, Ghasemi M. Investigating the Quality of Life and the Related Factors in Iranian Women with Breast Cancer. Asian Pac J Cancer Prev. 2017;18(8):2089–92. pmid:28843227; PubMed Central PMCID: PMCPMC5697465.
- 33. Sharma N, Purkayastha A. Factors Affecting Quality of Life in Breast Cancer Patients: A Descriptive and Cross-sectional Study with Review of Literature. J Midlife Health. 2017;8(2):75–83. pmid:28706408; PubMed Central PMCID: PMCPMC5496284.
- 34. Snyder CF, Blackford AL, Okuyama T, Akechi T, Yamashita H, Toyama T, et al. Using the EORTC-QLQ-C30 in clinical practice for patient management: identifying scores requiring a clinician's attention. Qual Life Res. 2013;22(10):2685–91. Epub 2013/03/28. pmid:23532341; PubMed Central PMCID: PMCPMC3843980.
- 35. Colombo R, Doherty DJ, Wilson CM, Krzys K, Lange S, Maynes H. Implementation and Preliminary Analysis of FACT-G Quality of Life Questionnaire within an Oncology Survivorship Clinic. Cureus. 2018;10(3):e2272. Epub 2018/05/08. pmid:29736356; PubMed Central PMCID: PMCPMC5935424.