Reference values of EORTC QLQ-C30, EORTC QLQ-BR23, and EQ-5D-5L for women with non-metastatic breast cancer at diagnosis and 2 years after.

Plain English summary

Breast Cancer is a chronic disease, since it is an ongoing condition that can recur, requires medical treatment and negatively affects health-related quality of life. The difficulty in interpreting quality of life scores prevents their use, but reference norms can help interpreting them. This study provides reference norms of three widespread quality of life measuring instruments (EORTC QLQ-C30, EORTC QLQ-BR23, and EQ-5D-5L), based on non-metastatic breast cancer patients in Spain.

Health-related quality of life questionnaires were administered to 1276 women with breast cancer at diagnosis and 2 years after. Quality of life was worse for women diagnosed at higher stages of cancer, and for those with other medical conditions. For this reason, reference norms at diagnosis and at the 2-year follow-up were provided according to age, number of conditions, and cancer stage. These reference norms can be useful to interpret the quality of life scores of women with non-metastatic breast cancer.

Background

Breast Cancer is a chronic disease [ 1 ] since it is an ongoing condition that can recur, requires medical treatment and affects negatively the health-related quality of life (HRQoL) [ 2 ], which therefore has become an important outcome in these patients [ 3 – 6 ].

HRQoL instruments are generic or specific according to their target population, and they can in turn be classified as psychometric profiles or econometric indexes according to their measurement model [ 7 ]. Generic instruments are applicable to any population, and are well suited for the comparison among diseases [ 5 , 8 , 9 ], while disease-specific instruments are more responsive in detecting changes over time and differences between groups. The EQ-5D has probably been the most widely used generic econometric instrument [ 8 , 9 ], and the instruments developed by the European Organization for Research and Treatment of Cancer (EORTC) are the most frequently used cancer-specific ones [ 10 ]: the Quality of Life Questionnaire C-30 (EORTC QLQ-C30), common for all tumor locations [ 11 ], and the specific module for Breast cancer (EORTC QLQ-BR23) [ 12 ].

The difficulty in interpreting HRQoL scores has been identified as one of the main barriers to the widespread use of this type of outcomes [ 13 ]. A well-established approach to aid interpretation of scores has been to produce tables of normative data [ 11 , 13 , 14 ]. Reference norms of the EQ-5D-5L based on general population are currently available for several countries [ 15 – 19 ], but not for population with breast cancer. Reference values of EORTC QLQ-C30 and EORTC QLQ-BR23 based on breast cancer patients are available since 2008 [ 20 ], and updated for the EORTC QLQ-C30 in 2020 stratifying by age, breast cancer stage (early or metastatic), comorbid conditions, and performance status [ 21 ]. However, in this update norms were constructed by pooling samples of multinational randomized clinical trials without providing data at country level, despite the consistent differences between countries [ 14 ] and geographic areas [ 21 ].

Although there are general population-based reference norms of EORTC QLQ-C30 available at country level [ 22 – 25 ], there are patient-based reference norms for women with breast cancer and other breast diseases only for Germany [ 26 ].

The present study aimed to obtain reference norms of the EORTC QLQ-C30, the EORTC QLQ-BR23, and the EQ-5D-5L, based on a population of Spanish non-metastatic breast cancer patients at diagnosis and 2 years after, according to relevant demographic and clinical characteristics.

Methods

Study population and setting

We analyzed data of patients included in the CaMISS (Spanish abbreviation for Health Services Research in Breast Cancer) prospective observational study [ 27 ] including consecutive women aged 18 years or older diagnosed with incident breast cancer in one of the participant Spanish hospitals from April 2013 to May 2015. Exclusion criteria were: diagnosis of sarcoma, lymphoma or inflammatory carcinoma; breast cancer recurrence; terminal illness; or inability to respond to questionnaires for any reason.

Women were selected from the lists for surgery and other oncological treatments through revision of inclusion and exclusion criteria in their medical records. Eligible patients were contacted, informed, and invited to participate by phone, and their written informed consent was requested. Out of the 1629 eligible patients invited to participate in the CaMISS study, 1456 accepted (89%): 1176 from 6 hospitals in the Basque Country, 97 from 2 hospitals in the Canary Islands, 97 from one hospital in Catalonia, and 86 from one hospital in Andalusia. After excluding 75 patients with no tumor stage information, 18 in stage IV and 87 without HRQoL data at diagnosis, 1276 patients were included in the analyses. Participants were followed for 2 years (Median = 1.98 years; P25–P75 = 1.94–2.05), and their re-evaluation was performed from May 2015 to December 2017.

HRQoL questionnaires were administered before surgery or before beginning the neoadjuvant therapy, and 2 years after diagnosis. The first administration between diagnosis and treatment was performed during a hospital visit (43.3%) or through telephone interviews (56.7%). 2 years after diagnosis, HRQoL questionnaires were sent by post mail, with reminders at 2 weeks and at 2 months. In the interval among reminders, non-responders were also telephoned to remind them that a questionnaire had been sent and also to offer them the option of responding over the phone if they preferred (17.1% were administered through telephone interviews). There was one person responsible for data collection per hospital, who were trained for recruitment procedures, extraction of data from medical records and administration of HRQoL questionnaires.

The study was approved by the ethics committees of all participating hospitals and conducted according to the principles expressed in the 2000 revision of the Declaration of Helsinki.

Study variables

Participants' age, date of breast cancer diagnosis, clinical TNM classification, and diagnosis of other diseases were collected from medical records at recruitment. The Charlson Comorbidity Index [ 28 ] was constructed with 17 items, scoring from 0 to 6 points. Information about the treatments performed and recurrences suffered during the follow-up were collected from medical records 2 years after diagnosis.

The following socio-demographic variables were self-reported: education level, occupation, social class, and marital status. Social class was based on the Spanish National Classification of Occupations 2011, using a neo-Weberian approach [ 29 ]: (I) Large employers (≥ 10 employees) and higher grade professionals or managers; (II) Small employers, lower grade professionals or managers, higher grade technicians, sports professionals and artists; (III) Intermediate occupations (white collar workers); (IV) Lower supervisory and lower technician occupations; (V) Skilled primary workers and semi-skilled workers; and VI) Unskilled workers.

Health-related quality of life measures

HRQoL was assessed using the Spanish validated versions of EORTC QLQ-C30 [ 30 , 31 ], EORTC QLQ-BR23 [ 12 ], and EQ-5D-5L [ 32 ].

The EORTC QLQ-C30 [ 31 , 33 ] is comprised of 30 items that assess five functional scales, eight cancer symptoms, a financial difficulties scale, and a global health status scale. A single higher-order summary score was calculated, using 27 out of the 30 items (excluding global health status and financial impact) [ 34 ]. The EORTC QLQ-BR23 [ 12 ] comprises 23 items that assess four functional and four symptoms scales. Responses were transformed into scores ranging from 0 to 100, were higher scores indicate greater burden for symptom scales, but better results in functional scales and the EORTC QLQ-C30 summary score [ 34 ].

The EQ-5D-5L [ 32 ] comprises 5 questions to measure the mobility, self-care, usual activities, pain/discomfort, and anxiety/depression dimensions with a 5 response options Likert scale (from none to extreme problems). The EQ-5D-5L includes also a 6 th question to self-rate health (EQ-VAS) with a visual analogue scale ranging from 0 to 100 (best health state imaginable). Applying the Spanish social preferences [ 35 ], a health index was obtained ranging from 1 (perfect health) to negative values for those health states considered worse than death. These preference values were obtained using a standardized protocol, combining the techniques of time trade-off and discrete choice [ 36 ].

Statistical analysis

The statistical power of the study was estimated as > 0.8, with an alpha risk of 0.05 (Type I error), to detect mean differences of 0.4 standard deviation on HRQoL scores for the comparison with the smallest sample size between women with breast cancer in stage 0 and stage III ( N = 116 and 72, respectively). The study power was calculated with R package version 1.3–0 [ 37 ].

Characteristics of women who completed the HRQoL telephone interview at diagnosis and after 2 years were compared to women who did not complete the follow-up evaluation, using the Chi square test. HRQoL differences according to age, comorbidity and stage were tested with ANOVA and Tukey post hoc analyses or Chi Square test. Bar chart figures were created showing our results together with general population-based reference norms of the EQ-5D-5L for Spanish women [ 15 ], and of the EORTC QLQ-C30 for patients with non-metastatic breast cancer from European and Anglo-Saxon countries [ 21 ].

To identify the factors independently associated with HRQoL at diagnosis and 2 years after, linear regression models with the EORTC QLQ-C30 summary score were constructed, as well as censored linear regression models (Tobit) with the EQ-5D-5L index due to the right-skewed distribution. Marginal effects were obtained from the Tobit model as averaged individual marginal effects to restore the original range of the EQ-5D-5L index [ 38 ].

Reference norms were estimated for all patients with non-metastatic breast cancer, stratifying by the variables independently associated with HRQoL. We provide the percentage and standard error for the EQ-5D-5L dimensions. For the continuous scores of EQ-5D-5L, EORTC QLQ-C30 and BR-23 we provide the deciles, percentiles 5 and 95, mean, standard deviation (SD), and 95% confidence interval (95% CI). All analyses were performed with IBM SPSS Statistics, version 25.

Results

Sample characteristics at diagnosis

Table 1 shows socio-demographic and clinical characteristics of the sample, as well as treatment and recurrences observed during the 2-year follow-up. Mean age of the 1276 participants at diagnosis was 58 years (SD = 12), most were married or with a couple (67%), and with breast cancer diagnosed in stage I (52%) and II (30%). The treatments adjuvant to surgery most frequently applied were hormonotherapy (85%) and external radiotherapy (83%). The most frequent treatment combinations are: surgery with radiotherapy and hormonotherapy, which was applied to more than 40% of patients, followed by this combination in addition with chemotherapy (18%), and surgery with hormonotherapy in almost 10% of the patients. Patients with other treatments received concomitant medication for side effects or other diseases, such as granulocyte colony-stimulating factor (8 patients), methotrexate or zoledronic acid. Table 1 Characteristics of women with non-metastatic breast cancer at diagnosis, treatment applied and recurrences detected during the 2-year follow-up All patients Patients with HRQoL assessment at diagnosis and follow-up Patients without HRQoL assessment at follow-up p value* N 1276 1108 168 Socio-demographic Age (years) < 40 76 (6.0%) 57 (5.1%) 19 (11.3%) 0.007 40–65 878 (68.8%) 771 (69.6%) 107 (63.7%) > 65 322 (25.2%) 280 (25.3%) 42 (25.0%) Education level Primary school or less 317 (25.3%) 267 (24.6%) 50 (30.3%) 0.066 Middle school 332 (26.5%) 299 (27.5%) 33 (20.0%) High school 302 (24.1%) 267 (24.6%) 35 (21.2%) University and above 300 (24.0%) 253 (23.3%) 47 (28.5%) Occupation Working 582 (46.7%) 511 (47.2%) 71 (43.3%) 0.039 Housewife 236 (18.9%) 211 (19.5%) 25 (15.2%) Retired or unable to work 91 (7.3%) 70 (6.5%) 21 (12.8%) Unemployed 314 (25.2%) 271 (25.0%) 43 (26.2%) Others 23 (1.8%) 19 (1.8%) 4 (2.4%) Social class I–II 240 (22.9%) 205 (22.3%) 35 (27.6%) 0.156 III 232 (22.2%) 213 (23.2%) 19 (15.0%) IV 425 (40.6%) 373 (40.5%) 52 (40.9%) V–VI 150 (14.3%) 129 (14.0%) 21 (16.5%) Missings 229 188 41 Marital status Single 133 (10.6%) 106 (9.7%) 27 (16.3%) 0.019 Married/couple 849 (67.4%) 750 (68.6%) 99 (59.6%) Widowed/divorced/separated 278 (22.1%) 238 (21.8%) 40 (24.1%) Clinical Screening detection No 598 (46.9%) 506 (45.7%) 92 (54.8%) 0.028 Yes 678 (53.1%) 602 (54.3%) 76 (45.2%) Tumor stage Stage 0 132 (10.3%) 116 (10.5%) 16 (9.5%) 0.058 Stage I 666 (52.2%) 588 (53.1%) 78 (46.4%) Stage II 386 (30.3%) 332 (30.0%) 54 (32.1%) Stage III 92 (7.2%) 72 (6.5%) 20 (11.9%) Charlson comorbidity index 0 1017 (79.7%) 881 (79.5%) 136 (81.0%) 0.299 1 165 (12.9%) 143 (12.9%) 22 (13.1%) 2 68 (5.3%) 63 (5.7%) 5 (3.0%) 3 21 (1.6%) 16 (1.4%) 5 (3.0%) 4 or more 5 (0.4%) 5 (0.5%) 0 (0.0%) Treatment type during 2 years follow-up Any neoadjuvant treatment 120 (9.4%) 98 (8.8%) 22 (13.1%) 0.079 Breast surgery Breast-conserving surgery 551 (43.2%) 490 (44.3%) 61 (36.3%) 0.001 Mastectomy 298 (23.4%) 239 (21.6%) 59 (35.1%) Missing 426 (33.4%) 378 (34.1%) 48 (28.6%) Lymphadenectomy 273 (21.4%) 227 (20.5%) 46 (27.4%) 0.042 Adjuvant treatment Chemotherapy 436 (34.3%) 379 (34.3%) 57 (34.3%) 0.944 External Radiotherapy 1059 (83.4%) 934 (84.6%) 125 (75.3%) 0.001 Brachytherapy 65 (5.1%) 56 (5.1%) 9 (5.4%) 0.868 Hormonotherapy 1081 (85.1%) 945 (85.5%) 136 (82.4%) 0.145 Anti-HER2 112 (8.8%) 95 (8.6%) 17 (10.3%) 0.510 Other 11 (0.9%) 9 (0.9%) 2 (1.3%) 0.607 Recurrences during 2 years follow-up Loco-regional 19 (1.5%) 11 (1.0%) 8 (4.8%) < 0.001 Metastases 27 (2.1%) 14 (1.3%) 13 (7.7%) < 0.001 PRO patient reported outcome *Chi-Squared Test

Statistically significant differences were found between the 1108 patients who completed the two HRQoL assessments and the 168 who did not complete the second evaluation. The latter group were younger, more frequently without couple, underwent mastectomy and lymphadenectomy, and had a higher percentage of detected recurrences.

Figure 1 shows that EQ-5D-5L index means for breast cancer patients were significantly lower (worse) than the reference norms based on general population of Spanish women [ 15 ] at the two time points, except for patients aged > 65 years. In general, the EORTC QLQ-C30 summary score means for breast cancer patients at diagnosis (Fig. 2 ) were similar to the reference norms based on European and Anglo-Saxon patients [ 21 ] at diagnosis, but significantly lower (worse) at the 2-year follow-up. Fig. 1 EQ-5D-5L Index according to age, tumor stage and Charlson Comorbidity Index: bars represent means and their 95% confidence intervals at diagnosis and at 2-year follow-up. Discontinuous lines represent the EQ-5D-5L index means of reference norms based on general population [ 15 ] Spanish women. Y axis represents the EQ-5D-5L index values from 1 (perfect health) to 0 (death). *p value < 0.05 obtained using Tukey post hoc analysis for comparing each category with the reference: aged < 40 years old, tumor stage 0, or Charlson Comorbidity Index 0 Fig. 2 EORTC QLQ-C30 summary score according to age, tumor stage and Charlson Comorbidity Index: bars represent means and their 95% confidence intervals at diagnosis and at 2-year follow-up. Discontinuous lines represent the EORTC QLQ-C30 reference norms based on patients with non-metastatic breast cancer at diagnosis [ 21 ]. Y axis represents the EORTC QLQ-C30 summary score from 0 (worst) to 100 (best results). *p value < 0.05 obtained using Tukey post hoc analysis for comparing each category with the reference: aged < 40 years old, tumor stage 0, or Charlson Comorbidity Index 0

Table 2 shows statistically significant differences on EQ-5D-5L by age group and comorbidity, both at diagnosis and 2 years after. Only usual activities and pain/discomfort EQ-5D dimensions presented differences by tumor stage at diagnosis; while all the dimensions, the index and the EQ-VAS presented statistically significant differences after 2 years. Similarly, more EORTC QLQ-C30 scales (Table 3 ) presented statistically significant differences by comorbidity index and tumor stage at 2 years of follow-up than at diagnosis. Some scores of the EORTC BR23 (Table 4 ) also presented significant differences among groups defined by these variables. Table 2 EQ-5D-5L results according to age, Charlson Comorbidity Index and stage: frequency and percentage of patients that reported having any problem in each dimension and mean (SD) of EQ-5D-5L index* and EQ-VAS** Mobility Self-care Activity Pain Anxiety EQ-5D-5L index EQ-VAS AT diagnosis All 146 (11.5%) 59 (4.6%) 162 (12.7%) 468 (36.8%) 811 (63.8%) 0.86 (0.14) 73.1 (19.9) Age < 40 3 (3.9%) 3 (3.9%) 13 (17.1%) 30 (40.0%) 43 (57.3%) 0.90 (0.10) 78.0 (20.8) 40–65 58 (6.6%) 29 (3.3%) 85 (9.7%) 306 (34.9%) 557 (63.4%) 0.87 (0.13) 73.5 (20.0) > 65 85 (26.6%) 27 (8.4%) 64 (20.0%) 132 (41.3%) 211 (66.1%) 0.84 (0.16) 72.3 (19.9) p value < 0.001 0.001 < 0.001 0.106 0.339 < .001 .259 Comorbidity index 0 73 (7.2%) 35 (3.4%) 112 (11.0%) 356 (35.1%) 638 (62.9%) 0.87 (0.13) 74.6 (18.9) ≥ 1 73 (28.3%) 24 (9.4%) 50 (19.4%) 112 (43.4%) 173 (67.1%) 0.82 (0.18) 67.4 (22.5) p value < 0.001 < 0.001 < 0.001 0.013 0.217 < .001 < .001 Tumor stage 0 12 (9.1%) 7 (5.3%) 13 (9.8%) 45 (34.1%) 81 (61.4%) 0.88 (0.12) 75.5 (18.8) I 66 (9.9%) 28 (4.2%) 72 (10.8%) 229 (34.4%) 434 (65.2%) 0.86 (0.14) 73.8 418.9) II 55 (14.3%) 19 (4.9%) 61 (15.9%) 164 (42.7%) 238 (62.0%) 0.85 (0.15) 72.1 (21.2) III 13 (14.1%) 5 (5.4%) 16 (17.4%) 30 (33.0%) 58 (64.4%) 0.86 (0.14) 69.5 (22.7) p value 0.109 0.888 0.038 0.038 0.696 .341 .085 At 2-year follow-up All 302 (26.5%) 117 (10.3%) 359 (31.5%) 639 (56.3%) 502 (44.2%) 0.84 (0.18) 74.5 (18.4) Age < 40 years 2 (5.6%) 2 (5.6%) 7 (19.4%) 16 (44.4%) 16 (44.4%) 0.90 (0.12) 79.9 (13.6) 40–65 years 168 (22.1%) 57 (7.5%) 223 (29.4%) 421 (55.4%) 334 (44.1%) 0.85 (0.16) 76.1 (17.8) > 65 years 131 (38.9%) 57 (17.0%) 128 (37.9%) 201 (60.2%) 152 (45.2%) 0.81 (0.21) 70.2 (19.6) p value < 0.001 < 0.001 0.006 0.114 0.937 < .001 < .001 Comorbidity index 0 191 (21.2%) 67 (7.4%) 251 (27.8%) 479 (53.2%) 383 (42.6%) 0.86 (0.16) 76.4 (17.4) ≥ 1 111 (46.8%) 50 (21.2%) 108 (45.6%) 160 (68.1%) 119 (50.2%) 0.77 (0.23) 67.1 (20.3) p value 0.278 < 0.001 0.001 0.007 0.155 < .001 < .001 Tumor stage 0 23 (19.7%) 5 (4.3%) 20 (17.2%) 56 (47.9%) 41 (34.5%) 0.87 (0.19) 78.6 (16.6) I 161 (26.4%) 51 (8.4%) 186 (30.5%) 326 (53.6%) 274 (45.2%) 0.85 (0.17) 74.9 (18.5) II 97 (28.8%) 53 (15.8%) 124 (36.6%) 208 (61.7%) 152 (45.1%) 0.82 (0.19) 73.2 (19.0) III 21 (28.4%) 8 (10.8%) 29 (39.2%) 49 (66.2%) 35 (47.3%) 0.83 (0.15) 69.9 (17.4) p value < 0.001 < 0.001 < 0.001 < 0.001 0.036 .027 .006 The five-level response scale of EQ-5D-5L dimensions was dichotomized into “no problems” versus “any problem” (slight, moderate, severe, or extreme problems), and percentages were compared with Chi Square test * EQ-5D-5L index ranged from 1 (perfect health) to negative values for those health states considered worse than death. ** EQ-VAS ranged from 0 to 100 (best state imaginable health). Differences on mean scores of the EQ-5D-5L index and EQVAS were tested with ANOVA test Table 3 Mean scores and standard deviations of EORTC QLQ-C30 according to age, Charlson Comorbidity Index, and tumor stage All Age Comorbidity index Tumor stage < 40 40–65 > 65 p value* 0 ≥ 1 p value* 0 I II III p value* At diagnosis Summary score 86.6 (11.5) 85.7 (13.0) 86.9 (11.2) 86.2 (12.2) .533 87.1 (10.9) 84.6 (13.6) .002 89.0 (10.3) 86.6 (11.7) 86.2 (11.7) 85.7 (11.6) .085 Physical function 92.6 (13.6) 96.9 (7.0) 94.5 (11.4) 86.6 (17.8) < .001 94.3 (11.2) 86.0 (19.0) < .001 93.9 (12.9) 93.4 (12.6) 91.1 (15.2) 91.9 (14.0) .045 Role function 91.4 (19.7) 89.5 (21.7) 91.7 (19.1) 91.0 (20.9) .589 91.7 (18.9) 90.4 (22.7) .365 92.2 (17.4) 91.9 (19.2) 90.8 (20.8) 89.7 (21.7) .643 Emotional function 65.7 (23.3) 60.0 (22.6) 65.5 (23.3) 67.4 (23.5) .043 65.9 (23.0) 64.7 (24.7) .442 70.5 (22.2) 64.9 (23.7) 66.8 (22.2) 59.6 (25.0) .003 Cognitive function 85.6 (20.3) 86.0 (17.4) 85.3 (20.7) 86.2 (20.0) .782 85.9 (19.9) 84.3 (21.9) .265 85.8 (20.6) 85.4 (20.1) 86.4 (20.3) 83.2 (21.6) .559 Social function 89.0 (21.0) 81.8 (27.4) 88.4 (21.2) 92.4 (17.7) < .001 89.1 (20.8) 88.4 (21.6) .640 90.7 (19.7) 89.7 (19.9) 87.7 (22.5) 87.0 (23.0) .282 Global health status 73.5 (19.6) 72.8 (18.9) 73.9 (19.3) 72.6 (20.8) .561 74.7 (18.7) 68.7 (22.4) < .001 75.0 (19.0) 74.2 (19.2) 72.1 (19.9) 71.9 (21.8) .263 Fatigue 15.9 (19.8) 16.1 (21.3) 15.0 (19.3) 18.2 (20.5) .041 14.8 (18.6) 19.9 (23.6) < .001 13.2 (17.8) 15.1 (19.1) 17.7 (21.1) 17.3 (20.8) .066 Nausea 2.7 (9.9) 2.9 (9.6) 2.9 (10.2) 1.9 (8.9) .257 2.6 (9.4) 2.9 (11.5) .722 2.6 (9.4) 2.5 (9.3) 2.9 (11.0) 2.9 (9.8) .926 Pain 13.0 (20.6) 13.6 (20.7) 11.7 (19.4) 16.2 (23.3) .003 12.3 (19.7) 15.6 (23.6) .020 11.0 (18.4) 12.4 (20.2) 14.8 (22.0) 11.8 (20.3) .161 Dyspnea 9.4 (19.9) 6.1 (14.1) 9.5 (20.1) 10.0 (20.7) .311 9.3 (19.6) 10.0 (21.2) .609 8.1 (18.5) 9.7 (20.2) 9.3 (20.3) 9.4 (18.7) .871 Insomnia 32.0 (31.1) 29.4 (31.7) 32.5 (30.9) 31.2 (31.5) .608 31.7 (30.5) 33.2 (33.3) .475 30.3 (31.2) 33.0 (31.1) 30.6 (30.4) 32.6 (33.1) .575 Appetite loss 12.7 (22.5) 17.8 (25.3) 12.9 (22.7) 11.1 (21.2) .065 12.3 (21.8) 14.2 (24.8) .247 9.3 (20.3) 12.4 (22.0) 14.4 (24.0) 12.3 (22.5) .147 Constipation 9.8 (21.2) 7.5 (18.5) 9.0 (20.3) 12.6 (23.7) .023 9.1 (20.0) 12.6 (25.0) .019 8.7 (17.9) 9.7 (21.5) 10.9 (22.1) 8.1 (18.8) .567 Diarrhea 5.0 (14.7) 4.8 (16.1) 5.2 (14.6) 4.4 (14.6) .753 4.6 (13.5) 6.4 (18.5) .075 2.6 (10.7) 5.2 (14.9) 4.7 (14.3) 7.7 (18.6) .075 Financial difficulties 6.2 (18.1) 10.1 (24.4) 6.4 (18.1) 4.5 (16.0) .039 5.8 (17.3) 7.5 (20.7) .187 5.4 (15.4) 6.6 (18.9) 6.1 (18.0) 4.4 (15.2) .681 At 2-year follow-up Summary score 84.7 (14.6) 86.9 (13.7) 84.9 (14.7) 83.9 (14.6) .368 86.1 (13.5) 79.6 (17.2) < .001 87.9 (12.5) 85.5 (14.0) 83.0 (15.6) 81.8 (16.4) .002 Physical function 86.3 (17.5) 93.0 (10.4) 88.4 (15.0) 81.0 (21.6) < .001 88.6 (15.0) 78.0 (22.9) < .001 91.6 (12.8) 87.5 (16.6) 82.9 (20.2) 83.3 (14.6) < .001 Role function 85.8 (23.6) 88.4 (20.6) 87.2 (22.0) 82.1 (27.0) .004 87.7 (21.8) 78.5 (28.4) < .001 89.4 (19.9) 87.2 (22.2) 82.6 (26.3) 81.9 (25.6) .004 Emotional function 78.1 (22.6) 77.8 (24.4) 77.6 (23.3) 78.9 (20.9) .714 78.9 (22.1) 75.1 (24.4) .020 81.1 (21.4) 77.8 (22.5) 78.0 (22.6) 76.0 (25.0) .427 Cognitive function 84.0 (22.2) 87.0 (22.9) 83.8 (22.9) 84.0 (20.6) .685 84.8 (21.8) 80.8 (23.7) .012 85.7 (21.1) 84.3 (21.8) 83.7 (22.6) 80.0 (25.7) .346 Social function 85.7 (23.8) 84.7 (19.3) 84.7 (24.5) 88.0 (22.6) .106 87.0 (22.6) 80.8 (27.5) < .001 91.7 (17.9) 87.0 (21.9) 82.1 (26.6) 82.2 (30.0) < .001 Global health status 72.3 (20.6) 76.4 (17.3) 73.3 (20.2) 69.4 (21.8) .008 74.4 (19.6) 64.4 (22.4) < .001 74.6 (20.1) 73.4 (19.6) 69.7 (22.6) 71.1 (19.8) .031 Fatigue 25.4 (24.5) 21.8 (19.8) 24.9 (24.5) 27.3 (24.9) .211 23.2 (23.3) 33.9 (26.8) < .001 21.6 (23.4) 24.9 (24.2) 27.5 (25.1) 26.8 (25.1) .114 Nausea 3.4 (11.0) 1.4 (4.7) 3.4 (10.6) 3.6 (12.5) .535 2.9 (9.6) 5.1 (15.1) .006 3.6 (11.1) 2.7 (9.7) 4.0 (11.9) 5.6 (15.9) .090 Pain 21.4 (24.8) 18.1 (23.4) 21.3 (24.7) 22.4 (25.2) .567 19.7 (23.5) 28.2 (28.2) < .001 17.5 (24.4) 20.0 (23.8) 24.9 (26.0) 24.1 (25.8) .006 Dyspnea 11.4 (21.4) 12.0 (22.8) 12.2 (21.6) 9.8 (20.8) .212 10.0 (19.7) 16.9 (26.0) < .001 11.7 (20.1) 10.5 (20.0) 12.8 (23.7) 12.7 (22.8) .429 Insomnia 31.4 (32.4) 26.9 (30.7) 32.3 (33.0) 30.1 (31.4) .407 30.3 (31.6) 35.3 (35.0) .035 26.6 (31.5) 31.3 (32.1) 31.7 (32.2) 38.4 (36.5) .111 Appetite loss 8.3 (20.0) 2.8 (9.3) 7.6 (18.8) 10.7 (23.2) .017 7.0 (17.8) 13.3 (26.3) < .001 4.4 (12.2) 7.5 (18.7) 10.3 (22.4) 12.7 (27.2) .007 Constipation 14.6 (24.9) 13.9 (24.4) 13.5 (24.1) 17.2 (26.6) .077 13.6 (24.1) 18.3 (27.5) .010 13.7 (23.5) 14.4 (24.6) 15.2 (26.2) 14.0 (23.4) .932 Diarrhea 6.0 (16.2) 4.6 (14.1) 5.0 (14.5) 8.5 (19.7) .003 5.1 (14.4) 9.1 (21.4) .001 4.5 (13.0) 5.7 (15.6) 6.6 (17.0) 7.7 (21.0) .470 Financial difficulties 11.6 (24.1) 18.5 (30.3) 13.2 (25.4) 7.4 (19.4) < .001 11.4 (23.7) 12.2 (25.4) .648 7.8 (19.7) 10.8 (23.7) 13.9 (26.0) 12.8 (24.0) .073 *EORTC QLQ-C30 differences according to age, comorbidity and stage were tested with ANOVA Table 4 Mean scores and standard deviations of EORTC QLQ-BR-23 according to age, Charlson Comorbidity Index, and stage All Age Comorbidity index Tumor stage < 40 40–65 > 65 p value* 0 ≥ 1 p value* 0 I II III p value* At diagnosis Body image 92.3 (16.7) 87.5 (20.8) 92.0 (17.0) 94.5 (14.4) .003 92.4 (16.3) 92.1 (18.4) .779 94.2 (12.6) 92.6 (16.7) 91.9 (17.2) 89.8 (19.8) .258 Sexual function 23.5 (26.1) 31.3 (27.1) 27.4 (26.6) 10.6 (19.2) < .001 24.9 (25.8) 18.2 (26.5) < .001 24.7 (26.5) 24.9 (26.1) 21.1 (25.4) 21.8 (28.3) .126 Sexual enjoy 54.6 (29.1) 59.4 (32.1) 56.2 (28.8) 42.5 (26.1) < .001 55.3 (28.9) 50.5 (29.9) .140 54.5 (26.6) 54.8 (28.3) 53.6 (29.7) 57 (36.0) .913 Future perspective 45.9 (31.9) 36.4 (32.0) 45.7 (31.7) 48.8 (32.2) .009 45.8 (31.3) 46.3 (34.2) .822 50.3 (29.9) 45.8 (32.1) 46.4 (32.4) 39.2 (31.3) .090 Systemic therapy effects 12.5 (13.9) 11.5 (13.9) 12.7 (14.4) 12.4 (12.7) .764 12.2 (13.8) 13.6 (14.3) .169 12.6 (13.5) 11.8 (13.2) 13.2 (14.8) 14.4 (16.2) .235 Breast symptoms 13.2 (16.9) 19.2 (20.4) 13.4 (16.9) 11.1 (15.8) .001 13.7 (17.2) 11.0 (15.6) .021 13.4 (17.2) 12.5 (17.2) 14.4 (16.7) 12.9 (15.8) .342 Arm symptoms 8.7 (15.6) 6.4 (12.5) 8.4 (14.7) 10.0 (18.3) .127 8.2 (14.7) 11.0 (18.5) .011 7.8 (14.0) 8.4 (15.5) 9.6 (15.8) 8.6 (17.2) .592 Upset hair loss 24.0 (31.6) 12.3 (27.7) 25.6 (33.2) 23.6 (27.7) .223 23.5 (31.4) 26.7 (33.1) .564 11.1 (18.5) 22.9 (32.8) 28.6 (32.5) 33.3 (31.2) .053 At 2-year follow-up Body image 84.6 (24.6) 79.7 (28.6) 82.9 (25.8) 88.8 (21.0) .001 84.6 (24.7) 84.7 (24.4) .956 90.1 (18.3) 86.7 (22.4) 81.4 (27.0) 73.5 (33.7) < .001 Sexual function 20.9 (23.5) 29.5 (21.0) 25 (24.1) 9.9 (17.9) < .001 22.4 (24.0) 15.4 (21.0) < .001 23.8 (24.1) 21.7 (24.3) 18.9 (22.5) 19 (19.8) .163 Sexual enjoy 50.3 (27.8) 62.8 (23.7) 53.2 (27.0) 34.3 (27.1) < .001 51.3 (28.1) 45.6 (26.2) .070 52.8 (26.3) 51.3 (29.2) 48.2 (27.1) 47 (22.6) .518 Future perspective 59.5 (32.1) 55.9 (37.4) 57.1 (31.9) 65.0 (31.4) .001 59.2 (31.9) 60.6 (33.0) .557 66.4 (29.3) 59.6 (31.6) 59.1 (32.4) 48.4 (36.9) .003 Systemic therapy effects 18.3 (16.5) 12.2 (11.1) 18.9 (16.8) 17.9 (16.1) .056 17.7 (16.3) 20.7 (17.3) .014 16.6 (15.4) 17.8 (15.8) 19.3 (17.8) 21.1 (17.8) .171 Breast symptoms 16.0 (17.8) 17.4 (19.5) 17.4 (18.0) 13.0 (16.9) .001 15.8 (16.8) 16.6 (21.0) .572 15.0 (18.5) 16.0 (17.0) 16.1 (18.7) 17.2 (18.5) .859 Arm symptoms 15.7 (20.3) 9.5 (15.0) 16.2 (20.3) 15.5 (20.8) .157 15.0 (19.5) 18.2 (23.0) .035 12.0 (18.0) 14.2 (19.4) 18.2 (21.0) 22.8 (24.8) < .001 Upset hair loss 31.1 (33.7) 13.9 (30.0) 32.0 (33.4) 31.2 (34.3) .192 29.4 (32.6) 36.9 (36.7) .058 22.0 (26.8) 29.8 (33.4) 34.4 (34.5) 42.0 (40.5) .066 * EORTC QLQ-BR-23 differences according to age, comorbidity and stage were tested with ANOVA

Multivariate models of EQ-5D-5L iIndex and EORTC QLQ-C30 summary score at diagnosis and at 2-year follow-up (Table 5 ) show the independent association of comorbidity and tumor stage with HRQoL. The standardized multivariate regression coefficient of EORTC QLQ-C30 summary score indicates that HRQoL was poorer for women with stage II and III than for those with stage 0 both at diagnosis (− 0.11 and − 0.07, p < 0.05) and at follow-up (− 0.15 and − 0.10, p < 0.01). The EQ-5D-5L index also indicated poorer HRQoL for women with Charlson comorbidity index ≥ 2 than comorbidity 0 at diagnosis (− 0.13, p < 0.001) and at follow-up (− 0.18, p < 0.001). Table 5 Multivariate models of the EQ-5D-5L index and EORTC QLQ-C30 summary score as dependent variables At diagnosis At 2-year follow-up Coefficient (SE) 95% CI Standardized Coefficient p value Coefficient (SE) 95% CI Standardized Coefficient p value EQ-5D-5L index Intercept 0.90 (0.02) [0.86, 0.93] < .001 0.93 (0.03) [0.86, 0.99] < 0.001 Age < 40 years Ref Ref 40–65 years − 0.01 (0.02) [− 0.04, 0.03] − 0.02 .774 − 0.03 (0.02) [− 0.07, 0.02] − 0.07 0.231 > 65 years − 0.03 (0.02) [− 0.07, 0.00] − 0.11 .055 − 0.06 (0.02) [− 0.11, -0.02] − 0.15 0.010 Comorbidity index 0 Ref Ref 1 − 0.04 (0.01) [− 0.06, -0.01] − 0.09 .002 − 0.07 (0.02) [− 0.10, -0.04] − 0.13 < 0.001 ≥ 2 − 0.07 (0.02) [− 0.10, -0.04] − 0.13 < .001 − 0.12 (0.02) [− 0.16, -0.08] − 0.18 < 0.001 Tumor stage 0 Ref Ref I − 0.01 (0.01) [− 0.04, 0.02] − 0.04 .415 − 0.01 (0.02) [− 0.05, 0.02] − 0.03 0.513 II − 0.02 (0.01) [− 0.05, 0.01] − 0.06 .186 − 0.04 (0.02) [− 0.08, -0.00] − 0.11 0.026 III − 0.01 (0.02) [− 0.05, 0.03] − 0.02 .545 − 0.03 (0.03) [− 0.08, 0.02] − 0.04 0.232 EORTC QLQ-C30 summary score Intercept 88.12 (1.66) [84.87, 91.36] < .001 90.66 (2.69) [85.38, 95.93] < .001 Age < 40 Ref Ref 40–65 1.28 (1.39) [− 1.44, 4.00] 0.05 .357 − 1.92 (2.45) [− 6.71, 2.88] − 0.06 .433 > 65 1.35 (1.49) [− 1.58, 4.28] 0.05 .367 − 1.39 (2.53) [− 6.35, 3.57] − 0.40 .582 Comorbidity Index 0 Ref Ref 1 − 1.36 (0.99) [− 3.30, 0.58] − 0.04 .171 − 4.76 (1.28) [− 7.27, -2.25] − 0.11 < .001 ≥ 2 − 4.43 (1.27) [− 6.92, -1.94] − 0.10 < .001 − 9.31 (1.64) [− 12.52, -6.11] − 0.17 < .001 Tumor stage 0 Ref Ref I − 2.23 (1.12) [− 4.42, -0.04] − 0.10 .047 − 2.06 (1.45) [− 4.91, 0.78] − 0.07 .155 II − 2.65 (1.19) [− 4.97, -0.32] − 0.11 .026 − 4.77 (1.55) [− 7.80, -1.74] − 0.15 .002 III − 3.22 (1.60) [− 6.35, -0.08] − 0.07 .045 − 5.88 (2.15) [− 10.10, -1.66] − 0.10 .006

The reference norms for EQ-5D-5L (dimensions, index, and EQ-VAS), EORTC QLQ-C30 and BR23 scores at diagnosis and at the 2-year follow-up are provided in Supplementary data, stratified by age, comorbidity index, and tumor stage (Supplementary materials, Tables 1.1.1 to 2.3.8).

Discussion

This is the first study to obtain the Spanish reference norms of the EORTC QLQ-C30, the EORTC QLQ-BR23 and the EQ-5D-5L, based on women with non-metastatic breast cancer. The results obtained indicate that the HRQoL of these women differs according to age, comorbidity, and tumor stage at diagnosis and at 2 years of follow-up and, therefore, reference norms based on patient population stratified by these factors are recommended to interpret HRQoL results.

Our results showing HRQoL differences by age and comorbid conditions are consistent with the available evidence from studies on reference norms of the EQ-5D [ 15 – 19 , 39 ] and the EORTC QLQ-C30 [ 21 , 22 ], and confirm the need to stratify them by these variables. According to the magnitude of the HRQoL differences among stages, we decided to provide reference norms separately for stage 0-I and II-III. Previous EORTC QLQ-C30 reference norms also stratified by tumor stage, but with different aggregations (I-II and III-IV in the first one [ 20 ], and I-II-III and IV in the 2020 update [ 21 ]), both at diagnosis.

There are important differences in content between EQ-5D-5L and EORTC QLQ-C30, as they target different populations. EORTC QLQ-C30 is specifically focused on patients with cancer and, therefore, it includes domains that are especially relevant for this population, such as insomnia or fatigue. The lack of these domains in EQ-5D-5L has been highlighted in patients with multiple myeloma [ 40 ] and leukemia [ 41 ]. From a clinical perspective, EORTC instruments can be more useful to identify cancer-specific problems, though utilities cannot be directly obtained from EORTC QLQ-C30 and BR23 since they are psychometric instruments. Utilities can be calculated using algorithms developed through mapping models to EQ-5D [ 42 – 44 ]: two developed in patients with metastatic breast cancer (from the EORTC QLQ-C30 [ 42 ] or also from the BR-23 [ 43 ]) and one specifically developed for HER2-positive patients with recurrent, unresectable, or metastatic breast cancer [ 44 ]. These mapping algorithms allow economic evaluations, but administering the utility instrument itself would be the best option: either the EQ–5D–5L or the new breast cancer-specific utility instrument based on the EORTC QLQ-C30 and the BR-45 [ 45 ].

The distribution of the EQ–5D–5L index and its five health dimensions shows a marked aggregation of individuals in the best response option (no problems) at diagnosis, which is consistent with the reference norm from Spanish general population [ 15 ]. Worse HRQoL in young breast cancer patients than in young general population can be explained by a more drastic HRQoL impact from diagnosis, related to a more advanced stage at diagnosis and worse prognosis. In fact, among the patients aged under 40 years 50% were diagnosed in stage II or III and 6.6% presented metastasis, while among those aged 40–65 years only 33.6% were diagnosed in these stages and 1.7% presented metastasis. This higher HRQoL impact in young breast cancer patients has been previously described in other studies [ 42 , 43 ].

Women presented worse EORTC QLQ-C30 results at the 2-year follow-up than at diagnosis for both functional and symptom dimensions, except for emotional function, insomnia and appetite loss. Probably these emotional aspects were already impacted just after discovering the cancer diagnosis. These results are consistent with long breast cancer survivors [ 46 ], who continue to experience limitations in a variety of HRQoL dimensions, with specific symptoms that persist or even increase over time and HRQoL restrictions not only associated with aging process but also with cancer and/or its treatment.

The women with breast cancer in our study presented similar HRQoL to the non-metastatic patients of the 2020 updated EORTC reference norms [ 21 ], which are also based on incident breast cancers cases at diagnosis. However, we obtained better results than the German reference values based on breast cancer patients in routine clinical practice without information about stages [ 26 ], and also better than the first EORTC reference norms from 2008 [ 20 ], which included patients at diagnosis (17% stage I-II, 14% stage III-IV, 29% not known stage) but also 41% patients recruited with recurrent/metastatic cancer. Our data at 2 years after diagnosis could not be compared with any of the abovementioned reference norms [ 20 , 21 , 26 ] because they did not report any follow-up.

On one hand, we constructed reference norms from a large sample of women with non-metastatic breast cancer consecutively recruited in ten Spanish hospitals, while the 2020 updated EORTC reference norms [ 21 ] were based on a polled analysis of randomized clinical trials, usually with restrictive inclusion criteria, which could not be representative of the population of women with breast cancer. On the other hand, our sample was composed mainly by participants from the Basque country, where the project was designed. Due to financial restrictions, the number of hospitals was limited in the other regions in order to recruit around a hundred participants in each one. The results of the comparison among regions followed the well-known geographic pattern of North–South inequalities on the socio-economic indicators, and also on HRQoL with EORTC QLQ-C30 summary means of: 87.0 at diagnosis and 85.5 at 2 years after in the Basque country, 87.3 and 83.6 in Catalonia, and 80.1 and 77.5 in Andalusia (p < 0.001). However, no differences on TNM stage of the breast tumor at diagnosis were found among regions, and the proportion of women diagnosed in the breast screening program in our study is consistent with the 49% reported in another Spanish region [ 47 ].

Therefore, as far as we know, this is the first study to provide reference norms based on breast cancer patients at 2 years after diagnosis in the EORTC and EQ–5D–5L, and also the first one specific for Spanish women. Furthermore, it provides values for the EORTC QLQ-BR-23, which was not included in the 2020 updated EORTC reference norms. Although the latter show relevant differences among European regions [ 21 ], no values at country level have been provided in these norms. Our study is one of the first, together with the German one [ 26 ], providing country-specific breast cancer patients-based reference norms.

As mentioned above, reference norms help to interpret results by comparing them to a control group, in this case Spanish women diagnosed with non-metastatic breast cancer. The difference between the observed score and the reference value provides the individual deviation from the population. For example, the EORCT QLQ-C30 global score of 88 at diagnosis and of 83 2 years later from a 60-year-old woman diagnosed in stage II indicated no deviation from the reference norms for women aged 40–65 years and diagnosed in stage II or III (means of 87 and 83), but these scores indicate a slightly worse HRQoL than expected when compared to the mean of 85, obtained by the whole group aged 40–65 years. This example illustrates why stratification by breast cancer stage could be suitable for the interpretation of HRQoL results.

The main limitation of the study is that CaMISS was not designed specifically to provide HRQoL reference norms, and therefore the recruitment strategy was not addressed to obtaining a sample that were equally representative of all Spanish areas, the North being overrepresented. Second, loss to follow-up is problematic in most cohort studies and often leads to bias. Although it is really small in our sample (13%), it is relevant to consider that women not answering HRQoL questionnaires at 2 years after diagnosis presented a higher rate of recurrences and received more aggressive treatments, which is consistent with results from German and Spanish cohorts of breast cancer patients [ 48 , 49 ]. Thus, loss to follow-up could have produced and overestimation of HRQoL at the 2-year follow-up. Third, trained interviewers administered the HRQoL questionnaires mainly by telephone interviews before treatment, while almost all patients self-completed them at home, as recommended, 2 years after diagnosis. However, little difference between both administration methods has been reported [ 50 ]. Finally, no reference norms had been provided for the new EORTC BR-45 [ 51 ], an update of the BR-23 originally developed in 1996.

Having reference norms based on Spanish patients with non-metastatic breast cancer is fundamental, as they will facilitate the assessment of the impact of this disease, monitoring its evolution, comparing the impact of treatments, identifying populations that need special attention, and carrying out comparisons among different countries. These reference norms can be useful to interpret the scores obtained in women with non-metastatic breast cancer, who are the majority in Spain, by comparing them with country-specific reference values for this population.

Supplementary Information

Below is the link to the electronic supplementary material. Supplementary file1 (DOCX 656 kb)

The original online version of this article was revised: Table 4 and supplementary information file were updated.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Change history

3/8/2024

A Correction to this paper has been published: 10.1007/s11136-024-03628-w

Acknowledgements

The authors acknowledge the dedication and support of the entire CAMISS Study Group : IMIM (Hospital del Mar Medical Research Institute), Barcelona: Xavier Castells, Mercè Comas, Laia Domingo, Francesc Macià, Marta Roman, Anabel Romero, and María Sala; Canary Islands Health Service: Teresa Barata, Isabel Diez de la Lastra, and Mariola de la Vega; Corporacio Sanitaria Parc Tauli, Sabadell: Marisa Bare, and Núria Torà; Hospital Santa Caterina, Girona: Joana Ferrer, and Francesc Castanyer; Epidemiology Unit and Girona Cancer Registry: Carmen Carmona; Hospital Galdakao-Usansolo, Vizcaya: Susana García, Maximina Martín, Nerea Gonzalez, Miren Orive, Maria Amparo Valverde, Alberto Saez, Inma Barredo, Manuel de Toro, Josefa Ferreiro, and Jose María Quintana; Canary Islands Foundation for Health Research: Jeanette Pérez, Amado Rivero, and Cristina Valcárcel; Hospital Costa del Sol, University of Málaga: María del Carmen Padilla, Maximino Redondo, Teresa Téllez, and Irene Zarcos; Hospital Universitario Donostia/BioDonostia: Cristina Churruca, Amaia Perales, Javier Recio, Irune Ruiz, Cristina Sarasqueta, and Jose María Urraca; Instituto Oncológico de Guipúzcoa-Onkologikoa: MªJesús Michelena; Hospital Universitario Basurto: Julio Moreno; Hospital Universitario Cruces: Gaizka Mallabiabarrena, Patricia Cobos, and Borja Otero; and Hospital Universitario Txagorritxu: Javier Gorostiaga, and Itsaso Troya. The authors would like to acknowledge the support given by the Basque Government (ref IT1598-22) and by the Ministry of Education (ref PID2020-115738GB-100). Finally, the authors also thank Áurea Martín for her support in English editing, proofreading, and preparing this manuscript for submission.

Author contributions

CM drafted the manuscript, designed the strategy of analysis and performed statistical analysis. MO contributed in preparing the manuscript and in acquisition of data, and MJL contributed in the data base management and in acquisition of data. MS, SGG, CS, MR, AR, XC, and JMQ contributed to the study’s conception and design, and interpretation of data. CM, OG and MF contributed in analyses, interpretation of results, and article composition. OG and MF supervised the whole process of the manuscript, performed a critical revision of it and approved the final version. All authors reviewed the manuscript and approved submission.

Funding

Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study has been funded by the Instituto de Salud Carlos III FEDER (PI21/00026 and PI12/01842), by the Basque Government Health Department (2012111045) and by Generalitat de Catalunya (2017 SGR 452). OG and MF acknowledge CIBER de Epidemiología y Salud Pública (CIBERESP) for partial funding to their research.

Declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Consent to participate

Witten informed consent was obtained from all the eligible patients who accepted to participate in the study.

Ethical approval

The study was approved by the ethics committees of all participating hospitals and conducted according to the principles expressed in the 2000 revision of the Declaration of Helsinki.

References

1. Kohler B Sherman R Howlader N Jemal A Ryerson A Henry K Annual Report to the Nation on the Status of Cancer, 1975–2011, featuring incidence of breast cancer subtypes by race/ethnicity, poverty, and state Journal of National Cancer Institute 2015 107 6 djv048 10.1093/jnci/djv048 PMC4603551 25825511

2. Taira N Shimozuma K Shiroiwa T Ohsumi S Kuroi K Saji S Associations among baseline variables, treatment-related factors and health-related quality of life 2 years after breast cancer surgery Breast Cancer Research and Treatment 2016 128 3 735 747 10.1007/s10549-011-1631-y 21681445

3. Chu W Dialla PO Roignot P Bone-Lepinoy MC Poillot ML Coutant C Determinants of quality of life among long-term breast cancer survivors Quality of Life Research 2016 25 8 1981 1990 10.1007/s11136-016-1248-z 26914102

4. Smyth EN Shen W Bowman L Peterson P John W Melemed A Patient-reported pain and other quality of life domains as prognostic factors for survival in a phase III clinical trial of patients with advanced breast cancer Health and Quality of Life Outcomes 2016 14 52 1000 10.1186/s12955-016-0449-z PMC4807577 27016084

5. Rautalin M Färkkilä N Sintonen H Saarto T Taari K Jahkola T Health-related quality of life in different states of breast cancer—Comparing different instruments Acta Oncologica 2017 57 5 622 628 10.1080/0284186X.2017.1400683 29140139

6. Ho PJ Gernaat SAM Hartman M Verkooijen HM Health-related quality of life in Asian patients with breast cancer: A systematic review British Medical Journal Open 2018 8 4 e020512 10.1136/bmjopen-2017-020512 PMC5914715 29678980

7. Fitzpatrick R Fletcher A Gore S Jones D Spiegelhalter D Cox D Quality of life measures in health care. I: Applications and issues in assessment British Medical Journal 1992 305 6861 1074 1077 10.1136/bmj.305.6861.1074 1467690 PMC1883623

8. Delgado-Sanz M García-Mendizábal M Pollán M Forjaz M López-Abente G Aragonés N Heath-related quality of life in Spanish breast cancer patients: A systematic review Health and Quality Life of Outcomes 2011 9 3 1000 10.1186/1477-7525-9-3 PMC3031190 21235770

9. Mishoe S Maclean J Assessment of health-related quality of life Respiratory Care 2001 46 11 1236 1257 11679145

10. Waldmann A Schubert D Katalinic A Normative data of the EORTC QLQ-C30 for the german population: A population-based survey PLoS ONE 2013 8 9 e74149 10.1371/journal.pone.0074149 24058523 PMC3769241

11. Mols F Husson O Oudejans M Vlooswijk C Horevoorts N van de Poll-Franse L Reference data of the EORTC QLQ-C30 questionnaire: Five consecutive annual assessments of approximately 2000 representative Dutch men and women Acta Oncologica 2018 57 10 1381 1391 10.1080/0284186X.2018.1481293 29912607

12. Sprangers MA Groenvold M Arraras JI Franklin J te Velde A Muller M The European Organization for Research and Treatment of Cancer breast cancer-specific quality-of-life questionnaire module: First results from a three-country field study Journal of Clinical Oncology 1996 14 10 2756 2768 10.1200/JCO.1996.14.10.2756 8874337

13. Garcia-Gordillo M Adsuar J Olivares P Normative values of EQ-5D-5L: In a Spanish representative population sample from Spanish Health Survey, 2011 Quality of Life Research 2016 25 5 1313 1321 10.1007/s11136-015-1164-7 26482825

14. Fayers P Interpreting quality of life data: Population-based reference data for the EORTC QLQ-C30 European Journal of Cancer 2001 37 11 1331 1334 10.1016/S0959-8049(01)00127-7 11435060

15. Hernandez G Garin O Pardo Y Vilagut G Pont À Suárez M Validity of the EQ–5D–5L and reference norms for the Spanish population Quality of Life Research 2018 27 9 2337 2348 10.1007/s11136-018-1877-5 29767329

16. Kim TH Jo M-W Lee S-I Kim SH Chung SM Psychometric properties of the EQ-5D-5L in the general population of South Korea Quality of Life Research 2013 22 2245 2253 10.1007/s11136-012-0331-3 23224560

17. Hinz A Kohlmann T Stöbel-Richter Y Zenger M Brähler E The quality of life questionnaire EQ-5D-5L: Psychometric properties and normative values for the general German population Quality of Life Research 2014 23 2 443 447 10.1007/s11136-013-0498-2 23921597

18. Golicki D Niewada M EQ-5D-5L Polish population norms Archives of Medical Science 2017 13 1 191 200 10.5114/aoms.2015.52126 28144271 PMC5206353

19. McCaffrey N Kaambwa B Currow DC Ratcliffe J Health-related quality of life measured using the EQ-5D-5L: South Australian population norms Health and Quality of Life Outcomes 2016 14 1 133 10.1186/s12955-016-0537-0 27644755 PMC5028927

20. Scott, N. W., Fayers, P. M., Aaronson, N. K., Bottomley, A., De Graeff, A., & Groenvold, M. EORTC QLQ-C30 Reference Values [Internet]. 2008. https://www.eortc.org/app/uploads/sites/2/2018/02/reference_values_manual2008.pdf . Accessed 21 Sep 2021N

21. Mierzynska J Taye M Pe M Coens C Martinelli F Pogoda K Reference values for the EORTC QLQ-C30 in early and metastatic breast cancer European Journal of Cancer 2020 125 69 82 10.1016/j.ejca.2019.10.031 31838407

22. Michelson H Bolund C Nilsson B Brandberg Y Health-related quality of life measured by the EORTC QLQ-C30: Reference values from a large sample of the Swedish population Acta Oncology (Madr). 2000 39 4 477 484 10.1080/028418600750013384 11041109

23. Schwarz R Hinz A Reference data for the quality of life questionnaire EORTC QLQ-C30 in the general German population European Journal of Cancer 2001 37 11 1345 1351 10.1016/S0959-8049(00)00447-0 11435063

24. Juul T Petersen MA Holzner B Laurberg S Christensen P Grønvold M Danish population-based reference data for the EORTC QLQ-C30: Associations with gender, age and morbidity Quality of Life Research 2014 23 8 2183 2193 10.1007/s11136-014-0675-y 24676897

25. Arraras JI Nolte S Liegl G Rose M Manterola A Illarramendi JJ General Spanish population normative data analysis for the EORTC QLQ-C30 by sex, age, and health condition Health and Quality of Life Outcomes 2021 19 208 10.1186/s12955-021-01820-x 34461909 PMC8404330

26. Karsten MM Roehle R Albers S Pross T Hage AM Weiler K Real-world reference scores for EORTC QLQ-C30 and EORTC QLQ-BR23 in early breast cancer patients European Journal of Cancer 2022 163 128 139 10.1016/j.ejca.2021.12.020 35066338

27. García-Gutierrez S Orive M Sarasqueta C Legarreta M Gonzalez N Redondo M Health services research in patients with breast cancer (CAMISS-prospective): Study protocol for an observational prospective study BMC Cancer 2018 18 1 54 10.1186/s12885-017-3926-9 29310641 PMC5759866

28. Charlson ME Pompei P Ales KL MacKenzie CR A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation Journal of Chronic Diseases 1987 40 5 373 383 10.1016/0021-9681(87)90171-8 3558716

29. Domingo-Salvany A Bacigalupe A Carrasco JM Espelt A Ferrando J Borrell C Propuestas de clase social neoweberiana y neomarxista a partir de la Clasificación Nacional de Ocupaciones 2011 [Proposals for social class classification based on the Spanish National Classification of Occupations 2011 using neo-Weberian and neo-Marxist Gaceta Sanitaria 2013 27 3 263 272 10.1016/j.gaceta.2012.12.009 23394892

30. Calderon C Ferrando PJ Lorenzo-Seva U Ferreira E Lee EM Oporto-Alonso M Psychometric properties of the Spanish version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) Quality of Life Research 2021 31 6 1859 1869 10.1007/s11136-021-03068-w 34928470 PMC9098585

31. Arraras J Arias F Tejedor M Pruja E Marcos M Martínez E The EORTC QLQ-C30 (version 3.0) Quality of Life questionnaire: Validation study for Spain with head and neck cancer patients Psycho-Oncology 2002 11 3 249 256 10.1002/pon.555 12112486

32. Herdman M Gudex C Lloyd A Janssen M Kind P Parkin D Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L) Quality of Life Research 2011 20 10 1727 1736 10.1007/s11136-011-9903-x 21479777 PMC3220807

33. Aaronson NK Ahmedzai S Bergman B Bullinger M Cull A Duez NJ The European Organization for Research and Treatment of Cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology Journal of the National Cancer Institute 1993 85 5 365 376 10.1093/jnci/85.5.365 8433390

34. Giesinger JM Kieffer JM Fayers PM Groenvold M Petersen MA Scott NW Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust Journal of Clinical Epidemiology 2016 69 79 88 10.1016/j.jclinepi.2015.08.007 26327487

35. Ramos-Goñi JM Craig BM Oppe M Ramallo-Fariña Y Pinto-Prades JL Luo N Handling data quality issues to estimate the Spanish EQ-5D-5L value set using a hybrid interval regression approach Value Health 2018 21 5 596 604 10.1016/j.jval.2017.10.023 29753358

36. Oppe M Devlin NJ Van Hout B Krabbe PFM De Charro F A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol Value Health 2014 17 4 445 453 10.1016/j.jval.2014.04.002 24969006

37. Stephane Champely. pwr: Basic functions for power analysis. R package version 1.3–0 [Internet]. 2020. Retrieved from https://cran.r-project.org/package=pwr

38. Cunillera O Encyclopedia of quality of life and well-being research 2014 Springer 6671 6676

39. Burström K Johannesson M Diderichsen F Swedish population health-related quality of life results using the EQ-5D Quality of Life Research 2001 10 7 621 635 10.1023/A:1013171831202 11822795

40. Rowen D Young T Brazier J Gaugris S Comparison of generic, condition-specific, and mapped health state utility values for multiple myeloma cancer Value Health 2012 15 8 1059 1068 10.1016/j.jval.2012.08.2201 23244808

41. van Dongen-Leunis A Redekop WK Uyl-de Groot CA Which questionnaire should be used to measure quality-of-life utilities in patients with acute leukemia? An evaluation of the validity and interpretability of the EQ-5D-5L and preference-based questionnaires derived from the EORTC QLQ-C30 Value Health 2016 19 6 834 843 10.1016/j.jval.2016.05.008 27712712

42. Crott R Briggs A Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences The European Journal of Health Economics 2010 11 4 427 434 10.1007/s10198-010-0233-7 20473703

43. Kim EJ Ko SK Kang HY Mapping the cancer-specific EORTC QLQ-C30 and EORTC QLQ-BR23 to the generic EQ-5D in metastatic breast cancer patients Quality of Life Research 2012 21 7 1193 1203 10.1007/s11136-011-0037-y 22012023

44. Gray LA Hernandez Alava M Wailoo AJ Mapping the EORTC QLQ-C30 to EQ-5D-3L in patients with breast cancer BMC Cancer 2021 21 1 1237 10.1186/s12885-021-08964-5 34794404 PMC8600775

45. Tsui TCO Trudeau M Mitsakakis N Torres S Bremner KE Kim D Developing the Breast Utility Instrument, a preference-based instrument to measure health-related quality of life in women with breast cancer: Confirmatory factor analysis of the EORTC QLQ-C30 and BR45 to establish dimensions PLoS ONE 2022 17 2 e0262635 10.1371/journal.pone.0262635 35120148 PMC8815914

46. Koch L Jansen L Herrmann A Stegmaier C Holleczek B Singer S Quality of life in long-term breast cancer survivors-a 10-year longitudinal population-based study Acta Oncology (Madr). 2013 52 6 1119 1128 10.3109/0284186X.2013.774461 23514583

47. Natal C Suárez MT Serrano S Díaz C González C Menéndez P Evaluación de resultados en el programa de detección precoz del cáncer de mama del Principado de Asturias Revista de Calidad Asistencial 2012 27 1 38 43 10.1016/j.cali.2011.07.003 22024048

48. Maurer T Thöne K Obi N Jung AY Behrens S Becher H Health-related quality of life in a cohort of breast cancer survivors over more than 10 years post-diagnosis and in comparison to a control cohort Cancers (Basel) 2021 13 1854 10.3390/cancers13081854 33924513 PMC8069882

49. Moro-Valdezate D Peiró S Buch-Villa E Caballero-Gárate A Morales-Monsalve MD Martínez-Agulló Á Evolution of health-related quality of life in breast cancer patients during the first year of follow-up Journal of Breast Cancer 2013 16 1 104 111 10.4048/jbc.2013.16.1.104 23593090 PMC3625756

50. Puhan MA Ahuja A Van Natta ML Ackatz LE Meinert C Interviewer versus self-administered health-related quality of life questionnaires—Does it matter? Health and Quality of Life Outcomes 2011 9 30 1000 10.1186/1477-7525-9-30 PMC3100232 21554737

51. Bjelic-Radisic V Cardoso F Cameron D Brain E Kuljanic K da Costa RA An international update of the EORTC questionnaire for assessing quality of life in breast cancer patients: EORTC QLQ-BR45 Annals of Oncology 2020 31 2 283 288 10.1016/j.annonc.2019.10.027 31959345