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Open Access 11-01-2023

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

Auteurs: Carme Miret, Miren Orive, Maria Sala, Susana García-Gutiérrez, Cristina Sarasqueta, Maria Jose Legarreta, Maximino Redondo, Amado Rivero, Xavier Castells, José M. Quintana, Olatz Garin, Montse Ferrer, the REDISSEC-CaMISS Group

Gepubliceerd in: Quality of Life Research | Uitgave 4/2023

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Abstract

Purpose

To obtain reference norms of EORTC QLQ-C30, EORTC QLQ-BR23, and 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

Multicentric prospective cohort study including consecutive women aged ≥ 18 years with a diagnosis of incident non-metastatic breast cancer from April 2013 to May 2015. Health-related quality of life (HRQoL) questionnaires were administered between diagnosis and beginning the therapy, and 2 years after. HRQoL differences according to age, comorbidity and stage were tested with ANOVA or Chi Square test and multivariate linear regression models.

Results

1276 patients were included, with a mean age of 58 years. Multivariate models of EORTC QLQ-C30 summary score and EQ-5D-5L index at diagnosis and at 2-year follow-up show the independent association of comorbidity and tumor stage with HRQoL. The standardized multivariate regression coefficient of EORTC QLQ-C30 summary score was lower (poorer HRQoL) for women with stage II and III than for those with stage 0 at diagnosis (− 0.11 and − 0.07, p < 0.05) and follow-up (− 0.15 and − 0.10, p < 0.01). The EQ-5D-5L index indicated poorer HRQoL for women with Charlson comorbidity index ≥ 2 than comorbidity 0 both at diagnosis (− 0.13, p < 0.001) and follow-up (− 0.18, p < 0.001). Therefore, we provided the reference norms at diagnosis and at the 2-year follow-up, stratified by age, comorbidity index, and tumor stage.

Conclusion

These HRQoL reference norms can be useful to interpret the scores of women with non-metastatic breast cancer, comparing them with country-specific reference values for this population.
Opmerkingen

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1007/​s11136-022-03327-4.
The original online version of this article was revised: Table 4 and supplementary information file were updated.
A correction to this article is available online at https://​doi.​org/​10.​1007/​s11136-024-03628-w.

Publisher's Note

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

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 [36].
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 [1519], 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 [2225], 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.
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 6th 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.
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 [1519, 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 [4244]: 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.

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.

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.
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.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​.

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Literatuur
1.
go back to reference Kohler, B., Sherman, R., Howlader, N., Jemal, A., Ryerson, A., Henry, K., Boscoe, F., Lake, A., Noone, A., Henley, S., Eheman, C., Anderson, R., & Penberthy, L. (2015). 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, 107(6), djv048.CrossRef Kohler, B., Sherman, R., Howlader, N., Jemal, A., Ryerson, A., Henry, K., Boscoe, F., Lake, A., Noone, A., Henley, S., Eheman, C., Anderson, R., & Penberthy, L. (2015). 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, 107(6), djv048.CrossRef
2.
go back to reference Taira, N., Shimozuma, K., Shiroiwa, T., Ohsumi, S., Kuroi, K., Saji, S., Saito, M., Iha, S., Watanabe, T., & Katsumata, N. (2016). Associations among baseline variables, treatment-related factors and health-related quality of life 2 years after breast cancer surgery. Breast Cancer Research and Treatment, 128(3), 735–747.CrossRef Taira, N., Shimozuma, K., Shiroiwa, T., Ohsumi, S., Kuroi, K., Saji, S., Saito, M., Iha, S., Watanabe, T., & Katsumata, N. (2016). Associations among baseline variables, treatment-related factors and health-related quality of life 2 years after breast cancer surgery. Breast Cancer Research and Treatment, 128(3), 735–747.CrossRef
3.
go back to reference Chu, W., Dialla, P. O., Roignot, P., Bone-Lepinoy, M. C., Poillot, M. L., Coutant, C., Arveux, P., & Dabakuyo-Yonli, TS. (2016). Determinants of quality of life among long-term breast cancer survivors. Quality of Life Research, 25(8), 1981–1990.PubMedCrossRef Chu, W., Dialla, P. O., Roignot, P., Bone-Lepinoy, M. C., Poillot, M. L., Coutant, C., Arveux, P., & Dabakuyo-Yonli, TS. (2016). Determinants of quality of life among long-term breast cancer survivors. Quality of Life Research, 25(8), 1981–1990.PubMedCrossRef
4.
go back to reference Smyth, E. N., Shen, W., Bowman, L., Peterson, P., John, W., Melemed, A., & Liepa, AM. (2016). 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, 14(52). Smyth, E. N., Shen, W., Bowman, L., Peterson, P., John, W., Melemed, A., & Liepa, AM. (2016). 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, 14(52).
5.
go back to reference Rautalin, M., Färkkilä, N., Sintonen, H., Saarto, T., Taari, K., Jahkola, T., & Roine, RP. (2017). Health-related quality of life in different states of breast cancer—Comparing different instruments. Acta Oncologica, 57(5), 622–628.PubMedCrossRef Rautalin, M., Färkkilä, N., Sintonen, H., Saarto, T., Taari, K., Jahkola, T., & Roine, RP. (2017). Health-related quality of life in different states of breast cancer—Comparing different instruments. Acta Oncologica, 57(5), 622–628.PubMedCrossRef
6.
go back to reference Ho, P. J., Gernaat, S. A. M., Hartman, M., & Verkooijen, H. M. (2018). Health-related quality of life in Asian patients with breast cancer: A systematic review. British Medical Journal Open, 8(4), e020512. Ho, P. J., Gernaat, S. A. M., Hartman, M., & Verkooijen, H. M. (2018). Health-related quality of life in Asian patients with breast cancer: A systematic review. British Medical Journal Open, 8(4), e020512.
7.
go back to reference Fitzpatrick, R., Fletcher, A., Gore, S., Jones, D., Spiegelhalter, D., & Cox, D. (1992). Quality of life measures in health care. I: Applications and issues in assessment. British Medical Journal, 305(6861), 1074–1077.PubMedPubMedCentralCrossRef Fitzpatrick, R., Fletcher, A., Gore, S., Jones, D., Spiegelhalter, D., & Cox, D. (1992). Quality of life measures in health care. I: Applications and issues in assessment. British Medical Journal, 305(6861), 1074–1077.PubMedPubMedCentralCrossRef
8.
go back to reference Delgado-Sanz, M., García-Mendizábal, M., Pollán, M., Forjaz, M., López-Abente, G., Aragonés, N., & Pérez-Gómez, B. (2011). Heath-related quality of life in Spanish breast cancer patients: A systematic review. Health and Quality Life of Outcomes, 9(3). Delgado-Sanz, M., García-Mendizábal, M., Pollán, M., Forjaz, M., López-Abente, G., Aragonés, N., & Pérez-Gómez, B. (2011). Heath-related quality of life in Spanish breast cancer patients: A systematic review. Health and Quality Life of Outcomes, 9(3).
9.
go back to reference Mishoe, S., & Maclean, J. (2001). Assessment of health-related quality of life. Respiratory Care, 46(11), 1236–1257.PubMed Mishoe, S., & Maclean, J. (2001). Assessment of health-related quality of life. Respiratory Care, 46(11), 1236–1257.PubMed
10.
go back to reference Waldmann, A., Schubert, D., & Katalinic, A. (2013). Normative data of the EORTC QLQ-C30 for the german population: A population-based survey. PLoS ONE, 8(9), e74149.ADSPubMedPubMedCentralCrossRef Waldmann, A., Schubert, D., & Katalinic, A. (2013). Normative data of the EORTC QLQ-C30 for the german population: A population-based survey. PLoS ONE, 8(9), e74149.ADSPubMedPubMedCentralCrossRef
11.
go back to reference Mols, F., Husson, O., Oudejans, M., Vlooswijk, C., Horevoorts, N., & van de Poll-Franse, L. (2018). Reference data of the EORTC QLQ-C30 questionnaire: Five consecutive annual assessments of approximately 2000 representative Dutch men and women. Acta Oncologica, 57(10), 1381–1391.PubMedCrossRef Mols, F., Husson, O., Oudejans, M., Vlooswijk, C., Horevoorts, N., & van de Poll-Franse, L. (2018). Reference data of the EORTC QLQ-C30 questionnaire: Five consecutive annual assessments of approximately 2000 representative Dutch men and women. Acta Oncologica, 57(10), 1381–1391.PubMedCrossRef
12.
go back to reference Sprangers, M. A., Groenvold, M., Arraras, J. I., Franklin, J., te Velde, A., Muller, M., Franzini, L., Williams, A., de Haes, H.C., Hopwood, P., Cull, A., & Aaronson, N.K. (1996). 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, 14(10), 2756–2768.PubMedCrossRef Sprangers, M. A., Groenvold, M., Arraras, J. I., Franklin, J., te Velde, A., Muller, M., Franzini, L., Williams, A., de Haes, H.C., Hopwood, P., Cull, A., & Aaronson, N.K. (1996). 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, 14(10), 2756–2768.PubMedCrossRef
13.
go back to reference Garcia-Gordillo, M., Adsuar, J., & Olivares, P. (2016). Normative values of EQ-5D-5L: In a Spanish representative population sample from Spanish Health Survey, 2011. Quality of Life Research, 25(5), 1313–1321.PubMedCrossRef Garcia-Gordillo, M., Adsuar, J., & Olivares, P. (2016). Normative values of EQ-5D-5L: In a Spanish representative population sample from Spanish Health Survey, 2011. Quality of Life Research, 25(5), 1313–1321.PubMedCrossRef
14.
go back to reference Fayers, P. (2001). Interpreting quality of life data: Population-based reference data for the EORTC QLQ-C30. European Journal of Cancer, 37(11), 1331–1334.PubMedCrossRef Fayers, P. (2001). Interpreting quality of life data: Population-based reference data for the EORTC QLQ-C30. European Journal of Cancer, 37(11), 1331–1334.PubMedCrossRef
15.
go back to reference Hernandez, G., Garin, O., Pardo, Y., Vilagut, G., Pont, À., Suárez, M., Neira, M., Rajmil, L., Gorostiza, I., Ramallo-Fariña, Y., Cabases, J., Alonso, J., & Ferrer, M. (2018). Validity of the EQ–5D–5L and reference norms for the Spanish population. Quality of Life Research, 27(9), 2337–2348.PubMedCrossRef Hernandez, G., Garin, O., Pardo, Y., Vilagut, G., Pont, À., Suárez, M., Neira, M., Rajmil, L., Gorostiza, I., Ramallo-Fariña, Y., Cabases, J., Alonso, J., & Ferrer, M. (2018). Validity of the EQ–5D–5L and reference norms for the Spanish population. Quality of Life Research, 27(9), 2337–2348.PubMedCrossRef
16.
go back to reference Kim, T. H., Jo, M.-W., Lee, S.-I., Kim, S. H., & Chung, S. M. (2013). Psychometric properties of the EQ-5D-5L in the general population of South Korea. Quality of Life Research, 22, 2245–2253.PubMedCrossRef Kim, T. H., Jo, M.-W., Lee, S.-I., Kim, S. H., & Chung, S. M. (2013). Psychometric properties of the EQ-5D-5L in the general population of South Korea. Quality of Life Research, 22, 2245–2253.PubMedCrossRef
17.
go back to reference Hinz, A., Kohlmann, T., Stöbel-Richter, Y., Zenger, M., & Brähler, E. (2014). The quality of life questionnaire EQ-5D-5L: Psychometric properties and normative values for the general German population. Quality of Life Research, 23(2), 443–447.PubMedCrossRef Hinz, A., Kohlmann, T., Stöbel-Richter, Y., Zenger, M., & Brähler, E. (2014). The quality of life questionnaire EQ-5D-5L: Psychometric properties and normative values for the general German population. Quality of Life Research, 23(2), 443–447.PubMedCrossRef
18.
go back to reference Golicki, D., & Niewada, M. (2017). EQ-5D-5L Polish population norms. Archives of Medical Science, 13(1), 191–200.PubMedCrossRef Golicki, D., & Niewada, M. (2017). EQ-5D-5L Polish population norms. Archives of Medical Science, 13(1), 191–200.PubMedCrossRef
19.
go back to reference McCaffrey, N., Kaambwa, B., Currow, D. C., & Ratcliffe, J. (2016). Health-related quality of life measured using the EQ-5D-5L: South Australian population norms. Health and Quality of Life Outcomes, 14(1), 133.PubMedPubMedCentralCrossRef McCaffrey, N., Kaambwa, B., Currow, D. C., & Ratcliffe, J. (2016). Health-related quality of life measured using the EQ-5D-5L: South Australian population norms. Health and Quality of Life Outcomes, 14(1), 133.PubMedPubMedCentralCrossRef
21.
go back to reference Mierzynska, J., Taye, M., Pe, M., Coens, C., Martinelli, F., Pogoda, K., Velikova, G., Bjelic-Radisic, V., Cardoso, F., Brain, E., Ignatiadis, M., Piccart, M., Van Tienhoven, G., Mansel, R., Wildiers, H., & Bottomley, A.. (2020). Reference values for the EORTC QLQ-C30 in early and metastatic breast cancer. European Journal of Cancer, 125, 69–82.PubMedCrossRef Mierzynska, J., Taye, M., Pe, M., Coens, C., Martinelli, F., Pogoda, K., Velikova, G., Bjelic-Radisic, V., Cardoso, F., Brain, E., Ignatiadis, M., Piccart, M., Van Tienhoven, G., Mansel, R., Wildiers, H., & Bottomley, A.. (2020). Reference values for the EORTC QLQ-C30 in early and metastatic breast cancer. European Journal of Cancer, 125, 69–82.PubMedCrossRef
22.
go back to reference Michelson, H., Bolund, C., Nilsson, B., & Brandberg, Y. (2000). Health-related quality of life measured by the EORTC QLQ-C30: Reference values from a large sample of the Swedish population. Acta Oncology (Madr)., 39(4), 477–484.CrossRef Michelson, H., Bolund, C., Nilsson, B., & Brandberg, Y. (2000). Health-related quality of life measured by the EORTC QLQ-C30: Reference values from a large sample of the Swedish population. Acta Oncology (Madr)., 39(4), 477–484.CrossRef
23.
go back to reference Schwarz, R., & Hinz, A. (2001). Reference data for the quality of life questionnaire EORTC QLQ-C30 in the general German population. European Journal of Cancer, 37(11), 1345–1351.PubMedCrossRef Schwarz, R., & Hinz, A. (2001). Reference data for the quality of life questionnaire EORTC QLQ-C30 in the general German population. European Journal of Cancer, 37(11), 1345–1351.PubMedCrossRef
24.
go back to reference Juul, T., Petersen, M. A., Holzner, B., Laurberg, S., Christensen, P., & Grønvold, M. (2014). Danish population-based reference data for the EORTC QLQ-C30: Associations with gender, age and morbidity. Quality of Life Research, 23(8), 2183–2193.PubMedCrossRef Juul, T., Petersen, M. A., Holzner, B., Laurberg, S., Christensen, P., & Grønvold, M. (2014). Danish population-based reference data for the EORTC QLQ-C30: Associations with gender, age and morbidity. Quality of Life Research, 23(8), 2183–2193.PubMedCrossRef
25.
go back to reference Arraras, J. I., Nolte, S., Liegl, G., Rose, M., Manterola, A., Illarramendi, J. J., Zarandona, U., Rico, M., Teiejria, L., Asin, G., Hernandez, I., Barrado, M., Vera, R., Efficace, F., & Giesinger, J.M. (2021). General Spanish population normative data analysis for the EORTC QLQ-C30 by sex, age, and health condition. Health and Quality of Life Outcomes, 19, 208.PubMedPubMedCentralCrossRef Arraras, J. I., Nolte, S., Liegl, G., Rose, M., Manterola, A., Illarramendi, J. J., Zarandona, U., Rico, M., Teiejria, L., Asin, G., Hernandez, I., Barrado, M., Vera, R., Efficace, F., & Giesinger, J.M. (2021). General Spanish population normative data analysis for the EORTC QLQ-C30 by sex, age, and health condition. Health and Quality of Life Outcomes, 19, 208.PubMedPubMedCentralCrossRef
26.
go back to reference Karsten, M. M., Roehle, R., Albers, S., Pross, T., Hage, A. M., Weiler, K., Fischer, F., Rose, M., Kühn, F., & Blohmer, J.U. (2022). Real-world reference scores for EORTC QLQ-C30 and EORTC QLQ-BR23 in early breast cancer patients. European Journal of Cancer, 163, 128–139.PubMedCrossRef Karsten, M. M., Roehle, R., Albers, S., Pross, T., Hage, A. M., Weiler, K., Fischer, F., Rose, M., Kühn, F., & Blohmer, J.U. (2022). Real-world reference scores for EORTC QLQ-C30 and EORTC QLQ-BR23 in early breast cancer patients. European Journal of Cancer, 163, 128–139.PubMedCrossRef
27.
go back to reference García-Gutierrez, S., Orive, M., Sarasqueta, C., Legarreta, M., Gonzalez, N., Redondo, M., Rivero, A., Serrano-Aguilar, P., Castells, X., Quintana, J., & Sala, M. (2018). Health services research in patients with breast cancer (CAMISS-prospective): Study protocol for an observational prospective study. BMC Cancer, 18(1), 54.PubMedPubMedCentralCrossRef García-Gutierrez, S., Orive, M., Sarasqueta, C., Legarreta, M., Gonzalez, N., Redondo, M., Rivero, A., Serrano-Aguilar, P., Castells, X., Quintana, J., & Sala, M. (2018). Health services research in patients with breast cancer (CAMISS-prospective): Study protocol for an observational prospective study. BMC Cancer, 18(1), 54.PubMedPubMedCentralCrossRef
28.
go back to reference Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases, 40(5), 373–383.PubMedCrossRef Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases, 40(5), 373–383.PubMedCrossRef
29.
go back to reference Domingo-Salvany, A., Bacigalupe, A., Carrasco, J. M., Espelt, A., Ferrando, J., & Borrell, C. (2013). 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, 27(3), 263–272.PubMedCrossRef Domingo-Salvany, A., Bacigalupe, A., Carrasco, J. M., Espelt, A., Ferrando, J., & Borrell, C. (2013). 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, 27(3), 263–272.PubMedCrossRef
30.
go back to reference Calderon, C., Ferrando, P. J., Lorenzo-Seva, U., Ferreira, E., Lee, E. M., Oporto-Alonso, M., Obispo-Portero, B.M., Mihic-Góngora, L., Rodríguez-González, A., & Jiménez-Fonseca, P. (2021). 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, 31(6), 1859–1869.PubMedPubMedCentralCrossRef Calderon, C., Ferrando, P. J., Lorenzo-Seva, U., Ferreira, E., Lee, E. M., Oporto-Alonso, M., Obispo-Portero, B.M., Mihic-Góngora, L., Rodríguez-González, A., & Jiménez-Fonseca, P. (2021). 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, 31(6), 1859–1869.PubMedPubMedCentralCrossRef
31.
go back to reference Arraras, J., Arias, F., Tejedor, M., Pruja, E., Marcos, M., Martínez, E., & Valerdi, J. (2002). The EORTC QLQ-C30 (version 3.0) Quality of Life questionnaire: Validation study for Spain with head and neck cancer patients. Psycho-Oncology, 11(3), 249–256.PubMedCrossRef Arraras, J., Arias, F., Tejedor, M., Pruja, E., Marcos, M., Martínez, E., & Valerdi, J. (2002). The EORTC QLQ-C30 (version 3.0) Quality of Life questionnaire: Validation study for Spain with head and neck cancer patients. Psycho-Oncology, 11(3), 249–256.PubMedCrossRef
32.
go back to reference Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., Bonsel, G., & Badia, X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.PubMedPubMedCentralCrossRef Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., Bonsel, G., & Badia, X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.PubMedPubMedCentralCrossRef
33.
go back to reference Aaronson, N. K., Ahmedzai, S., Bergman, B., Bullinger, M., Cull, A., Duez, N. J., Filiberti, A., Flechtner, H., Fleishman, S.B., Haes, J.C.J.M. de, Kaasa, S., Klee, M., Osoba, D., Razavi, D., Rofe, P.B., Schraub, S., Sneeuw, K., Sullivan, M., & Takeda, F. (1993). 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, 85(5), 365–376.PubMedCrossRef Aaronson, N. K., Ahmedzai, S., Bergman, B., Bullinger, M., Cull, A., Duez, N. J., Filiberti, A., Flechtner, H., Fleishman, S.B., Haes, J.C.J.M. de, Kaasa, S., Klee, M., Osoba, D., Razavi, D., Rofe, P.B., Schraub, S., Sneeuw, K., Sullivan, M., & Takeda, F. (1993). 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, 85(5), 365–376.PubMedCrossRef
34.
go back to reference Giesinger, J. M., Kieffer, J. M., Fayers, P. M., Groenvold, M., Petersen, M. A., Scott, N. W., Sprangers, M.A.G., Velikova, G., & Aaronson, N.K. (2016). Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust. Journal of Clinical Epidemiology, 69, 79–88.PubMedCrossRef Giesinger, J. M., Kieffer, J. M., Fayers, P. M., Groenvold, M., Petersen, M. A., Scott, N. W., Sprangers, M.A.G., Velikova, G., & Aaronson, N.K. (2016). Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust. Journal of Clinical Epidemiology, 69, 79–88.PubMedCrossRef
35.
go back to reference Ramos-Goñi, J. M., Craig, B. M., Oppe, M., Ramallo-Fariña, Y., Pinto-Prades, J. L., Luo, N., & Rivero-Arias, O. (2018). Handling data quality issues to estimate the Spanish EQ-5D-5L value set using a hybrid interval regression approach. Value Health, 21(5), 596–604.PubMedCrossRef Ramos-Goñi, J. M., Craig, B. M., Oppe, M., Ramallo-Fariña, Y., Pinto-Prades, J. L., Luo, N., & Rivero-Arias, O. (2018). Handling data quality issues to estimate the Spanish EQ-5D-5L value set using a hybrid interval regression approach. Value Health, 21(5), 596–604.PubMedCrossRef
36.
go back to reference Oppe, M., Devlin, N. J., Van Hout, B., Krabbe, P. F. M., & De Charro, F. (2014). A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol. Value Health, 17(4), 445–453.PubMedCrossRef Oppe, M., Devlin, N. J., Van Hout, B., Krabbe, P. F. M., & De Charro, F. (2014). A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol. Value Health, 17(4), 445–453.PubMedCrossRef
38.
go back to reference Cunillera, O. (2014). Encyclopedia of quality of life and well-being research (pp. 6671–6676). Springer.CrossRef Cunillera, O. (2014). Encyclopedia of quality of life and well-being research (pp. 6671–6676). Springer.CrossRef
39.
go back to reference Burström, K., Johannesson, M., & Diderichsen, F. (2001). Swedish population health-related quality of life results using the EQ-5D. Quality of Life Research, 10(7), 621–635.PubMedCrossRef Burström, K., Johannesson, M., & Diderichsen, F. (2001). Swedish population health-related quality of life results using the EQ-5D. Quality of Life Research, 10(7), 621–635.PubMedCrossRef
40.
go back to reference Rowen, D., Young, T., Brazier, J., & Gaugris, S. (2012). Comparison of generic, condition-specific, and mapped health state utility values for multiple myeloma cancer. Value Health, 15(8), 1059–1068.PubMedCrossRef Rowen, D., Young, T., Brazier, J., & Gaugris, S. (2012). Comparison of generic, condition-specific, and mapped health state utility values for multiple myeloma cancer. Value Health, 15(8), 1059–1068.PubMedCrossRef
41.
go back to reference van Dongen-Leunis, A., Redekop, W. K., & Uyl-de Groot, C. A. (2016). 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, 19(6), 834–843.PubMedCrossRef van Dongen-Leunis, A., Redekop, W. K., & Uyl-de Groot, C. A. (2016). 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, 19(6), 834–843.PubMedCrossRef
42.
go back to reference Crott, R., & Briggs, A. (2010). Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences. The European Journal of Health Economics, 11(4), 427–434.PubMedCrossRef Crott, R., & Briggs, A. (2010). Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences. The European Journal of Health Economics, 11(4), 427–434.PubMedCrossRef
43.
go back to reference Kim, E. J., Ko, S. K., & Kang, H. Y. (2012). 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, 21(7), 1193–1203.PubMedCrossRef Kim, E. J., Ko, S. K., & Kang, H. Y. (2012). 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, 21(7), 1193–1203.PubMedCrossRef
44.
go back to reference Gray, L. A., Hernandez Alava, M., & Wailoo, A. J. (2021). Mapping the EORTC QLQ-C30 to EQ-5D-3L in patients with breast cancer. BMC Cancer, 21(1), 1237.PubMedPubMedCentralCrossRef Gray, L. A., Hernandez Alava, M., & Wailoo, A. J. (2021). Mapping the EORTC QLQ-C30 to EQ-5D-3L in patients with breast cancer. BMC Cancer, 21(1), 1237.PubMedPubMedCentralCrossRef
45.
go back to reference Tsui, T. C. O., Trudeau, M., Mitsakakis, N., Torres, S., Bremner, K. E., Kim, D., Davis, A.M., & Krahn, M.D. (2022). 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, 17(2), e0262635.PubMedPubMedCentralCrossRef Tsui, T. C. O., Trudeau, M., Mitsakakis, N., Torres, S., Bremner, K. E., Kim, D., Davis, A.M., & Krahn, M.D. (2022). 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, 17(2), e0262635.PubMedPubMedCentralCrossRef
46.
go back to reference Koch, L., Jansen, L., Herrmann, A., Stegmaier, C., Holleczek, B., Singer, S., Brenner, H., & Arndt, V. (2013). Quality of life in long-term breast cancer survivors-a 10-year longitudinal population-based study. Acta Oncology (Madr)., 52(6), 1119–1128.CrossRef Koch, L., Jansen, L., Herrmann, A., Stegmaier, C., Holleczek, B., Singer, S., Brenner, H., & Arndt, V. (2013). Quality of life in long-term breast cancer survivors-a 10-year longitudinal population-based study. Acta Oncology (Madr)., 52(6), 1119–1128.CrossRef
47.
go back to reference Natal, C., Suárez, M. T., Serrano, S., Díaz, C., González, C., Menéndez, P., Castañón, R., García, M.L., & Blázquez, E. (2012). Evaluación de resultados en el programa de detección precoz del cáncer de mama del Principado de Asturias. Revista de Calidad Asistencial, 27(1), 38–43.PubMedCrossRef Natal, C., Suárez, M. T., Serrano, S., Díaz, C., González, C., Menéndez, P., Castañón, R., García, M.L., & Blázquez, E. (2012). Evaluación de resultados en el programa de detección precoz del cáncer de mama del Principado de Asturias. Revista de Calidad Asistencial, 27(1), 38–43.PubMedCrossRef
48.
go back to reference Maurer, T., Thöne, K., Obi, N., Jung, A. Y., Behrens, S., Becher, H., & Chang-Claude, J. (2021). 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), 13, 1854.PubMedPubMedCentralCrossRef Maurer, T., Thöne, K., Obi, N., Jung, A. Y., Behrens, S., Becher, H., & Chang-Claude, J. (2021). 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), 13, 1854.PubMedPubMedCentralCrossRef
49.
go back to reference Moro-Valdezate, D., Peiró, S., Buch-Villa, E., Caballero-Gárate, A., Morales-Monsalve, M. D., Martínez-Agulló, Á., Checa-Ayet, F., & Ortega-Serrano, J. (2013). Evolution of health-related quality of life in breast cancer patients during the first year of follow-up. Journal of Breast Cancer, 16(1), 104–111.PubMedPubMedCentralCrossRef Moro-Valdezate, D., Peiró, S., Buch-Villa, E., Caballero-Gárate, A., Morales-Monsalve, M. D., Martínez-Agulló, Á., Checa-Ayet, F., & Ortega-Serrano, J. (2013). Evolution of health-related quality of life in breast cancer patients during the first year of follow-up. Journal of Breast Cancer, 16(1), 104–111.PubMedPubMedCentralCrossRef
50.
go back to reference Puhan, M. A., Ahuja, A., Van Natta, M. L., Ackatz, L. E., & Meinert, C. (2011). Interviewer versus self-administered health-related quality of life questionnaires—Does it matter? Health and Quality of Life Outcomes, 9(30). Puhan, M. A., Ahuja, A., Van Natta, M. L., Ackatz, L. E., & Meinert, C. (2011). Interviewer versus self-administered health-related quality of life questionnaires—Does it matter? Health and Quality of Life Outcomes, 9(30).
51.
go back to reference Bjelic-Radisic, V., Cardoso, F., Cameron, D., Brain, E., Kuljanic, K., da Costa, R. A., Conroy, T., Inwald, E.C., Serpentini, S., Pinto, M., Weis, J., Morag, O., Lindviksmoen Astrup, G., Tomaszweksi, K.A., Pogoda, K., Sinai, P., Sprangers, M., Aaronson, N., Velikova, G., Greimel, E., Arraras, J., Bottomley, A., Bleiker, E., Bliem, B., Chie, W., Creutzberg, C., Deville, V., Duhoux, F., Eilf, K., Hartup, S., Koller, M., Nagele, E., Nicolatou-Galitis, O., Oberguggenberger, A., Schmalz, C., & Winters, Z. (2020). An international update of the EORTC questionnaire for assessing quality of life in breast cancer patients: EORTC QLQ-BR45. Annals of Oncology, 31(2), 283–288.PubMedCrossRef Bjelic-Radisic, V., Cardoso, F., Cameron, D., Brain, E., Kuljanic, K., da Costa, R. A., Conroy, T., Inwald, E.C., Serpentini, S., Pinto, M., Weis, J., Morag, O., Lindviksmoen Astrup, G., Tomaszweksi, K.A., Pogoda, K., Sinai, P., Sprangers, M., Aaronson, N., Velikova, G., Greimel, E., Arraras, J., Bottomley, A., Bleiker, E., Bliem, B., Chie, W., Creutzberg, C., Deville, V., Duhoux, F., Eilf, K., Hartup, S., Koller, M., Nagele, E., Nicolatou-Galitis, O., Oberguggenberger, A., Schmalz, C., & Winters, Z. (2020). An international update of the EORTC questionnaire for assessing quality of life in breast cancer patients: EORTC QLQ-BR45. Annals of Oncology, 31(2), 283–288.PubMedCrossRef
Metagegevens
Titel
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
Auteurs
Carme Miret
Miren Orive
Maria Sala
Susana García-Gutiérrez
Cristina Sarasqueta
Maria Jose Legarreta
Maximino Redondo
Amado Rivero
Xavier Castells
José M. Quintana
Olatz Garin
Montse Ferrer
the REDISSEC-CaMISS Group
Publicatiedatum
11-01-2023
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 4/2023
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-022-03327-4