You are here

Importance of patient reported outcome measures versus clinical outcomes for breast cancer patients evaluation on quality of care

The Breast, June 2016, Pages 62 - 68



Given increasing numbers of breast cancer survivors, there is an increased focus on quality of life and quality of care. This study aims to investigate whether clinical or patient reported outcomes are most important for perceived quality of care by breast cancer patients.


Overall, 606 patients aged 18 years or older, who underwent breast cancer surgery 9–18 months ago in five hospitals in the Netherlands, were invited to complete an internet-based questionnaire. Patients were asked to judge a random selection of 24 patient profiles and choose which of 2 presented patients had received the best quality of care, using conjoint analysis. The individual relative importance (RI) for each outcome was estimated using Hierarchical Bayes Estimation, and averaged over all patients to assess which outcomes were most important.


Complete data were available for 350 patients (58%). Avoiding severe breast symptoms was most important for good quality of care according to patients (RI 23.22 [95% Confidence Interval (95% CI) 22.32–24.12]), followed by a 2 year longer disease free survival (18.30 [17.38–19.22]). However, the importance differed by age: younger patients (<50 years) assigned higher importance to longer disease free survival (21.99 [19.52–24.46]) than older patients (65 + years) (15.03 [13.88–16.18]).


Avoiding severe breast symptoms rather than 2 year longer disease free survival is considered most important in our population of breast cancer patients for evaluation of quality of care. These data should thus be included in both information provision prior to treatment choices and post treatment quality of care evaluation.


  • Avoiding severe breast symptoms were most important for perceived quality of care.
  • Patients would exchange 2 year disease free survival to avoid severe breast symptoms.
  • Younger patients (<50 years) assign higher importance to longer disease free survival.

Keywords: Breast cancer, Patient reported outcome measures (PROMs), Quality of care.


Breast cancer is the most frequent cancer affecting women all over the world and its incidence has doubled during the last 25 years. In the Netherlands, one in every eight women will be diagnosed with breast cancer during her life. Due to early detection and improved treatment there is an increased number of long-term breast cancer survivors [1], [2], and [3]. Associated with this increased survival is a prolonged period of medical interventions with concurrent physical and psychosocial problems [4]. Therefore, there is an increased focus on quality of life (QoL) and quality of care [5] and [6].

Currently, treatment decisions are more frequently made by doctor and patient together [7]. The doctor informs the patients about all treatment options and possible outcomes so that the patient can indicate her preferences. However, the information given to support treatment choices is mostly based on clinical outcomes, especially on disease free survival [8], [9], [10], [11], [12], and [13], whereas the impact on the patients (quality of) life may be just as important. Many previous studies showed that treatment did not influence global QoL but that an effect was found on many specific symptoms like fatigue, breast symptoms and arm symptoms [8], [14], [15], [16], [17], [18], [19], [20], [21], and [22]. This suggests that more specific patient reported outcome measures (PROMs) are needed to measure the impact of treatment, but it is not clear which PROM is considered most important by patients [23]. Currently, most indicators to evaluate quality of care are also based on clinical outcomes and processes. However, the question is whether these clinical outcomes or PROMs are more important for the patient's judgement of quality of care [8], [14], [15], [16], [18], [19], and [22].

The present study aims to assess which outcomes of breast cancer treatment are most important for patients in their judgement for good quality of care. This may be useful for two reasons. First, it may improve the information given to patients prior to treatment, so that they will be prepared for the impact of treatment on outcomes most important for their daily lives. Secondly, in the follow-up of breast cancer patients it may help doctors to monitor the outcomes considered most important by patients, so that patients are satisfied with the care provided to them.



The study was approved by the Medical Ethics Committee of the Leiden University Medical Center (project number P13.211).


All patients (n = 606) with stage I, II and III breast cancer were selected in five hospitals in the western part of the Netherlands, and invited to participate. Patients were selected if they were at least 18 years of age, and underwent surgery for breast cancer 9–18 months ago. Patients were selected after treatment being given because a certain knowledge and experience with breast cancer and its treatment options is required to properly judge which outcomes are most important. For people without breast cancer it is very hard to predict and fully grasp the influence of the disease, treatment and outcomes on their lives. The interval of 9–18 months after surgery was chosen in consultation with experts (clinical oncologists and surgeons), to have the most optimal balance of not burdening patients emotionally while still undergoing treatment versus having sufficient experience to evaluate the quality of care, as by this time chemotherapy and radiation therapy will have ended for most patients.

The invitations and informed consent forms were sent by mail. Reminders were sent after 3 weeks.


An internet-based questionnaire was developed including a choice-based conjoint (CBC) analysis, using Sawtooth Software SSI Web 8.2.4 (Sequim, WA,

The first part of the questionnaire consisted of questions about the respondent and her diagnosis with and treatment for breast cancer. In the second part, the different outcomes of breast cancer treatment as well as possible side-effects were first described and explained (Table 1). Outcomes and side effects which in previous studies demonstrated to influence quality of life were taken in account, i.e. type of surgery, lymphedema of the arm, fatigue and side effects of chemotherapy and endocrine therapy (e.g. hair loss, nausea and vomiting, menopausal complaints and joint problems) [8], [15], [16], [18], [19], [21], and [22]. Patients may for instance consider it important to receive chemotherapy to feel reassured that they have done everything possible to make sure that the cancer will not return. On the other hand, it may also induce side effects which they might try to avoid. To help respondents think about these outcomes, they were then asked how important each of these outcomes was to them and subsequently to rank the importance of the different outcomes from most to least important. The last part consisted of 12 conjoint tasks. Conjoint analysis is a technique used to understand how consumers choose between different products or services [24], [25], and [26]. In the case of breast cancer treatment, it operates on the premise that each treatment can be represented by a number of outcomes (attributes). These attributes can be broken down into levels. The attributes and levels were used to create patient profiles, with different treatment regimens and concurrent outcomes. In this way, conjoint analysis forces the respondent to choose the most preferred treatment regimen, thereby making trade-offs between preferred and adverse outcomes, which is more similar to evaluations made in daily life than a rating or ranking exercise. For example, it shows the extent and duration of side effects patients are willing to endure for one extra disease free year of their life.

Table 1 Attributes and levels, with the explanation of the levels to the patients.

Attributes Explanation to patients Levels
1. Disease free survival The disease free survival is an indicator of the period a patient lives without recurrence of cancer. In disease free survival it is about clinical diagnosis, not about how the patient is feeling. 9 year
10 years
11 years
2. Type of surgery The choice between the different types of surgery is usually made by patient and doctor together. The options are: Breast conserving surgery, with radiation therapy after surgery for 16–21 times (depending on tumour characteristics) in the hospital. The other option is mastectomy, with or without breast reconstruction. Usually there is no radiotherapy indicated after this. Breast conserving surgery, radiation therapy after surgery (16–21 times)
Mastectomy, no radiotherapy after surgery
Mastectomy, with breast reconstruction.
No radiotherapy after surgery
3. Treatment of the axilla After the sentinel node procedure there are different treatment options for the axilla, depending on whether there are metastasis in the sentinel node. The axilla can be left untreated, radiation therapy can be given to the axilla (16–25 times, depending on tumour characteristics), an axillary lymph node dissection can be performed. No axillary treatment
Radiation therapy of the axilla (16–25 times)
Axillary lymph node dissection
4. Breast
After surgery and/or radiation therapy various symptoms of the breast can occur. Breast symptoms are: Pain, hypersensitivity, skin problems, oedema of the breast. No complaints of the breast
Pain every now and then, but in control with painkillers
Continuously pain, even with painkillers
5. Arm symptoms After surgery or radiation therapy of the axilla various symptoms of the arm and shoulder can occur. Arm symptoms are: Oedema, pain and restriction in movement of the arm/shoulder. No complaints of the arm/shoulder
Some oedema, some pain, no movement restrictions
Severe oedema, pain, movement restriction
6. Fatigue Having cancer can make you feel weak and tired, some treatments may make you feel even weaker or more tired. If you feel tired you may not have the energy to do your daily activities. No more fatigue than before diagnoses
Fatigue, relieved by rest. Can do all daily activities
Fatigue, not relieved by rest. Difficulty doing daily activities
7. Chemotherapy After surgery chemotherapy could be given, the therapy is given through an infusion so patients are required to come to the hospital for their chemotherapy. In most cases patients receive the treatment every 3 weeks, with a total duration of 4–6 months. This chemotherapy can cause different adverse events, most common: hair loss, nausea and vomiting, menopausal complaints and dryness of the mouth. Yes, 4–6 months chemotherapy given trough an infusion with mild to severe adverse events
No chemotherapy, no adverse events
8. Endocrine therapy After surgery it is also possible to start endocrine therapy. This treatment consists of one tablet a day for a duration of 5 years. This treatment can cause adverse events as well, most common: joint problems and menopausal complaints. Yes, 5 years endocrine therapy, taking one tablet a day with mild to severe adverse events
No endocrine therapy, no adverse events

Respondents were presented with 12 different comparisons of 2 patient profiles. Each patient profile was characterized by 8 attributes. Before starting the conjoint tasks in the questionnaire, the different categories as presented in the profiles were first explained, including an example task (see Fig. 1). The selected attributes, levels and the way they were explained to the respondents are presented in Table 1. Two or three levels were defined for each attribute. The attributes and levels were identified using 3 criteria:

  • - Available empirical data on the outcome.
  • - Available evidence that the outcomes differed between different treatment regimens.
  • - Available evidence of an association between the outcome and quality of life/quality of care [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], and [22].

Fig. 1 Example conjoint task.

All profiles were presented in the third person for two patients, to prevent bias from the patients' own experience (hindsight bias) [27]. Patients were asked to choose which of the two patients in their opinion had received the more preferable outcome of treatment, and thereby the best quality of care. An example choice task is presented in Fig. 1.

Conjoint analysis considers all possible combinations of attribute levels. Using 8 attributes, 6 with 3 levels and 2 with 2 levels, theoretically 2916 patient profiles could be made. To prevent the presentation of clinically impossible combinations so that patients would make illogical choices, some prohibitions were made (e.g. having severe arm symptoms without having any therapy of the axilla). A d-efficient experimental design was developed using Sawtooth Software SSI Web 8.2.4, consisting of 10 questionnaire versions. With this 10 versions, 12 tasks and 2 profiles per task, the resulting experimental design consisted of 240 patient profiles, of which each respondent received a subset of 12 random pairs, thereby evaluating 24 patient profiles.

The questionnaires were pilot tested among breast cancer patients by asking them to think out loud when filling in the questionnaire, which told us which questions were misunderstood or not clear. These questions were adjusted and piloted again under other patients until no more issues came up (which was the case after testing under 11 patients).

Statistical analysis

Baseline characteristics were compared between respondents and non-respondents, using chi-square and t-tests. This was done to assess whether the respondents were representative for the total breast cancer population or that selection bias may have occurred.

Then we assessed which attribute was ranked highest by most of the respondents prior to the conjoint tasks. As the attributes were ranked on a scale from 1 to 8 (8 for the most important attribute, 1 for the least important attribute), we calculated a mean rank for each attribute. Consequently, we calculated the percentage of respondents who assigned this rank to this attribute, e.g. the percentage of respondents who assigned rank 2 to attribute X.

Hierarchical Bayes estimation was used to calculate the relative importance (RI) of each attribute for each respondent, according to the choices made in the conjoint tasks (using the maximum difference in the average overall utility between levels) [28]. The relative importance was averaged over all respondents, to assess which attributes on average are most important for patients in their judgement of good quality of care.

The average relative importance based on the conjoint analysis was compared to the direct ranking, to assess whether this would result in a different order of importance of the attributes.

To assess whether different groups of patients assign a greater importance to specific attributes, the relative importance was compared between these groups. The groups were created by age (under 50 years, 50–64 years, 65 years and older), marital status, having children, age of children as well as treatment received. These comparisons were made using an independent t-test. Because personal characteristics, treatment options and importance assigned to the different attributes may vary with age, these outcomes were adjusted for age, using a linear regression model.

All data were analysed using the Sawtooth Software SSI Web 8.2.4. and the statistical package SPSS for Windows 17.0 (SPSS Inc, Chicago, IL, USA). Descriptive data are given as a mean (SD) or median (range). In all analysis, P < 0.05 was considered statistically significant.


In total, 350 patients returned a complete questionnaire (response 58%).

Table 2 shows that respondents on average are 7 years younger than non-respondents. Among the respondents there were more patients who received chemotherapy (48.3% versus 29.7%) and radiation therapy (72.0% versus 59.0%) than among the non-respondents. These differences between respondents and non-respondents could potentially give bias, if the importance patients assign to the different attributes differs between older and younger patients, or between patients who did or did not receive chemotherapy or radiation therapy. For all other baseline characteristics (type of tumour, type of surgery, axillary lymph node dissection, endocrine therapy and intra-operative radiation therapy) the respondents and non-respondents were comparable.

Table 2 Baseline characteristics responders versus non-responders.

Responders (%)
N = 350
Non-responders (%)
N = 256
Mean age (SD) 59.34 (11.62) 66.25 (13.84) t = −6.49
p < 0.01
 Invasive ductal carcinoma 230 (65.7%) 149 (58.2%)
 Invasive lobular carcinoma 61 (17.4%) 44 (17.2%)
 Ductal carcinoma in situ 40 (11.4%) 34 (13.3%)
 Other (pre)malign 16 (4.6%) 24 (9.4%) x2 = 7.962
 Benign 1 (0.3%) 2 (0.8%) p = 0.140
Type of surgery
 Mastectomy 142 (40.6%) 116 (45.3%) x2 = 1.359
 Breast conserving therapy 208 (59.4%) 140 (54.7%) p = 0.244
Axillary lymph node dissection
 Yes 88 (25.1%) 73 (28.5%) x2 = 0.927
 No 261 (74.6%) 182 (71.1%) p = 0.629
 Yes 169 (48.3%) 76 (29.7%) x2 = 21.292
 No 172 (49.1%) 172 (67.2%) p < 0.01
Endocrine therapy
 Yes 170 (48.6%) 130 (50.8%) x2 = 0.296
 No 169 (48.3%) 118 (46.1%) p = 0.862
Radiation therapy
 Yes 252 (72.0%) 151 (59.0%) x2 = 12.150
 No 97 (27.2%) 102 (46.1%) p < 0.01
Intra-operative radiation therapy
 Yes 69 (19.7%) 39 (15.2%) x2 = 5.745
 No 281 (80.3%) 215 (84.0%) p = 0.098

The most important outcome from the direct ranking is disease free survival, with 84.3% of the patients assigning the highest rank to this outcome (Table 3). Among the other outcomes there was more diversity between patients. The percentages of patients assigning the same ranks to the outcomes are clearly lower than for disease free survival (varying between 9.4% and 27.7%). This suggests that all of these outcomes are less important than disease free survival and that patients vary considerably in which outcome they consider to be second most important (or least important).

Table 3 Mean ranking of the attributes, with the percentage of patients who put the attribute at that rank.

Rank Attribute (mean ranking) % Of patients
1 Prolonged disease free survival (7.3) 84.3%
2 No chemotherapy (5.0) 27.7%
3 Breast conserving therapy (4.5) 9.4%
4 No fatigue (4.1) 12.3%
5 No breast symptoms (4.0) 16.3%
6 No axillary treatment (3.9) 18.6%
7 No arm symptoms (3.7) 20.6%
8 No endocrine therapy (3.5) 25.4%

Given the choices patients made in the conjoint tasks, avoiding severe breast symptoms such as continuous pain or breast oedema (RI 23.22 [95% Confidence Interval (95% CI) 22.32–24.12]) rather than a 2 year longer disease free survival (RI 18.30 [95% CI 17.38–19.22]) on average was the most important outcome to determine quality of care according to patients (Table 4). The average utilities in this table, show how much each level of each attribute is preferred over the alternative, with higher numbers indicating stronger preference for that level. So the larger the difference between the most and least preferred level, the higher the relative importance of a particular attribute. Having no breast symptoms (2.29) is for example more strongly preferred over having severe breast symptoms (−4.05), than the preference for a lumpectomy (0.59) over a mastectomy (−0.38).

Table 4 Selected attributes, the constructed levels and their average overall utilities with standard deviation and overall Relative Importance (RI) with 95% Confidence Interval (95% CI).

Attributes Levels Average overall utility per level (SD) Overall RI (95% CI)
Breast symptoms None 2.286 (1.196) 23.22 (22.32–24.12)
Mild 1.761 (1.024)
Severe −4.047 (2.079)
Disease free survival 9 years −2.439 (0.922) 18.30 (17.38–19.22)
10 years 0.152 (0.466)
11 years 2.287 (0.943)
Chemotherapy Yes 1.423 (1.706) 13.76 (12.78–14.74)
No −1.423 (1.706)
Fatigue None 1.215 (0.796) 13.09 (12.58–13.60)
Mild 0.849 (0.787)
Severe −2.064 (1.145)
Arm symptoms None 1.320 (0.772) 12.13 (11.70–12.56)
Mild 0.497 (0.653)
Severe −1.816 (0.859)
Type of surgery Lumpectomy 0.587 (1.155) 8.14 (7.55–8.73)
with reconstruction −0.204 (0.776)
Mastectomy −0.383 (0.935)
Axillary treatment None 0.093 (0.620) 5.80 (5.45–6.15)
Radiation therapy 0.012 (0.686)
ALND −0.105 (0.863)
Endocrine therapy Yes 0.406 (0.846) 5.58 (5.13–6.03)
No −0.406 (0.846)

The importance of avoiding severe breast symptoms and disease free survival was followed by the importance to undergo chemotherapy (with possible side effects) and avoiding severe fatigue, with the relative importance of the latter two not being significantly different (13.76 versus 13.09; p = 0.258). Avoiding severe arm symptoms, type of surgery, avoiding axillary lymph node dissection and undergoing endocrine therapy (including possible side effects) are all less important outcomes.

The results from the direct ranking do not match the results from the conjoint tasks. Most remarkable in this is that not disease free survival (clearly most important in direct ranking), but avoiding severe breast symptoms appears to be the most important outcome. Although this result may seem unexpected at first, they do match the open comments given by many respondents at the end of the questionnaire, for example “prior to the choice tasks I thought disease free survival was most important to me, but the choice tasks made me realise that disease free survival is important, but not at all costs” or “I realised that my mind makes different decisions than my feelings, I do not want to live 1 or 2 years longer with many adverse events”. Therefore we consider the relative importance from the conjoint analysis to be a more accurate and reliable reflection of the true importance assigned by patients, consistent with previous literature [24] and [29].

Table 5 shows that avoidance of severe breast symptoms is the most important outcome in all age groups, although in younger women (<50 years) the difference between avoiding severe breast symptoms and a 2 year longer disease free survival is not significant (22.41 versus 21.99; p = 0.842). The importance of a 2 year longer disease free survival is clearly lower in elderly women than avoidance of severe breast symptoms (15.03 versus 24.02; p < 0.001). The importance to receive chemotherapy seems even higher in this oldest age group than the importance of longer disease free survival (16.24 versus 15.03), but this difference is not significant (p = 0.354).

Table 5 Mean RI for each attribute for the different age groups with 95% Confidence Interval (95% CI).

Attributes Mean RI (95% CI)
<50 years
N = 63
Mean RI (95% CI)
50–64 years
N = 163
Mean RI (95% CI)
65 + years
N = 124
Breast symptoms 1. 22.41 1. 22.92 1. 24.02
(20.26–24.56) (21.61–24.23) (22.50–25.54)
Disease free survival 2. 21.99 2. 19.35 3. 15.03
(19.52–24.46) (17.94–20.76) (13.88–16.18)
Chemotherapy 4. 12.36 4. 12.41 2. 16.24
(10.79–13.93) (10.95–13.87) (14.51–17.97)
Fatigue 3. 13.01 3. 12.94 4. 13.32
(11.67–14.35) (12.13–13.75) (12.61–14.03)
Arm symptoms 5. 12.22 5. 12.06 5. 12.17
(11.19–13.25) (11.43–12.69) (11.42–12.92)
Type of surgery 6. 7.65 6. 8.07 6. 8.48
(6.22–9.08) (7.23–8.91) (7.47–9.49)
Axillary treatment 8. 5.15 7. 6.24 7. 5.54
(4.42–5.88) (5.75–6.73) (4.87–6.21)
Endocrine therapy 7. 5.22 8. 6.01 8. 5.20
(4.12–6.32) (5.29–6.73) (4.60–5.80)

Between patient groups with different personal characteristics (marital status, having children, age of children) no differences in importance of outcomes were seen after adjustment for age (data not shown). Furthermore, no differences were seen between groups of patients with different treatment regimens, except for patients who received chemotherapy and endocrine therapy. Patients with chemotherapy assigned higher importance to a 2 year longer disease free survival compared to patients without chemotherapy (23.30 versus 14.71; p < 0.001) and patients with endocrine therapy also assigned higher importance to this outcome than patients without endocrine therapy (20.35 versus 16.63; p = 0.024), even after adjustment for age.

Given the utilities for the minimum and maximum attribute level as reported in Table 4, trade-off rates were calculated as the ratio between the utility differences in the two attributes (Table 6). This illustrates how patients conduct the trade-off between outcomes they want and side-effects they want to avoid. In this way, it is shown that the average respondent cares 1.34 times more about the difference between experiencing severe breast symptoms versus no breast symptoms than about a two year difference of 5 versus 7 years of disease free survival. By applying this ratio of 1.34 to the 2 years difference in disease free survival, the utility difference is estimated to be equivalent in both attributes at a 2.7-years difference in disease free survival. This suggests that the average breast cancer patient is willing to exchange up to 2 years and 9 months disease free survival to avoid having severe breast symptoms like continuous pain even with medication, hypersensitivity and oedema.

Table 6 Trade-off rates in comparison to the attribute on average considered as most important.

Attribute (difference) Utility difference (SE) Trade-off rates
1. Breast symptoms (none versus severe) 6.34 (5.52) 1
2. Disease free survival (11 versus 9 years) 4.73 (1.79) 1.34
3. Chemotherapy (yes versus no) 2.84 (4.62) 2.23
4. Fatigue (none versus severe) 3.28 (2.11) 1.93
5. Arm symptoms (none versus severe) 3.14 (1.51) 2.02
6. Type of surgery (lumpectomy versus mastectomy) 0.97 (2.03) 8.03
7. Axillary treatment (none versus ALND) 0.20 (1.09) 31.70
8. Endocrine therapy (yes versus no) 0.82 (1.56) 7.73


The present study has shown that breast cancer patients consider avoiding severe breast symptoms rather than a 2 year longer disease free survival to be the most important outcome in their judgement for good quality of care. Only age affects the importance patients assign to specific outcomes. For all age groups the avoidance of severe breast symptoms is the most important outcome, but younger patients assign higher importance to a 2 year longer disease free survival than older patients so that avoiding breast symptoms and longer disease free survival are equally important in younger patients.

Our sample may have been a selected population, as e.g. it was shown that respondents were younger than non-respondents. Therefore, response bias may have occurred, but this will only affect the results if respondents and non-respondents differ with respect to a certain variable (e.g. age) and if the importance assigned to the outcomes also differs with respect to this variable. Based on available data, this is the case for only two variables. The first is age, that is older patients assign higher importance to receiving chemotherapy and lower importance to a 2 year longer disease free survival. This could mean that the importance of chemotherapy, in our younger population, was underestimated, whereas the importance of disease free survival was overestimated. Furthermore, among the respondents there were more patients who received radiation therapy and chemotherapy than among the non-respondents. This could cause bias if the importance of the outcomes differs between patients who did and did not receive these treatments. There were no differences between patients with or without radiation therapy. However, patients who received chemotherapy assign higher importance to a 2 year longer disease free survival. This could mean that, in our population with more patients who received chemotherapy, the importance of longer disease free survival was overestimated. Regarding other characteristics possibly causing bias, such as marital status, having children and age of children, we did not have data for non-respondents to formally compare them. However, within respondents no differences were found between patient groups in the importance assigned to outcomes, so that this will not have induced bias. We did not have data on characteristics like education, income and literacy, so that the possibility remains that this has created bias. Similarly, we did not have data on stage of cancer. Because stage is correlated to treatment regimens, we assessed differences between patient groups undergoing different treatment regimens. Still, there is a (small) possibility that stage of cancer would influence the importance assigned to outcomes even within these treatment regimens and may have biased our results. Taking the possibility of these biases into account and based on available data, this suggests that the importance of disease free survival may be even lower in reality and thus only strengthens our conclusion that avoiding severe breast symptoms are more important than a 2 year longer disease free survival for patients' evaluation of quality of care.

A remarkable result is that elderly patients assign higher importance to undergoing chemotherapy (including possible side effects) than younger patients. Only 16% of the patients in the oldest age group received chemotherapy, versus 72% of the patients in the youngest age group. Because most of the elderly patients did not receive chemotherapy, and thus did not experience the side effects, it could be that they cannot fully assess the influence chemotherapy may have on their (quality of) life. Another possible explanation could be that elderly patients are more likely to think that the treatment the doctor recommends for them will be the best treatment. In other words, if chemotherapy is an option this will be to improve the prognosis and is perceived as needed, and therefore that will be the best treatment.

For the interpretation of the results of this study it is important to realise that severe breast symptoms were described as having continuous pain, even when taking painkillers. This might explain why breast symptoms are considered so important by patients. Furthermore, it is a retrospective study in which responding patients are recovered from surgery and have experience with and possibly got adjusted to some of the effects of treatment when completing the questionnaire. It may be expected that a patient's first reaction, after receiving the diagnosis of breast cancer, is that she wants to be cured from the disease. Therefore, the purpose of the study is not to change the breast cancer treatment, but to improve the information given to patients prior to treatment, and thereby to improve quality of care. It becomes clear from this study that the given information should not only be about curing breast cancer, but also about the impact of treatment on the patients' daily lives. The impact on their daily lives is what is important to them to judge the quality of care, as well as that these are the aspects they will have to deal with once they are cured. This may be especially important for elderly patients (65 years and older), as this group assigns lower importance to a 2 year longer disease free survival.

Another implication of our results is that doctors should ask for specific outcomes as breast symptoms in the follow-up, of which we now know these are important to patients, to make patients feel more understood and satisfied with the care provided to them.

Previous studies [14], [15], [16], [17], [18], [19], [20], [21], [22], and [24] suggested that it may be indicated to ask for specific patient reported outcomes to assess the effects of breast cancer treatment, but it remained unclear which outcomes are most important to patients. The current study is the first one investigating this, and the results should be incorporated in communicating information to patients. According to previous studies among cancer patients, there is a discrepancy between the information patients want and need and the information that doctors actually give to them [30] and [31]. Furthermore, as shown by Mallinger and colleagues for breast cancer patients, satisfaction about treatment information is very high whereas patients were less satisfied about information related to survival ship issues (e.g. long-term side effects of treatment) [32]. Given the results from the present study, more attention may be given to patient reported outcomes rather than focussing only on clinical outcomes. Furthermore, the results may help in developing core outcome sets [33] for breast cancer patients, so that if patient reported outcomes are collected and used in routine daily practice, these at least include the outcomes considered most important by patients.

In conclusion, this study demonstrates that avoiding severe breast symptoms are most important for breast cancer patients in their judgement of quality of care, and more important than a 2 year longer disease free survival. This information can help to improve quality of care of breast cancer patients by improving information given prior to treatment as well as monitoring these outcomes in the follow-up of patients.

Conflict of interest statement

None of the authors have any conflicts of interest.


Zoleon, Stichting Zorg & Leven, Oncologie.


We would like to thank E.M.M. Krol-Warmerdam and G.M.C. Ranke for their help in developing the questionnaires. We would also like to thank A. Does-den Heijer, M. Goemans, H. de Lange-van Bruggen, M.E.M. Bouwman, K.M. Fennema-Bensink, A.H. van der Wilden and P.H.B. Keunen-Dekkers for their help in collecting data.

This study was funded by Zoleon (project nr 13.06), a regional charity organisation aimed to improve quality of care and welfare for oncological patients.


  • [1] D. Klein, M. Mercier, E. Abeilard, M. Puyraveau, A. Danzon, V. Dalstein, et al. Long-term quality of life after breast cancer: a French registry-based controlled study. Breast Cancer Res Treat. 2011;129:125-134
  • [2] L.A. Kiemeney, F.A. Lemmers, R.H. Verhoeven, K.K. Aben, C. Honing, N.J. de Nooijer, et al. The risk of cancer in the Netherlands. Ned Tijdschr Geneeskd. 2008;152(41):2233-2241
  • [3] A. Jemal, F. Bray, M.M. Center, J. Ferlay, E. Ward, D. Forman. Global cancer statistics. CA Cancer J Clin. 2011 Mar–Apr;61(2):69-90 10.3322/caac.20107 Epub 2011 Feb 4
  • [4] L.G. Gordon, D. Battistutta, P. Scuffham, M. Tweeddale, B. Newman. The impact of rehabilitation support services on health related quality of life for women with breast cancer. Breast Cancer Res Treat. 2005;93(3):217-226
  • [5] S.J. Cano, A. Klassen, A.L. Pusic. The science behind quality-of-life measurement: a primer for plastic surgeons. Plast Reconstr Surg. 2009;123 98e-106e536
  • [6] M.A.G. Sprangers, A. Cull, M. Groenvold, K. Bjordal, J. Blazeby, N.K. Aaronsonand. The European organization for research and treatment of cancer approach to developing questionnaire modules: an update and overview. Qual Life Res. May, 1998;7(4):291-300
  • [7] A.M. Stiggelbout, T. Van der Weijden, M.P.T. De Wit, F. Légaré, V.M. Montori, L. Trevena, et al. Shared decision making: really putting patients at the centre of healthcare. BMJ. 2012;344 10.1136/bmj.e256 e256
  • [8] H.Y. Shi, Y.H. Uen, L.C. Yen, R. Culbertson, C.H. Juan, M.F. Hou. Two-year quality of life after breast cancer surgery: a comparison of three surgical procedures. Eur J Surg Oncol. 2011; 10.1016/j.ejso.2011.05.008
  • [9] B. Fisher, C. Redmond, R. Poisson, R. Margolese, N. Wolmark, L. Wickerham, et al. Eight-year results of a randomized clinical trial comparing total mastectomy and lumpectomy with or without irradiation in the treatment of breast cancer. N Engl J Med. 1989;320:822-828
  • [10] U. Veronesi, A. Luini, M. Del Vecchio, M. Greco, V. Galimberti, M. Merson, et al. Radiotherapy after breast-preserving surgery in women with localized cancer of the breast. N Engl J Med. 1993;328:1587-1591
  • [11] R. Arriagada, M.G. Le, F. Rochard, G. Contesso. Conservative treatment versus mastectomy in early breast cancer: patterns of failure with 15 years of follow-up data. Institut Gustave-Roussy Breast Cancer Group. J Clin Oncol. 1996;14:1558-1564
  • [12] Early Breast Cancer Trialists' Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005 May 14-20;365(9472):1687-1717
  • [13] M. Martín, M.A. Seguí, A. Antón, A. Ruiz, M. Ramos, E. Adrover, et al., GEICAM 9805 Investigators. Adjuvant docetaxel for high-risk, node-negative breast cancer. N Engl J Med. 2010 Dec 2;363(23):2200-2210
  • [14] N.K. Janz, M. Mujahid, L.K. Chung, P.M. Lantz, S.T. Hawley, M. Morrow, et al. Symptom experience and quality of life of women following breast cancer treatment. J Women's Health. 2007;9:1348-1361
  • [15] V. Arndt, C. Stegmaier, H. Ziegler, H. Brenner. A population-based study of the impact of specific symptoms on quality of life in women with breast cancer 1 year after diagnosis. Cancer. 2006;107:2496-2503
  • [16] L.H. Gerber, N. Stout, C. McGarvey, P. Soballe, C.Y. Shieh, G. Diao, et al. Factors predicting clinically significant fatigue in women following treatment for primary breast cancer. Support Care Cancer. 2011 Oct;19(10):1581-1591
  • [17] S. Haghighat, M.E. Akbari, K. Holakouei, A. Rahimi, A. Montazeri. Factors predicting fatigue in breast cancer patients. Support Care Cancer. 2003;11:533-538
  • [18] D.J. Dawes, S. Meterissian, M. Goldberg, N.E. Mayo. Impact of lymphoedema on arm function and health-related quality of life in women following breast cancer surgery. J Rehabil Med. 2008;40:651-658
  • [19] S.M. Beaulac, L.A. Mcnair, T.E. Scott, W.W. LaMorte, M.T. Kavanah. Lymphedema and quality of life in survivors of early-stage breast cancer. Arch Surg. 2002;137:1253-1257
  • [20] A.E. Giuliano, K.K. Hunt, K.V. Ballman, P.D. Beitsch, P.W. Whitworth, P.W. Blumencranz, et al. Axillary dissection vs no axillary dissection in women with invasive breast cancer and sentinel node metastasis: a randomized clinical trial. JAMA. 2011;305:569-575
  • [21] S.R. Burwell, L.D. Case, C. Kaelin, N.E. Avis. Sexual problems in younger women after breast cancer surgery. J Clin Oncol. 2006;24:2815-2821
  • [22] S.Y. Hwang, S.J. Chang, B.W. Park. Does chemotherapy really affect the quality of life of women with breast cancer?. J Breast Cancer. 2013 June;16(2):229-235
  • [23] A.L. Pusic, A.F. Klassen, A.M. Scott, J.A. Klok, P.G. Cordeiro, S.J. Cano. Development of a new patient-reported outcome measure for breast surgery: the brEAST-Q. Plast Reconstr Surg. 2009;124:345
  • [24] M. Ryan, S. Farrar. Using conjoint analysis to elicit preferences for health care. BMJ. 2000;320:1530-1533
  • [25] B.K. Orme. Getting started with conjoint analysis: strategies for product design and pricing research. (Research Publishers, LLC, Madison, WI, 2006)
  • [26] J.J. Louviere. Analyzing decision making: metric conjoint analysis. (Sage, Newbury Park, CA, 1988)
  • [27] A.B. Hauber, A.F. Mohamed, F.R. Johnson, O. Oyelowo, B.H. Curtis, C. Coon. Estimating importance weights for the IWQOL-Lite using conjoint analysis. Qual Life Res. 2010;19(5):701-709
  • [28] B.K. Orme. Hierarchical Bayes: why all the attention? Sequim WA: Sawtooth software. (2000) Available from: URL
  • [29] M. Ryan, D.A. Scott, C. Reeves, A. Bate, E.R. van Teijlingen, E.M. Russell, et al. Eliciting public preferences for health care: a systematic review of techniques. Health Technol Assess. 2001;5(5) 1–186
  • [30] V. Jenkins, L. Fallowfield, J. Saul. Information needs of patients with cancer: results from a large study in UK cancer centres. Br J Cancer. 2001 Jan 5;84(1):48-51
  • [31] A. Brédart, C. Bouleuc, S. Dolbeault. Doctor-patient communication and satisfaction with care in oncology. Curr Opin Oncol. 2005 July;17(4):351-354
  • [32] J.B. Mallinger, J.J. Griggs, C.G. Shields. Patient-centered care and breast cancer survivors' satisfaction with information. Patient Educ Couns. 2005 Jun;57(3):342-349
  • [33] R.C. Macefield, M. Jacobs, I.J. Korfage, J. Nicklin, R.N. Whistance, S.T. Brookes, et al. Developing core outcomes sets: methods for identifying and including patients-reported outcomes (PROs). Trials. 2014 Feb 5;15:49 10.1186/1745-6215-15-49


a Department of Medical Decision Making, Leiden University Medical Center, Leiden, The Netherlands

b Department of Surgery, Medical Center Haaglanden, The Hague, The Netherlands

c Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands

d Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands

e Department of Surgery, Haga Hospital, The Hague, The Netherlands

f Department of Surgery, Bronovo Hospital, The Hague, The Netherlands

g Department of Surgery, Diaconessenhuis, Leiden, The Netherlands

Corresponding author. Leiden University Medical Center, Department of Medical Decision Making, J10-S, P.O. Box 9600, 2300 RC Leiden, The Netherlands.

Search this site

Featured videos

Free access to ebooks on cachexia and CINV


Prevention of nausea and vomiting in
adult cancer patients receiving tumour-
directed therapy – 2017 update –

Cancer cachexia: mechanisms and progress in treatment


Stay up-to-date with our monthly e-alert

If you want to regularly receive information on what is happening in Quality of Life in Oncology research sign up to our e-alert.

Subscribe »

QOL (Quality of Life) newsletter e-alert

Quality of Life promotional video

Made possible by an educational grant from Helsinn

Helsinn does not have any influence on the content and all items are subject to independent peer and editorial review

Society Partners

European Cancer Organisation Logo