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Health-Related Quality of Life Parameters As Prognostic Factors in a Nonmetastatic Breast Cancer Population: An International Multicenter Study

From the European Organization for Research and Treatment of Cancer, Quality of Life Unit; Institute Jules Bordet, Brussels; Limburgs Universitair Centrum, Diepenbeek, Belgium; Harvard University, Department of Biostatistics, Boston, MA; Medical University of Gdansk, Poland; Institute of Oncology, Ljubljana, Slovenia; Medical Academy of Lodz, Poland; Cancer Research Center, Moscow, Russia; National Cancer Institute Canada, Clinical Trials Group, Kingston, Canada; and Department of Medical Psychology, University of Amsterdam, The Netherlands

Address reprint requests to Fabio Efficace, MSc, European Organisation for Research and Treatment of Cancer, EORTC Data Center, Quality of Life Unit, Ave E Mounier 83, 1200 Brussels, Belgium; e-mail: fef{at}eortc.be

	ABSTRACT

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PURPOSE: The purpose of this research was to evaluate whether baseline health-related quality of life (HRQOL) parameters are prognostic factors for survival in locally advanced breast cancer patients. Although the literature highlights the important role of HRQOL parameters in predicting survival in advanced metastatic disease, little evidence exists for earlier stages.

PATIENTS AND METHODS: The overall sample consisted of 448 patients randomly assigned to receive cyclophosphamide, epirubicin, and fluorouracil versus epirubicin, cyclophosphamide, and granulocyte colony-stimulating factor. Patients were enrolled in 12 countries. HRQOL baseline scores were assessed using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30. The Cox proportional hazards regression model was used for both univariate and multivariate analyses of survival. In addition, a bootstrap resampling technique was used to assess the stability of the outcomes. Bootstrap results were then applied for model averaging purposes as a means to account for the observed model selection uncertainty.

RESULTS: The final multivariate model retained inflammatory breast cancer (T4d) as the only factor predicting overall survival (OS) with a hazard ratio of 1.375 (95% CI, 1.027 to 1.840; P = .03). The presence of inflammatory breast cancer lowers the median survival time from 6.6 to 4.2 years (36% reduction). None of the preselected HRQOL variables were prognostic for OS or disease-free survival, in either the univariate or multivariate analysis.

CONCLUSION: Our findings suggest that baseline HRQOL parameters have no prognostic value in a nonmetastatic breast cancer population.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... REFERENCES

 
It has become increasingly accepted that, in addition to the traditional assessment of clinical outcomes, health-related quality of life (HRQOL) assessment may play a key role in cancer research. Patients' self-assessment of HRQOL is now an established end point for treatment comparisons in breast cancer patients.¹

HRQOL outcomes could have various uses, including supporting clinical decision making by providing the patient's perspective or, as recently highlighted, providing prognostic information for survival. Several recent studies have shown that HRQOL parameters can be independent prognostic factors for survival in cancer patients.^2,3 In general, the studies in this area have used different measures; for example, the Functional Living Index-Cancer⁴ and the Rotterdam Symptom Checklist,⁵ and several have also used the European Organization for Research and Treatment of Cancer, Quality of Life Questionnaire C30 (EORTC QLQ-C30).^6-9

Although the use of different measures has hindered outcomes comparisons, they do provide complementary evidence of the strong and important association between HRQOL and survival. HRQOL prognostic factor analyses have been carried out on several different cancer populations, including colorectal,⁸ lung,⁹ melanoma,¹⁰ and breast,^11,12 highlighting the important value of HRQOL scores in predicting survival. Nevertheless, the reason for this association is still not clear. It is notable that, overall, the majority of such studies investigating the prognostic significance of HRQOL data focused mainly on advanced disease stages.

Although previous reports on breast cancer patients have shown that patients' self-evaluation of HRQOL parameters such as pain^11,13 and physical well-being¹⁴ are independent prognostic factors for survival in metastatic disease, few studies have investigated this issue in earlier stage diseases while also controlling for important clinical variables.¹⁵

Interpreting results of studies assessing the potential value of HRQOL data in predicting survival in cancer patients requires some caution. Possible difficulties can arise from inadequate statistical control of known clinical prognostic factors¹⁶ and from the correlation among items or subscales of the questionnaires used to assess HRQOL.¹⁷ As such, it could be difficult to disentangle their influence and thus obtain a real estimate of their individual effect. The statistical handling of this phenomenon, known as multicollinearity, is complex and has been addressed recently by Van Steen et al.¹⁷ Hence, to control or limit these possible biases, we strengthened the classical statistical analyses, consisting of Cox multivariate regressions, in two ways. First, we applied a bootstrap resampling procedure to investigate model selection instability.^18,19 Second, we used the information derived thereof for model averaging (MA) purposes.²⁰ Hence, the main purpose of this retrospective exploratory study is to evaluate the value of HRQOL baseline parameters in predicting overall survival (OS) in a nonmetastatic breast cancer population.

	PATIENTS AND METHODS

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The original trial was a randomized, multicenter, phase III study. Forty-six centers from 12 countries and three cooperative groups (European Organization for Research and Treatment of Cancer, National Cancer Institute Canada, and the Swiss Group for Clinical Cancer Research) participated in this trial. Overall, 448 women with locally advanced breast cancer were recruited. Eleven of the 12 countries involved in the study provided HRQOL data (Belgium, Canada, Czech Republic, France, Poland, Russia, Slovenia, South Africa, Switzerland, the Netherlands, and United Kingdom). One center (Portugal) did not participate in the HRQOL study and the 13 patients enrolled were excluded from the analysis; thus, the overall sample consisted of 435 patients. Patients were randomly allocated to two arms to compare cyclophosphamide 75 mg/m² orally days 1 to 14, epirubicin 60 mg/m² intravenously (IV) days 1 and 8, and fluorouracil 500 mg/m² IV days 1 and 8 for six cycles every 28 days (CEF arm) versus epirubicin 120 mg/m² IV day 1, cyclophosphamide 830 mg/m² IV day 1, and granulocyte colony-stimulating factor (filgrastim) 5 µg/kg/d subcutaneously days 2 to 13 for six cycles every 14 days (EC arm). Full details of treatment schedule and treatment-related clinical outcomes have been reported previously.²¹ Overall, after a median follow-up of 5.5 years, 277 events were reported. The median progression-free survival was 34 and 33.7 months for CEF and EC, respectively (P = .68), and the 5-year survival rate was 53% and 51% for CEF and EC, respectively (P = .94).

Patients
To be eligible for inclusion in the trial, female patients were required to be diagnosed with locally advanced breast cancer. Locally advanced breast cancer was defined as belonging to one of the following categories: any T4, any N, M0; or any TN2-3M0; or inflammatory breast cancer. Other eligibility criteria were as follows: WHO performance status 0 or 1; adequate bone marrow, liver, and kidney function; no evidence of metastasis; no previous treatment for breast cancer; and no previous or concomitant malignancy. Eligible patients were randomly assigned centrally after stratification for the following factors: institution, age 50 years or younger versus older than 50 years, and inflammatory versus noninflammatory breast cancer.

The study, approved by the EORTC protocol review committee and the ethics committee of each participating center, was conducted in compliance with the Helsinki declaration. All patients provided written informed consent.

Methods
HRQOL was assessed using the EORTC QLQ-C30 (version 1.0). The EORTC QLQ-C30 is an internationally validated HRQOL measure suitable for use with a generic cancer population; it is available in several languages and has proven robust psychometric properties.²²

The EORTC QLQ-C30 is composed of five functional scales (physical, role, emotional, cognitive, and social); three symptom scales (fatigue, nausea or vomiting, and pain); six single items (dyspnea, insomnia, appetite loss, constipation, diarrhea, and financial difficulties); and a global health status or QOL scale.

Assessments were performed at baseline or just after random assignment but before treatment. To maximize compliance and minimize error variance resulting from uncontrolled differences in the timing or other external aspects of the assessments, HRQOL data collection was an integral part of the clinical trial.²³ Wherever possible, the questionnaires were administered at the clinic, in a room where the patient would not be disturbed. The protocol specified that a responsible person (a nurse, clinician, or data manager) administer the questionnaire to the patient, request its completion, and be responsible for returning it to the EORTC Data Center. EORTC guidelines for administering questionnaires were provided, ensuring a standard approach to the collection of HRQOL data.

To limit the number of HRQOL variables investigated, we only selected those previously shown to have some prognostic value for OS either in the univariate or multivariate analysis when using the EORTC QLQ-C30 as observed by Luoma et al.¹³ The following HRQOL variables were therefore preselected for this analysis: physical functioning, emotional functioning, role functioning, social functioning, fatigue, pain, global health status, and appetite loss. Although in previous studies cognitive functioning, dyspnea, and constipation were also seen to have some prognostic value, they were not included in this analysis because they were believed to be irrelevant for our study population. We also controlled for important clinical factors; specifically, age, tumor-node-metastasis system stage, performance status, and estrogen receptor (ER) status.²⁴ The EORTC QLQ-C30 raw scores were calculated using the recommended EORTC procedures.²⁵ These involved transformation of raw scores into a linear scale ranging from 0 to 100, with a higher score representing a higher level of functioning or higher level of symptoms. In the case of missing items within a scale, the scale score was calculated using only those for which values were available, provided at least half of the items in the scale were completed.

Statistical Methods
The primary end point for the original trial was progression-free survival; secondary end points were response rate, safety, survival, HRQOL, and cost effectiveness. The planned sample size of 440 patients was based on the primary end point.

Survival curves and probabilities were estimated using the Kaplan-Meier technique.²⁶ Differences between survival curves were assessed using the log-rank test.²⁷ The Cox proportional hazards regression model²⁸ was used for both univariate and multivariate analyses of survival. For the analysis of prognostic factors for survival analysis the proportionality assumption was checked for each of the variables under study by testing the dependency of their hazard ratio over time.²⁹ The HRQOL scales described above were all included as continuous factors, using data from baseline assessments. Pearson's correlation coefficients were used to investigate the association between different covariates. All univariate analyses were stratified for treatment. Treatment was also included as a fixed covariate in the starting model for the multivariate analyses along with all of the covariates from the univariate analyses. When using a stepwise variable selection procedure to identify independent factors prognostic for survival, variables were added using forward selection according to a selection entry criterion of 0.05 and removed using backward elimination according to a selection stay criterion of 0.05. The importance of a prognostic factor was assessed via Wald-type test statistics, the hazard ratio, and its 95% CI for survival. A significance level of 5% was used for both clinical and patient-assessed HRQOL variables.

The replication stability of the final model predicting OS was investigated using a bootstrap resampling procedure as proposed by Sauerbrei et al,¹⁸ applied in the context of HRQOL by Van Steen et al.¹⁷ This technique generates a number of samples (each the same size as the original data set), by randomly selecting patients and replacing them before selecting the next patient (ie, bootstrap resampling). The frequency of inclusion of the component variables in the Cox proportional hazards regression models, including all of the selected covariates and stratified for treatment, fitted to each of these data sets using automatic forward stepwise selection (entry level of = .05), can be considered to be indicative for the importance of the factors.¹⁸ However, when we are interested in the best set of prognostic factors (which we usually are) rather than in the best independent prognostic factor, we need to account for the correlation structure of the potential prognostic factors under consideration. Therefore, we calculated the model selection probabilities on the basis of how many times a permissible model was selected in the bootstrap samples. These probabilities were then used as weights to obtain weighted averaged parameters.²⁰ All data analyses were performed using Statistical Analysis Software version 8.02 (2001, SAS Institute, Cary, NC).

	RESULTS

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A total of 435 locally advanced breast cancer patients were evaluated in this study (EORTC protocol 10921); 218 patients were allocated to the CEF arm and 217 patients were allocated to the EC arm. Of these patients, 182 (CEF) and 177 (EC) had baseline HRQOL measures completed and used in the analysis. Hence, the overall HRQOL baseline compliance was 82.5% (359 patients). In these 359 patients, 183 deaths were observed. This number of events is sufficient to detect a 0.66 hazard ratio (ie, increase from 5 years median survival to 7.57) with a power of 80% (given a two-sided test at 5% significance level). Median survival was 5.48 years for patients without a valid baseline HRQOL form and 5.34 years for patients with a valid baseline HRQOL form (P = .94, log-rank test). Characteristics of all the patients enrolled onto the trial were classified according to the availability of HRQOL data at baseline. Overall, patients' characteristics with or without baseline scores were well balanced with no significant differences between groups (data are listed in Table 1). All of the following analyses are based exclusively on patients having valid HRQOL baseline data.

View larger version (15K): [in this window] [in a new window]   Fig 1. Duration of overall survival in patients with inflammatory breast cancer. O, observed number of deaths; N, number of patients.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... REFERENCES

In the univariate analysis we included three important clinical variables (age, ER status, and tumor-node-metastasis system stage) and eight preselected HRQOL parameters (physical, emotional, role, and social functioning, as well as fatigue, pain, appetite loss, and global health status or quality of life; Table 2). Although performance status is an important clinical prognostic factor, we did not include it in our analyses because 89% of the patients presented a normal activity level according to the WHO performance status evaluation (Table 1). Previous findings found a link between ER status and psychosocial variables in breast cancer patients³⁰; however, we did not investigate this issue given the amount of missing data on ER status in our population. We tried to limit the number of HRQOL parameters to be included in the analysis to reduce multiple significance testing, but none of these variables were significant at the P = .05 level.

In the multivariate analysis only the tumor-node-metastasis system stage variable showed an impact in predicting OS (Fig 1). Patients diagnosed with inflammatory breast cancer (T4d) were shown to have poor survival when compared with other stages (P = .03). To check for the stability of these outcomes and to overcome possible bias related to the intercorrelation of the subscales of the EORTC QLQ-C30, we also applied a bootstrap-based MA technique.¹⁸ This is the first study to investigate the prognostic value of HRQOL parameters using this statistical technique, hence taking into account the issue of model uncertainty possibly induced by multicollinearity. The latter has been reported previously as a possible source of bias when interpreting outcomes.¹⁷

To limit the variables tested, we preselected eight key HRQOL variables shown to have some prognostic value, in either the univariate or multivariate analysis, in previous studies that have used the EORTC QLQ-C30. This might be a limitation of this work because the remaining parameters could have had a possible impact in predicting OS. However, we also conducted a secondary exploratory analysis including all the variables of the EORTC QLQ-C30, which resulted in similar findings; none of the HRQOL parameters were prognostic and only tumor-node-metastasis system stage significantly predicted survival (not shown).

This study showed that baseline HRQOL data are not predictive of OS in nonmetastatic breast cancer patients. Furthermore, given the stage of our population, we also investigated the impact of HRQOL data on disease-free survival (DFS), but there were no significant relationships. None of the preselected HRQOL variables was associated with longer DFS in the univariate analysis, and none was shown to predict independently DFS in the multivariate analysis (not shown). Our findings are consistent with previous research on early-stage breast cancer that has shown that psychologic symptoms and HRQOL parameters are not predictive of either DFS or OS when controlling for important clinical variables.^12,15 For example, Coates et al,¹² using the linear analog self-assessment to evaluate HRQOL in early breast cancer in the adjuvant setting, showed that pretreatment HRQOL scores were not predictive of DFS. Similar results were found by Tross et al,¹⁵ who showed that baseline psychologic symptoms, measured by the Symptoms Checklist-90-Revised, were not predictive of both DFS and OS in women with stage II breast cancer. Along with these previous studies, present research seems to support the view that, when controlling for important clinical factors, HRQOL does not predict survival in breast cancer patients with no distant metastasis.

Conversely, it must be emphasized that previous reports on baseline HRQOL parameters in metastatic breast cancer patients have shown strong correlation in predicting survival even when adjusting for important biomedical variables.^11-14,31 Although the evidence is now well documented for this advanced disease population, the reason for this association is still not clear, given that the different methodologies used so far have hampered a clear understanding. Different hypotheses, however, have been proposed as possible explanations for this association.^12,14,32 First, patients might be aware of the severity of their underlying illness, in a more accurate way than conventional prognostic indices, and this perception might affect their quality of life in such a way that those with worse underlying disease have a worse reported HRQOL. Second, it could be possible that a better perception of HRQOL might somehow positively influence length of survival. Nevertheless, although the first hypothesis does not indicate a true causative relationship between HRQOL and survival, the second hypothesis does. As previously suggested,¹² if there is a causative relationship, one can expect to see a correlation with clinical benefits when dealing with earlier stages of breast cancer and not only with advanced disease stages. In this respect, our findings, as well as those of previous reports,^12,15 seem to support the first hypothesis; we did not find a correlation between any of the HRQOL parameters investigated in our nonmetastatic breast cancer population and OS or DFS. Our results also seem to confirm that previously hypothesized in 1994 by Osoba³³; namely, that pretreatment HRQOL scores might not be of prognostic value for early-stage disease. It would seem that patients with advanced disease are better judges of their own health than is certain traditional clinical information.³⁴ This view also might reflect the finding that self-reported HRQOL has been shown to be more accurate than pure medical data, such as tumor size, in predicting survival in metastatic disease.³⁵

Within this possible scenario, we might speculate that, for early disease, clinical examinations (such as performance status or tumor staging) are more likely to override patients' self-reported HRQOL scores in predicting survival. Hence, this might explain the gap between the results obtained with metastatic disease and those from earlier stages.

This topic, however, needs additional evaluation before definitive conclusions can be drawn; different measures have been used to detect HRQOL and different analysis also have been used. Furthermore, more studies are needed to address this issue in nonmetastatic cancer patients. These findings encourage researchers to explore further the value of HRQOL in predicting survival, while also continuing to control for important biomedical variables.

	Appendix

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... REFERENCES

 
Participating centers of the original study (number of patients recruited): EORTC, Belgium: Institut Jules Bordet (18), Algemeen Ziekenhuis Middelheim (4), Centre Hospitalier Régional de la Citadelle (7), UZ Gasthuisberg (14), Clinique Saint Elisabeth (5); Czech Republic: General Teaching Hospital in Prague (2), Thomayer's Teaching Hospital (6), Center of Clinical Oncology (2), University Hospital in Plzen (2); France: Centre Henri Becquerel (16), Institut Bergonie (52), Centre Georges-François-Leclerc (11), Centre Alexis Vautrin (8), Centre René Huguenin (10); Poland: Medical University of Gdansk (47), Maria Skoldowska-Curie Cancer Center (1), Medical Academy of Lodz (16), Maria S. Curie Memorial Institute (14); Portugal: Hospitais da Universidade de Coimbra (13); Russia: Petrov Research Institute of Oncology (10), Cancer Research Center (17); Slovenia: The Institute of Oncology (22); South Africa: The Medical Oncology Center of Rosebank (3); the Netherlands: Diakonessenhuis (4), Antoni van Leeuwenhoekhuis (24), AZ Rotterdam-Daniel Den Hoed Kliniek (2), University Medical Center Nijmegen (5), AZ Utrecht (2), Leiden University Medical Center (2), AZ Maastricht (2); United Kingdom: Weston Park Hospital (7), Guy's Hospital (4); NCIC Clinical Trials Group (68); SAKK: Hopital Cantonal Universitaire de Genève (14), Inselspital (1), Kantonsspital St Gallen (6), Centre Hospitalier Universitaire Vaudois (7).

	Authors' Disclosures of Potential Conflicts of Interest

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... REFERENCES

 
The following authors or their immediate family members have indicated a financial interest. No conflict exists for drugs or devices used in a study if they are not being evaluated as part of the investigation. Acted as a consultant within the last 2 years: Martine J. Piccart, Amgen.

	Acknowledgment

 
We wish to thank Sheila Sanderson Scott.

	NOTES

 
F.E. is supported by the Camilla Samuel Fellowship in Memory of Lady Grierson. This work was carried out within the framework of the Belgian IUAP/PAI Network Statistical Techniques and Modeling for Complex Substantive Questions with Complex Data, and supported by grant MH59532 of the National Institutes of Health (K.V.S.).

Presented at the 40th Annual Meeting of the American Society of Clinical Oncology, New Orleans, LA, June 5-8, 2004.

Authors' disclosures of potential conflicts of interest are found at the end of this article.

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Submitted February 9, 2004; accepted May 26, 2004.

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				V. Arndt, H. Merx, C. Stegmaier, H. Ziegler, and H. Brenner Persistence of Restrictions in Quality of Life From the First to the Third Year After Diagnosis in Women With Breast Cancer J. Clin. Oncol., August 1, 2005; 23(22): 4945 - 4953. [Abstract] [Full Text] [PDF]

				F. Efficace and A. Bottomley Toward a Clearer Understanding of the Prognostic Value of Health-Related Quality-of-Life Parameters in Breast Cancer J. Clin. Oncol., February 20, 2005; 23(6): 1335 - 1336. [Full Text] [PDF]

				P. J. Goodwin and M. Ennis In Reply: J. Clin. Oncol., February 20, 2005; 23(6): 1336 - 1336. [Full Text] [PDF]

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