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The aim of the study was to compare the quality of life (QL) of patients treated with single-agent paclitaxel versus doxorubicin as first-line chemotherapy for advanced breast cancer. 331 patients with advanced breast cancer were randomised, with 294 eligible for analysis. Patients completed both the EORTC QLQ-C30 questionnaire and the Rotterdam Symptom Checklist (RSCL) with six additional items, at baseline and after the third, fifth and seventh cycles of chemotherapy. A significant difference in progression-free survival in favour of doxorubicin caused a bias in the data with differences in expected completion rates of questionnaires beyond cycle three. Therefore, statistical comparisons were performed only for the first three cycles. Baseline compliance was 64% and 61% for the QLQ-C30 and RSCL questionnaires, respectively. Doxorubicin was associated with significantly more nausea/vomiting (P=0.001), loss of appetite (P=0.010) and a greater burden of disease and treatment (P=0.044), but with less bone pain (P=0.042) and rash (P=0.045) than paclitaxel. Both treatments were associated with improved emotional function and reduction in psychological distress at cycle 3. Longitudinal data suggested that doxorubicin was associated with less pain, specifically bone pain. Doxorubicin was more active but may have had more side-effects during the first three cycles. Long-term QL outcomes could not be assessed.

The focus of the paper is to describe how to present data from studies on health-related quality of life (H-QoL) in a way that is simple and clinically relevant. Data from a longitudinal study of patients with advanced stages of cervix cancer are used. One hundred and eighteen patients filled out questionnaires (including EORTC QLQ-C30) 7 times over a period of 2 years. The following issues are considered: (1) The use of a panel for an initial overview of data. (2) The visual difference between using mean and median values. (3) Box-whisker plots to illustrate the variability of the data. (4) The effect of combining categorical data into fewer categories. (5) Individual patient profiles showing the wide variability among patients. (6) A table showing the change of scores over a one-year period. (7) "Prognostic plots" dividing the initial scores and the following scores. (8) Plotting changes over time. (9) Illustration of the impact of non-random dropout. (10) The effect of drop-out for the patients who fill out two sequential assessments. (11) The use of healthy controls to help answer the question "what is normal?".

Palliative care aims at improving the patient's quality of life. Clinical trials, therefore, often include the patient's subjective evaluation of symptoms and psychosocial problems, so-called health-related quality of life (HRQL), as end-points. Unfortunately, there are frequently methodological weaknesses in the assessment of HRQL. This paper discusses four criteria which can be used in the evaluation of the quality of such studies: I. The authors should document that they have included the relevant HRQL issues in the questionnaire. If a trial misses important issues, its results may be misleading. II. The sample size should be sufficient to detect meaningful differences. Many trials are too small. III. The assessment of HRQL should have the appropriate timing, reflecting the research questions. The symptoms and the benefit resulting from treatments are not constant over time and often have cyclic patterns. The results may therefore be dependent on the timing of the administration of questionnaires to patients and on the time frames specified in the instructions. IV. The data must be reasonably complete. Incomplete data cannot be avoided in palliative care research, but missing data due to administrative failures or unrealistic schedules must be avoided. A pilot study may show whether a study is feasible. Missing data are likely to bias results. Many published palliative care studies are suboptimal with regard to one or more of these four criteria. This should be considered when reading published studies and when new trials are planned.

Objectives: To investigate the effect of the bisphosphonate clodronate on the occurrence of skeletal events (hypercalcaemia, fractures and radiotherapy) in breast cancer patients with bone metastases., Design: Prospective, randomized, controlled, clinical trial., Setting: A department of oncology in a university hospital., Subjects: One hundred patients who received firstline systemic antineoplastic treatment for metastatic breast cancer with bone involvement were randomized to receive clodronate as two 400 mg capsules twice a day for 2 years or no additional therapy., Results: In the clodronate group the number of skeletal events was reduced to 14 events in 48 evaluable patients as compared with 21 events in 51 evaluable control patients. The time to the first skeletal event was significantly longer in the clodronate group than in the control group (P = 0.015) and the most distinct difference was a lower occurrence of fractures in the clodronate group (P = 0.023). After 15 months the effect of clodronate tended to decline as the need for radiotherapy increased in the clodronate group compared with the control group (P = 0.069). Significant improvements in several quality-of-life aspects were seen in both groups during the first 6 months, but there was no significant difference between the groups. No effect was observed on time to radiologically evaluated disease progression in bone or on survival. The most frequent side-effects resulting in discontinuation of clodronate were nausea and diarrhoea., Conclusion: Oral clodronate is associated with a temporary reduction of morbidity related to bone metastases in breast cancer patients.

Breast cancer and its treatment have been associated with psychological morbidity. In this study our aim was to quantify the excess anxiety and depression resulting from breast cancer. We compared 538 newly diagnosed breast cancer patients at low risk of recurrence (87.0% responded) to 872 women randomly selected from the Danish general population (69.7% responded) using the Hospital Anxiety and Depression Scale (HADS). Contrary to expectations, the proportions classified as "cases" of anxiety and depression were not significantly different in the two groups. The breast cancer patients' mean HADS scores were significantly lower than those in the general population sample (anxiety, P = 0.021; depression, P < 0.001), indicating less anxiety and depression. However, we question the validity of this comparison. The HADS may not be suitable for use in the general population and there may be methodological problems in comparisons of groups whose life situations are very different.

This study examines the effect of socio-economic inequalities on the tumour size at diagnosis and the choice of surgical treatment in Danish women with breast cancer. The Danish Breast Cancer Cooperative Group (DBCG) registers all women with breast cancer in Denmark and provides clinical register data on tumour size and surgical treatment for 1594 women <75 yr diagnosed with breast cancer between 1991 and 1996. A questionnaire including questions on social class was sent to the women. The tumour size at diagnosis (an indicator of access to treatment) and the surgical procedure (lumpectomy or mastectomy) for patients who were potential candidates for lumpectomy were the main outcome measures examined. Social class was not associated with tumour size at diagnosis. The tumour size was associated with age and the existence of a mammographic screening program in the county. However, treatment was strongly related to social class. Among women considered candidates for lumpectomy 77% underwent lumpectomy in the highest social class, compared to 50% in the lowest social class. Treatment was associated with age, tumour size and hospital status. It was concluded that the study showed no socio-economic inequalities related to access to health services as measured by tumour size, though significant social differences were found regarding treatment.

We used general population data (n = 4084) to examine data completeness, response consistency, tests of scaling assumptions, and reliability of the Danish SF-36 Health Survey. We compared traditional multitrait scaling analyses to analyses using polychoric correlations and Spearman correlations. The frequency of missing values was low, except for elderly people and people with lower levels of education. Response consistency was high and compared well with results for the U.S. SF-36. For respondents with computable scales in all eight domains, scaling assumptions (item internal consistency, item discriminant validity, equal item-own scale correlations, and equal variances) were satisfactory in the total sample and in all subgroups. The SF-36 could discriminate between levels of health in all subgroups, but there were skewness, kurtosis, and ceiling effects in many subgroups (elderly people and people with chronic diseases excepted). Concerning correlation methods, we found interesting differences indicating advantages of using methods that do not assume a normal distribution of answers as an addition to traditional methods.

In clinical trials with a quality of life (QoL) component, it is usual to monitor several QoL dimensions at several points in time. Multiple significance tests without formal hypotheses are problematic. It is not always feasible to specify a priori hypotheses for all variables. Can such studies be used to generate hypotheses for testing in later research only? We developed a method which can allow for formal hypothesis testing on a data set collected without a priori hypotheses in the protocol. We surveyed experienced physicians and nurses treating patients, to obtain independent expectations about differences in QoL dimensions. These 'staff expectations' will be used in the analysis of QoL data collected from breast cancer patients taking part in three randomized trials of adjuvant therapy. We propose frameworks for the informal and formal use of the experience of the staff in testing for group differences in patients' QoL scores. The method described here is anticipated to be useful for QoL studies in general, even when a priori hypotheses were specified before the studies were initiated.

The European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Study Group has adopted a modular approach to quality of life (QoL) assessment in cancer clinical trials. The core instrument (the EORTC QLQ-C30) covers a range of QoL issues relevant to a broad spectrum of patients with cancer. The QLQ-C30 is designed to be supplemented by more specific subscales ('modules') to assess aspects of QoL of particular importance to specific subgroups of patients. Since individual members of the study group were to be involved in module development, guidelines were established. The primary aim of these guidelines was to standardize the module development process in order to ensure uniformly high quality across modules. This paper gives an update of the work completed to date. First, while the guidelines proved practical for module development, producing modules that exhibit adequate levels of psychometric and cross-cultural validity, experience pointed to three areas where the guidelines required more precision. These amendments will be provided and include (1) stricter monitoring of the developmental process from within the study group, (2) the explicit requirement of involvement of the study group and (3) a more precise definition of the criteria to be fulfilled before modules are allowed to be called 'EORTC modules'. Second, an overview of the modules currently under development or available for general use is provided. These modules include those for body image, high-dose chemotherapy, leukaemia, myeloma, palliative care and the following cancers: bladder, brain, breast, colorectal, head and neck, lung, oesophageal, ophthalmic, ovarian, pancreas and prostate. Finally, the need for the coordination of efforts in module development, both from within and outside the EORTC, is discussed.

Quality of Life (QOL) questionnaires contain two different types of items. Some items, such as assessments of symptoms of disease, may be called causal indicators because the occurrence of these symptoms can cause a change in QOL. A severe state of even a single symptom may suffice to cause impairment of QOL, although a poor QOL need not necessarily imply that a patient suffers from all the symptoms. Other items, for example anxiety and depression, can be regarded as effect indicators which reflect the level of QOL. These indicators usually have a more uniform relationship with QOL, and therefore a patient with poor QOL is likely to have low scores on all effect indicators. In extreme cases it may seem intuitively obvious which items are causal and which are effect indicators, but often it is less clear. We propose a model which includes these two types of indicators and show that they behave in markedly different ways. Formal quantitative methods are developed for distinguishing them. We also discuss the impact of this distinction upon instrument validation and the design and analysis of summary subscales.

Patient-rated questionnaires are increasingly used to assess health-related quality of life. We studied one aspect of the validity of such measures that has rarely been investigated do patients interpret questionnaires in the same way as do the researchers reporting the results? If not, there may be a problem. We employed the EORTC QLQ-C30 quality-of-life questionnaire to study 95 cancer patients and measured the agreement between (1) the patient's self-assessment and (2) an observer's rating of the patient's open-ended responses to the same questionnaire administered as an interview. The observer made qualitative recordings describing potential misinterpretations. The agreement between patients' and observers' ratings was high (median kappa = 0.85, range 0.49-1.00). The qualitative data revealed a few minor validity problems. One of these, selective reporting, may lead to systematic errors; some patients reported only what they considered "relevant" symptoms. The combination of quantitative and qualitative methods proved useful for questionnaire validation.

The aim of this was to derive population-based norms for women completing the EORTC QLQ-C30 version 1 which is designed for use with patients who have cancer. The study was conducted using two different questionnaires: one designed for use in female patients with breast cancer, the other for those with gynaecological cancers, but both including the EORTC QLQ-C30. The women were drawn from the Danish Central Population Register without knowledge of their health status and divided at random between the two questionnaires. All procedures for collecting data were identical. The response rate for those receiving the gynaecological cancer (GS) questionnaire was 49% and it was 71% for the breast cancer (BS) questionnaire. Detailed comparison between the two samples revealed several EORTC QLQ-C30 items showing a clear difference in distribution of scores between them. Because of this and the possible bias due to the relative low age-related response rate in GS, only the results from the BS are used for constructing norms. The norms cover all 30 single items on the EORTC QLQ-C30 and the nine derived scales, for women in four 10-year age groups commencing at 30 years and for those aged 70-75. Clear trends in, for example, declining ability to undertake strenuous activity are illustrated and quantified. Levels of certain symptoms, such as pain, are surprisingly high although it is recognized that the population sampled will contain a proportion of women with active disease including cancer. We recommend the use of these norms both as an aid to the clinical assessment of an individual patient, and to assist in the interpretation of clinical trial and longitudinal quality of life data. As a secondary result, we note that a population-based sample will have a lower response rate to a questionnaire with more questions, especially if many of these extra questions are on sexual issues.

Purpose: To construct a breast cancer-specific quality-of-life questionnaire (QLQ) module to be used in conjunction with the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and to test its reliability and validity cross-culturally., Patients and Methods: Module construction took place after the EORTC guidelines for module development. The module--the QLQ-BR23--consists of 23 items covering symptoms and side effects related to different treatment modalities, body image, sexuality, and future perspective. This module was tested in 170 Dutch, 168 Spanish, and 158 American cancer patients at two points in time. The timing for the Dutch and Spanish patients was before and during treatment with radiotherapy or chemotherapy. For the American patients, the questionnaire was administered at admission at the breast clinic and 3 months after the first assessment., Results: Multitrait scaling analysis confirmed the hypothesized structure of four of the five scales. Cronbach's alpha coefficients were, in general, lowest in Spain (range; .46 to .94) and highest in the United States (range; .70 to .91). On the basis of known-groups comparisons, selective scales distinguished clearly between patients differing in disease stage, previous surgery, performance status, and treatment modality, according to expectation. Additionally, selective scales detected change over time as a function of changes in performance status and treatment-induced change., Conclusion: These results lend support to the clinical and cross-cultural validity of the QLQ-BR23 as a supplementary questionnaire for assessing specific quality-of-life issues relevant to patients with breast cancer.

Item bias (differential item functioning) analysis examines whether the construction of an index from two or more variables results in bias in relation to sex, age, or other criteria. Item bias may lead to erroneous conclusions because of distortion or dilution of the effects measured. In comparing groups, item bias analysis, tests whether the information about possible differences between groups, obtained by the variables constituting an index, are correctly passed on by the index score. We examined a quality of life questionnaire answered by 1189 breast cancer patients. We found age-bias or bias in the comparison of groups receiving different treatments in three out of nine indexes. Recommendations for the interpretation of these indexes are made. Item bias analysis is a useful method examining an issue not covered by traditional psychometric tests.

The EORTC Study Group on Quality of Life (the Study Group) has adopted a modular approach to quality of life (QOL) assessment in cancer clinical trials. A 'core' instrument-the QLQ-C30-has been designed to cover a range of QOL issues relevant to a broad spectrum of cancer patients. It is intended that this QLQ-C30 be supplemented by more specific subscales ('modules') to assess aspects of QOL of particular importance to specific subgroups of patients. Since individual members of the Study Group were to be involved in module development, guidelines were required to standardize the module development process in order to ensure uniformly high quality across modules. These guidelines are presented in this paper. The term 'module' is defined, the composition of modules is outlined, and the criteria used to develop modules are specified. The module development process, consisting of four phases (generation of relevant QOL issues, operationalization of the QOL issues into a set of items, pretesting the module questionnaire, and large-scale field-testing) is described in detail. Further, issues related to cross-cultural instrument development, and the need for monitoring the module development process from within the Study Group are discussed. Finally, experiences with developing two site-specific modules (i.e., for head and neck, and breast cancer), are presented and the extent to which the guidelines meet practical requirements is discussed. The guidelines appear to provide a practical tool for module construction, that can facilitate the development of a comprehensive system for assessing the QOL of cancer patients internationally.