Missing data in quality of life research in Eastern Cooperative Oncology Group (ECOG) clinical trials: problems and solutions

Incorporation of quality of life (QOL) investigation into Eastern Cooperative Oncology Group (ECOG) multi-centre clinical trials has led to innovative strategies for protocol design and high quality data collection. A scientific advisory committee reviews protocol design components, measurement selection, timing of assessments and compliance issues. Extensive educational programmes provide information about the scientific and clinical relevance of QOL protocols, as well as practical strategies for data collection and management. Compliance with QOL data collection standards is prospectively monitored and evaluated. Preliminary results from eight ECOG-run protocols found overall compliance to be approximately 85 per cent (94 per cent at baseline and 73 per cent during treatment). Selected patient and institutional factors were evaluated for their association with compliance.     

Comparison of several model-based methods for analysing incomplete quality of life data in cancer clinical trials

This paper considers five methods of analysis of longitudinal assessment of health related quality of life (QOL) in two clinical trials of cancer therapy. The primary difference in the two trials is the proportion of participants who experience disease progression or death during the period of QOL assessments. The sensitivity of estimation of parameters and hypothesis tests to the potential bias as a consequence of the assumptions of missing completely at random (MCAR), missing at random (MAR) and non-ignorable mechanisms are examined. The methods include complete case analysis (MCAR), mixed-effects models (MAR), a joint mixed-effects and survival model and a pattern-mixture model. Complete case analysis overestimated QOL in both trials. In the adjuvant breast cancer trial, with 15 per cent disease progression, estimates were consistent across the remaining four methods. In the advanced non-small-cell lung cancer trial, with 35 per cent mortality, estimates were sensitive to the missing data assumptions and methods of analysis.     

Why are missing quality of life data a problem in clinical trials of cancer therapy?

Assessment of health related quality of life has become an important endpoint in many cancer clinical trials. Because the participants of these trials often experience disease and treatment related morbidity and mortality, non-random missing assessments are inevitable. Examples are presented from several such trials that illustrate the impact of missing data on the analysis of QOL in these trials. The sensitivity of different analyses depends on the proportion of assessments that are missing and the strength of the association of the underlying reasons for missing data with disease and treatment related morbidity and mortality. In the setting of clinical trials of cancer therapy, the assumption that the data are missing completely at random (MCAR) and analyses of complete cases is usually unjustified. Further, the assumption of missing at random (MAR) may also be violated in many trials and models appropriate for non-ignorable missing data should be explored. Recommendations are presented to minimize missing data, to obtain useful documentation concerning the reasons for missing data and to perform sensitivity analyses.     

Incomplete quality of life data in randomized trials: missing forms

Analysing quality of life (QOL) data may be complicated for several reasons, such as: repeated measures are obtained; data may be collected on ordered categorical responses; the instrument may have multidimensional scales, and complete data may not be available for all patients. In addition, it may be necessary to integrate QOL with length of life. The major undesirable effects of missing data, in QOL research, are the introduction of biases due to inadequate modes of analysis and the loss of efficiency due to reduced sample sizes. Currently, there is no standard method for handling missing data in QOL studies. In fact, there are very few references to methods of handling missing data in this context. The aim of this paper is to provide an overview of methods for analysing incomplete longitudinal QOL data which have either been presented in the QOL literature or in the missing data literature. These methods of analysis include complete case, available case, summary measures, imputation and likelihood-based approaches. We also discuss the issue of bias and the need for sensitivity analyses.     

Incomplete quality of life data in randomized trials: missing items

Missing data has been a problem in many quality of life studies. This paper focuses upon the issues involved in handling forms which contain one or more missing items, and reviews the alternative procedures. One of the most widely practised approaches is imputation using the mean of all observed items in the same subscale. This, together with the related estimation of the subscale score, is based upon traditional psychometric approaches to scale design and analysis. We show that it may be an inappropriate method for many of the items in quality of life questionnaires, and would result in biased or misleading estimates. We provide examples of items and subscales which violate the psychometric foundations that underpin simple mean imputation. A checklist is proposed for examining the adequacy of simple imputation, and some alternative procedures are indicated.     

Guidelines for reporting results of quality of life assessments in clinical trials

BACKGROUND: Current guidelines on the management of asthma advocate the use of anti-inflammatory treatment in all but mild disease. They define disease control in terms of clinical criteria such as lung function and symptoms. However, the relationship between the clinical control of the disease and inflammation of the airways is not clear. A cross sectional study was therefore undertaken to investigate the relationship between airways inflammation and measures of clinical control and bronchial hyperresponsiveness in asthmatic patients treated with inhaled steroids. METHODS: Twenty six atopic adults (19-45 years) with mild to moderate asthma (baseline forced expiratory volume in one second (FEV1) > or = 50% predicted, concentration of histamine causing a 20% fall in FEV1 (PC20) 0.02-7.6 mg/ml) on regular treatment with inhaled steroids entered the study. Diary card recordings during the two weeks before a methacholine challenge test and bronchoscopic examination were used to determine peak flow variability, symptom scores, and use of beta 2 agonists. Biopsy specimens were taken by fibreoptic bronchoscopy from the carina of the right lower and middle lobes, and from the main carina. Immunohistochemical staining was performed on cryostat sections with monoclonal antibodies against: eosinophil cationic protein (EG1, EG2), mast cell tryptase (AA1), CD45, CD22, CD3, CD4, CD8, CD25, and CD45RO. The number of positively stained cells in the lamina propria was counted twice by using an interactive display system. RESULTS: There were no differences in cell numbers between the three sites from which biopsy specimens were taken. The PC20 for methacholine was inversely related to the average number of total leucocytes, EG1+, and EG2+ cells, mast cells, CD8+, and CD45RO+ cells in the lamina propria. These relationships were similar for each of the biopsy sites. Symptom scores, beta 2 agonist usage, FEV1, and peak flow variability were not related to any of the cell counts. CONCLUSIONS: Infiltration of inflammatory cells in the lamina propria of the airways seems to persist in asthmatic outpatients despite regular treatment with inhaled steroids. The number of infiltrating leucocytes such as mast cells, (activated) eosinophils, CD8+, and CD45RO+ cells in bronchial biopsy specimens from these patients appears to be reflected by airway hyperresponsiveness to methacholine, but not by symptoms or lung function. These findings may have implications for the adjustment of anti-inflammatory treatment of patients with asthma.     

Methodological and statistical issues of quality of life (QoL) and economic evaluation in cancer clinical trials: report of a workshop

In recent years, quality of life (QoL) and economic evaluations have become increasingly important as additional outcome measures in cancer clinical trials. However, both fields of research are relatively new and in need of finding solutions to a substantial number of specific methodological problems. This paper reports on the proceedings of a symposium aimed at summarising and discussing some of the most contentious methodological and statistical issues in QoL and economic evaluations. In addition, possible solutions are indicated and the most pertinent areas of research are identified. Issues specific to QoL evaluations that are addressed include clinically meaningful changes in QoL scores; how to analyse QoL data and to handle missing and censored data and integration of length of life and QoL outcomes. Issues specific to economic evaluations are the advantages and disadvantages of various outcome measures; statistical methods to analyse economic data and choice of decision criteria and analytical perspective. How to perform QoL and economic evaluations in large and simple trials and whether the gap between QoL and utility measures can be bridged are also discussed.     

Evaluating the effects of drugs on behavior and quality of life: An alternative strategy for clinical trials.

Conventional clinical trials involve tests of hypotheses with statistics computed from values of dependent variables alone. An alternative is to test hypotheses with statistics computed from benefit/harm scores that measure longitudinal associations between dose and values of the dependent variables. The proposed standardized measure of benefit/harm quantifies the strength of evidence that a patient did either better or worse while on treatment. A benefit/harm score, particularly when obtained from a randomized, N-of-1 trial, indicates a beneficial or harmful treatment effect for the individual. Benefit/harm scores from samples of patients are evaluated with standard statistical tests, with or without group comparisons, to make inferences about populations. The proposed alternative strategy can yield within-patient indicators of treatment effect that are more reliable, valid, comprehensive, and detailed. This, in turn, could help make many population-based clinical trials more informative, cost-effective, and clinically useful for participants. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluating health-related quality of life in patients with facial acne: development of a self-administered questionnaire for clinical trials

Although psychosocial aspects of skin diseases are well known, disease-specific questionnaires validated for use in clinical trials are not available to assess the impact of facial acne on health-related quality of life or to evaluate therapeutic change. Development of such an instrument was undertaken and included item generation, reduction and pilot-testing phases. By interviewing acne subjects and dermatologists and literature review, 168 possible items were identified. Next, 165 acne subjects identified which items affected them and rated importance on a 5-point scale. Reduction to a brief questionnaire was performed by evaluating patient-perceived importance and factor analysis; four domains were identified (self-perception, role-emotional, role-social, acne symptoms). After pilot-testing for comprehension in acne subjects, further revisions were made to improve clarity and applicability. The resulting instrument takes 10 minutes to complete, and consists of 24 questions assessing how acne affected certain aspects of patients' lives during the past week on a 7-point scale. Thus, an instrument with excellent content validity was developed to assess health-related quality of life in patients with facial acne, and is comprised of statistically meaningful items of importance to patients. Other measurement characteristics are being assessed in a recently initiated study to evaluate test-retest reliability and responsiveness to therapy.     

Compliance in quality of life data: a Norwegian experience

Compliance is of extreme importance in assessing quality of life since lost data never can be retrieved. In order to assess this issue in various studies, a cross-sectional study in cured cancer patients, three prospective trials and a normative study were explored. In the cross-sectional study 82 per cent of the patients completed the questionnaires after one reminder. More females than males answered the questionnaires. The compliance rate varied from 99 per cent to 62 per cent in the prospective studies depending upon time after inclusion. It seems that compliance decreases during follow up, primarily because of disease progression. In one of the prospective studies low compliance rate (approximately 30 per cent) was found in the questionnaire assessing religious issues. In the normative study 68 per cent of the population completed the questionnaire. No gender differences were found, but younger males and elderly women were poor compliers. In conclusion, our data support that most patients complete quality of life questionnaires. It seems that patients with inferior education, reduced physical function and with progressive/terminal disease are low compliers. Introduction of the first quality of life questionnaires to the patients is of great importance. Detailed information about the study should be given and the importance of completing the questionnaires should be underlined.     

Lung cancer and quality of life

Quality of life (QOL) is frequently used as an endpoint of measurement in cancer treatment. Compared to other cancers, there are only a few reports of QOL in the treatment of lung cancer. Several QOL instruments have been developed and this paper reports experience with the functional Living-Index-Cancer and Quality of Life Index tools in Lung Cancer treatment, in a randomised controlled trial of chemotherapy.     

Effect of non-random missing data mechanisms in clinical trials

A simple form of non-ignorable missing data mechanisms based on two parameters is used to characterize the amount of missing data and the severity of non-randomness in clinical trials. Based on the formulation, the effect of non-randomly missing data on simple analyses which ignore the missing data is studied for binary and normally distributed response variables. In general, the effect of the non-randomly missing data on the bias and the power increases with the severity of non-randomness. The bias can be positive or negative and the power can be less than or greater than when the data are missing at random. The results of the analysis, ignoring the missing data, can be seriously flawed if the non-randomness is severe, even when only a small proportion of the sample is missing. The problem is more pronounced in the case of normally distributed response variables with unequal variances.     

Meta-analysis of clinical trials for chemotherapy in cancer

Meta-analysis has attracted great interest among clinical practitioners in recent years, leading to a steady output of related publications. Meta-analytic articles are easily found in the MEDLINE database using the publication-type option. This paper reviews how to use and understand meta-analysis with a special reference to chemotherapy applied to cancer patients. It is described in relationship to evidence-based medicine (EBM) and clinical practice guidelines. Cochrane collaboration is also referred to as an active voluntary organization conducting meta-analysis. In the technical sections, statistical issues and graphic representations are clearly illustrated using the example of hepatic arterial infusion for colorectal cancer patients. The difference between fixed and random effects models is briefly explained. Finally, an example from Cochrane Library, namely progestagen therapy for endometrial cancer, is illustrated to show the implications of meta-analysis for clinical practice.     

Health-related quality of life assessment in clinical practice

Assessment of biochemical responses to therapy is routine in the management of patients with end stage renal disease (ESRD). Assessment of health-related quality of life (HRQOL), however, is less common. Previous research indicates that HRQOL is a meaningful indicator that should be integrated into clinical practice. HRQOL is longitudinally evaluated in in-centre hemodialysis patients using the RAND 36-item Health Survey 1.0. Caregivers incorporate scores from this instrument into their assessment of patient functioning and well-being. HRQOL scores can be utilized to evaluate responses to changes in therapy, and to direct clinical decision-making, adding an important dimension to holistic, quality care for ESRD patients.