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.     

Missing quality of life data in cancer clinical trials: serious problems and challenges

Measurement of quality of life (QOL) in cancer clinical trials has increased in recent years as more groups realize the importance of such endpoints. A key problem has been missing data. Some QOL data may unavoidably be missing, as for example when patients are too ill to complete forms. Other important sources are potentially avoidable and can broadly be divided into three categories: (i) methodological factors; (ii) logistic and administrative factors; (iii) patient-related factors. Logistic and administrative factors, for example, staff oversights, have proven to be most important. Since most QOL measurements require patient self-report, it is usually not possible to rectify the failure to collect baseline data or any follow-up assessments. There is strong evidence that such data are not 'missing at random', and cannot be ignored without introducing bias. Although several approaches to the analysis of partly missing data have been described, none is entirely satisfactory. Prevention of avoidable missing data is better than attempted cure. In July 1996, an international conference on missing QOL data in cancer clinical trials reported the experience of most major groups involved. This paper will serve as an introduction to the problem and provide an estimation of its magnitude, and approaches to its prevention and solution.     

Guidelines for the design and conduct of clinical trials on dentine hypersensitivity

Clinical trials on dentine hypersensitivity have been numerous and protocols varied. To date there is little consensus as to the conduct of studies on this poorly-understood yet common and painful dental condition. A committee of interested persons from academia and industry was convened to discuss the subject of clinical trials on dentine hypersensitivity and a consensus report is presented. A double-blind randomized parallel groups design is recommended, although cross-over designs may be used for the preliminary screening of agents. Subjects may have multiple sites scored. Sample size will be determined by estimating the variability in the study population, the effect to be detected and the power of the statistical test to be used. Subject selection is based on a clinical diagnosis of dentine hypersensitivity, excluding those with conflicting characteristics such as currently-active medical or dental therapy. The vestibular surfaces of incisors, cuspids and bicuspids are preferred as sites to be tested. A range of sensitivity levels should be included. Tactile, cold and evaporative air stimuli should be applied. Negative and benchmark controls should be incorporated. Most trials should last 8 weeks. Sensitivity may be assessed either in terms of the stimulus intensity required to evoke pain or the subjective evaluation of pain produced by a stimulus using a visual analog or other appropriate scale. The subject's overall assessment may be determined by questionnaire. Outcomes should be expressed in terms of clinically significant changes in symptoms. Follow-up evaluation is required to determine the persistence of changes. At least 2 independent trials should be conducted before a product receives approval.     

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.     

Guidelines for determining and reporting food yields

The author discusses problems in compiling and evaluating data and recommends a standard protocol for determing yield of food. The recent extensive revision of Agriculture Handbook No. 102, Food Yields Summarized by Different Stages of Preparation, points up the urgent need for guidelines and a standard protocol.     

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.     

Statistical reporting of clinical trials with individual changes from allocated treatment

We consider clinical trials in which information is available about subjects' treatment changes after randomization. To understand whether any difference between randomized groups in the intention-to-treat analysis can be explained by such treatment changes, we need analysis strategies which take account of treatment actually received. Selection bias is then a potentially serious problem. We relate risk in a time-dependent proportional hazards model to current treatment, with treatment combinations coded in two alternative ways. To reduce selection bias, treatment history (number of treatments dropped) and baseline covariates can be added to the model. Including current risk markers would also reduce selection bias but makes interpretation difficult. The methods are illustrated using data from the British Medical Research Council (MRC) elderly hypertension trial, with time to cardiovascular death as an outcome. Results for the comparison of diuretic and beta-blocker treatment are similar in all analyses, suggesting that selection bias is small and adding support to the hypothesis that the observed treatment differences are due to the randomized treatments themselves.     

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)     

RAPORT radiology system: results of clinical trials

RAPORTTM, an automated radiology management and reporting system is currently operational in more than 25 hospital departments of varying sizes and types. Data have been gathered from 19 installations in operation for 6 months or longer and four systems which failed. Findings were as follows: 1. Mark sense forms were used in 71% of cases (29% dictation) and for an average of 70% of all pathologic material. 2. Report turnaround time ranged from 0.1 to 6 hr (average 2.5 hr) depending on departmental priorties and organization. 3. Rejection of the system was based upon inadequate documentation of needs prior to installation, poor preparation of staff members, and underestimation of the impact on computer systems on existing organizations. 4. System downtime averaged 2.5 hr per month. 5. The ratio of pathologic to normal reports did not vary significantly among university, government, and private hospitals. 6. RAPORT can no longer be considered an experimental system. Properly managed, it is an effective administrative tool which can significantly improve departmental service.     

Guidelines for assessments: Reactions to the commentators.

In this short article, the authors respond to the critiques of the four commentators (see records 2001-17060-010, 2001-17060-011, 2001-17060-012, 2001-17060-013 respectively) on the original "Guidelines" article (see record 2001-17060-009). They highlight areas of agreement and disagreement with the other authors in an effort to move the discussion forward. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Differences in urologist and patient assessments of health related quality of life in men with prostate cancer: results of the CaPSURE database

Premenstrual syndrome (PMS) is characterized by distressing somatic and behavioral symptoms that develop after ovulation, reach a maximum during the premenstrual days, and disappear within 4 days after the onset of menstruation. Corpus luteum formation is necessary for the presence of symptoms, but the role of luteal hormones is unclear. The aim of this work was to investigate the relationship between sex hormone serum concentrations and premenstrual symptom severity in patients with PMS. Mental and physical symptoms were marked on a validated visual analog scale by 30 PMS patients every evening. Daily blood samples were taken in the luteal phase and in most of the follicular phase. Estradiol, progesterone, FSH, and LH were analyzed. Symptom severity was calculated as the number of negative symptoms expressed per day and as summarized scores of negative ratings. Based on premenstrual hormone concentrations and using the median split method, patients were divided into groups with high and low hormone levels. The pattern of expressed symptoms and summarized scores during the menstrual cycle was similar for the 2 groups. High concentration of luteal-phase estradiol and LH were related to the severity of negative premenstrual symptoms.     

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.     

Resource costing for multinational neurologic clinical trials: methods and results

Failure of synthetic heart valves is usually caused by tearing and calcification of the leaflets. It is postulated that leaflet fibre-reinforcement leads to a decrease of tears and perforations as a result of reduced stresses in the weaker parts of the leaflets. A three-dimensional finite element model of a reinforced three-leaflet valve prosthesis was developed to analyse the stress reduction. Different fibre reinforcements were investigated and the model responses were analysed for stresses that are expected to contribute to failure of fibre-reinforced valve prostheses. Results of these simulations show that, in peak stress areas of reinforced models, up to 60% of the maximum principal stresses is taken over by fibres and that, in some cases of reinforcement, a more homogeneous stress distribution is obtained.