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P M Fayers

Publications and source records attributed to P M Fayers.

At least 37 records · Page 2Linked to original sources
PubMed1998

Testing for differences in multiple quality of life dimensions: generating hypotheses from the experience of hospital staff.

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.

Bayes Theorem↗
PubMed1998

Health-related quality of life in the general Norwegian population assessed by the European Organization for Research and Treatment of Cancer Core Quality-of-Life Questionnaire: the QLQ=C30 (+ 3).

PURPOSE: To obtain reference data on health-related quality of life (HRQOL) for the functional and symptom scales and single items of the European Organization for Research and Treatment of Cancer Core Quality-of-Life Questionnaire (EORTC QLQ-C30 [+ 3]) in a representative sample of the Norwegian general population. PATIENTS AND METHODS: A randomly selected sample of 3,000 people from the Norwegian population, aged 18 to 93 years, who represent geographic diversity, took part in this postal survey. The EORTC QLQ-C30 (+ 3) and a questionnaire about demographic data and health were sent by mail. A new questionnaire package was sent as a reminder after 3 weeks. RESULTS: The survey yielded a high response rate with 1,965 of 2,892 eligible persons responding (68%). There was a low amount of missing data (1.8%). Internal consistency was highly satisfactory and yielded Cronbach's alpha coefficients greater than 0.70 for all but two functional scales and one symptom scale. The sensitivity of the questionnaire was shown by the excellent discrimination between age and sex groups. Clinical validity was shown by the distinct differences according to age and sociodemographic characteristics. Women reported lower functional status and global quality of life (mean scale scores from 71.7 to 91.0) than men (mean scale scores from 75.4 to 94.4), and also more symptoms and problems. This was remarkably consistent across age groups, as was a decline in functional status with an increase in age. CONCLUSION: This is the first study that presented reference data from the EORTC QLQ-C30 (+ 3) in a sample from a general population and seems to provide valid measures of HRQOL within different age groups. The results may serve as a guideline for clinicians when interpreting HRQOL in their own groups of patients, and contributes to a better understanding of the significance of mean scores and their clinical relevance.

Adult↗
PubMed1997

Tutorial in biostatistics Bayesian data monitoring in clinical trials.

Many clinical trials organizations use regular interim analyses to monitor the accruing results in large clinical trials. In disease areas such as cancer, where survival is usually a major outcome variable, ethical considerations may lead to a stipulated requirement for data monitoring of mortality. This monitoring has frequently taken the form of limiting interim analyses to be few in number, and specifying an extreme p-value of, for example, p < 0.001 or p < 0.01 as grounds for early termination of the trial. Group-sequential methods are also used. However, none of these approaches formally assesses the impact that the results of a clinical trial may have upon clinical practice. Thus a trial might be terminated early because of apparent treatment benefits, but might fail to influence sceptical clinicians to modify their future treatment policy. We discuss the application of Bayesian methods, including the use of uninformative, sceptical and enthusiastic priors, and demonstrate that the necessary calculations are both straightforward to perform and easy to interpret statistically and clinically. Methods are illustrated with interim analyses of a clinical trial in oesophageal cancer.

Bayes Theorem↗
PubMed1997

Thirty years of Medical Research Council randomized trials in solid tumours.

This paper reviews the survival outcome from the randomized Phase III trials in solid tumours published on behalf of, or in collaboration with, the Cancer Therapy Committee (CTC) of the British Medical Research Council over a 30-year period to 31 December 1995. We review briefly the innovations in statistical methodology that have occurred over the period. We also note the ways in which standards of reporting the trials have improved, with more recent publications including, for example, estimates of the size of effect and confidence intervals. In all, 32 trials, involving over 5000 deaths in more than 8000 patients, have been published. Tumour types have included bladder, bone, brain, cervix, colon and rectum, head and neck, kidney, lung, ovary, prostate and skin. This paper presents a bibliography of these trials and gives details of the treatment comparisons made, the numbers of patients randomized and included in the analysis for each treatment arm, the observed numbers of deaths, and an estimate of the hazard ratio with associated 95% confidence intervals. The bibliography also indicates the main endpoint of each trial, whether recurrence-free survival or survival, and whether the trial was aimed at finding a difference or showing equivalence. The MRC trials have made an impact on both clinical practice and research activities. For example, the lung cancer programme has helped to establish the role of chemotherapy in small cell lung cancer and has developed better palliative treatment for non-small cell lung cancer. Trials of the radiosensitizer misonidazole have demonstrated that it has no role in the treatment of a number of cancers, trials of hyperbaric oxygen have defined the biological activity of this approach, and the appropriate dose of radiotherapy in patients with brain tumours has been found. The individual trials recruited between 44 and 824 patients (median 213). A better measure of the information in a trial is the number of deaths reported, which varied from 28 to 661 (median 145). A large proportion of the comparisons (8/29 or 28%) anticipating a survival difference, demonstrated such a difference at the 5% level of significance. Despite this, it is concluded that some of the trials should have been larger. In such cases, hindsight suggests either that an overoptimistic view of the anticipated survival benefit was taken at the design stage, or, for equivalence trials, the planned confidence interval was too wide for definitive statements to be made. As a consequence, the current CTC profolio of ongoing randomized trials open to patient accrual at 1 January 1996 have a projected median size of 600 and range from 120 to 2000 patients.

Clinical Trials, Phase III as Topic↗
PubMed1997

Quality of life assessment in clinical trials--guidelines and a checklist for protocol writers: the U.K. Medical Research Council experience. MRC Cancer Trials Office.

Many clinical trials groups now routinely consider including Quality of Life (QoL) assessment in trials. Indeed, several have policies stating that QoL should be considered as a potential endpoint in all new trials and that if it is not to be evaluated the applicants should justify not doing so. However, inclusion of QoL in clinical trials presents a number of difficult organisational issues, and serious problems in compliance have frequently been reported. Thus, in multicentre clinical trials many of the expected QoL questionnaires fail to be successfully completed and returned, although a few groups have claimed high success rates. However, it is well recognised that if questionnaires are missing, there may be bias in the interpretation of trial results, and the estimates of treatment differences and the overall level of QoL may be inaccurate and misleading. Hence it is important to seek methods of improving compliance, at the level of both the participating institution and the patient. We describe a number of methods for addressing these issues, which we suggest should be considered by all those writing clinical trial protocols involving QoL assessment. These are based upon over a decade of experience with assessing QoL in Medical Research Council (MRC) cancer clinical trials. In particular, we provide a checklist for points that should be covered in protocols. Examples are given from a range of current MRC Cancer Trials Office protocols, which it is proposed might act as templates when writing new protocols.

Clinical Protocols↗
PubMed1997

Causal indicators in quality of life research.

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.

Breast Neoplasms↗
PubMed1997

Factor analysis, causal indicators and quality of life.

Exploratory factor analysis (EFA) remains one of the standard and most widely used methods for demonstrating construct validity of new instruments. However, the model for EFA makes assumptions which may not be applicable to all quality of life (QOL) instruments, and as a consequence the results from EFA may be misleading. In particular, EFA assumes that the underlying construct of QOL (and any postulated subscales or 'factors') may be regarded as being reflected by the items in those factors or subscales. QOL instruments, however, frequently contain items such as diseases, symptoms or treatment side effects, which are 'causal indicators'. These items may cause reduction in QOL for those patients experiencing them, but the reverse relationship need not apply: not all patients with a poor QOL need be experiencing the same set of symptoms. Thus a high level of a symptom item may imply that a patient's QOL is likely to be poor, but a poor level of QOL need not imply that the patient probably suffers from that symptom. This is the reverse of the common EFA model, in which it is implicitly assumed that changes in QOL and any subscales 'cause' or are likely to be reflected by corresponding changes in all their constituent items; thus the items in EFA are called 'effect indicators.' Furthermore, disease-related clusters of symptoms, or treatment-induced side-effects, may result in different studies finding different sets of items being highly correlated; for example, a study involving lung cancer patients receiving surgery and chemotherapy might find one set of highly correlated symptoms, whilst prostate cancer patients receiving hormone therapy would have a very different symptom correlation structure. Since EFA is based upon analyzing the correlation matrix and assuming all items to be effect indicators, it will extract factors representing consequences of the disease or treatment. These factors are likely to vary between different patient subgroups, according to the mode of treatment or the disease type and stage. Such factors contain little information about the relationship between the items and any underlying QOL constructs. Factor analysis is largely irrelevant as a method of scale validation for those QOL instruments that contain causal indicators, and should only be used with items which are effect indicators.

Causality↗
PubMed1996

Randomization in clinical trials and experimental molecular medicine.

Randomization has become a standard procedure for clinical trial design, and is also widely used in other areas of biological research. This article will examine the reasons why randomization has become a sine qua non in some areas, yet remains far less widely adopted in experimental studies of molecular medicine. Should randomization be used routinely in the design of most laboratory experiments?

Bias↗
PubMed1995

Randomised consent designs in cancer clinical trials.

In 1977, Zelen proposed a new design for clinical trials with the aim of increasing recruitment by avoiding some of the problems associated with obtaining informed consent. These 'randomised consent' designs have proved controversial, and have not often been used. This paper explains the statistical aspects of single and double randomised consent designs and reviews some of the ethical issues. All identified published cancer treatment trials using a randomised consent design are considered in some detail. Reasons for and against the use of these designs are summarised.

Ethics, Medical↗
PubMed1995

Sample size: how many patients are necessary?

The need for sample size calculations is briefly reviewed: many of the arguments against small trials are already well known, and we only cursorily repeat them in passing. Problems that arise in the estimation of sample size are then discussed, with particular reference to survival studies. However, most of the issues which we discuss are equally applicable to other types of study. Finally, prognostic factor analysis designs are discussed, since this is another area in which experience shows that far too many studies are of an inadequate size and yield misleading results.

Clinical Trials as Topic↗
PubMed1994

On the development of the Medical Research Council trial of alpha-interferon in metastatic renal carcinoma. Urological Working Party Renal Carcinoma Subgroup.

This paper describes the steps taken by the British Medical Research Council (MRC) in developing the MRC RE01 trial, a randomized clinical trial for patients with metastatic renal cancer; we discuss the reasons for adopting a triangular sequential design and the impact that this has upon the monitoring of the trial. It had been suggested to the MRC that a trial of biological agents for metastatic renal carcinoma should be initiated. The Cancer Therapy Committee (CTC) of the MRC, through its associated site specific working parties, is responsible for designing and co-ordinating randomized trials of alternative treatments in cancer in solid tumours. Since no MRC working party for renal carcinoma existed at that time, development began by the formation of an ad hoc group set up under the auspices of the CTC. They assessed, by means of a postal questionnaire, U.K. interest in the trials of, and modalities utilized for, treatment of renal cancer. The responses focused attention on the important questions to ask and indicated the level of potential collaboration. These responses and related clinical and statistical issues suggested a protocol to compare medroxy-progesterone acetate (MPA) against alpha-interferon (alpha-IFN). In view of the special problems of comparing an expensive and potentially toxic therapy with an inexpensive and non-toxic standard, a sequential design was used rather than a fixed sample size design. Statistical issues raised and solutions provided are described. The method of establishing the trial data monitoring committee and a brief review of mortality from renal carcinoma in England and Wales are also included. The trial opened to patient recruitment on 1 January 1992. The formal statements regarding statistical issues that appear in the formal trial protocol (RE01) are set out in the Appendix.

Aged↗
PubMed1994

The use of multiple parameters to characterize cadmium-induced renal dysfunction resulting from occupational exposure.

Renal function has been examined in a group of 77 subjects occupationally exposed to cadmium fume and dust, together with a referent group of 103 age- and socioeconomically matched subjects. Fourteen biochemical parameters were measured on each subject. Three different ways of combining the information from all 14 tests were used to identify those subjects with renal dysfunction. These were first to count the number of parameters in which a subject recorded an abnormal test result. Second, the z value was computed for each parameter for each person by comparison with the mean and standard deviation of a derived normal population; these z scores were then summed. Lastly a multivariate distance measure, Mahalanobis D2, was determined for each subject from the distribution of normal subjects. The three approaches showed a considerable degree of agreement in identifying subjects with renal dysfunction, but they also displayed complementary strengths and weaknesses. The consensus of the three techniques was then taken to define truly dysfunctional subjects and each of the 14 parameters, and some combinations of pairs of parameters were tested as to their sensitivity and specificity. For this group of subjects, it was not possible to improve greatly on the use of retinol binding protein on its own. Were a second parameter to be chosen, it would be desirable to choose one reflecting the glomerular filtration rate, but the absence of a suitable sensitive biological monitoring parameter precludes a firm recommendation.

Blood Proteins↗
PubMed1993

Initiation of hypertension in utero and its amplification throughout life.

OBJECTIVE: To determine whether the relation between high blood pressure and low birth weight is initiated in utero or during infancy, and whether it changes with age. DESIGN: A longitudinal study of children and three follow up studies of adults. SETTING: Farnborough, Preston, and Hertfordshire, England, and a national sample in Britain. SUBJECTS: 1895 children aged 0-10 years, 3240 men and women aged 36 years, 459 men and women aged 46-54 years, and 1231 men and women aged 59-71 years. The birth weight of all subjects had been recorded. MAIN OUTCOME MEASURE: Systolic blood pressure. RESULTS: At all ages beyond infancy people who had lower birth weight had higher systolic blood pressure. Systolic blood pressure was not related to growth during infancy independently of birth weight. The relation between systolic pressure and birth weight became larger with increasing age so that, after current body mass was allowed for, systolic pressure at ages 64-71 years decreased by 5.2 mm Hg (95% confidence interval 1.8 to 8.6) for every kg increase in birth weight. CONCLUSIONS: Essential hypertension is initiated in fetal life. A raised blood pressure is then amplified from infancy to old age, perhaps by a positive feedback mechanism.

Adult↗