Quality of life six months after myocardial infarction treated with thrombolytic therapy. AUS-TASK Group. Australian arm of International tPA/SK Mortality Trial

OBJECTIVE

To assess and compare quality of life of patients six months after an acute myocardial infarction treated with one of two thrombolytic agents, streptokinase (SK) or recombinant tissue plasminogen activator (tPA).

DESIGN

A cohort study of consecutive patients randomly allocated to thrombolytic therapy and treated in hospitals participating in the Australian arm of the International tPA/SK Mortality Trial (AUS-TASK).

PATIENTS AND SETTING

776 patients with acute myocardial infarction were asked to complete questionnaires at their follow-up clinic visit six months after the infarct.

MAIN OUTCOME MEASURES

Two measures were used: (i) the York Health Measurement Questionnaire, which measures activities and distress and provides basic descriptors of quality of life; and (ii) a time trade-off question about the number of years a person would be willing to give up in exchange for returning to full health.

RESULTS

The quality of life of the 714 respondents (92%) was generally high, with a mean index of 0.98. The five main areas causing distress were: lack of energy; breathlessness; anxiety; difficulty sleeping; and pain. In the time trade-off question, the mean number of years respondents were willing to forgo, out of 15 years, was 0.87 years; while 76% did not think it worthwhile to forgo any time. The 8% of patients who declined to answer the questionnaire were in significantly poorer health (New York Heart Association classification, P = 0.01; and Karnofsky index, P < 0.001). There were no significant differences in quality of life or time trade-off answers between patients allocated to streptokinase or tPA (P = 0.96 and 0.73, respectively).

CONCLUSIONS

Quality of life six months after myocardial infarction is generally high, and most patients are able to return to normal activities. However, it is significantly impaired in a small group of patients, mainly those with a subsequent stroke or re-infarction. There was no significant difference in quality of life between those treated with tPA and those with streptokinase.

Efficient study designs to assess the accuracy of screening tests

Evaluating a screening test often requires estimation of test sensitivity and specificity with appropriately narrow confidence intervals and at least cost. If the major cost is the reference ("gold") standard, savings arise from reducing the large number of test negatives that are verified by the reference standard. On the basis of the formulae of Begg and Greenes (Biometrics 1983;39:207-15), the authors determine the optimal sampling strategy for test positives and test negatives to minimize the total sample size that needs to be verified for a given confidence interval width for sensitivity. Unless sensitivity is very high, verifying more test positives and fewer test negatives than would occur with equal sampling fractions is appropriate. For example, if the sensitivity is 0.7 and the specificity is 0.99, the optimal sampling strategy is for 6.2% of those verified to be test positives, compared with 1.7% in the case of equal sampling fractions. At a disease prevalence of 0.01, the 3.3-fold increase in test positives results in a saving of about 15% in the test negatives and 11% in the total verified sample size. Overall, savings are about 50% for a sensitivity of 0.3, but are negligible when sensitivity is greater than 0.8. Optimal sampling strategies for sensitivity do not materially alter confidence intervals for specificity. Figures are presented from which readers can easily obtain the optimal sampling strategy given an estimate of specificity, approximated by the proportion of screenees who are test negative, and the range of likely sensitivity.

Quality-adjusted life years: origins, measurements, applications, objections

Quality-adjusted life years or QALYs are used to combine, in a single measure, information about the quantity and quality of life produced by a health intervention. They have been used as outcome measures in clinical trials and in cost-effectiveness analyses. This paper describes how QALYs are assessed and how they are used. Methodological and theoretical problems are discussed as are ethical objections to the utilitarian ethos underlying their use. It is concluded that QALYs are part of a technology that is still in development but, because of the lack of alternatives, they will certainly continue to be used. It is important to resolve the outstanding methodological issues and reach an ethical consensus to ensure that QALYs truly reflect community goals.

Vitamin A supplementation in infectious diseases: a meta-analysis

OBJECTIVE

To study the effect of vitamin A supplementation on morbidity and mortality from infectious disease.

DESIGN

A meta-analysis aimed at identifying and combining mortality and morbidity data from all randomised controlled trials of vitamin A.

RESULTS

Of 20 controlled trials identified, 12 trials were randomised trials and provided "intention to treat" data: six community trials in developing countries, three in children admitted to hospital with measles, and three in very low birth weight infants. Combined results for community studies suggest a reduction of 30% (95% confidence interval 21% to 38%; two tailed p < 0.0000001) in all cause mortality. Analysis of cause specific mortality showed a reduction in deaths from diarrhoeal disease (in community studies) by 39% (24% to 50%; two tailed p < 0.00001); from respiratory disease (in measles studies) by 70% (15% to 90%; two tailed p = 0.02); and from other causes of death (in community studies) by 34% (15% to 48%; two tailed p = 0.001). Reductions in morbidity were consistent with the findings for mortality, but fewer data were available.

CONCLUSIONS

Adequate supply of vitamin A, either through supplementation or adequate diet, has a major role in preventing morbidity and mortality in children in developing countries. In developed countries vitamin A may also have a role in those with life threatening infections such as measles and those who may have a relative deficiency, such as premature infants.

Meta-analysis adjusting for compliance: the example of screening for breast cancer

Randomized controlled trials are usually analysed by the group to which the patient was randomized, i.e. by "intention-to-treat", regardless of the degree of compliance. However, the "explanatory" effect, i.e. the effect that would occur if we had 100% compliance, is often of interest. This "explanatory" effect is diluted by poor compliance, and hence meta-analyses should ideally avoid both the heterogeneity of effect due to variation in compliance rates among studies, and the undeserved weight given to trials with poor compliance. Newcombe's deattenuation method, which adjusts estimates for the degree of compliance, is extended and applied to a meta-analysis of the five reported randomized controlled trials of mammographic screening. Compliance with screening varied across studies: from 61 to 93% assigned to screening had one or more mammograms. The adjusted estimate of the reduction in breast cancer mortality at 9 years follow-up is 0.37 (95% confidence interval: 0.21, 0.49).

Meta-analysis and quality of evidence in the economic evaluation of drug trials

Meta-analysis is an important part of assessing cost-effectiveness in that it may help determine which treatments are indeed effective and estimate the level of effectiveness of each. Meta-analysis uses the data from all the relevant trials and is a powerful tool for detecting effects too small to be picked up by individual trials. The assessment of quality of studies in a meta-analysis is critical, with priority needing to be given to high quality randomised studies. A written protocol, literature retrieval system, evaluation and selection criteria, choice of endpoints and ways to evaluate bias must all be pre-defined. Nevertheless, problems can arise when meta-analysis is used for cost-effectiveness analysis, due to variation in study medication protocols, duration of follow-up, and difficulties in interpreting patient subgroups and compliance. Despite being subject to the design flaws of both the trials analysed and the methods used in the analysis itself, meta-analysis provides a more objective and thorough means of evaluating effectiveness and hence the cost-effectiveness of treatments. Based on the meta-analysis evidence, we recommend that the current QALY league tables be split into an implementation table for clearly effective therapies, and a research priority table where the evidence of treatment effectiveness is less clear and more research is needed.

A pitfall in utility assessment--patients' undisclosed investment decisions

Among those decisions that may be made by a patient in response to an illness, the authors single out a certain class: contingent investment decisions. They are characterized by the patient's committing him- or herself, on the basis of prognostic counseling, to a certain action or non-action that he or she may regret in retrospect. Examples show that, when assessing utilities, the decision analyst runs a risk of handling such investment decisions incorrectly, unless they are made explicit and incorporated into the medical decision process. The anomaly is explained as a violation of the structural rules for decision trees and is also interpreted in terms of "the price of prognostic ignorance," a quantity closely related to the expected utility value of perfect information.

Quality adjusted survival analysis

We present a technique, quality adjusted survival analysis, for the analysis of controlled trials where patients may experience several health states which differ in their quality of life. When the data are censored, a survival analysis of the quality adjusted life years achieved may involve informative censoring, and produce biased estimates. To overcome this, we partition the survival curve; the resulting areas, which represent the mean time in each state, are multiplied by utility weights to provide an unbiased estimate of (restricted) quality adjusted survival. If the appropriate weights are in doubt, the results are best presented as a threshold analysis over the utility weights, allowing individual recommendation to be read from a simple graph. The certainty of the conclusions can be presented as confidence bands on the threshold line. The techniques are illustrated with a re-analysis of a large three-arm trial of adjuvant chemoendocrine therapy for stage II breast cancer in postmenopausal women. This shows that if the value of time spent in toxicity is greater than the time spent in relapse, we can be 95 per cent confident that chemoendocrine therapy is the preferred option.