Valerian does not appear to reduce symptoms for patients with chronic insomnia in general practice using a series of randomised n-of-1 trials.

OBJECTIVE: To investigate the effectiveness of valerian for the management of chronic insomnia in general practice. DESIGN: Valerian versus placebo in a series of n-of-1 trials, in Queensland, Australia. RESULTS: Of 42 enrolled patients, 24 (57%) had sufficient data for inclusion into the n-of-1 analysis. Response to valerian was fair for 23 (96%) participants evaluating their "energy level in the previous day" but poor or modest for all 24 (100%) participants' response to "total sleep time" and for 23 (96%) participants' response to "number of night awakenings" and "morning refreshment". As a group, the proportion of treatment successes ranged from 0.35 (95% CI 0.23, 0.47) to 0.55 (95% CI 0.43, 0.67) for the six elicited outcome sleep variables. There was no significant difference in the number (P=0.06), distribution (P=1.00) or severity (P=0.46) of side effects between valerian and placebo treatments. CONCLUSIONS: Valerian was not shown to be appreciably better than placebo in promoting sleep or sleep-related factors for any individual patient or for all patients as a group.

Quality adjusted survival analysis with repeated quality of life measures.

One way of examining trade-offs between quantity and quality of life (QOL) is to combine them into a single measure such as quality-adjusted life year (QALY). If censoring occurs, then estimation presents some difficulties. One approach, known as Q-TWiST, is to define a series of health states, use a 'partitioned' survival analysis to calculate the average time in each state, and then weight each state according to its quality of life to calculate QALYs. Such health-state models, however, are unhelpful when the transitions between health states are unclear or if they do not adequately reflect variations in quality of life. We therefore examine an alternative analysis to be used when repeated measures of quality of life are available from individual patients in a clinical trial. The method proceeds by separating quality of life and survival, that is, dQALY/dt = S(t)Q(t), where S(t) is the survival curve, estimated from the standard Kaplan-Meier method, and Q(t) is the quality of life function, derived from individual repeated measures of quality of life. We derive single health-state (QALY) and multiple health-state (Q-TWiST) models and illustrate the approach by comparing different durations of adjuvant chemotherapy for breast cancer.

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.