Objective : To evaluate the risk for hepatocellular carcinoma (HCC) and the effect of interferon therapy on the incidence of HCC in patients with chronic hepatitis C by combining results from different studies in Japan.
Design : Literature-based meta-analysis
Methods : Thirteen follow-up studies for patients with chronic hepatitis C conducted in Japan were selected by systematic review of MEDLINE, EMBASE and manual searching. An unadjusted incidence rate ratio of HCC between treatment groups was calculated and an adjusted incidence rate ratio was estimated after adjustments using estimates for the degree of confounding from some of the studies.
Results : A total of 7 observational studies (1, 498 patients in the non-interferon group and 5, 451 patients in the interferon group) were included in this meta-analysis. The summary estimate of unadjusted incidence rate ratio was 0.37 (95% confidence interval [CI], 0.30 to 0.46). For 4 studies that had performed a multivariate analysis to adjust confounding factors such as sex, age, histological stage of hepatitis, the correction factor, which was estimated from the ratio of an unadjusted incident rate ratio to an adjusted incident rate ratio, was 0.64. The adjusted incidence rate ratio for incidence of HCC estimated using the correction factor was 0.58 (95% CI, 0.46 to 0.73) for interferon treatment to non-interferon treatment. After including all studies, the pooled 5-year estimated risk for HCC was 0.107 in the non-interferon group (n=2, 016) and the risk was 0.051 in the interferon group (n=6, 691).
Conclusion : Treatment with interferon reduces the risk for HCC in patients with chronic hepatitis C.

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Under the prevailing ”disease-oriented” paradigm of health, Quality of Life (QOL) has been treated with profound skepticism. Two facts, however, militate for taking QOL seriously into account : first, both social and clinical decision making today require evidence presented in the form of patient outcomes; second, of patient outcomes, one of the most important from the patient's standpoint is QOL. Giving several examples, the author discusses why traditional endpoints are insufficient and why patient-based outcomes are relevant in modern social and clinical decision making.
And yet not all outcomes are relevant : for the purposes of assessment of health and medical care, QOL should be confined to its health-related elements, and instruments to measure health-related quality of life (HRQOL) should be rigorously tested with psychometric methods. Even more important, however, is the instrument's content validity : i. e., whether it measures what one wants to measure. This paper lists criteria for selection of appropriate instruments and describes the recent debate and moves to formulate guidelines on the use of HRQOL evidence in pharmaceutical product approvals and manufacturers' product efficacy claims. Finally, the author discusses the future of HRQOL research and uses of HRQOL in clinical practice.

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Quality of life (QOL) evaluated by patients themselves has become one of the important outcomes in clinical practice as well as clinical trials. Recently clinicians have attempted to gather QOL evaluation data in their clinical practice setting and integrate the findings into the medical decision-making process. To date, several multidimensional generic questionnaires consisting of multiple domains such as functional, physical, mental and social well-being, have been developed and utilized for generic QOL evaluation in clinical trials, especially in the oncology area. To develop a well-constructed and valid QOL questionnaire, its psychometric characteristics such as reliability, validity, responsiveness and feasibility must be adequately assessed in the research setting.
In clinical trials, QOL data are generally measured in a longitudinal fashion and there are two prominent embarrassing statistical problems : one is the multiplicity due to replication (in time) of statistical tests and the other is the occurrence of missing data due to a variety of reasons. Non-random missing data which occurs because of any reasons related to a patient's present status and/or future prognosis possibly leads to bias and misinterpretation of the results of a trial. To solve the multiplicity problem, the repeated-measures ANOVA-type data analysis or summarization of a repeated measures into an appropriate summary measure can be applied. Missing data can be prevented to some extent by allocating/training coordinators at each participating institute and establishing a communication network between a data center and participating institutes. However, missing data will occur inevitably due to the deterioration of a patient's physical status in the area of life threatening diseases suchas advanced cancer or other diseases with poor prognosis. Although several statistical approaches to cope with missing data even including non-random one have been proposed, there is no single complete analytical solution that can handle the non-random missing problem. The best remedy would be to collect information about reasons why the missing data occurred so that we can identify the missing mechanism and take it into account in a statistical analysis. A so-called “sensitivity analysis” of comparing the results of several analytical methods suchas different imputation techniques or newly proposed ideas would also be a useful approach. The QALY (Quality Adjusted Life Year) used the idea of weighting life time by utility evaluated by patients themselves and is coined for incorporating a patient's judgment into the treatment selection. Ultimately, an assessment of QOL should be utilized for “individualized” or “tailor-made” treatment and statistical methodology should be developed further for gathering, analyzing and utilizing QOL data.

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Health-related quality of life (HR-QOL) has become one of the important endpoints in cancer clinical trials. However, a relatively small proportion of oncologists truly understand the concepts and uses of QOL assessments. In this article, I discuss in detail the psychometric properties that should be verified with QOL instruments, the range of QOL concepts that should be assessed in oncology, how to choose the appropriate QOL instruments, cross-cultural issues and statistical problems. Several examples of QOL assessments in cancer clinical trials are also introduced.

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In a common saying, “good sleep, good eating, and good defecation” is a synonym to wellness of human health. Not only the absence of gastrointestinal (GI) symptoms but also a good appetite and comfortable defecation are necessary for the wellness of health. Such wellness or well-being is now called health-related quality of life (HR-QOL). Generic QOL scales consistently indicate disturbed QOL in patients with GI symptoms, which correlates well with the specific QOL for many GI disorders, showing that the presence of GI symptoms contributes disturbance in HR-QOL, proving that a good appetite is critical for HR-QOL.

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Quality of Life (QOL) is attracting attention as a concept which pursues the humanity of patients in contrast to conventional treatment which mainly consists of treatment for sustaining life. In particular, as senile dementia is one of the diseases for which a complete cure is not available to date and for which the main goal of medical treatment and care is improvement in QOL, appropriate evaluation of the effectiveness of treatment for elderly people with dementia cannot be employed without evaluating their QOL.
As well, in the field of pharmacoepidemiology, with the development of antidementia drugs for Alzheimer's disease (AD), utilization of a QOL scale in evaluating drug efficacy has become an important subject. Considering the characteristics of dementia, it is not necessarily easy to evaluate how much QOL improvement antidementia drugs bring about, because many patients have difficulty in evaluating themselves. Therefore, in addition to QOL evaluation, utilizing objective evaluation by observing patients'behavior or the scale measuring the patients'preferences should be examined.
Furthermore, maintaining QOL of caregivers is an important issue as this is closely related with QOL of patients themselves. To care for elderly people with dementia, a caregiver such as a patient's family member shoulders significant mental/physical burden, which could lead to “collapse by caring”. Therefore, in evaluating antidementia drugs, it is necessary to take QOL of caregivers as well as the patients themselves into consideration.

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