GOALS OF WORK: Quality of life (Qol) represents a relevant end point in the clinical management of advanced ovarian cancer (AOC). However, there exist only a few specific instruments which have been designed for patients with ovarian cancer. The aim of this study was to develop a systematic checklist (Berlin Symptom Checklist Ovary (BSCL-O)) as an instrument of Qol for patients with AOC and to discriminate between the frequency and the importance of symptoms. PATIENTS AND METHODS: The main symptoms were identified in a phase I study via free interviews of five patients with ovarian cancer (OC) as well as five medical doctors, family dependants, and care workers. In the phase II study, the capability of BSCL-O was evaluated by questionnaire-guided interviews of 200 patients with primary OC, recurrent OC, metastasized breast cancer, and benign ovarian tumors. MAIN RESULTS: In phase I, 36 main symptoms were identified. In phase II, 7,200 answers from 98.5% of all patients were evaluable. Of the 36 symptoms of the BSCL-O, 23 revealed clinical relevance. There was a correlation of frequency and importance of symptoms (p < 0.05). The symptoms of the BSCL-O were deemed twice as strenuous in patients with recurrent OC. CONCLUSIONS: The BSCL-O can measure Qol of patients with OC. The BSCL-O is being validated in a phase III study.

When depicting the relationship between evidence and the cost of an innovation in the health-care system, the overall risks of assessment, the redistribution of risks in a regulated market, and the ethical consequences must first be taken into account. There are also evidence-based criteria and economic considerations which are relevant when calculating the cost of an innovation. These topics can indicate, but not exhaustively deal with the complicated relationship between scientific evidence and calculating the cost of an innovation in the health-care system. The following three statements summarize the current considerations in the continuing discussion of this topic:*Scientific evidence undoubtedly exists which should be taken into consideration when calculating the cost of an innovation in the health-care system.*The existing scientific evidence is, however, not sufficient to reach such a decision. Additional information about the benefit perceived by the patient is required.*No standardized method exists to measure this additional information. Therefore, a definition problem also exists in the health-care system when setting a price according to scientific evidence.

BACKGROUND: In patients with very severe dementia self-rating of quality of life usually is not possible and appropriate instruments for proxy-ratings are not available. The aim of this project is to develop an instrument of clinical proxy-ratings for this population. METHODS: Using electronic instruments, physicians and nurses recorded patient behaviour and changes of behaviour over a period of one year. Based on these data a list of 65 items was generated and subsequently allocated to 14 categories. This list was tested in 217 patients (61-105 yrs) with dementia diagnosed according to ICD-10 by both physicians and nurses. The severity of dementia was assessed by means of the Global Deterioration Scale (GDS) and the Brief Cognitive Rating Scale (BCRS). The Spitzer-Index (proxy-rating) was used as a global quality of life measure. Activity of daily living was rated using the Barthel Index. RESULTS: A factor analysis of the original 65 items revealed 5 factors (communication, negative affect, bodily contact, aggression, and mobility). By stepwise removing items we obtained satisfactory internal consistencies of the factors both for nurses' and physicians' ratings. The factors were generally unrelated. The validity of the instrument was proven by correlations of the factors communication and mobility with the Brief Cognitive Rating Scale (BCRS) and the Barthel-Index. CONCLUSION: The results demonstrate the reliability and validity of the Vienna List as a proxy rating measurement of quality of life in patients with severe dementia. The psychometric properties of the scale have to be proved in further studies.

Finding the optimal use of health-care resources requires the reliable estimation of costs and consequences. Acquiring these estimates may not be difficult for some common treatments. More difficult is the optimization of resources in the area of diagnostics. Only a few attempts have been made to optimize the use of resources in the area of prevention. Several aspects have to be considered when optimizing the resources for prevention:(1) participation rates in structured prevention programs are low,(2), acquiring data on follow-up and outcomes is difficult,(3) there are concerns about the quality of information available to public, and (4), the public is often unaware of scientific assessments of prevention programs. As prevention programs are costly long-term projects, a strategy to select these programs according to possible predictors of success might be useful. The few analyses of cancer prevention in the literature have been directed towards the most common malignant diseases (as assessed by incidence) such as cancer of the breast, colon, lung and prostate. We argue that incidence is a poor marker for selecting secondary prevention programs. Incidence may be a misleading indicator for two reasons: incidence of disease does not predict efficiency of management or good health outcomes, and incidence does not separate clinically significant from non-significant disease. The traditional strategy is based on the assumption that more screening increases the chance of cure. We propose an alternative outcomes model that suggests better disease management justifies new prevention programs. Indicators for better disease management are effective and efficient treatments as well as high-quality screening (sensitivity and specificity) techniques and possibly "side-effects of prevention programs," which provide early signs of success to motivate the patient's participation, to keep up with the program and finally to succeed.