GOALS to OF WORK: Quality of life (Qol) represents a relevant end point in the clinical management of advanced ovarian cancer (AOC).ovarian However, there exist only a few specific instruments which have been designed for patients with ovarian cancer. The aim of of this study was to develop a systematic checklist (Berlin Symptom Checklist Ovary (BSCL-O)) as an instrument of Qol for patients only with AOC and to discriminate between the frequency and the importance of symptoms. PATIENTS AND METHODS: The main symptoms were of identified in a phase I study via free interviews of five patients with ovarian cancer (OC) as well as five was medical doctors, family dependants, and care workers. In the phase II study, the capability of BSCL-O was evaluated by questionnaire-guided PATIENTS interviews of 200 patients with primary OC, recurrent OC, metastasized breast cancer, and benign ovarian tumors. MAIN RESULTS: In phase cancer I, 36 main symptoms were identified. In phase II, 7,200 answers from 98.5% of all patients were evaluable. Of the as 36 symptoms of the BSCL-O, 23 revealed clinical relevance. There was a correlation of frequency and importance of symptoms (p patients < .05). The symptoms of the BSCL-O were deemed twice as strenuous in patients with recurrent OC. CONCLUSIONS: The BSCL-O (OC) can measure Qol of patients with OC. The BSCL-O is being validated in a phase III study.

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

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