| Objective To survey the situation of the quality of life of cancer patients at the end of life, explore the influencing factors and effective measures in the literature by content analysis, and develop the prognostic scale for prediction of survival time in advanced cancer patients, which can help medical staffs better understand their situation and make optimizing care planning to improve their quality of life.Methods①A cross-sectional survey was carried out to understand the quality of life of 531 terminal cancer patients by purposive sampling in 13 medical institution of Shanghai, who was predicted to survive no longer than 6 months. The McGill Quality of Life Questionnaire Chinese version was used as the instrument after cultural revision. Statistical analyses including Kruskal-Wallis test and Nemenyi test, Wilcoxon test, multivariate stepwise regression analysis were performed to explore the influential factors of quality of life of patients. The reliability and validity of McGill Quality of Life Questionnaire Chinese version were evaluated by Cronbach'sαcoefficient and factor analysis.②Literature review and content analyses were conducted to systematically summarize the influencing factors and effective interventions (41 articles and 25 articles respectively).③Based on the former study in Chinese Prognostic Scale, a series of indexes were gathered to form the questionnaire. Then we investigated 320 terminal cancer patients and followed up to get the time of their death. At last the prognostic scale for prediction of survival time in advanced cancer patients was developed by the statistical analysis of the data.Results①The results of cross-sectional survey revealed that the quality of life in terminal cancer patients was not high on the whole(SIS = 4.12±2.20,Total score = 5.09±0.90), with highest score in support dimension (6.82±2.17) and lowest in existential dimension (4.65±1.97). The physical care was not ideal, either. Pain, loss of appetite, fatigue, weakness and dyspnea were most common distressing symptoms in patients. Univariate analysis and multivariate stepwise regression analysis showed that financial burden of treatment, understanding of the disease, marital status, chronic diseases and hospital size were related to patients'overall and dimensional quality of life(P <0.05). Cronbach'sαcoefficient of McGill Quality of Life Questionnaire Chinese version was 0.551. And the Cronbach'sαcoefficients of dimensions were more than 0.85 except that of the physical dimension. The factor analysis extracted five factors, which explained 74.828 % of the total variance. All of these convinced us of the reliability and validity of the McGill Quality of Life Questionnaire Chinese version.②Ten aspects of influencing factors were summarized by content analysis including patients'physical symptoms and signs, overall health, psychological symptoms, issues associated with spiritual or existential dimensions, issues associated with social dimension, treatment methods, communication, environment, values and adaptation, and demographic characteristics. And there are 8 areas of effective interventions including physical symptoms management, psychological symptoms management, spiritual support or spiritual care, social support, appropriate treatment methods, effective communication, environment management, and palliative/hospice care.③Fourteen prognostic factors were defined by prospective survey and content analysis, including KPS, pain, ascites, pleural fluid, edema, delirium, cachexia, white blood cells count, the amount of hemoglobin, natrium, total bilirubin, direct bilirubin, aspartate aminotransferase and alkaline phosphatase.. And then the prognostic scale for cancer patients was developed with the total scores ranging from 0 to 30. The scale can predict 1-week, 1-month, 3-month and 6-month survival of patients, scored 12, 10, 8, and 6 respectively.Conclusion This study could play an important role in helping medical professionals understand terminal cancer patients'quality of life and influencing factors and perform effective care programs. We explored terminal cancer patients'current situation, influencing factors of quality of life. Using content analysis, the influencing factors and effective measures in the literature were concluded, which can be the basis to construct the care plans for the cancer patients at the end of life. And the prognostic scale could help improving the accuracy of survival prediction in cancer patients. However, the framework and the model should be revised and accomplished in future, the effectiveness of which should be tested in clinical practice. In addition, the accuracy of the prognostic scale needs to be tested.
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