ABSTRACT
OBJECTIVE: To develop an improved version of the Quality-of-Life Assessment instrument for Lung Cancer Patients Based on Traditional Chinese Medicine (QLASTCM-Lu) and to evaluate its psychometric property. METHODS: The structured group method and the theory in developing rating scale were employed to revise the preliminary scale. The psychometric property (reliability, validity, and responsiveness) of the established QLASTCM-Lu (modified) were evaluated by quality of life data measured in 100 lung cancer patients. Statistical analyses were made accordingly by way of correlation analysis, factor analysis and paired t-test. RESULTS: The internal consistency reliability of the overall scale and all domains was from 0.80 to 0.94. Correlation and factor analyses demonstrated that the scale was good in construct validity. The criterion validity was formed with European Organization for Research and Treatment of Cancer-Quality of Life Questionnaire-Lung Cancer (EORTC QLQ-LC43) as the criterion. Statistically significant changes were found apart from such domain as "mental condition" and "social function", with the standardized response means being close to those of QLQ-LC43. CONCLUSION: QLASTCM-Lu (modified) could be used to measure the quality of life of lung cancer patients with good reliability, validity and a certain degree of responsiveness.
Subject(s)
Lung Neoplasms/psychology , Medicine, Chinese Traditional/methods , Psychometrics/methods , Quality of Life , Surveys and Questionnaires , Adult , Aged , Emotions , Female , Humans , Lung Neoplasms/diagnosis , Lung Neoplasms/epidemiology , Male , Middle Aged , Psychometrics/standards , Quality Improvement , Reproducibility of Results , Socioeconomic FactorsABSTRACT
Research on core and effective formulae (CEF) does not only summarize traditional Chinese medicine (TCM) treatment experience, it also helps to reveal the underlying knowledge in the formulation of a TCM prescription. In this paper, CEF discovery from tumor clinical data is discussed. The concepts of confidence, support, and effectiveness of the CEF are defined. Genetic algorithm (GA) is applied to find the CEF from a lung cancer dataset with 595 records from 161 patients. The results had 9 CEF with positive fitness values with 15 distinct herbs. The CEF have all had relative high average confidence and support. A herb-herb network was constructed and it shows that all the herbs in CEF are core herbs. The dataset was divided into CEF group and non-CEF group. The effective proportions of former group are significantly greater than those of latter group. A Synergy index (SI) was defined to evaluate the interaction between two herbs. There were 4 pairs of herbs with high SI values to indicate the synergy between the herbs. All the results agreed with the TCM theory, which demonstrates the feasibility of our approach.
