Background: One important concept in traditional Chinese medicine (TCM) is "treating different diseases with the same therapy". In TCM practice, some patients with Rheumatoid Arthritis (RA) and some other patients with Coronary Heart Disease (CHD) can be treated with similar therapies. This suggests that there might be something commonly existed between RA and CHD, for example, biological networks or biological basis. As the amount of biomedical data in leading databases (i.e., PubMed, SinoMed, etc.) is growing at an exponential rate, it might be possible to get something interesting and meaningful through the techniques developed in data mining.Results: Based on the large data sets of Western medicine literature (PubMed) and traditional Chinese medicine literature (SinoMed), by applying data slicing algorithm in text mining, we retrieved some simple and meaningful networks. The Chinese herbs used in treatment of both RA and CHD, might affect the commonly existed networks between RA and CHD. This might support the TCM concept of treating different diseases with the same therapy.Conclusions: First, the data mining results might show the positive answer that there are biological basis/networks commonly existed in both RA and CHD. Second, there are basic Chinese herbs used in the treatment of both RA and CHD. Third, these commonly existed networks might be affected by the basic Chinese herbs. Forth, discrete derivative, the data slicing algorithm is feasible in mining out useful data from literature of PubMed and SinoMed.

Background: The common randomized controlled trial design has distinct limitations when applied to Chinese medicine, because Chinese medicine identifies and treats 'Chinese medicine patterns' rather than diagnosed diseases. Chinese medicine patterns are a group of associated symptoms, tongue appearances and pulse characteristics. These limitations could be overcome by developing new strategies to evaluate the effect of Chinese medicine. The idea behind pattern-based efficacy evaluations may optimize clinical trial design by identifying the responsiveness-related Chinese medicine patterns. Methods/Design: This is a two-stage multi-center trial of Chinese herbal medicine for the management of rheumatoid arthritis. The stage one trial is an open-label trial and aims to explore what groups of Chinese medicine information (such as symptoms) correlates with better efficacy, and the stage two trial is a randomized, controlled, double-blind, double-dummy clinical trial that incorporates the efficacy-related information identified in the stage-one trial into the inclusion criteria. Discussion: The indication of a Chinese herbal formula is a specific Chinese medicine pattern and not a single disease and stratifying a disease into several patterns with a group of symptoms is a feasible procedure in clinical trials. This study is the first to investigate whether this approach in the design of Chinese herbal medicine trials can improve responses. Trial registration: ChiCTR-TRC-10000989