Background: Adjuvant! Online () is an Internet-based software program that allows clinicians to make predictions about the benefits of adjuvant therapy and 10-year survival probability for early-stage breast cancer patients. This model has been validated in Western countries such as the United States, United Kingdom, Canada, Germany, and Holland. The aim of our study was to investigate the performance and accuracy of Adjuvant! Online in a cohort of Taiwanese breast cancer patients. Methods. Data on the prognostic factors and clinical outcomes of 559 breast cancer patients diagnosed at the National Cheng Kung University Hospital in Tainan between 1992 and 2001 were enrolled in the study. Comprehensive demographic, clinical outcome data, and adjuvant treatment data were entered into the Adjuvant! Online program. The outcome prediction at 10 years was compared with the observed and predicted outcomes using Adjuvant! Online. Results: Comparison between low- and high-risk breast cancer patient subgroups showed significant differences in tumor grading, tumor size, and lymph node status (p<0.0001). The mean 10-year predicted death probability in 559 patients was 19.44%, and the observed death probability was 15.56%. Comparison with the Adjuvant! Online-predicted breast cancer-specific survival (BCSS) showed significant differences in the whole cohort (p<0.001). In the low-risk subgroup, the predicted and observed outcomes did not differ significantly (3.69% and 3.85%, respectively). In high-risk patients, Adjuvant! Online overestimated breast cancer-specific survival (p=0.016); the predicted and observed outcomes were 21.99% and 17.46%, respectively. Conclusions: Adjuvant! Online accurately predicted 10-year outcomes and assisted in decision making about adjuvant treatment in low-risk breast cancer patients in our study, although the results were less accurate in the high-risk subgroup. Development of a prognostic program based on a national database should be considered, especially for high-risk breast cancer patients in Taiwan.
All Science Journal Classification (ASJC) codes