Is Mistletoe Treatment Beneficial in Invasive Breast Cancer? A New Approach to an Unresolved Problem.

BACKGROUND/AIM: In this retrospective study, we compared breast cancer patients treated with and without mistletoe lectin I (ML-I) in addition to standard breast cancer treatment in order to determine a possible effect of this complementary treatment. PATIENTS AND METHODS: This study included 18,528 patients with invasive breast cancer. Data on additional ML-I treatments were reported for 164 patients. We developed a "similar case" method with a distance measure retrieved from the beta variable in Cox regression to compare these patients, after stage adjustment, with their non-ML-1 treated counterparts in order to answer three hypotheses concerning overall survival, recurrence free survival and life quality. RESULTS: Raw data analysis of an additional ML-I treatment yielded a worse outcome (p=0.02) for patients with ML treatment, possibly due to a bias inherent in the ML-I-treated patients. Using the "similar case" method (a case-based reasoning approach) we could not confirm this harm for patients using ML-I. Analysis of life quality data did not demonstrate reliable differences between patients treated with ML-I treatment and those without proven ML-I treatment. CONCLUSION: Based on a "similar case" model we did not observe any differences in the overall survival (OS), recurrence-free survival (RFS), and quality of life data between breast cancer patients with standard treatment and those who in addition to standard treatment received ML-I treatment.

Postoperative survival of lung cancer patients: are there predictors beyond TNM?

BACKGROUND/AIM: We report on survival data of 595 patients with stage I-III lung cancer with respect to TNM classification. MATERIALS AND METHODS: We constructed a basic model consisting of stage and grade, and assessed the improvement of survival prediction after adding comorbidity data, spirometric data, clinical and laboratory parameters. RESULTS: Body mass index (BMI) and presence of a cardiac disease reached statistical significance for prediction of overall survival in a Cox regression model. In addition to BMI (<25 kg/m(2)) and the presence of cardiovascular disease, the spirometric variable (FEV1) predicted early death (less than five months postoperatively). When the survival random forest method was employed to predict disease outcome, creatinine levels and VO2 max became additional variables of interest for predicting survival. CONCLUSION: We propose that our lung cancer database may help to identify variables (aside from histomorphological variables) that are suitable for identifying patients at risk of death after surgical treatment of lung cancer.