The objective of this study was to determine which elements in serum best differentiated breast cancer in a case-control study. Concentrations of 13 elements in serum of 68 breast tumor patients (25 malignant and 43 benign) and 26 healthy controls were measured. Logistic regression with different variable-selection procedures was used to determine a possible configuration of elements. Sensitivity and specificity of the model were calculated to obtain the optimal cutoff point for discriminating malignant breast cancers vs other individuals (including benign breast disease and normal ones). Acombination of Cd, Mn, and Fe was found to have a specificity and sensitivity of 100% using forward-type logistic regression, when the cutoff value of the combination score was 52.71. Using stepwise-type logistic regression, a combination of Cr and Mn had a sensitivity of 100% and a specificity of 97.1% when the combination score of 17.4 was chosen as the cutoff. Similar analysis could be implemented to compare the malignant and control groups. Specificity and sensitivity were 100% for Mn (forward and stepwise type) with a cutoff point of 6.40. For the backward regression, specificity was 84.6% and sensitivity was 100% for Zn, with a cutoff point of 869.1. In conclusion, there was a significant difference in concentrations of all 13 elements in serum between breast cancer patients and controls. A combination among Cd, Mn, Fe, Cr, and Zn might be important to determine a differentiating reference for breast cancers if a long-term followed-up study is to be conducted.
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