We show that (1)H NMR based metabonomicsof serum allows the diagnosis of early stage I/II epithelial ovarian cancer (EOC) required for successful treatment. Because patient specimens are highly precious, we conducted an exploratory study using a microflow probe requiring only 20 μL of serum. By use of logistic regression on principal components (PCs) of the NMR profiles, we built a 4-variable model for early stage EOC prediction (training set: 69 EOC specimens, 84 healthy controls; test set: 40 EOC, 44 controls) with operating characteristics estimated for the test set at 80% specificity [95% confidence interval (CI): 65-90%], 63% sensitivity (95% CI: 46-77%), and an area under the Receiver Operator Characteristic Curve (AUC) of 0.796. Independent validation (50 EOC, 50 controls) of the model yielded 95% specificity (95% CI: 86-99.5%), 68% sensitivity (95% CI: 53-80%) and an AUC of 0.949. A test on cancer type specificity showed that women diseased with renal cell carcinoma were not incorrectly diagnosed with EOC, indicating that metabonomics bears significant potential for cancer type-specific diagnosis. Our model can potentially be applied for women at high risk for EOC, and our study promises to contribute to developing a screening protocol for the general population.