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In the past, even complex systems have been regarded mainly as a collection of components which work together in a definable way like a technical machine. The clear functional connection between two components (nodes) A and B underlines a direct causal relationship and allows the prediction of the effect for B after acting on A. In contrast, current consideration of biological systems increasingly includes the many cross-links and feedback loops that form a functional network. Correspondingly, in a network it is more difficult to predict the response of B to any stimulating effect applied to A, and thereby to verify the causal impact. Generally, a highly interconnected network is hard to control, but a system without any crosslinking is more susceptible to loss of function, due to any interruption [1,2]. The construction of many current networks, with only few nodes with low degree of crosslinking and many nodes that are highly linked, appear to be the most favourable to guarantee both resistance to damage and maintained ability to differential regulation. However, such a construction, which has developed to become highly effective during evolution, raises questions for our common thinking of causal relationships and causal relevance. Although human beings should be regarded as a biological system rather than a machine, in medicine, it is often preferable to assume direct functional and causal relationships. For various malignancies, tissue-specific tumour markers have been identified, which indicate a low or high risk for recurrence of tumour growth. Their usefulness is tested by relating the relapses to the expression of these markers. Whereas estrogenand progesterone-receptor expressions are assumed to be favourable for the patient [3,4] because they reflect a more differentiated (and hence less aggressive) tumour, the proto-oncogene p53 [5,6] and human epidermal growth factor receptor (HER2) [7] are associated with accelerated malignant growth. Additionally, the nuclear Y-box (YB) protein-1 staining pattern in breast cancer cells and surrounding tissue has been shown to be predictive for drug resistance, indicating a poorer long-term outcome [8]. Hence, in general it is assumed that expressions of estrogenor

Problem Poser—How to Interpret Divergent Prognostic Evidence of Simultaneously Measured Tumor Markers?