We previously showed that for hepatocellular cancer (HCC) prognostication, disease parameters need to be considered within a total personal clinical context. This requires preserving the coherence of data values, observed simultaneously for each patient during baseline diagnostic evaluation. Application of the Network Phenotyping Strategy (NPS) provided quantitative descriptors of these patient coherences. Combination of these descriptors with Fisher information about the patient tumor mass and the histogram of the tumor masses in the whole cohort permitted estimation of the time from disease onset until clinical diagnosis (t(baseline)). We found faster growth of smaller tumors having total masses<70 (80% of cohort) which involved about three times more interacting cellular processes than were observed for slower growing larger tumors (20% of cohort) with total masses>70. Combining the clinical survival and t(baseline) normalized all HCC patients to a common 1,045 days of mean total disease duration (t(baseline) plus post diagnosis survival). We also found a simple relationship between the baseline clinical status, t(baseline), and survival. Every difference between individual patient baseline clinical profiles and special coherent clinical status (HL1) reduced the above common overall survival (OVS) by 65 days. In summary, we showed that HCC patients with any given tumor can best have their tumor biology understood, when account is taken of the total clinical and liver contexts, and with knowing the point in the tumor history when an HCC diagnosis is made. This ability to compute the t(baseline) from standard clinical data brings us closer to calculating survival from diagnosis of individual HCC patients.
