e15679 Background: Various serum inflammatory factors are implicated in pathogenesis and prognostication of HCC but none of them is incorporated into a HCC prognostic model. We aim to build an inflammation-integrated prognostic model without any radiological feature. Methods: A prospective-retrospective cohort of patients with HCC was accrued from 2001 to 2013, and was randomly spitted into training and validation cohorts. Cox proportional hazards model was used for univariable and multivariable survival analyses. The risk score was constructed by factors and their coefficients identified by multivariable Cox model. Results: The entire cohort was composed of 1315 patients (BCLC 0/A/B/C/D 73/533/237/425/47; Surgery/Locoablation/TACE/Systemic agent/BSC 538/128/318/122/209). In the training cohort (n=657), a novel model, PANALA score, was generated by using6 independent prognostic factors: 1.488*(Performance status >0) – 0.057*Albumin + 0.098*Neutrophil – 50.4*Alkaline phosphatase^-1 – 0.269*Lymphocyte + 0.11*ln(Alpha fetoprotein). PANALA outperformed other staging systems (Table) and allowed the prediction of survival of an individual patient. In the validation cohort (n=658), the prognostic performance of PANALA was still the most superior one. The goodness of fit of PANALA score in prediction of survival was evaluated by dividing patients into 4 equal quartiles by PANALA. In the quartile 1, overall survival between actual observation and prediction was highly comparable (6m survival: 100% vs. 95%, 3y survival: 80% vs. 79%, 5y survival: 72% vs. 74%; P=0.71). Discrepancies between observed and predicted survival were also insignificant in other quartiles. Moreover, PANALA was able to stratify each BCLC stage into 3 prognostically different subgroups. Conclusions: PANALA is a novel and validated model with high prognostic performance. [Table: see text]