Recalibrating survival prediction among patients receiving trans‐arterial chemoembolization for hepatocellular carcinoma. Issue 2 (18th July 2021) - Cucchetti, Alessandro; Giannini, Edoardo G.; Mosconi, Cristina; Plaz Torres, Maria Corina; Pieri, Giulia; Farinati, Fabio; Rapaccini, Gian Ludovico; Di Marco, Maria; Caturelli, Eugenio; Sacco, Rodolfo; Cabibbo, Giuseppe; Campani, Claudia; et al.
Abstract: Background & Aims: The Pre‐TACE‐Predict model was devised to assess prognosis of patients treated with trans‐arterial chemoembolization (TACE) for hepatocellular carcinoma (HCC). However, before entering clinical practice, a model should demonstrate that it performs a useful role. Methods: We performed an independent external validation of the Pre‐TACE model in a cohort that differs in setting and time period from the one that generated the original model. Data from 826 patients treated with TACE for naïve HCC (2008‐2018) were used to assess calibration and discrimination of the Pre‐TACE‐Predict model. Results: The four risk‐categories identified by the Pre‐TACE‐Predict model had gradient monotonicity, with median survivals of 52.0, 36.2, 29.9, and 14.1 months respectively. However, predicted survivals systematically underestimated observed survivals ( R 2 : 0.667). A recalibration was adopted maintaining fixed the prognostic index and modifying the baseline survival function. This resulted in an almost perfect calibration ( R 2 : 0.995) in all the four risk categories. Cox regressions showed that aetiology and macrovascular invasion, included in the Pre‐TACE‐Predict model, had no prognostic impact in the present study population, and that coefficients for tumour size and multiplicity were overestimated. The c ‐index was similar to that of the m‐HAP‐III, but higher than those of HAP, m‐HAP‐II and the six‐and‐twelve models. Conclusions: The recalibration of Pre‐TACE‐Predict model improved the estimation of survival probabilities of HCC patients treated with TACE. The highest discriminatory ability of the Pre‐TACE‐model in comparison to other available models, together with risk stratification and recalibration, makes it the best prognostic tool currently available for these patients. Abstract :