Dynamic risk profiling of HCC recurrence after curative intent liver resection

Abstract

Background and Aims: Following liver resection (LR) for HCC, the likelihood of survival is dynamic, in that multiple recurrences and/or metastases are possible, each having variable impacts on outcomes. We sought to evaluate the natural progression, pattern, and timing of various disease states after LR for HCC using multistate modeling and to create a practical calculator to provide prognostic information for patients and clinicians. Approach and Results: Adult patients undergoing LR for HCC betweenJanuary 2000 and December 2018 were retrospectively identified at a single center. Multistate analysis modeled post-LR tumor progression by describing transitions between distinct disease states. In this model, the states included surgery, intrahepatic recurrence (first, second, third, fourth, fifth), distant metastasis with or without intrahepatic recurrence, and death. Of the 486 patients included, 169 (34.8%) remained recurrence-free, 205 (42.2%) developed intrahepatic recurrence, 80 (16.5%) developed distant metastasis, and 32 (7%) died. For an average patient having undergone LR, there was a 33.1% chance of remaining disease-free, a 31.0% chance of at least one intrahepatic recurrence, a 16.3% chance of distant metastasis, and a 19.8% chance of death within the first 60 months post-LR. The transition probability from surgery to first intrahepatic recurrence, without a subsequent state transition, increased from 3% (3 months) to 17.4% (30 months) and 17.2% (60 months). Factors that could modify these probabilities included tumor size, satellite lesions, and microvascular invasion. The online multistate model calculator can be found on https://multi state hcc.shiny apps.io/home/. Conclusions:In contrast to standard single time-to-event estimates, multistate modeling provides more realistic prognostication of outcomes after LR for HCC by taking into account many postoperative disease states and transitions between

Reply

“…We thank Jiang et al for their letter and keen interest in our study. [ 1 ] In accordance with interpreting results from application of any statistical technique, we acknowledge the value of contextualizing our findings with inherent limitations in mind.…”

Accurate prediction of microvascular invasion occurrence and effective prognostic estimation for patients with hepatocellular carcinoma after radical surgical treatment

“…The tumor diameter and TNM stage based on the imaging data are also independent risk factors for postoperative MVI [30,31]. A larger tumor size might be associated with capsular invasion, satellite nodules, and tumor thrombus, and an advanced TNM stage might be relevant to the degree of aggressiveness and malignancy of the tumor [32,33]. In our MVI prediction model, preoperative AFP ≥ 400 kU/L, TD ≥ 5 cm, and TNM stage III-IV demonstrated a reasonable predictive ability of MVI.…”

Derivation and validation of machine learning models for preoperative estimation of microvascular invasion risk in hepatocellular carcinoma

“…Microvascular invasion (MVI) is defined by the presence of cancer cell clusters in vessels located within the tumor capsule or in the peritumoral liver under microscopy ( 5 ). MVI has been well recognized as a risk factor for the early recurrence and survival of HCC after hepatectomy ( 6 , 7 ). Preoperative assessment of MVI is of great value for selecting suitable surgical strategies and improving the survival outcomes of patients with HCC ( 8 ).…”