Machine Learning Predictive Model to Guide Treatment Allocation for Recurrent Hepatocellular Carcinoma After Surgery.

Importance: Clear indications on how to select retreatments for recurrent hepatocellular carcinoma (HCC) are still lacking. Objective: To create a machine learning predictive model of survival after HCC recurrence to allocate patients to their best potential treatment. Design, Setting, and Participants: Real-life data were obtained from an Italian registry of hepatocellular carcinoma between January 2008 and December 2019 after a median (IQR) follow-up of 27 (12-51) months. External validation was made on data derived by another Italian cohort and a Japanese cohort. Patients who experienced a recurrent HCC after a first surgical approach were included. Patients were profiled, and factors predicting survival after recurrence under different treatments that acted also as treatment effect modifiers were assessed. The model was then fitted individually to identify the best potential treatment. Analysis took place between January and April 2021. Exposures: Patients were enrolled if treated by reoperative hepatectomy or thermoablation, chemoembolization, or sorafenib. Main Outcomes and Measures: Survival after recurrence was the end point. Results: A total of 701 patients with recurrent HCC were enrolled (mean [SD] age, 71 [9] years; 151 [21.5%] female). Of those, 293 patients (41.8%) received reoperative hepatectomy or thermoablation, 188 (26.8%) received sorafenib, and 220 (31.4%) received chemoembolization. Treatment, age, cirrhosis, number, size, and lobar localization of the recurrent nodules, extrahepatic spread, and time to recurrence were all treatment effect modifiers and survival after recurrence predictors. The area under the receiver operating characteristic curve of the predictive model was 78.5% (95% CI, 71.7%-85.3%) at 5 years after recurrence. According to the model, 611 patients (87.2%) would have benefited from reoperative hepatectomy or thermoablation, 37 (5.2%) from sorafenib, and 53 (7.6%) from chemoembolization in terms of potential survival after recurrence. Compared with patients for which the best potential treatment was reoperative hepatectomy or thermoablation, sorafenib and chemoembolization would be the best potential treatment for older patients (median [IQR] age, 78.5 [75.2-83.4] years, 77.02 [73.89-80.46] years, and 71.59 [64.76-76.06] years for sorafenib, chemoembolization, and reoperative hepatectomy or thermoablation, respectively), with a lower median (IQR) number of multiple recurrent nodules (1.00 [1.00-2.00] for sorafenib, 1.00 [1.00-2.00] for chemoembolization, and 2.00 [1.00-3.00] for reoperative hepatectomy or thermoablation). Extrahepatic recurrence was observed in 43.2% (n = 16) for sorafenib as the best potential treatment vs 14.6% (n = 89) for reoperative hepatectomy or thermoablation as the best potential treatment and 0% for chemoembolization as the best potential treatment. Those profiles were used to constitute a patient-tailored algorithm for the best potential treatment allocation. Conclusions and Relevance: The herein presented algorithm should help in allocating patients with recurrent HCC to the best potential treatment according to their specific characteristics in a treatment hierarchy fashion.

Hyperthermic isolation limb perfusion with TNFalpha in the treatment of in-transit melanoma metastasis.

BACKGROUND: Hyperthermic isolation limb perfusion (HILP) with tumor necrosis factor alpha (TNFalpha) and IFNgamma was pioneered by Liénard and Lejeune in 1988. The TNFalpha was empirically employed at a dosage of 3-4 mg, that is ten times the systemic maximum tolerated dose (MTD). After eighteen years from its first clinical application, more than 300 patients have been treated. The aim of this study is to clarify two major arguments: the TNFalpha dose and eligibility criteria for patient selection. PATIENTS AND METHODS: A phase I-II study has previously been conducted in 20 patients with in-transit melanoma metastases using a combination of melphalan and TNFalpha at dosages ranging from 0.5 to 3.3 mg. Twenty patients were treated and a complete pathological response of 70% was recorded, with no correlation between tumor response and TNFalpha. The dose of 1 mg of TNFalpha provided the best results regarding efficacy and toxicity. On the basis of this results a large phase II SITILO study was undertaken. Patients with stage IIIA - IIIAB (presence of in transit metastases and/or regional node involvement) were considered eligible; a total of 113 patients were enrolled in the study. The disease was bulky (> 10 nodules or fewer nodules with a diameter > or = 3 cm) in 42.5% of the patients and unresectable in 33%. Forty patients were treated with a TNFalpha dosage > 1 mg and 73 with 1 mg. All the patients were submitted to HILP via axillary and iliac vessels for tumor of upper and lower limb, respectively. TNFalpha was injected in the extracorporal circuit at the pre-established dose, followed after 30 minutes by melphalan (13 and 10 mg/L of limb volume for upper and lower limbs, respectively). RESULTS: A grade 1 and 2 limb toxicity was found in 52.9% and 30.1% of the patients, respectively, 5.5% of patients exhibited a grade 3 and 4, whereas grade 5 limb toxicity was not found. The complete and partial responses were 63% and 24.5%, respectively, with an objective response of 87.5%. We tried to correlate the typed tumor response (CR or not CR) and the TNFalpha dosage < or = 1 mg or > 1 mg, but no statistically significant difference was found between the two groups. The bulky disease was the only prognostic factor able to influence the tumor response. CONCLUSION: Only patients with bulky melanoma disease can benefit from HILP with TNFalpha at a low dose of 1 mg.