Predicting waitlist dropout in hepatocellular carcinoma: a narrative review.

Background and Objective: Liver transplantation is the gold standard treatment for patients with hepatocellular carcinoma (HCC). Current allocation systems face a complex issue due to the imbalance between available organs and recipients. The prioritization of HCC patients remains controversial, leading to potential disparities in access to transplantation. Factors such as tumor size, alpha-fetoprotein (AFP) levels, Model of End-Stage Liver Disease (MELD) score, and response to locoregional therapy (LRT) contribute to determining waitlist dropout risk in HCC patients. Several statistical and machine learning (ML) models have been proposed to predict waitlist dropout, incorporating variables related to tumor and patient factors, underlying liver disease, and waitlist time. This narrative review aims to summarize the evidence regarding different prediction models of HCC waitlist dropout. Methods: All published articles up to December 25, 2023, were considered. Articles not based on prediction models using conventional statistical methods or ML models were excluded. Key Content and Findings: Factors such as tumor size, AFP levels, MELD score, and LRT response have been shown to impact disease progression in these patients, influencing waitlist dropout. Most articles in the literature are based on statistical models. Both ML and statistical models may offer promising results, but their application is currently limited. Several attempts have been made to find the best model to stratify the risk of waitlist dropout in HCC patients. However, to date, none of the explored models have been implemented. The allocation of HCC recipients is still based on supplementary scoring systems or geographical criteria. Conclusions: Improving methodology and databases in future research is essential to obtain accurate and reliable models for clinicians. This is the only way to achieve real applicability.

Surgical treatment of vena cava leiomyosarcomas: Series of cases in a referral center and literature review.

BACKGROUND: Primary tumors of the inferior vena cava are rare tumors of mesenchymal origin. They arise from the smooth muscles of the vena cava wall. Due to its low prevalence, there are few definitive data on its treatment and prognosis. Its treatment is based on general oncological principles. METHODS: A series of 6 cases operated from 2010 to 2020 were analyzed. Different parameters related to the demographic characteristics, the tumor, the treatment received, and the results obtained in survival and morbidity were analyzed. In addition, a bibliographical review of the currently available evidence was carried out. RESULTS: Optimal surgical resection was accomplished in all patients with R0 in 4/6 and R1 in 2/6. The greatest morbidity occurred in a patient who died in the intraoperative period. Cavorraphy was performed in one patient and cavoplasty in 5/6 using cryopreserved graft in 3/6 and prothesis in 2/6. The 50% were still alive at the end of the follow-up (with a mean follow-up of 10.7 months). The mean survival was 11.3 ± 9.07 months. 3/6 patients presented hematogenous recurrences with a disease-free interval of 9 ± 2 months. CONCLUSION: The diagnosis and treatment of inferior vena cava leiomyosarcoma is still a challenge. Due to its low prevalence, it will be difficult to establish a totally standardized treatment and its approach is recommended in specialized centers. On the other hand, a multicentric study should be made to collect the most cases as possible in order to advance in the understanding of the approach to this disease.

Surgical treatment of vena cava leiomyosarcomas: Series of cases in a referral center and literature review. / Tratamiento quirúrgico de los leiomiosarcomas de vena cava. Serie de casos en un hospital de tercer nivel y revisión de la literatura.

INTRODUCTION: Primary tumors of the inferior vena cava are rare tumors of mesenchymal origin. They arise from the smooth muscles of the vena cava wall. Due to its low prevalence, there are few definitive data on its treatment and prognosis. Its treatment is based on general oncological principles. METHODS: A series of six cases operated from 2010 to 2020 were analyzed. Different parameters related to the demographic characteristics, the tumor, the treatment received, and the results obtained in survival and morbidity were analyzed. In addition, a bibliographical review of the currently available evidence was carried out. RESULTS: Optimal surgical resection was accomplished in all patients with R0 in 4/6 and R1 in 2/6. The greatest morbidity occurred in a patient who died in the intraoperative period. Cavography was performed in one patient and cavoplasty in 5/6 using cryopreserved graft in 3/6 and prothesis in 2/6. The 50% were still alive at the end of the follow-up (with a mean follow-up of 10.7 months). The mean survival was 11.3±9.07 months. 3/6 patients presented hematogenous recurrences with a disease-free interval of 9±2 months. CONCLUSION: The diagnosis and treatment of inferior vena cava leiomyosarcoma is still a challenge. Due to its low prevalence, it will be difficult to establish a totally standardized treatment and its approach is recommended in specialized centers. On the other hand, a multicentric study should be made to collect the most cases as possible in order to advance in the understanding of the approach to this disease.