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Hepatocellular carcinoma (HCC) is one of the leading indications for liver transplantation and has been the treatment of choice due to the oncologic benefit for patients with advanced chronic liver disease (AdvCLD) and small tumors for the last 25 years. For HCC patients undergoing liver transplantation, alpha fetoprotein (AFP) has increasingly been applied as an independent predictor for overall survival, disease free recurrence, and waitlist drop out. In addition to static AFP, newer studies evaluating the AFP dynamic response to downstaging therapy show enhanced prognostication compared to static AFP alone. While AFP has been utilized to select HCC patients for transplant, despite years of allocation policy changes, the US allocation system continues to take a uniform approach to HCC patients, without discriminating between those with favorable or unfavorable tumor biology. We aim to review the history of liver allocation for HCC in the US, the utility of AFP in liver transplantation, the implications of weaving AFP as a biomarker into policy. Based on this review, we encourage the US transplant community to revisit its HCC organ allocation model, to incorporate more precise oncologic principles for patient selection, and to adopt AFP dynamics to better stratify waitlist dropout risk.

Hepatocellular Carcinoma (HCC) is the most common liver malignancy and third leading cause of cancer death worldwide. For early- and intermediate-stage disease, liver-directed therapies for locoregional control, or down-staging prior to definitive surgical therapy with hepatic resection or liver transplantation, have been studied broadly, and are the mainstays of current treatment guidelines. As HCC incidence has continued to grow, and with more patients presenting with advanced disease, our current treatment modalities do not suffice, and better therapies are needed to improve disease-specific and overall survival. Until recently, sorafenib was the only systemic therapy utilized, and was associated with dismal results. The advent of immuno-oncology has been of significant interest, and has changed the paradigm of therapy for HCC. Lately, combination regimens including atezolizumab plus bevacizumab; durvalumab plus tremelimumab; and pembrolizumab plus Lenvatinib have shown impressive responses of between 25–35%; this is much higher than responses observed with single agents. Complete responses with checkpoint inhibitor therapy have been observed in advanced-stage HCC patients. These dramatic results have naturally led to several questions. Can or should checkpoint inhibitors, or other immunotherapy combinations, be used routinely before resection or transplant? Is there a synergistic effect of immunotherapy with locoregional therapy, and will pre-treatment increase disease-free survival after surgical intervention? Is it immunologically safe to use these therapies prior to transplantation? Much is still to be learned in terms of the dosing, timing, and overall utility of the use of immune checkpoint inhibitors for pre-transplant care and down-staging. More studies will be needed to understand the management of adverse events while maximizing the therapeutic window of these agents. In this review, we look at the current data on therapy with immune checkpoint inhibitors in advanced HCC, with a focus on pre-transplant treatment prior to liver transplant.

Background. The risk of donor-derived severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in solid organ (heart, lung, liver, kidney, pancreas, and intestine) transplant recipients is poorly understood. Since hematogenous transmission of SARS-CoV-2 has not been documented to date, nonlung solid organs might be suitable for transplantation since they likely portend a low risk of viral transmission. Methods. Abdominal solid organs from SARS-CoV-2–infected donors were transplanted into uninfected recipients. Results. Between April 18, 2021, and October 30, 2021, we performed transplants of 2 livers, 1 simultaneous liver and kidney, 1 kidney, and 1 simultaneous kidney and pancreas from SARS-CoV-2–infected donors into 5 uninfected recipients. None of the recipients developed SARS-CoV-2 infection or coronavirus disease 2019, and when tested, allograft biopsies showed no evidence of SARS-CoV-2 RNA. Conclusions. Transplanting nonlung organs from SARS-CoV-2–infected donors into uninfected recipients demonstrated no evidence of virus transmission.

AbstractBiliary strictures can be a challenging clinical problem to manage and often have unclear etiologies, including benign and malignant causes. Left untreated, these problems can lead to significant morbidity and mortality linked to their underlying diagnosis. The approach to adult patients with biliary strictures requires a multidisciplinary team involving surgeons, interventional endoscopists, and interventional radiologists for diagnosis, symptom relief, palliation, as well as potential curative management. From a surgeon's perspective, there are many ways to classify and approach these strictures. It is of paramount importance to start with an excellent understanding of the patient's prior surgical history. In approaching a patient with a new diagnosis of biliary stricture, it is also critical to understand its etiology relatively quickly, as 70% are malignant in the adult population. Concurrently, one must clearly define the location and extent of the stricture: intrahepatic, hilar, or distal extrahepatic bile duct, as well as whether it is a singular lesion or multifocal phenotypes. This information provides a path forward in clinical decision-making regarding durability and efficacy of therapy, which is typically aimed at decompression and/or surgical resection to prevent cholangitis, sepsis, and progressive hepatic insufficiency.

AbstractBackgroundWhile simultaneous pancreas kidney transplant (SPKTx) is a therapeutic option for patients with type 1 diabetes (T1DM) and renal failure, few centers offer SPKTx to “select” non‐T1DM patients. To address concerns that existing insulin resistance may limit the benefits of the pancreas allograft among non‐T1DM, we compared several indices of glucose homeostasis, in “select” non‐T1DM and T1DM patients who received SPKTx.MethodsCriteria for “select” non‐T1DM included the following: positive C‐peptide, BMI <30 kg/m2, treatment with oral agents before insulin initiation, and insulin at <1 unit/kg/d. We compared several indices of glucose homeostasis within 1 yr post‐SPKTx among seven “select” patients with non‐T1DM and nine patients with T1DM with similar age, BMI, and immunosuppression. Measurements of insulin resistance included the following: homeostatic model, insulin sensitivity index, and insulin–glucose ratio; insulin secretion measures included the following: corrected insulin response.ResultsNon‐T1DM had similar pre‐transplant metabolic (fasting glucose, HbA1c, blood pressure, and lipid) parameters to the T1DM cohort. There were no significant differences in the various measures of insulin resistance and secretion between T1DM and “select” non‐T1DM patients.ConclusionOur results suggest SPKTx should be considered in the therapeutic armamentarium among carefully select non‐T1DM with features of minimal insulin resistance; however, a larger cohort with longer follow‐up is needed to confirm our results.

SAGE-Journals-Accessible-Video-Player 10.1089/vid.2015.0007.M1 sj-vid-1-vid-10.1089_vid.2015.0007

OBJECTIVE New-onset diabetes after kidney transplantation (NODAT) has adverse clinical and economic implications. A risk score for NODAT could help identify research subjects for intervention studies. RESEARCH DESIGN AND METHODS We conducted a single-center retrospective cohort study using pretransplant clinical and laboratory measurements to construct a risk score for NODAT. NODAT was defined by hemoglobin A1c (HbA1c) ≥6.5%, fasting serum glucose ≥126 mg/dL, or prescribed therapy for diabetes within 1 year posttransplant. Three multivariate logistic regression models were constructed: 1) standard model, with both continuous and discrete variables; 2) dichotomous model, with continuous variables dichotomized at clinically relevant cut points; and 3) summary score defined as the sum of the points accrued using the terms from the dichotomous model. RESULTS A total of 316 subjects had seven pretransplant variables with P &lt; 0.10 in univariate logistic regression analyses (age, planned corticosteroid therapy posttransplant, prescription for gout medicine, BMI, fasting glucose and triglycerides, and family history of type 2 diabetes) that were selected for multivariate models. Areas under receiver operating curves for all three models were similar (0.72, 0.71, and 0.70). A simple risk score calculated as the sum of points from the seven variables performed as well as the other two models in identifying risk of NODAT. CONCLUSIONS A risk score computed from seven simple pretransplant variables can identify risk of NODAT.