Aggressive surgical approach in patients with adrenal-only metastases from hepatocellular carcinoma enables higher survival rates than standard systemic therapy.

BACKGROUND: Although guidelines recommend systemic therapy even in patients with limited extrahepatic metastases from hepatocellular carcinoma (HCC), a few recent studies suggested a potential benefit for resection of extrahepatic metastases. However, the benefit of adrenal resection (AR) for adrenal-only metastases (AOM) from HCC was not proved yet. This is the first study to compare long-term outcomes of AR to those of sorafenib in patients with AOM from HCC. METHODS: The patients with adrenal metastases (AM) from HCC were identified from the electronic records of the institution between January 2002 and December 2018. Those who presented AM and other sites of extrahepatic disease were excluded. Furthermore, the patients with AOM who received other therapies than AR or sorafenib were excluded. RESULTS: A total of 34 patients with AM from HCC were treated. Out of these, 22 patients had AOM, 6 receiving other treatment than AR or sorafenib. Eventually, 8 patients with AOM underwent AR (AR group), while 8 patients were treated with sorafenib (SOR group). The baseline characteristics of the two groups were not significantly different in terms of age, sex, number and size of the primary tumor, timing of AM diagnosis, Child-Pugh and ECOG status. After a median follow-up of 15.5 months, in the AR group, the 1-, 3-, and 5-year overall survival rates (85.7%, 42.9%, and 0%, respectively) were significantly higher than those achieved in the SOR group (62.5%, 0% and 0% at 1-, 3- and 5-year, respectively) (P = 0.009). The median progression-free survival after AR (14 months) was significantly longer than that after sorafenib therapy (6 months, P = 0.002). CONCLUSIONS: In patients with AOM from HCC, AR was associated with significantly higher overall and progression-free survival rates than systemic therapy with sorafenib. These results could represent a starting-point for future phase II/III clinical trials.

Pharmacogenomic analyses of sunitinib in patients with pancreatic neuroendocrine tumors.

Aim: Evaluate associations between clinical outcomes and SNPs in patients with well-differentiated pancreatic neuroendocrine tumors receiving sunitinib. Patients & methods: Kaplan-Meier and Cox proportional hazards models were used to analyze the association between SNPs and survival outcomes using data from a sunitinib Phase IV (genotyped, n = 56) study. Fisher's exact test was used to analyze objective response rate and genotype associations. Results: After multiplicity adjustment, progression-free and overall survivals were not significantly correlated with SNPs; however, a higher objective response rate was significantly associated with IL1B rs16944 G/A versus G/G (46.4 vs 4.5%; p = 0.001). Conclusion: IL1B SNPs may predict treatment response in patients with pancreatic neuroendocrine tumors. VEGF pathway SNPs are potentially associated with survival outcomes.

Efficacy and Safety of Sunitinib in Patients with Well-Differentiated Pancreatic Neuroendocrine Tumours.

BACKGROUND: In a phase III study, sunitinib led to a significant increase in progression-free survival (PFS) versus placebo in patients with pancreatic neuroendocrine tumours (panNETs). This study was a post-marketing commitment to support the phase III data. METHODS: In this ongoing, open-label, phase IV trial (NCT01525550), patients with progressive, advanced unresectable/metastatic, well-differentiated panNETs received continuous sunitinib 37.5 mg once daily. Eligibility criteria were similar to those of the phase III study. The primary endpoint was investigator-assessed PFS per Response Evaluation Criteria in Solid Tumours v1.0 (RECIST). Other endpoints included PFS per Choi criteria, overall survival (OS), objective response rate (ORR), and adverse events (AEs). RESULTS: Sixty-one treatment-naive and 45 previously treated patients received sunitinib. By March 19, 2016, 82 (77%) patients had discontinued treatment, mainly due to disease progression. Median treatment duration was 11.7 months. Investigator-assessed median PFS per RECIST (95% confidence interval [CI]) was 13.2 months (10.9-16.7): 13.2 (7.4-16.8) and 13.0 (9.2-20.4) in treatment-naive and previously treated patients, respectively. ORR (95% CI) per RECIST was 24.5% (16.7-33.8) in the total population: 21.3% (11.9-33.7) in treatment-naive and 28.9% (16.4-44.3) in previously treated patients. Median OS, although not yet mature, was 37.8 months (95% CI, 33.0-not estimable). The most common treatment-related AEs were neutropenia (53.8%), diarrhoea (46.2%), and leukopenia (43.4%). CONCLUSIONS: This phase IV trial confirms sunitinib as an efficacious and safe treatment option in patients with advanced/metastatic, well-differentiated, unresectable panNETs, and supports the phase III study outcomes. AEs were consistent with the known safety profile of sunitinib.

Real-Life Results of Palliative Chemotherapy in Metastatic Pancreatic Ductal Adenocarcinoma.

PURPOSE: To assess the efficacy of FOLFIRINOX(FFX), gemcitabine-based regimens (GB), and gemcitabine monotherapy (Gem) in patients with metastatic pancreatic ductal adenocarcinoma (mPDAC). METHODS: This is a retrospective study that included 83 patients with mPDAC treated with first-line chemotherapy (L1) with either FFX, GB or Gem between 2015 and 2017. Progression-free survival (PFS) for L1 and second-line chemotherapy (L2) (PFS-L1 and PFS-L2) and overall survival (OS) were estimated using the Kaplan-Meier method. RESULTS: Median PFS-L1 for FFX, GB and Gem groups was 9 months (95% (Confidence Interval) CI 2.76-15.24), 5 months (95%CI 3.44-6.56), and 5 months (95%CI 3.76-6.24), respectively (p = 0.04). OS was 14 months (95%CI 11.16-16.85), 12 months (95%CI: 9.44-11.56), and 7 months (95%CI: 5.7-8.3) for patients treated with FFX, GB, and Gem, respectively (p = 0.0001). ECOG-PS (0/1) (Hazard Ratio (HR) 6.74, p = 0.002), age > 70 years (HR 0.25, p = 0.04), body tumors (HR 2.8, p = 0.048), CA19-9 > 39 U/mL (HR 0.26, p = 0.02), and neutrophil-to-lymphocyte ratio (NLR) > 4.15 (HR 6.76, p = 0.001) were independent prognostic factors for PFS-L1. Male gender (HR 3.02, p = 0.026), ECOG-PS (0/1) (HR 4.21, p = 0.003), L1 with FFX (HR 0.255, p = 0.007), and NLR > 4.15 (HR 2.65, p = 0.04) were independent prognostic factors of OS. PFS-L2 (HR 6.91, p = 0.013) and OS-L2 (HR 6.95, p = 0.037) were significantly higher in patients first treated with FFX. CONCLUSIONS: The OS of patients who receive FFX or GB is comparable. The best PFS-L1 belongs to the FFX group. Male gender, ECOG-PS 0/1, the FFX regimen, and NLR > 4.15 were independent predictors of OS. PFS-L2 and OS-L2 were favorably impacted by L1 with FFX.

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.