Machine learning-based model for prediction and feature analysis of recurrence in pancreatic neuroendocrine tumors G1/G2.

BACKGROUND: Pancreatic neuroendocrine neoplasms (PanNENs) are a heterogeneous group of tumors. Although the prognosis of resected PanNENs is generally considered to be good, a relatively high recurrence rate has been reported. Given the scarcity of large-scale reports about PanNEN recurrence due to their rarity, we aimed to identify the predictors for recurrence in patients with resected PanNENs to improve prognosis. METHODS: We established a multicenter database of 573 patients with PanNENs, who underwent resection between January 1987 and July 2020 at 22 Japanese centers, mainly in the Kyushu region. We evaluated the clinical characteristics of 371 patients with localized non-functioning pancreatic neuroendocrine tumors (G1/G2). We also constructed a machine learning-based prediction model to analyze the important features to determine recurrence. RESULTS: Fifty-two patients experienced recurrence (14.0%) during the follow-up period, with the median time of recurrence being 33.7 months. The random survival forest (RSF) model showed better predictive performance than the Cox proportional hazards regression model in terms of the Harrell's C-index (0.841 vs. 0.820). The Ki-67 index, residual tumor, WHO grade, tumor size, and lymph node metastasis were the top five predictors in the RSF model; tumor size above 20 mm was the watershed with increased recurrence probability, whereas the 5-year disease-free survival rate decreased linearly as the Ki-67 index increased. CONCLUSIONS: Our study revealed the characteristics of resected PanNENs in real-world clinical practice. Machine learning techniques can be powerful analytical tools that provide new insights into the relationship between the Ki-67 index or tumor size and recurrence.

Disturbance of consciousness due to hyperammonemia and lactic acidosis during mFOLFOX6 regimen: Case report.

INTRODUCTION: FOLFOX therapy is the main chemotherapy regimen for colorectal cancer. Peripheral neuropathy, hematotoxicity, and digestive symptoms are known to be the most frequent adverse events. Hyperammonemia and lactic acidosis rarely occur simultaneously during treatment with FOLFOX therapy; the number of case reports is limited worldwide. We report a case of disturbance of consciousness, considered to be caused by hyperammonemia and lactic acidosis that occurred during treatment with mFOLFOX6 therapy that was administered as postoperative adjuvant treatment for rectal cancer. PATIENT CONCERNS: This case was of a 71-year-old man who had been receiving oral treatment for chronic kidney disease and diabetes mellitus. Laparoscopic low anterior resection and artificial anal construction surgery were performed for stage III rectal cancer. As adjuvant postoperative therapy, mFOLFOX6 therapy was started but was followed by a disturbance of consciousness. DIAGNOSES: Results of the blood tests revealed notable hyperammonemia (ammonia level, 1,163 µg/dl) and lactic acidosis (pH 7.207; lactate, 17.56 mmol/L); however, imaging diagnosis did not reveal intracranial lesions that could cause disturbance of consciousness. INTERVENTIONS: For hyperammonemia, branched-chain amino acid agents and Ringers solution supplementation were administered. For acidosis, 7% sodium hydrogen carbonate was administered as treatment. OUTCOMES: The disturbance of consciousness improved within 12 hours of initiating the treatment, and the patient was discharged with no sequelae on 7th day after hospitalization. CONCLUSION: In patients with chronic kidney disease, FOLFOX regimen may confer risks of hyperammonemia and lactic acidosis.