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Background: The mechanisms of distant metastasis in pancreatic cancer (PC) have not been elucidated, and this study aimed to explore the risk factors affecting the metastasis and prognosis of metastatic patients and to develop a predictive model. Method: Clinical data from patients meeting criteria from 1990 to 2019 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and two machine learning methods, random forest and support vector machine, combined with logistic regression, were used to explore risk factors influencing distant metastasis and to create nomograms. The performance of the model was validated using calibration curves and ROC curves based on the Shaanxi Provincial People's Hospital cohort. LASSO regression and Cox regression models were used to explore the independent risk factors affecting the prognosis of patients with distant PC metastases. Results: We found that independent risk factors affecting PC distant metastasis were: age, radiotherapy, chemotherapy, T and N; the independent risk factors for patient prognosis were: age, grade, bone metastasis, brain metastasis, lung metastasis, radiotherapy and chemotherapy. Conclusion: Together, our study provides a method for risk factors and prognostic assessment for patients with distant PC metastases. The nomogram we developed can be used as a convenient individualized tool to facilitate aid in clinical decision making. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to elucidate the role of quantitative tumor burden based on PET/CT of somatostatin receptors in well-differentiated neuroendocrine tumors (NETs). Methods: This study enrolled patients with [68 Ga]Ga-DOTA-NOC PET/CT-positive advanced NETs who did not receive medical treatment prior to PET/CT. Tumor burden was calculated using methods based on the background threshold and relative fixed threshold values (30%, 40%, and 50%). The prognostic value of the measured tumor burden in reference to overall survival (OS) and progression-free survival (PFS) on treatment with octreotide long-acting repeatable (LAR) was assessed using Cox regression analysis, Harrell's C-index, and survival analysis. A classification and regression tree (CART) was used to determine the optimal threshold for tumor burden. Results: A total of 204 patients were included. Somatostatin receptor-expressing tumor volume (SRETV) and liver SRETV derived from a relative fixed threshold of 30% (SRETV30 and liver SRETV30) were statistically significantly associated with OS (C-index: 0.802 [95% confidence interval (CI), 0.658–0.946] and 0.806 [95% CI, 0.664–0.948], respectively). Extrahepatic tumor burden was not correlated with OS (hazard ratio: 0.617, 95% CI: 0.241–1.574, P = 0.312). Among 155 patients with non-functional NETs with a ki-67 index of ≤ 10%, those with a high SRETV30 (P = 0.016) or high liver SRETV30 (P = 0.014) showed statistically significantly worse PFS on treatment with octreotide LAR. Patients receiving a higher dose of octreotide LAR normalized by SRETV30 or liver SRETV30 (a normalized dose or a liver normalized dose) showed prolonged PFS on treatment with octreotide LAR and a prolonged OS. Conclusion: Quantitative tumor burden based on [68 Ga]Ga-DOTA-NOC PET/CT was correlated with OS and PFS in patients with non-functional NETs with a ki-67 index of ≤ 10% who received octreotide LAR. Calculating normalized and liver normalized doses may help in selecting the starting dose of octreotide LAR. [ABSTRACT FROM AUTHOR]