Machine learning for predicting liver and/or lung metastasis in colorectal cancer: A retrospective study based on the SEER database.

OBJECTIVE: This study aims to establish a machine learning (ML) model for predicting the risk of liver and/or lung metastasis in colorectal cancer (CRC). METHODS: Using the National Institutes of Health (NIH)'s Surveillance, Epidemiology, and End Results (SEER) database, a total of 51265 patients with pathological diagnosis of colorectal cancer from 2010 to 2015 were extracted for model development. On this basis, We have established 7 machine learning algorithm models. Evaluate the model based on accuracy, and AUC of receiver operating characteristics (ROC) and explain the relationship between clinical pathological features and target variables based on the best model. We validated the model among 196 colorectal cancer patients in Beijing Electric Power Hospital of Capital Medical University of China to evaluate its performance and universality. Finally, we have developed a network-based calculator using the best model to predict the risk of liver and/or lung metastasis in colorectal cancer patients. RESULTS: 51265 patients were enrolled in the study, of which 7864 (15.3 %) had distant liver and/or lung metastasis. RF had the best predictive ability, In the internal test set, with an accuracy of 0.895, AUC of 0.956, and AUPR of 0.896. In addition, the RF model was evaluated in the external validation set with an accuracy of 0.913, AUC of 0.912, and AUPR of 0.611. CONCLUSION: In this study, we constructed an RF algorithm mode to predict the risk of colorectal liver and/or lung metastasis, to assist doctors in making clinical decisions.

Machine Learning for Predicting Distant Metastasis of Medullary Thyroid Carcinoma Using the SEER Database.

Objectives: We aimed to establish an effective machine learning (ML) model for predicting the risk of distant metastasis (DM) in medullary thyroid carcinoma (MTC). Methods: Demographic data of MTC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database of the National Institutes of Health between 2004 and 2015 to develop six ML algorithm models. Models were evaluated based on accuracy, precision, recall rate, F1-score, and area under the receiver operating characteristic curve (AUC). The association between clinicopathological characteristics and target variables was interpreted. Analyses were performed using traditional logistic regression (LR). Results: In total, 2049 patients were included and 138 developed DM. Multivariable LR showed that age, sex, tumor size, extrathyroidal extension, and lymph node metastasis were predictive features for DM in MTC. Among the six ML models, the random forest (RF) had the best predictability in assessing the risk of DM in MTC, with an accuracy, precision, recall rate, F1-score, and AUC higher than those of the traditional binary LR model. Conclusion: RF was superior to traditional LR in predicting the risk of DM in MTC and can provide a valuable reference for clinicians in decision-making.

Critical values of monitoring indexes for perioperative major adverse cardiac events in elderly patients with biliary diseases.

BACKGROUND: Major adverse cardiac events (MACE) in elderly patients with biliary diseases are the main cause of perioperative accidental death, but no widely recognized quantitative monitoring index of perioperative cardiac function so far. AIM: To investigate the critical values of monitoring indexes for perioperative MACE in elderly patients with biliary diseases. METHODS: The clinical data of 208 elderly patients with biliary diseases in our hospital from May 2016 to April 2021 were retrospectively analysed. According to whether MACE occurred during the perioperative period, they were divided into the MACE group and the non-MACE group. RESULTS: In the MACE compared with the non-MACE group, postoperative complications, mortality, hospital stay, high sensitivity troponin-I (Hs-TnI), creatine kinase isoenzyme (CK-MB), myoglobin (MYO), B-type natriuretic peptide (BNP), and D-dimer (D-D) levels were significantly increased (P < 0.05). Multivariate logistic regression showed that postoperative BNP and D-D were independent risk factors for perioperative MACE, and their cut-off values in the receiver operating characteristic (ROC) curve were 382.65 pg/mL and 0.965 mg/L, respectively. CONCLUSION: The postoperative BNP and D-D were independent risk factors for perioperative MACE, with the critical values of 382.65 pg/mL and 0.965 mg/L respectively. Consequently, timely monitoring and effective maintenance of perioperative cardiac function stability are of great clinical significance to further improve the perioperative safety of elderly patients with biliary diseases.

Therapeutic experience of a pancreatic mixed serous neuroendocrine neoplasm invading peripancreatic vessels: A case report.

RATIONALE: Pancreatic mixed serous neuroendocrine neoplasm (PMSNN) is an extremely rare disease. Only a few cases on the surgical treatment of PMSNN have been reported in the literature, and it is unclear whether there is invasion of important peripancreatic vessels. PATIENT CONCERNS: We report the case of a 39-year-old female patient with PMSNN accompanied by invasion of important peripancreatic vessels. She underwent surgery and achieved satisfactory recovery. DIAGNOSIS: Abdominal enhanced CT images showed an enhanced mass with a nonenhanced cyst involving the head and body of the pancreas, which invaded important peripancreatic vessels. The lesion had been misdiagnosed and mistreated as a metastatic carcinoma before admission. INTERVENTIONS: CT 3-dimensional (3D) visualization reconstruction images showed intact peripancreatic vessels. Radical pancreatoduodenectomy was successfully performed and confirmed that the main blood vessels around the pancreas were only compressed or even wrapped by the mass, but not penetrated. OUTCOMES: The patient recovered well and was discharged on the 19th day after surgery. Pathological examination reported the diagnosis of PMSNN with the collision type combination and the well-differentiated grade 2 pancreatic neuroendocrine tumor. She was followed up for 18 months without any abnormalities. LESSONS: This case demonstrates that surgical treatment of PMSNN with invasion of peripancreatic vessels can be successful. Preoperative abdominal CT 3D visualization reconstruction is helpful in determining the degree of invasion of important peripancreatic vessels, and plays a key role in formulating an accurate surgical plan and improving patient outcome.

Hb Wanjiang: A New ß-Globin Chain Variant with Two Amino Acid Substitutions (HBB: c.255_264delinsTTTTTCTCAG).

We report a new hemoglobin (Hb) variant that we have named Hb Wanjiang (HBB: c.255_264delinsTTTTTCTCAG). We identified this variant in a Chinese man by the next-generation sequencing (NGS) method. The father of the proband also carried the same variant. This variant results from a 10 bp deletion at codons 84-87 of the ß-globin chain, replaced with 10 nucleotides coming from the δ-globin gene at the same position, leading to the substitution of two amino acids in the peptide chain with no change in the ß-globin chain length. The heterozygotes had a normal hematological feature with no abnormal Hb variant detectable on capillary electrophoresis (CE) and high performance liquid chromatography (HPLC). The combination of Hb Wanjiang and ß-thalassemia (ß-thal) was not found to aggravate anemia.