The Value of Contrast-Enhanced Ultrasound in the Detection of Sentinel Lymph Nodes in Malignant Melanoma.

OBJECTIVE: To evaluate the location and characterization value of contrast-enhanced ultrasound (CEUS) in the detection of sentinel lymph nodes (SLNs) in malignant melanoma. METHODS: SLNs and the lymph node network were tracked by subcutaneous injection of ultrasonic contrast agent around the tumor and preoperative localization, and qualitative analyses were performed. The SLNs were also detected by the intraoperative subcutaneous injection of carbon nanoparticles, and the findings were compared with lymph nodes located by CEUS. The accuracy of the preoperative lymph node identification was evaluated by the results of postoperative pathology, which served as the gold standard of detection. RESULTS: In 47 patients with malignant melanoma, the mean number of SLNs detected by CEUS was 1.72 ± 0.10, while that by carbon nanoparticle administration it was 1.79 ± 1.07 (P = .371 > .05). Seven cases of lymph node metastasis were detected by CEUS, with a sensitivity of 70.0%, specificity of 97.3%, positive predictive value of 87.5%, negative predictive value of 92.3%, and accuracy of 91.5%. There was high consistency between the findings of CEUS and pathology in differentiating benign and malignant lymph nodes (kappa = 0.726, χ2  = 25.243, P < .001). CONCLUSIONS: CEUS can localize and differentiate SLNs in malignant melanoma, and thus, may potentially guide clinical treatment in the future.

Establishment and validation of a prognostic nomogram for patients with colorectal neuroendocrine carcinoma.

BACKGROUND: Colorectal neuroendocrine carcinoma is a relatively rare tumor, for which a prognosis prediction model is lacking. Based on the data from Surveillance, Epidemiology, and End Results (SEER) database and Fujian Cancer Hospital, the study constructed and validated a prognostic nomogram to assess overall survival of patients with colorectal neuroendocrine carcinoma(CRNEC). METHODS: We extracted data of patients diagnosed with CRNEC from the SEER database. These patients were randomly divided into a training cohort(N = 1425) and an internal validation cohort(N = 612). Data of patients diagnosed with CRNEC in Fujian Cancer Hospital was collected as an external validation cohort(N = 54). A prognostic nomogram was established. The performance of the nomogram was assessed with ROC curve, C-index and calibration curve. Decision curve analysis(DCA) and ROC curve were used to compare the prediction efficacy of nomogram with the seventh edition of the TNM classification of the American Joint Commission of Cancer. RESULTS: Nine variables were identified as independent predictors. Nomogram were established by the nine variables. AUC of the nomogram in predicting 1-, 3- and 5-year OS were 0.900, 0.912 and 0.915 in training cohort, 0.900, 0.925 and 0.919 in internal validation cohort, 0.900, 0.903 and 0.928 in external validation cohort. C-index were 0.845, 0.854 and 0.837. Calibration curves overlapped well with reference lines. Compared with the AJCC TNM staging system, the nomogram performed more effectively. Patients classified into low-risk and high-risk groups by the nomogram scores and performed well in stratification. CONCLUSION: The prognostic nomogram established and validated in our study can accurately and effectively predict the prognosis of patients with CRNEC.

The relationship between cancer-related fatigue, quality of life and pain among cancer patients.

Objectives: This study aimed to select patients with cancer-related pain to further analyze the relationship between pain severity, fatigue severity, and quality of life. Methods: A cross-sectional study was conducted. A convenience sampling method was used to select 224 patients with cancer-related pain who were undergoing chemotherapy and met the inclusion criteria in two hospitals of two provinces from May to November 2019. All participants were invited to complete a general information questionnaire, the Brief Fatigue Inventory (BFI), the Numerical Rating Scale (NRS) for pain intensity, and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Results: In the 24 h before completing the scales, 85 patients (37.9%) had mild pain, 121 (54.0%) had moderate pain, and 18 (8.0%) had severe pain. In addition, 92 (41.1%) patients had mild fatigue, 72 (32.1%) had moderate fatigue, and 60 (26.8%) had severe fatigue. Most patients with mild pain only experienced mild fatigue, and their quality of life was also at a moderate level. Patients with moderate and severe pain mostly had moderate or higher levels of fatigue and a lower quality of life. There was no correlation between fatigue and quality of life in patients with mild pain (r = -0.179, P = 0.104). There was a correlation between fatigue and quality of life in patients with moderate and severe pain (r = -0.537, P < 0.01; r = -0.509, P < 0.05). Conclusions: Patients with moderate and severe pain have more fatigue symptoms and lower quality of life than those with mild pain. Nurses should pay more attention to patients with moderate and severe pain, explore the interaction mechanism between symptoms, and carry out joint symptom intervention to improve the quality of life of patients.