Primary small cell carcinoma of kidney after renal transplantation: a case report and literature review

An online tool for survival prediction of extrapulmonary small cell carcinoma with random forest

Purpose

Extrapulmonary small cell carcinoma (EPSCC) is rare, and its knowledge is mainly extrapolated from small cell lung carcinoma. Reliable survival prediction tools are lacking.

Methods

A total of 3,921 cases of EPSCC were collected from the Surveillance Epidemiology and End Results (SEER) database, which form the training and internal validation cohorts of the survival prediction model. The endpoint was an overall survival of 0.5-5 years. Internal validation performances of machine learning algorithms were compared, and the best model was selected. External validation (n = 68) was performed to evaluate the generalization ability of the selected model.

Results

Among machine learning algorithms, the random forest model performs best on internal validation, whose area under the curve (AUC) is 0.736-0.800. The net benefit is higher than the TNM classification in decision curve analysis. The AUC of this model on the external validation cohort is 0.739-0.811. This model was then deployed online as a free, publicly available prediction tool of EPSCC (http://42.192.80.13:4399/).

Conclusion

This study provides an excellent online survival prediction tool for EPSCC with machine learning and large-scale data. Age, TNM stages, and surgery (including potential performance status information) are the most critical factors for the prediction model.

[Disseminated combined small cell carcinoma with graft involvement after kidney transplantation from a deceased donor to two patients]

The paper describes cases of disseminated small-cell carcinoma after kidney transplantation from a deceased donor to two patients. Microscopic examination showed that the kidney graft tumor consisted of tightly packed small rounded cells with hyperchromatic nuclei and a narrow cytoplasmic rim with invisible nucleoli. The mitotic index was 25-40/2 mm². Azzopardi's phenomenon and crush artifact were detected in the tumor. Giant cell and large cell components were 30-40% of the area of sections. Immunohistochemical examination revealed the expression of synaptophysin, chromogranin A, CD56, TTF-1, HMWK, СК7, СК18, and Ki-67 (80% of tumor cells). Histological findings and immunophenotype in both cases led to the conclusion about combined small cell carcinoma with renal graft involvement. Both patients died from tumor dissemination 9 and 11 months after transplantations. In reviewing the literature, the authors found only one such observation.

Value of (18)F-FDG PET/CT and MRI in diagnosing primary endometrial small cell carcinoma

Primary small cell carcinoma (SCC) is a group of aggressive neoplasms that mainly arise from the lung and digestive tract. Endometrial small cell carcinoma (ESCC) is extremely rare. To our knowledge, less than 90 cases have been reported, and most of these reports were dedicated to describing the clinicopathologic or immunochemical features of ESCC. Herein, we present a new case of ESCC involving a 51-year-old woman and mainly focus on the magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) findings. MRI showed that the uterus was significantly enlarged (11.6 cm × 11.1 cm × 14.4 cm), and a giant irregular mass (7.5 cm × 8.4 cm × 8.5 cm) was observed in the uterine cavity. The lesion demonstrated an extremely low apparent diffusion coefficient (ADC) value [(0.553±0.088)×10(-3) mm(2)/s] and a high FDG uptake value (22.7). Multiple metastatic lymph nodes (LNs) were identified at different positions, with diameters ranging from 0.3 to 2.8 cm and a maximum standardized uptake value (SUVmax) ranging from 6.9 to 19.3.