Neuroendocrine carcinoma of the cervix: A comprehensive clinicopathologic study and literature review

Aims

Neuroendocrine carcinoma of the cervix (NECC) is a rare variant of cervical cancer. This study aims to investigate the clinicopathological features and prognosis of NECC.

Methods

A retrospective analysis was conducted on twenty-one patients diagnosed with NECC between May 2008 and September 2021 ​at Peking University People's Hospital. The study involved histopathological examination, immunohistochemistry, ThinPrep cytology test (TCT), and high-risk HPV hybrid capture 2 (HC2) assay. Follow-up was conducted through telephone interviews and medical records for a range of 3–160 months, with an average follow-up period of 49.8 months.

Results

The average age of the patients was 48.6 years (range: 33–69 years). Seventeen patients were diagnosed with neuroendocrine carcinoma through biopsy. Nine cases underwent TCT and HC2 tests before biopsy, and TCT results of four cases showed high-grade squamous intraepithelial lesion (HSIL). High-risk HPV(HR-HPV) positive was detected in seven cases. The cancer cells exhibited consistent morphological features, including sparse cytoplasm, intensely stained nuclei, and extensive neoplastic necrosis. Thirteen cases were classified as pure NECC (61.9%), while eight cases were mixed types (38.1%). Three cases were associated with squamous cell carcinoma (SCC), and five cases were associated with adenocarcinoma. Prognosis varied significantly among these subtypes (p ​< ​0.05). The overall survival rate in the follow-up period was 66.7% (12/18).

Conclusions

NECC is an extremely rare and highly aggressive tumor with a poor prognosis, particularly in cases of mixed histology. It is strongly associated with HPV infection. TCT and HPV testing significantly enhance the detection rate before the biopsy. The diagnosis of NECC relies on histological and immunohistochemical examinations. This study provides valuable clinical observations on NECC and emphasizes the importance of early detection and accurate diagnosis for improved patient outcomes.