Sınıflandırılamayan akciğer yüksek dereceli nöroendokrin karsinomaların klinik özellikleri ve sağ kalım sonuçları

Author:

SÖYLER Yasemin1ORCID,AKIN KABALAK Pınar1ORCID,KAVURGACI Suna1ORCID,DEMİRAĞ Funda2ORCID,YILMAZ Ülkü1ORCID

Affiliation:

1. Ankara Ataturk Sanatorium Training and Research Hospital, Department of Chest Diseases

2. Ankara Ataturk Sanatorium Training and Research Hospital, Department of Pathology

Abstract

Background: Differentiating high-grade neuroendocrine carcinomas (HGNEC) is difficult. We aimed to assess the clinical features and survival outcomes of unclassified HGNEC (uHGNEC) and to compare it with small-cell lung cancer (SCLC). Material and Methods: This was a retrospective and observational study of HGNEC patients. Kaplan-Meier method was used to estimate progression-free survival (PFS) and overall survival (OS). Cox-regression analyses were used to determine the risk factors independently associated with PFS and OS. Results: One hundred twenty-one patients [uHGNEC (n = 35), SCLC (n = 86)] were analysed. The primary tumour was mostly right-sided, located in the centre of the lungs. The IASLC stage at diagnosis was locally advanced in 43 (35.5%) patients and advanced in 78 (64.5%) patients. uHGNEC and SCLC groups shared similar clinical features. The study population's median PFS and OS were 8.8 (95%Cl 7.29 – 10.30) and 10.9 (95%Cl 9.9 – 11.8) months, respectively. uHGNEC- and SCLC groups had a similar PFS (9.4 vs 8.6 months, p = 0.99) and OS (12 vs 10.7 months, p = 0.51). The six-month, one- and two-year PFS and OS of two groups were also similar. Among all patients, a right-sided tumour (HR: 1.558, 95%Cl 1.044 – 2.325, p = 0.03) and advanced-stage disease (HR: 1.928, 95%Cl 1.292 – 2.877, p = 0.001) were prognostic factors for poor OS. Cox-regression analysis indicated that histopathology did not have an impact on PFS and OS. Conclusion: HGNEC patients who cannot be classified pathologically behave like SCLC.

Funder

None

Publisher

Sakarya Tip Dergisi

Subject

General Computer Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Understanding Time Series Analysis in Early Detection of Unclassified Endocrine Tumors;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

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