Article

Reclassification of neuroendocrine tumors improves the separation of carcinoids and the prediction of survival.

Department of Pathology, Herlev University Hospital, division Gentofte, Copenhagen, Denmark.
Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer (Impact Factor: 4.55). 01/2009; 3(12):1410-5. DOI: 10.1097/JTO.0b013e31818e0dd4
Source: PubMed

ABSTRACT The classification of neuroendocrine lung tumors has changed over the last decades. Reliable diagnoses are crucial for the quality of clinical databases. The purpose of this study is to determine to which extent the use of different diagnostic criteria of neuroendocrine lung tumors has influenced the classification of these tumors. The prognostic information of tumor, node, metastasis descriptors was also evaluated.
We retrieved 110 tumors from the period 1989 to 2007. All tumors were reclassified according to the World Health Organization classification of 2004. Tumor, node, metastasis descriptors were evaluated.
By reclassification, the diagnoses on 48 tumors (44%) were changed. More diagnoses were changed in the older part of the material. A significantly different survival was shown for all patients in relation to tumor size (p < 0.0001). An endobronchial component was seen in 54%, 31%, and 11% of typical carcinoid, atypical carcinoid, and large cell neuroendocrine carcinoma, respectively with no impact on survival (p = 0.90). For all included patients the survival was significantly worse for patients having metastasis to N1 nodes as compared with N0 (p = 0.03). However, the number of removed lymph nodes were insufficient for definitive determination of the prognostic impact of node metastases. Regarding the revised diagnoses, a significant difference in survival between typical carcinoid, atypical carcinoid, large cell neuroendocrine carcinoma and small cell carcinoma was noted (p < 0.005).
Tumors must be rediagnosed before entering a central database. Tumor and node seem to be useful predictors of survival.

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