Publication: Predictive values of clinical and pathological parameters for malignancy of gastrointestinal stromal tumors
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Date
2009
Authors
Hou, Ying-Yong ; Lu, Shao-Hua ; Zhou, Yang ; Xu, Jian-Fang ; Ji, Yuan ; Hou, Jun ; Qi, Wei-Dong ; Shi, Yuan ; Tan, Yun-Shan ; Zhu, Xiong-Zeng
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Publisher
Murcia : F. Hernández
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DOI
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info:eu-repo/semantics/article
Description
Abstract
Gastrointestinal stromal tumors (GISTs)
possess a wide spectrum of biological properties, from
indolent to highly aggressive. In this study, we evaluated
a set of clinical and pathological parameters for their
predicative values for malignancy of GISTs by
retrospective reviews of tumor specimens and their
relevant medical records from 840 patients. All GIST
cases were first assigned as malignant if they met any of
the following criteria: gross spreads, including liver
metastassis and/or peritoneal dissemination, microscopic
spreads, including lymph node metastasis, infiltrations to
vascular, fat, nerve and muscularis mucosal tissues, or
relapse. The remaining cases were recorded as biological
behavior uncertain. This initial assignment revealed a set
of five morphological features to be associated with
malignancy. They were: mitotic counts greater than 10
per 50HPFs (P<0.0001), muscularis propria infiltration
(P<0.0001), coagulative necrosis (P<0.0001),
perivascular growth pattern (P=0.005), and severe
nuclear atypia (P=0.014). Therefore, a new classification system, including criteria of 2 gross spreads, 5
microscopic spreads, and 5 histopathological parameters
was developed. All the GIST cases were re-classified
into a group of 485 malignant tumors, and a group of
355 nonmalignant tumors. Patient follow-up data
revealed 5-year disease-free and overall survival rates as
high as 99.3% and 100% for the nonmalignant group,
but low rates of 43.9% and 59.7% for the malignant
group. These results demonstrated a correlation of the
new classification with clinical outcomes. Therefore, this
set of 12 parameters has predictive values for
malignancy of GISTs, and is potentially useful in the
grading of the tumors.
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