Zhai YH, Zheng Z, Deng W, Yin J, Bai ZG, Liu XY, Zhang J, Zhang ZT. Inflammation-related indicators to distinguish between gastric stromal tumors and leiomyomas: A retrospective study.
World J Clin Cases 2022;
10:458-468. [PMID:
35097070 PMCID:
PMC8771401 DOI:
10.12998/wjcc.v10.i2.458]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 10/20/2021] [Accepted: 12/02/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND
Gastric leiomyomas and gastric stromal tumors are the most common types of gastric tumors encountered. In recent years, the incidence of the two types of tumors has been increasing, but the differential diagnosis is still a challenge in clinical work. However, as there are many reports on stromal tumors and inflammation-related indicators are gradually being paid attention to as important factors in predicting tumor prognosis, the two main purposes of this study were to explore the inflammation-related differences between the two types of tumors and to develop a nomogram as a predictive model.
AIM
To explore the differences in platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), lymphocyte mononuclear cell ratio (LMR), and SII between the two types of tumors, and simultaneously create the nomogram model.
METHODS
This study enrolled 88 patients in the gastric stromal tumor group and 56 patients in the gastric leiomyoma group, and the relevant data of the two groups were entered into the system for an integrated analysis. The primary objective of this study was to identify the differences in the inflammation index between the two types of tumors.
RESULTS
There were statistically significant differences between the two groups in sex, age, and tumor location. In comparison, gastric leiomyomas seem to be more common in women, young patients, and gastric cardia, which is in line with our previous research; the groups showed the following statistical differences: PLR (158.2% vs 134.3%, P = 0.028), NLR (2.35 vs 1.68, P = 0.000), LMR (5.75 vs 10.8, P = 0.004), and SII (546.2 vs 384.3, P = 0.003). The results of the multivariate logistic regression analysis showed that sex, age, tumor location, and LMR were independent risk factors for the identification of the two types of tumors. After considering the risk factors selected by the above analysis into the predictive model, a predictive model for distinguishing gastrointestinal stromal tumors from gastric leiomyomas was established as the nomogram.
CONCLUSION
Gastric leiomyomas and gastric stromal tumors are not only different in factors such as age of the patient, but also in inflammatory indicators such as LMR and PLR. We have established a predictive model related to the laboratory indicators and are looking forward to further research conducted in this clinical area.
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