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Development of a Novel Prognostic Risk Classification System for Malignant Pleural Mesothelioma

Authors :
Kazuhiro Kitajima
Hiroshi Doi
Takashi Kijima
Koichiro Yamakado
Kozo Kuribayashi
Source :
Clinical Lung Cancer. 21:66-74.e2
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

Introduction This study aimed to assess prognostic factors to better understand malignant pleural mesothelioma (MPM) and to develop a new classification protocol beyond the standard tumor node metastasis (TNM) staging system. Materials and Methods We retrospectively reviewed the data of 188 patients with MPM who had not undergone surgical resection. For each patient, we calculated the maximum standardized uptake value (SUVmax), metabolic tumor volume, and total lesion glycolysis (TLG) on pretreatment 18F-fluoro-2-deoxyglucose-positron emission tomography/computed tomography. Using the Cox proportional hazards model, we evaluated the relationships among potential MPM predictors, including age, gender, performance status, histologic type, stage, possible serum markers, and volume-based positron emission tomography parameters, as well as overall survival. Results The median survival was 461 days, and the 1- and 2-year overall survival rates were 60.70% and 31.10%, respectively. Univariate and multivariate analyses revealed that the significant independent predictors of poor survival outcomes were the non-epithelioid histologic type, elevated serum lactate dehydrogenase levels, a neutrophil-to-lymphocyte ratio of ≥ 5.0, and a TLG of ≥ 525 g. We then used these results to develop a prognostic risk classification system. From the resulting survival curve, we found a significant difference among the 3 risk groups of independent variables. Moreover, there were significant differences between all pairs of 2 separated risk groups. Conclusions Pathologic subtypes, serum lactate dehydrogenase, neutrophil-to-lymphocyte ratio, and TLG in 18F-fluoro-2-deoxyglucose-positron emission tomography/computed tomography were independent and significant prognostic factors of MPM. Using this model, we created a new risk classification system that supplants the standard TNM staging protocol.

Details

ISSN :
15257304
Volume :
21
Database :
OpenAIRE
Journal :
Clinical Lung Cancer
Accession number :
edsair.doi.dedup.....08a6c6ef8169655ceb685037da9f9806