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Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes
BACKGROUND: Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681585/ https://www.ncbi.nlm.nih.gov/pubmed/33239911 http://dx.doi.org/10.2147/CMAR.S275422 |
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author | Xu, Shao-Jun Lin, Guo-Sheng Ling, Hong-Jian Guo, Ren-Jie Chen, Jie Liao, Yi-Ming Lin, Tao Zhou, Yong-Jian |
author_facet | Xu, Shao-Jun Lin, Guo-Sheng Ling, Hong-Jian Guo, Ren-Jie Chen, Jie Liao, Yi-Ming Lin, Tao Zhou, Yong-Jian |
author_sort | Xu, Shao-Jun |
collection | PubMed |
description | BACKGROUND: Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of GIST. PATIENTS AND METHODS: GIST patients seen between April 2002 and December 2018 were selected from an institutional database. Using multivariate logistic regression analyses, we created a nomogram to predict occult PM of GIST and validated it with an independent cohort from the same center. The concordance index (C-index), decision curve analysis (DCA) and a clinical impact curve (CIC) were used to evaluate its predictive ability. RESULTS: A total of 522 eligible GIST patients were enrolled in this study and divided into training (n=350) and validation cohorts (n=172). Factors associated with occult PM were included in the model: tumor size (odds ratio [OR] 1.194 95% confidence interval [CI], 1.034–1.378; p=0.016), primary location (OR 7.365 95% CI, 2.192–24.746; p=0.001), tumor capsule (OR 4.282 95% CI, 1.209–15.166; p=0.024), Alb (OR 0.813 95% CI, 0.693–0.954; p=0.011) and FIB (OR 2.322 95% CI, 1.410–3.823; p=0.001). The C-index was 0.951 (95% CI, 0.917–0.985) in the training cohort and 0.946 (95% CI, 0.900–0.992) in the validation cohort. In the training cohort, the prediction model had a sensitivity of 82.8%, a specificity of 93.8%, a positive predictive value of 54.7%, and a negative predictive value of 98.4%; the validation cohort values were 94.7%, 85.0%, 43.9% and 99.2%, respectively. DCA and CIC results showed that the nomogram had clinical value in predicting occult PM in GIST patients. CONCLUSION: Imaging and inflammatory indexes are significantly associated with microscopic metastases of GIST. A nomogram including these factors would have an excellent ability to predict occult PM. |
format | Online Article Text |
id | pubmed-7681585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-76815852020-11-24 Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes Xu, Shao-Jun Lin, Guo-Sheng Ling, Hong-Jian Guo, Ren-Jie Chen, Jie Liao, Yi-Ming Lin, Tao Zhou, Yong-Jian Cancer Manag Res Original Research BACKGROUND: Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of GIST. PATIENTS AND METHODS: GIST patients seen between April 2002 and December 2018 were selected from an institutional database. Using multivariate logistic regression analyses, we created a nomogram to predict occult PM of GIST and validated it with an independent cohort from the same center. The concordance index (C-index), decision curve analysis (DCA) and a clinical impact curve (CIC) were used to evaluate its predictive ability. RESULTS: A total of 522 eligible GIST patients were enrolled in this study and divided into training (n=350) and validation cohorts (n=172). Factors associated with occult PM were included in the model: tumor size (odds ratio [OR] 1.194 95% confidence interval [CI], 1.034–1.378; p=0.016), primary location (OR 7.365 95% CI, 2.192–24.746; p=0.001), tumor capsule (OR 4.282 95% CI, 1.209–15.166; p=0.024), Alb (OR 0.813 95% CI, 0.693–0.954; p=0.011) and FIB (OR 2.322 95% CI, 1.410–3.823; p=0.001). The C-index was 0.951 (95% CI, 0.917–0.985) in the training cohort and 0.946 (95% CI, 0.900–0.992) in the validation cohort. In the training cohort, the prediction model had a sensitivity of 82.8%, a specificity of 93.8%, a positive predictive value of 54.7%, and a negative predictive value of 98.4%; the validation cohort values were 94.7%, 85.0%, 43.9% and 99.2%, respectively. DCA and CIC results showed that the nomogram had clinical value in predicting occult PM in GIST patients. CONCLUSION: Imaging and inflammatory indexes are significantly associated with microscopic metastases of GIST. A nomogram including these factors would have an excellent ability to predict occult PM. Dove 2020-11-18 /pmc/articles/PMC7681585/ /pubmed/33239911 http://dx.doi.org/10.2147/CMAR.S275422 Text en © 2020 Xu et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Xu, Shao-Jun Lin, Guo-Sheng Ling, Hong-Jian Guo, Ren-Jie Chen, Jie Liao, Yi-Ming Lin, Tao Zhou, Yong-Jian Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes |
title | Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes |
title_full | Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes |
title_fullStr | Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes |
title_full_unstemmed | Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes |
title_short | Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes |
title_sort | nomogram to predict preoperative occult peritoneal metastasis of gastrointestinal stromal tumors (gist) based on imaging and inflammatory indexes |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681585/ https://www.ncbi.nlm.nih.gov/pubmed/33239911 http://dx.doi.org/10.2147/CMAR.S275422 |
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