A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer
BackgroundPreoperative assessment of the presence of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) remains difficult. We aimed to develop a practical prediction model based on preoperative pathological data and inflammatory or nutrition-related indicators.MethodsThis study...
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| Format: | Article |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1201499/full |
| _version_ | 1797730108464693248 |
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| author | Hongyu Wu Wen Liu Minyue Yin Lu Liu Shuting Qu Wei Xu Chunfang Xu |
| author_facet | Hongyu Wu Wen Liu Minyue Yin Lu Liu Shuting Qu Wei Xu Chunfang Xu |
| author_sort | Hongyu Wu |
| collection | DOAJ |
| description | BackgroundPreoperative assessment of the presence of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) remains difficult. We aimed to develop a practical prediction model based on preoperative pathological data and inflammatory or nutrition-related indicators.MethodsThis study retrospectively analyzed the clinicopathological characteristics of 1,061 patients with EGC who were randomly divided into the training set and validation set at a ratio of 7:3. In the training set, we introduced the least absolute selection and shrinkage operator (LASSO) algorithm and multivariate logistic regression to identify independent risk factors and construct the nomogram. Both internal validation and external validation were performed by the area under the receiver operating characteristic curve (AUC), C-index, calibration curve, and decision curve analysis (DCA).ResultsLNM occurred in 162 of 1,061 patients, and the rate of LNM was 15.27%. In the training set, four variables proved to be independent risk factors (p < 0.05) and were incorporated into the final model, including depth of invasion, tumor size, degree of differentiation, and platelet-to-lymphocyte ratio (PLR). The AUC values were 0.775 and 0.792 for the training and validation groups, respectively. Both calibration curves showed great consistency in the predictive and actual values. The Hosmer–Lemeshow (H-L) test was carried out in two cohorts, showing excellent performance with p-value >0.05 (0.684422, 0.7403046). Decision curve analysis demonstrated a good clinical benefit in the respective set.ConclusionWe established a preoperative nomogram including depth of invasion, tumor size, degree of differentiation, and PLR to predict LNM in EGC patients and achieved a good performance. |
| first_indexed | 2024-03-12T11:39:30Z |
| format | Article |
| id | doaj.art-4cc85121e2474ae0a65d8f0445f6273a |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-12T11:39:30Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-4cc85121e2474ae0a65d8f0445f6273a2023-08-31T20:05:54ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-08-011310.3389/fonc.2023.12014991201499A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancerHongyu WuWen LiuMinyue YinLu LiuShuting QuWei XuChunfang XuBackgroundPreoperative assessment of the presence of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) remains difficult. We aimed to develop a practical prediction model based on preoperative pathological data and inflammatory or nutrition-related indicators.MethodsThis study retrospectively analyzed the clinicopathological characteristics of 1,061 patients with EGC who were randomly divided into the training set and validation set at a ratio of 7:3. In the training set, we introduced the least absolute selection and shrinkage operator (LASSO) algorithm and multivariate logistic regression to identify independent risk factors and construct the nomogram. Both internal validation and external validation were performed by the area under the receiver operating characteristic curve (AUC), C-index, calibration curve, and decision curve analysis (DCA).ResultsLNM occurred in 162 of 1,061 patients, and the rate of LNM was 15.27%. In the training set, four variables proved to be independent risk factors (p < 0.05) and were incorporated into the final model, including depth of invasion, tumor size, degree of differentiation, and platelet-to-lymphocyte ratio (PLR). The AUC values were 0.775 and 0.792 for the training and validation groups, respectively. Both calibration curves showed great consistency in the predictive and actual values. The Hosmer–Lemeshow (H-L) test was carried out in two cohorts, showing excellent performance with p-value >0.05 (0.684422, 0.7403046). Decision curve analysis demonstrated a good clinical benefit in the respective set.ConclusionWe established a preoperative nomogram including depth of invasion, tumor size, degree of differentiation, and PLR to predict LNM in EGC patients and achieved a good performance.https://www.frontiersin.org/articles/10.3389/fonc.2023.1201499/fullearly gastric cancerlymph node metastasisplatelet-to-lymphocyte ratioprediction modelnomogram |
| spellingShingle | Hongyu Wu Wen Liu Minyue Yin Lu Liu Shuting Qu Wei Xu Chunfang Xu A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer Frontiers in Oncology early gastric cancer lymph node metastasis platelet-to-lymphocyte ratio prediction model nomogram |
| title | A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer |
| title_full | A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer |
| title_fullStr | A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer |
| title_full_unstemmed | A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer |
| title_short | A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer |
| title_sort | nomogram based on platelet to lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer |
| topic | early gastric cancer lymph node metastasis platelet-to-lymphocyte ratio prediction model nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1201499/full |
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