Zan Hou , Xiaoping Lin , Baiqiang Dong , Zaishan Lin , Yuan Zhang , Xu Liu , Chenfei Wu , Qingqing Xu , Ying Wang , Keying Chen , Qiwen Li , Ming Chen
{"title":"高估非转移性非小细胞肺癌对侧肺门淋巴结转移及其预测模型HAM","authors":"Zan Hou , Xiaoping Lin , Baiqiang Dong , Zaishan Lin , Yuan Zhang , Xu Liu , Chenfei Wu , Qingqing Xu , Ying Wang , Keying Chen , Qiwen Li , Ming Chen","doi":"10.1016/j.radonc.2024.110575","DOIUrl":null,"url":null,"abstract":"<div><h3>Background and purpose</h3><div>Metastasis of non-metastatic non-small cell lung cancer (NMNSCLC) to contralateral hilar lymph nodes (CHLN) eliminates the opportunity for radical therapy. This study aims to analyze whether CHLN metastasis in NMNSCLC is commonly overestimated in clinical practice and to establish a predictive model for enhanced precision.</div></div><div><h3>Methods and materials</h3><div>We conducted a retrospective analysis of 834 pathologically confirmed NMNSCLC patients. Monitoring of treatment responses and regular ≥ 1 year CT follow-up was used to determine the nature of CHLN. Lasso regression was used to select predictive factors, and a multivariate binary logistic regression model (HAM) was constructed. Internal validation was performed using ten-fold cross-validation.</div></div><div><h3>Results</h3><div>The CHLN metastasis rate was 4.4% among the NMNSCLC patients. The positive predictive value (PPV) and sensitivity for PET-CT diagnosis were 36.8% and 67.5%, while for CT they are 44.8% and 70.2%, respectively. The five optimal predictive factors (emphysema or bullae, central-type lung cancer, short diameter of CHLN, calcification and SUVmax) were used to develop the HAM model. The Area under curve (AUC) values for PET-CT, CT, and HAM model were 0.81, 0.83, and 0.96, respectively. The F1 scores for PET-CT and CT were 0.48 and 0.55, respectively, while the maximum F1 score of our model was 0.73, with corresponding PPV and sensitivity of 66.7%, and 81.1%, respectively.</div></div><div><h3>Conclusions</h3><div>CHLN metastasis is rare in NMNSCLC patients. PET-CT diagnosis significantly overestimates CHLN metastasis and the HAM model improves clinical decision-making in this study. Prospective studies are needed to confirm these conclusions.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110575"},"PeriodicalIF":4.9000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Overestimation of contralateral hilar lymph node metastasis in non-metastatic non-small cell lung cancer and its predictive model: HAM\",\"authors\":\"Zan Hou , Xiaoping Lin , Baiqiang Dong , Zaishan Lin , Yuan Zhang , Xu Liu , Chenfei Wu , Qingqing Xu , Ying Wang , Keying Chen , Qiwen Li , Ming Chen\",\"doi\":\"10.1016/j.radonc.2024.110575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background and purpose</h3><div>Metastasis of non-metastatic non-small cell lung cancer (NMNSCLC) to contralateral hilar lymph nodes (CHLN) eliminates the opportunity for radical therapy. This study aims to analyze whether CHLN metastasis in NMNSCLC is commonly overestimated in clinical practice and to establish a predictive model for enhanced precision.</div></div><div><h3>Methods and materials</h3><div>We conducted a retrospective analysis of 834 pathologically confirmed NMNSCLC patients. Monitoring of treatment responses and regular ≥ 1 year CT follow-up was used to determine the nature of CHLN. Lasso regression was used to select predictive factors, and a multivariate binary logistic regression model (HAM) was constructed. Internal validation was performed using ten-fold cross-validation.</div></div><div><h3>Results</h3><div>The CHLN metastasis rate was 4.4% among the NMNSCLC patients. The positive predictive value (PPV) and sensitivity for PET-CT diagnosis were 36.8% and 67.5%, while for CT they are 44.8% and 70.2%, respectively. The five optimal predictive factors (emphysema or bullae, central-type lung cancer, short diameter of CHLN, calcification and SUVmax) were used to develop the HAM model. The Area under curve (AUC) values for PET-CT, CT, and HAM model were 0.81, 0.83, and 0.96, respectively. The F1 scores for PET-CT and CT were 0.48 and 0.55, respectively, while the maximum F1 score of our model was 0.73, with corresponding PPV and sensitivity of 66.7%, and 81.1%, respectively.</div></div><div><h3>Conclusions</h3><div>CHLN metastasis is rare in NMNSCLC patients. PET-CT diagnosis significantly overestimates CHLN metastasis and the HAM model improves clinical decision-making in this study. Prospective studies are needed to confirm these conclusions.</div></div>\",\"PeriodicalId\":21041,\"journal\":{\"name\":\"Radiotherapy and Oncology\",\"volume\":\"201 \",\"pages\":\"Article 110575\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiotherapy and Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167814024035539\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiotherapy and Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167814024035539","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
Overestimation of contralateral hilar lymph node metastasis in non-metastatic non-small cell lung cancer and its predictive model: HAM
Background and purpose
Metastasis of non-metastatic non-small cell lung cancer (NMNSCLC) to contralateral hilar lymph nodes (CHLN) eliminates the opportunity for radical therapy. This study aims to analyze whether CHLN metastasis in NMNSCLC is commonly overestimated in clinical practice and to establish a predictive model for enhanced precision.
Methods and materials
We conducted a retrospective analysis of 834 pathologically confirmed NMNSCLC patients. Monitoring of treatment responses and regular ≥ 1 year CT follow-up was used to determine the nature of CHLN. Lasso regression was used to select predictive factors, and a multivariate binary logistic regression model (HAM) was constructed. Internal validation was performed using ten-fold cross-validation.
Results
The CHLN metastasis rate was 4.4% among the NMNSCLC patients. The positive predictive value (PPV) and sensitivity for PET-CT diagnosis were 36.8% and 67.5%, while for CT they are 44.8% and 70.2%, respectively. The five optimal predictive factors (emphysema or bullae, central-type lung cancer, short diameter of CHLN, calcification and SUVmax) were used to develop the HAM model. The Area under curve (AUC) values for PET-CT, CT, and HAM model were 0.81, 0.83, and 0.96, respectively. The F1 scores for PET-CT and CT were 0.48 and 0.55, respectively, while the maximum F1 score of our model was 0.73, with corresponding PPV and sensitivity of 66.7%, and 81.1%, respectively.
Conclusions
CHLN metastasis is rare in NMNSCLC patients. PET-CT diagnosis significantly overestimates CHLN metastasis and the HAM model improves clinical decision-making in this study. Prospective studies are needed to confirm these conclusions.
期刊介绍:
Radiotherapy and Oncology publishes papers describing original research as well as review articles. It covers areas of interest relating to radiation oncology. This includes: clinical radiotherapy, combined modality treatment, translational studies, epidemiological outcomes, imaging, dosimetry, and radiation therapy planning, experimental work in radiobiology, chemobiology, hyperthermia and tumour biology, as well as data science in radiation oncology and physics aspects relevant to oncology.Papers on more general aspects of interest to the radiation oncologist including chemotherapy, surgery and immunology are also published.