Bao-Tian Huang, Pei-Xian Lin, Ying Wang, Li-Mei Luo
{"title":"基于临床、剂量学和炎症相关参数的肺癌立体定向放射治疗患者局部控制预测nomogram的开发和验证","authors":"Bao-Tian Huang, Pei-Xian Lin, Ying Wang, Li-Mei Luo","doi":"10.1186/s12890-025-03800-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The incidence of local recurrence remains noteworthy among lung cancer patients treated with stereotactic body radiation therapy (SBRT). The aim of the study is to identify the risk factors and develop a nomogram for local control (LC) prediction.</p><p><strong>Methods: </strong>One hundred fifty-eight primary or metastatic lung cancer patients treated with SBRT were retrospectively analyzed. The clinical, dosimetric and inflammation-related parameters were collected. The Cox regression analysis was performed to determine the independent prognostic factors. A nomogram based on the prognostic factors was established and internally validated using a bootstrap resampling method.</p><p><strong>Results: </strong>The median follow-up time for the whole cohort was 40 months (95% CI: 34-46) and 35.4% of the patients (56/158) experienced local recurrence. The 1-year, 3-year and 5-year LC rates were 97.4%, 85.8% and 76.1%. Multivariate Cox regression analysis revealed that six independent factors were associated with LC, including age, clinical stage, planning target volume (PTV) volume, BED of the prescription dose (BEDPD), lymphocyte count, and neutrocyte count. The bootstrap-corrected C-index of the developed nomogram was 0.745 (95% CI, 0.663-0.793). The time-dependent AUC indicated the nomogram exhibited strong discriminatory capability. Calibration curves demonstrated a good concordance between the predicted and the observed probabilities. The results of decision curve analysis highlighted the clinical utility of the model. Additionally, the high- and low-risk patients were stratified based on the cut-off point from the nomogram (P < 0.0001).</p><p><strong>Conclusions: </strong>A nomogram based on the clinical, dosimetric, and inflammation-related predictors is developed for LC prediction in lung cancer patients treated with SBRT. External validation is required for further confirm its validity.</p>","PeriodicalId":9148,"journal":{"name":"BMC Pulmonary Medicine","volume":"25 1","pages":"332"},"PeriodicalIF":2.8000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12243256/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and validation of a nomogram for local control prediction in lung cancer patients treated with stereotactic body radiation therapy based on clinical, dosimetric, and inflammation-related parameters.\",\"authors\":\"Bao-Tian Huang, Pei-Xian Lin, Ying Wang, Li-Mei Luo\",\"doi\":\"10.1186/s12890-025-03800-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The incidence of local recurrence remains noteworthy among lung cancer patients treated with stereotactic body radiation therapy (SBRT). The aim of the study is to identify the risk factors and develop a nomogram for local control (LC) prediction.</p><p><strong>Methods: </strong>One hundred fifty-eight primary or metastatic lung cancer patients treated with SBRT were retrospectively analyzed. The clinical, dosimetric and inflammation-related parameters were collected. The Cox regression analysis was performed to determine the independent prognostic factors. A nomogram based on the prognostic factors was established and internally validated using a bootstrap resampling method.</p><p><strong>Results: </strong>The median follow-up time for the whole cohort was 40 months (95% CI: 34-46) and 35.4% of the patients (56/158) experienced local recurrence. The 1-year, 3-year and 5-year LC rates were 97.4%, 85.8% and 76.1%. Multivariate Cox regression analysis revealed that six independent factors were associated with LC, including age, clinical stage, planning target volume (PTV) volume, BED of the prescription dose (BEDPD), lymphocyte count, and neutrocyte count. The bootstrap-corrected C-index of the developed nomogram was 0.745 (95% CI, 0.663-0.793). The time-dependent AUC indicated the nomogram exhibited strong discriminatory capability. Calibration curves demonstrated a good concordance between the predicted and the observed probabilities. The results of decision curve analysis highlighted the clinical utility of the model. Additionally, the high- and low-risk patients were stratified based on the cut-off point from the nomogram (P < 0.0001).</p><p><strong>Conclusions: </strong>A nomogram based on the clinical, dosimetric, and inflammation-related predictors is developed for LC prediction in lung cancer patients treated with SBRT. External validation is required for further confirm its validity.</p>\",\"PeriodicalId\":9148,\"journal\":{\"name\":\"BMC Pulmonary Medicine\",\"volume\":\"25 1\",\"pages\":\"332\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12243256/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Pulmonary Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12890-025-03800-z\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RESPIRATORY SYSTEM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Pulmonary Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12890-025-03800-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
Development and validation of a nomogram for local control prediction in lung cancer patients treated with stereotactic body radiation therapy based on clinical, dosimetric, and inflammation-related parameters.
Background: The incidence of local recurrence remains noteworthy among lung cancer patients treated with stereotactic body radiation therapy (SBRT). The aim of the study is to identify the risk factors and develop a nomogram for local control (LC) prediction.
Methods: One hundred fifty-eight primary or metastatic lung cancer patients treated with SBRT were retrospectively analyzed. The clinical, dosimetric and inflammation-related parameters were collected. The Cox regression analysis was performed to determine the independent prognostic factors. A nomogram based on the prognostic factors was established and internally validated using a bootstrap resampling method.
Results: The median follow-up time for the whole cohort was 40 months (95% CI: 34-46) and 35.4% of the patients (56/158) experienced local recurrence. The 1-year, 3-year and 5-year LC rates were 97.4%, 85.8% and 76.1%. Multivariate Cox regression analysis revealed that six independent factors were associated with LC, including age, clinical stage, planning target volume (PTV) volume, BED of the prescription dose (BEDPD), lymphocyte count, and neutrocyte count. The bootstrap-corrected C-index of the developed nomogram was 0.745 (95% CI, 0.663-0.793). The time-dependent AUC indicated the nomogram exhibited strong discriminatory capability. Calibration curves demonstrated a good concordance between the predicted and the observed probabilities. The results of decision curve analysis highlighted the clinical utility of the model. Additionally, the high- and low-risk patients were stratified based on the cut-off point from the nomogram (P < 0.0001).
Conclusions: A nomogram based on the clinical, dosimetric, and inflammation-related predictors is developed for LC prediction in lung cancer patients treated with SBRT. External validation is required for further confirm its validity.
期刊介绍:
BMC Pulmonary Medicine is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of pulmonary and associated disorders, as well as related molecular genetics, pathophysiology, and epidemiology.