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

IF 2.8 3区 医学 Q2 RESPIRATORY SYSTEM
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}
引用次数: 0

摘要

背景:在接受立体定向全身放射治疗(SBRT)的肺癌患者中,局部复发率仍然值得注意。该研究的目的是确定风险因素,并制定一个nomogram用于局部控制(LC)预测。方法:对158例接受SBRT治疗的原发性或转移性肺癌患者进行回顾性分析。收集临床、剂量学和炎症相关参数。采用Cox回归分析确定独立预后因素。建立了基于预后因素的nomogram,并使用bootstrap重采样方法进行了内部验证。结果:整个队列的中位随访时间为40个月(95% CI: 34-46), 35.4%的患者(56/158)出现局部复发。1年、3年和5年LC率分别为97.4%、85.8%和76.1%。多因素Cox回归分析显示,年龄、临床分期、计划靶体积(PTV)体积、处方剂量BED (BEDPD)、淋巴细胞计数、中性细胞计数等6个独立因素与LC相关。开发的nomogram经bootstrap校正的C-index为0.745 (95% CI, 0.663-0.793)。随时间变化的AUC表明nomogram具有较强的区分能力。校正曲线显示预测概率与观测概率之间有很好的一致性。决策曲线分析结果突出了该模型的临床应用价值。此外,根据图中的截断点对高危和低危患者进行分层(P结论:基于临床、剂量学和炎症相关预测因素的图用于SBRT治疗肺癌患者的LC预测。为了进一步确认其有效性,需要外部验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
BMC Pulmonary Medicine
BMC Pulmonary Medicine RESPIRATORY SYSTEM-
CiteScore
4.40
自引率
3.20%
发文量
423
审稿时长
6-12 weeks
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信