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左侧乳腺癌放疗中 DIBH 适应征的变量识别和预测模型的建立:具有时间验证的前瞻性队列研究。

Identification of variables and development of a prediction model for DIBH eligibility in left-sided breast cancer radiotherapy: a prospective cohort study with temporal validation.

机构信息

Department of Radiation Oncology, Rajiv Gandhi Cancer Institute & Research Centre, Sector 5, Rohini, New Delhi, India.

Department of Radiation Oncology, Illawarra Cancer Care Centre, Wollongong, NSW, Australia.

出版信息

Radiat Oncol. 2024 Aug 29;19(1):115. doi: 10.1186/s13014-024-02512-8.

Abstract

OBJECTIVE

To identify variables associated with a patients' ability to reproducibly hold their breath for deep-inspiration breath-hold (DIBH) radiotherapy (RT) and to develop a predictive model for DIBH eligibility.

METHODS

This prospective, single-institution, IRB-approved observational study included women with left-sided breast cancer treated between January 2023 and March 2024. Patients underwent multiple breath-hold sessions over 2-3 consecutive days. DIBH waveform metrics and clinical factors were recorded and analysed. Logistic mixed modelling was used to predict DIBH eligibility, and a temporal validation cohort was used to assess model performance.

RESULTS

In total, 253 patients were included, with 206 in the model development cohort and 47 in the temporal validation cohort. The final logistic mixed model identified increasing average breath-hold duration (OR, 95% CI: 0.308, 0.104-0.910. p = 0.033) and lower amplitude (OR, 95% CI: 0.737, 0.641-0.848. p < 0.001) as significant predictors of DIBH eligibility. Increasing age was associated with higher odds of being ineligible for DIBH (OR, 95% CI: 1.040, 1.001-1.081. p = 0.044). The model demonstrated good discriminative performance in the validation cohort with an AUC of 80.9% (95% CI: 73.0-88.8).

CONCLUSION

The identification of variables associated with DIBH eligibility and development of a predictive model has the potential to serve as a decision-support tool. Further external validation is required before its integration into routine clinical practice.

摘要

目的

确定与患者重复性深吸气屏气(DIBH)放疗能力相关的变量,并开发 DIBH 合格性预测模型。

方法

本前瞻性、单中心、IRB 批准的观察性研究纳入了 2023 年 1 月至 2024 年 3 月期间接受左侧乳腺癌治疗的女性患者。患者在 2-3 天内进行多次屏气训练。记录并分析 DIBH 波形指标和临床因素。采用逻辑混合模型预测 DIBH 合格性,并使用临时验证队列评估模型性能。

结果

共纳入 253 例患者,其中 206 例患者纳入模型开发队列,47 例患者纳入临时验证队列。最终的逻辑混合模型确定,平均屏气持续时间的增加(OR,95%CI:0.308,0.104-0.910,p=0.033)和振幅的降低(OR,95%CI:0.737,0.641-0.848,p<0.001)是 DIBH 合格性的显著预测因素。年龄的增加与 DIBH 不合格的可能性增加相关(OR,95%CI:1.040,1.001-1.081,p=0.044)。该模型在验证队列中具有良好的判别性能,AUC 为 80.9%(95%CI:73.0-88.8)。

结论

确定与 DIBH 合格性相关的变量并开发预测模型有可能成为决策支持工具。在将其纳入常规临床实践之前,需要进一步进行外部验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d8/11363400/4e4c22636670/13014_2024_2512_Fig1_HTML.jpg

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