Scholarlink

Objective <p>To establish a prediction model for recurrent laryngeal nerve thermal injury (RLNTI) in radiofrequency ablation (RFA) of papillary thyroid carcinoma (PTC).</p> Materials and methods <p>This prospective study was conducted at a single center from July 2016 to September 2022. Patients diagnosed with PTC and received US-RFA by different interventional therapy groups were enrolled, and classified as derivation cohort and validation cohort based on therapy groups. The logistic regression analysis was used in derivation cohort to develop the model and internal and external validation was performed in derivation and validation cohort respectively.</p> Results <p>The derivation cohort included 1632 patients (mean age, 40 years, ±11 (standard deviation), 1300 female), and the validation cohort comprised 755 patients (mean age, 38 years, ±11 (standard deviation), 584 female). Three variables were independently associated with RLNTI: the minimum distance from tumor to tracheoesophageal groove (TEG-D) ≤ 2.95 mm (odds ratio, 8.179; <i>p</i> &lt; 0.0001), tumor posterior location (odds ratio, 3.849; <i>p</i> = 0.0008) and ablation energy &gt; 0.695 kcal (odds ratio, 4.537; <i>p</i> &lt; 0.0001). The area under the receiver operating characteristic curve (AUC) of the model in the derivation cohort, validation cohort, and total group were 0.877 (95% CI: 0.845, 0.910), 0.901 (95% CI: 0.835, 0.967) and 0.886 (95% CI: 0.85, 0.915) respectively. The calibration plot and Hosmer-Lemeshow test demonstrated a good fit (<i>χ</i>² = 3.49, <i>p</i> = 0.321).</p> Conclusion <p>The prediction model of RLNTI was derived based on TEG-D, tumor posterior location, and ablation energy and exhibited good discrimination and calibration abilities.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis> <i>Recurrent laryngeal nerve thermal injury (RLNTI) is a major complication of radiofrequency ablation (RFA) for papillary thyroid carcinoma (PTC), while related risk factors are unclear.</i></p> <p><Emphasis Type="BoldItalic">Findings</Emphasis> <i>The minimum distance from tumor to tracheoesophageal groove ≤</i><i> 2.95 mm, tumor posterior location, and ablation energy &gt; 0.695 kcal are factors independently associated with RLNTI</i>.</p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis> <i>This study developed a simple prediction model with good discrimination and calibration abilities, which provided interventional radiologists an evidence-based method to predict RLNTI and thereby reduce the incidence of RLNTI in RFA of PTC.</i></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Recurrent laryngeal nerve thermal injury in radiofrequency ablation for papillary thyroid carcinoma and related risk factors: a prospective large cohort study

  • 期刊论文

  • 发表日期：

    2025年3月6日

查看全文
  • Qing Hua,
  • YanYan Song,
  • Wei Zhou,
  • ZhenHua Liu,
  • Lu Zhang,
  • Ying Zhu,
  • LiMei Lai,
  • Yat Hin Yeung,
  • Ning Li,
  • WeiWei Zhan,
  • YiJie Dong,
  • ShuJun Xia,
  • JianQiao Zhou,
  • Xie Xiang,
  • Wang Jinping,
  • Chen Yongchao,
  • He Nian’an,
  • Lin Lianhe,
  • Liang Rongxi,
  • Zhang Zuobing,
  • Wu Huining,
  • Zheng Jian,
  • Hu Shidi,
  • Wang Shunlan,
  • Huang Fugao,
  • Cen Geng,
  • Niu Zongbao,
  • Mei Wenjuan,
  • Wang Song,
  • Fu Xiandong,
  • Wang Zhiyuan,
  • Hu Zhongqian,
  • Chen Baoding,
  • Ye Xinhua,
  • Li Chun,
  • Zhang Chunquan,
  • Sang Liang,
  • Zhang Yingxia,
  • Liu Jingping,
  • Yan Ruibin,
  • Zhang Wenxiao,
  • Lu Yong,
  • Shi Yunzhen,
  • Niu Huiping,
  • Bai Baoyan,
  • Wu Fan,
  • Xu Dong,
  • Chen Yingchao,
  • Xu Xinliang,
  • Hu Qinglin,
  • Lv De,
  • Ma Ting,
  • Wang Jing,
  • Luo Xiaomao,
  • Qi Lingbin,
  • Zhou Ruhai,
  • Shou Jinduo,
  • Wang Han,
  • Liu Xinglan,
  • Zhang Wei,
  • ShuJun Xia,
  • Wei Zhou,
  • Qing Hua,
  • YiJie Dong,
  • JianQiao Zhou,
  • Zhenhua Liu,
  • Lu Zhang,
  • Ning Li

摘要

Objective

To establish a prediction model for recurrent laryngeal nerve thermal injury (RLNTI) in radiofrequency ablation (RFA) of papillary thyroid carcinoma (PTC).

Materials and methods

This prospective study was conducted at a single center from July 2016 to September 2022. Patients diagnosed with PTC and received US-RFA by different interventional therapy groups were enrolled, and classified as derivation cohort and validation cohort based on therapy groups. The logistic regression analysis was used in derivation cohort to develop the model and internal and external validation was performed in derivation and validation cohort respectively.

Results

The derivation cohort included 1632 patients (mean age, 40 years, ±11 (standard deviation), 1300 female), and the validation cohort comprised 755 patients (mean age, 38 years, ±11 (standard deviation), 584 female). Three variables were independently associated with RLNTI: the minimum distance from tumor to tracheoesophageal groove (TEG-D) ≤ 2.95 mm (odds ratio, 8.179; p < 0.0001), tumor posterior location (odds ratio, 3.849; p = 0.0008) and ablation energy > 0.695 kcal (odds ratio, 4.537; p < 0.0001). The area under the receiver operating characteristic curve (AUC) of the model in the derivation cohort, validation cohort, and total group were 0.877 (95% CI: 0.845, 0.910), 0.901 (95% CI: 0.835, 0.967) and 0.886 (95% CI: 0.85, 0.915) respectively. The calibration plot and Hosmer-Lemeshow test demonstrated a good fit (χ² = 3.49, p = 0.321).

Conclusion

The prediction model of RLNTI was derived based on TEG-D, tumor posterior location, and ablation energy and exhibited good discrimination and calibration abilities.

Key Points

Question Recurrent laryngeal nerve thermal injury (RLNTI) is a major complication of radiofrequency ablation (RFA) for papillary thyroid carcinoma (PTC), while related risk factors are unclear.

Findings The minimum distance from tumor to tracheoesophageal groove ≤ 2.95 mm, tumor posterior location, and ablation energy > 0.695 kcal are factors independently associated with RLNTI.

Clinical relevance This study developed a simple prediction model with good discrimination and calibration abilities, which provided interventional radiologists an evidence-based method to predict RLNTI and thereby reduce the incidence of RLNTI in RFA of PTC.