Department of Pathology, Beijing Tongren Hospital, Capital Medical University; Beijing Key Laboratory of Head and Neck Molecular Diagnostic Pathology, Beijing, China.
Ann Otol Rhinol Laryngol. 2023 Mar;132(3):259-265. doi: 10.1177/00034894221086990. Epub 2022 Apr 10.
To analyze the factors related to postoperative recurrence in patients with localized laryngeal amyloidosis (LocLA) and to construct a nomogram prediction model (NPM).
We collected the data for LocLA patients diagnosed from March 2000 to May 2019 and clinical characteristics data were extracted. Factors related to recurrence were analyzed using multivariate logistic regression. The NPM was constructed for predicting the recurrence risk of LocLA. The receiver operating characteristic (ROC) curve evaluated the distinguishing ability using the area under curve (AUC). The calibration curve was created to evaluate the consistency of the NPM.
A total of 226 confirmed LocLA cases were included. One hundred seventy-five cases (77.4%) had localized single nodule, and 51 cases had more than one lesions. Sixty-three (27.9%) cases had no multinucleated giant cell (MGC) around amyloid, and 163 (72.1%) cases had MGC around amyloid. Multivariate logistic regression analysis showed that more than one lesions (odds ratio [OR] = 3.206 and 95% confidence interval [CI]: 1.492-6.888; value: .003), subglottic involvement (OR = 2.926 and 95% CI: 1.300-6.585; = .010), and no multinucleated giant cell (MGC) around amyloid (OR = 2.503 and 95% CI: 1.173-5.342; = .018) had a statistically significant effect on postoperative LocLA recurrence ( < .05). The AUC of the ROC curve was 0.753 (95% CI: 0.667-0.832). The bias-corrected curve approached the ideal curve, with an average absolute error of 0.037.
More than one lesions, subglottic involvement, and no MGC around amyloid are risk factors for postoperative recurrence of LocLA. The NPM constructed has good applicability.
分析局限性喉淀粉样变（LocLA）患者术后复发的相关因素，并构建列线图预测模型（NPM）。
收集 2000 年 3 月至 2019 年 5 月期间诊断为 LocLA 的患者临床资料，提取患者临床特征数据。采用多因素 logistic 回归分析LocLA 复发的相关因素。构建预测 LocLA 复发风险的 NPM。采用曲线下面积（AUC）评估 ROC 曲线的鉴别能力。绘制校准曲线以评估 NPM 的一致性。
共纳入 226 例确诊 LocLA 患者。175 例（77.4%）患者为局限性单结节，51 例患者有多个病灶。63 例（27.9%）患者淀粉样物周围无多核巨细胞（MGC），163 例（72.1%）患者淀粉样物周围有 MGC。多因素 logistic 回归分析显示，多个病灶（比值比 [OR] = 3.206，95%置信区间 [CI]：1.492-6.888；P =.003）、声门下累及（OR = 2.926，95%CI：1.300-6.585；P =.010）和淀粉样物周围无 MGC（OR = 2.503，95%CI：1.173-5.342；P =.018）与 LocLA 术后复发有统计学意义（P <.05）。ROC 曲线的 AUC 为 0.753（95%CI：0.667-0.832）。校正偏倚曲线接近理想曲线，平均绝对误差为 0.037。
多个病灶、声门下累及和淀粉样物周围无 MGC 是 LocLA 术后复发的危险因素。构建的 NPM 具有良好的适用性。
