Department of Oral and Maxillofacial Surgery, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, 56 West Lingyuan Road, Guangzhou, 510055, Guangdong, China.
Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Khon Kaen University, Khon Kaen, Thailand.
BMC Cancer. 2021 Apr 15;21(1):408. doi: 10.1186/s12885-021-08135-6.
Nomograms are currently used in predicting individualized outcomes in clinical oncology of several cancers. However, nomograms for evaluating occult nodal metastasis of patients with squamous cell carcinoma of lateral tongue (SCCLT) have not been widely investigated for their functionality. This retrospective cohort study was designed to address this question.
This study was divided into primary and validation cohorts. The primary cohort comprised 120 patients diagnosed between 2012 and 2017, whereas the validation cohort included 41 patients diagnosed thereafter. The diagnostic value of multiparametric MRI, including radiologic tumor thickness threshold (rTTT) in three-dimensions, paralingual distance, and sublingual distance were investigated. A nomogram was developed based on stepwise logistic regression of potential predictors associated with nodal metastasis in the primary cohort and then tested for predictive accuracy in the validation cohort using area under the curve (AUC) and goodness-of-fit tests.
Multivariate analysis, tumor size (odd ratio [OR] 15.175, 95% confidence interval [CI] 1.436-160.329, P = 0.024), rTTT (OR 11.528, 95% CI 2.483-53.530, P = 0.002), paralingual distance (OR 11.976, 95% CI 1.981-72.413, P = 0.005), and tumor location (OR 6.311, 95% CI 1.514-26.304, P = 0.011) were included in the nomogram to predict the likelihood of having cervical metastasis. A nomogram cutoff value of 210 points (sensitivity 93.8%, specificity 87.5%) was significantly different to classify the patients metastasis risk group (P < 0.001). Nomogram showed predictive accuracy with AUC 0.881 (95% CI 0.779-0.983, P < 0.001) and good calibration after the validation.
A preoperative nomogram incorporating multiparametric MRI demonstrated good prediction and performed adequately in our study. Three-dimensional assessment of occult metastasis risk value obtained from this nomogram can assist in preoperative decision making for individual patients with early-stage SCCLT. The probability of nodal metastasis tended to be greater than 20% in patients with high metastasis risk or nomogram total score > 210 points.
目前,列线图被广泛应用于预测多种癌症的临床肿瘤学的个体化预后。然而,用于评估侧舌鳞状细胞癌(SCCLT)患者隐匿性淋巴结转移的列线图在功能方面尚未得到广泛研究。本回顾性队列研究旨在解决这一问题。
本研究分为主队列和验证队列。主队列纳入了 2012 年至 2017 年间诊断的 120 例患者,验证队列纳入了此后诊断的 41 例患者。研究评估了多参数 MRI 的诊断价值,包括三维放射学肿瘤厚度阈值(rTTT)、旁舌距离和舌下距离。在主队列中,基于与淋巴结转移相关的潜在预测因素进行逐步逻辑回归,建立了一个列线图,然后使用曲线下面积(AUC)和拟合优度检验在验证队列中对其预测准确性进行测试。
多因素分析显示,肿瘤大小(比值比 [OR] 15.175,95%置信区间 [CI] 1.436-160.329,P=0.024)、rTTT(OR 11.528,95%CI 2.483-53.530,P=0.002)、旁舌距离(OR 11.976,95%CI 1.981-72.413,P=0.005)和肿瘤位置(OR 6.311,95%CI 1.514-26.304,P=0.011)被纳入列线图,以预测发生颈部转移的可能性。列线图截断值为 210 分(灵敏度 93.8%,特异性 87.5%),可显著区分患者的转移风险组(P<0.001)。验证后,列线图的 AUC 为 0.881(95%CI 0.779-0.983,P<0.001),预测准确性高,校准度良好。
本研究中,纳入多参数 MRI 的术前列线图具有良好的预测性能。该列线图获得的三维隐匿性转移风险值可协助早期 SCCLT 患者的术前决策。高转移风险或列线图总分>210 分的患者,淋巴结转移的概率倾向于大于 20%。