Department of Urology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China.
Department of Urology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Front Immunol. 2022 Nov 15;13:1070043. doi: 10.3389/fimmu.2022.1070043. eCollection 2022.
Transurethral resection of the bladder tumor with or without adjuvant intravesical instillation (IVI) has been the standard treatment for non-muscle-invasive bladder cancer (NMIBC), whereas a high percentage of patients still experience local tumor recurrence and disease progression after receiving the standard treatment modalities. Unfortunately, current relevant prediction models for determining the recurrent and progression risk of NMIBC patients are far from impeccable.
Clinicopathological characteristics and follow-up information were retrospectively collected from two tertiary medical centers between October 2018 and June 2021. The least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were used to screen potential risk factors affecting recurrence-free survival (RFS) of patients. A nomogram model was established, and the patients were risk-stratified based on the model scores. Both internal and external validation were performed by sampling the model with 1,000 bootstrap resamples.
The study included 299 patient data obtained from the Affiliated Hospital of Xuzhou Medical University and 117 patient data obtained from the First Affiliated Hospital of Guangxi Medical University. Univariate regression analysis suggested that urine red blood cell count and different tumor invasion locations might be potential predictors of RFS. LASSO-Cox regression confirmed that prior recurrence status, times of IVI, and systemic immune-inflammation index (SII) were independent factors for predicting RFS. The area under the curve for predicting 1-, 2-, and 3-year RFS was 0.835, 0.833, and 0.871, respectively. Based on the risk stratification, patients at high risk of recurrence and progression could be accurately identified. A user-friendly risk calculator based on the model is deposited at https://dl0710.shinyapps.io/nmibc_rfs/.
Internal and external validation analyses showed that our model had excellent predictive discriminatory ability and stability. The risk calculator can be used for individualized assessment of survival risk in NMIBC patients and can assist in guiding clinical decision-making.
经尿道膀胱肿瘤切除术（TURBT）联合或不联合膀胱内灌注（IVI）已成为非肌层浸润性膀胱癌（NMIBC）的标准治疗方法，但仍有很大比例的患者在接受标准治疗后出现局部肿瘤复发和疾病进展。不幸的是，目前用于确定 NMIBC 患者复发和进展风险的相关预测模型远非完美。
回顾性收集了 2018 年 10 月至 2021 年 6 月期间两家三级医疗中心的临床病理特征和随访信息。使用最小绝对收缩和选择算子（LASSO）和 Cox 回归分析筛选影响患者无复发生存率（RFS）的潜在危险因素。建立列线图模型，并根据模型评分对患者进行风险分层。通过 1000 次 bootstrap 重采样对模型进行内部和外部验证。
该研究纳入了来自徐州医科大学附属医院的 299 例患者数据和来自广西医科大学第一附属医院的 117 例患者数据。单因素回归分析提示尿红细胞计数和肿瘤不同侵犯部位可能是 RFS 的潜在预测因素。LASSO-Cox 回归证实既往复发状态、IVI 次数和全身免疫炎症指数（SII）是预测 RFS 的独立因素。预测 1、2、3 年 RFS 的曲线下面积分别为 0.835、0.833 和 0.871。根据风险分层，可准确识别出复发和进展风险高的患者。基于模型的易于使用的风险计算器已存放在 https://dl0710.shinyapps.io/nmibc_rfs/。
内部和外部验证分析表明，我们的模型具有出色的预测区分能力和稳定性。风险计算器可用于对 NMIBC 患者的生存风险进行个体化评估，并有助于指导临床决策。
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