Prosthesis-related complications, after knee reconstruction with endoprosthesis during operation for tumors around the knee, remain an unresolved problem which necessitate a revision or even an amputational surgery. The purpose of the current study was to identify significant risk factors associated with implant failure, and establish a novel model to predict survival of the prosthesis in patients operated with endoprostheses for tumor around knee. We retrospectively reviewed the clinical database of our institution for patients who underwent knee reconstruction due to tumors. A total of 203 patients were included, including 123 males (60.6%) and 80 (39.4%) females, ranging in age from 14 to 77 years (mean: 34.3 ± 17.3 years). The cohort was randomly divided into training (n = 156) and validation (n = 47) samples. Univariable COX analysis was used for initially identifying potential independent predictors of prosthesis survival with the training group (p < 0.150). Multivariate COX proportional hazard model was selected to identify final significant prognostic factors. Using these significant predictors, a graphic nomogram, and an online dynamic nomogram were generated for predicting the prosthetic survival. C-index and calibration curve were used for evaluate the discrimination ability and accuracy of the novel model, both in the training and validation groups. The 1-, 5-, and 10-year prosthetic survival rates were 94.0, 90.8, and 83.0% in training sample, and 96.7, 85.8, and 76.9% in validation sample, respectively. Anatomic sites, length of resection and length of prosthetic stem were independently associated with the prosthetic failure according to multivariate COX regression model (p<0.05). Using these three significant predictors, a graphical nomogram and an online dynamic nomogram model were generated. The C-indexes in training and validation groups were 0.717 and 0.726 respectively, demonstrating favourable discrimination ability of the novel model. And the calibration curve at each time point showed favorable consistency between the predicted and actual survival rates in training and validation samples. The length of resection, anatomical location of tumor, and length of prosthetic stem were significantly associated with prosthetic survival in patients operated for tumor around knee. A user-friendly novel online model model, with favorable discrimination ability and accuracy, was generated to help surgeons predict the survival of the prosthesis.

中文翻译：

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一种预测用于肿瘤切除术后膝关节重建的内置假体存活率的新工具：一项回顾性队列研究

在膝关节周围肿瘤手术期间使用内置假体进行膝关节重建后，与假体相关的并发症仍然是一个未解决的问题，需要进行翻修甚至截肢手术。本研究的目的是确定与种植体失败相关的重要风险因素，并建立一个新模型来预测使用内置假体手术治疗膝关节周围肿瘤的患者的假体存活率。我们回顾性地审查了我们机构中因肿瘤而接受膝关节重建的患者的临床数据库。共纳入 203 名患者，其中男性 123 名（60.6%）和女性 80 名（39.4%），年龄 14 至 77 岁（平均：34.3 ± 17.3 岁）。该队列随机分为训练（n = 156）和验证（n = 47）样本。单变量 COX 分析用于初步确定训练组假体存活的潜在独立预测因子 (p < 0.150)。选择多变量 COX 比例风险模型来确定最终的重要预后因素。使用这些重要的预测因子，生成了图形列线图和在线动态列线图来预测假肢存活率。C-index 和校准曲线用于评估新模型在训练和验证组中的辨别能力和准确性。训练样本中的 1、5 和 10 年假肢存活率分别为 94.0、90.8 和 83.0%，验证样本中分别为 96.7、85.8 和 76.9%。解剖部位，根据多元COX回归模型，切除长度和假体柄长度与假体失败独立相关（p<0.05）。使用这三个重要的预测变量，生成了图形列线图和在线动态列线图模型。训练组和验证组的 C 指数分别为 0.717 和 0.726，表明新模型具有良好的区分能力。并且每个时间点的校准曲线在训练和验证样本中的预测和实际存活率之间显示出良好的一致性。切除的长度、肿瘤的解剖位置和假体柄的长度与膝关节周围肿瘤手术患者的假体存活率显着相关。一个用户友好的新颖在线模型模型，