背景:Wilms肿瘤(WT)的生存受到临床和生物学预后因素演变的影响。生存率的显着差异表明需要进一步努力减少这些差异。本研究旨在评估临床病理数据对Wilm诊断后患者生存的影响。
方法:该研究利用SEERStat数据库来识别Wilms肿瘤患者,应用SEERStat软件8.3.9.2版进行数据提取。选择标准涉及基于国际肿瘤疾病分类(ICDO-3)的特定代码,不包括SEER阶段未知的病例,不完整的生存数据,未知大小,或淋巴结状态。统计分析,包括Kaplan-Meier估计和Cox回归模型,使用R软件3.5版进行。标准化死亡率(SMR)用SEER*Stat软件计算,我们进行了相对生存分析和条件生存分析,以评估长期生存结局.
结果:在诊断为Wilms肿瘤的2273例患者中,(1219名患者,53.6%为女性,平均年龄为3-8岁(50.2%)。诊断五年后的总平均生存率为93.6%(2.6-94.7),诊断十年后,总平均生存率为92.5%(91.3-93.8)。肾癌被确定为主要死亡原因(77.3%),其次是非肾癌(11%)和非癌症原因(11%)。此外,稳健相对生存率为98.10%,92.80%,91.3%,五,十年,分别,被观察到,相应的5年条件生存率表明诊断后每增加1年生存的可能性增加。单变量Cox回归确定了重要的预后因素:3岁以下患者的CSS较好(cHR0.48),而15岁以上患者的CSS较差(cHR2.72)。远处传播(cHR10.24),区域传播(cHR3.09),和未知阶段(cHR4.97)。在多变量模型中,年龄不是一个重要的预测因素,但远距离传播(AHR9.22),区域传播(AHR2.84),与局部肿瘤相比,未知阶段(aHR4.98)与更差的CSS相关。
结论:这项深入研究WT生存动态的研究揭示了受临床病理变量影响的多方面景观。这种全面的理解强调了持续研究和个性化干预措施的必要性,以提高生存率并解决不同年龄的微妙挑战。舞台,和WT患者的肿瘤扩散。
BACKGROUND: Wilms tumor (WT) survival has been affected by the evolution in clinical and biological prognostic factors. Significant differences in survival rates indicate the need for further efforts to reduce these disparities. This study aims to evaluate the clinicopathological data impact on survival among patients after Wilm\'s diagnosis.
METHODS: The study utilized the SEERStat Database to identify Wilms tumor patients, applying SEERStat software version 8.3.9.2 for data extraction. Selection criteria involved specific codes based on the International Classification of Diseases for Oncology (ICDO-3), excluding cases with unknown SEER stage, incomplete survival data, unknown size, or lymph node status. Statistical analyses, including Kaplan-Meier estimates and Cox regression models, were conducted using R software version 3.5. Standardized mortality ratios (SMR) were computed with SEER*Stat software, and relative and conditional survival analyses were performed to evaluate long-term survival outcomes.
RESULTS: Of 2273 patients diagnosed with Wilms tumor, (1219 patients, 53.6% were females with an average age group of 3-8 years (50.2%). The overall mean survival after five years of diagnosis was 93.6% (2.6-94.7), and the overall mean survival rate was 92.5% (91.3-93.8) after ten years of diagnosis. Renal cancers were identified as the leading cause of death (77.3%), followed by nonrenal cancers (11%) and noncancer causes (11%). Additionally, robust relative survival rates of 98.10%, 92.80%, and 91.3% at one, five, and ten years, respectively, were observed, with corresponding five-year conditional survival rates indicating an increasing likelihood of survival with each additional year post-diagnosis. Univariate Cox regression identified significant prognostic factors: superior CSS for patients below 3 years (cHR 0.48) and poorer CSS for those older than 15 years (cHR 2.72), distant spread (cHR 10.24), regional spread (cHR 3.09), and unknown stage (cHR 4.97). In the multivariate model, age was not a significant predictor, but distant spread (aHR 9.22), regional spread (aHR 2.84), and unknown stage (aHR 4.98) were associated with worse CSS compared to localized tumors.
CONCLUSIONS: This study delving into WT survival dynamics reveals a multifaceted landscape influenced by clinicopathological variables. This comprehensive understanding emphasizes the imperative for ongoing research and personalized interventions to refine survival rates and address nuanced challenges across age, stage, and tumor spread in WT patients.