生存预测评分:一种预测姑息性放疗患者预后的简单但与年龄相关的方法。

ISRN oncology Pub Date : 2014-03-19 eCollection Date: 2014-01-01 DOI:10.1155/2014/912865
Kent Angelo, Astrid Dalhaug, Adam Pawinski, Ellinor Haukland, Carsten Nieder
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引用次数: 18

摘要

目的。在挪威接受姑息放疗(PRT)的癌症患者中验证加拿大三层预后模型(生存预测评分,SPS),并评估该模型的年龄依赖性表现。患者和方法。我们分析了2007年6月20日至2009年12月31日期间在一个专门的PRT设施进行的所有579个PRT课程。SPS按照最初的描述进行分配,即考虑三个变量:原发癌症类型、转移部位和表现状态。结果。预后不良的患者(非乳腺癌,骨以外的转移,Karnofsky性能状态(KPS)≤60)的中位生存期为13周。预后中等(其中两个参数)的患者中位生存期为29周,预后良好的患者中位生存期为114周,P < 0.001。虽然该模型在60岁以上患者中表现良好,但在年轻患者中则不太令人满意(良好和中等预后组之间无显著差异)。结论。SPS应主要用于预测老年肿瘤患者的生存。然而,即使在该组中,准确性也受到限制,因为预后良好组中有短期生存的患者,而预后较差组中有长期生存的患者。因此,应该开发改进的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Survival prediction score: a simple but age-dependent method predicting prognosis in patients undergoing palliative radiotherapy.

Survival prediction score: a simple but age-dependent method predicting prognosis in patients undergoing palliative radiotherapy.

Survival prediction score: a simple but age-dependent method predicting prognosis in patients undergoing palliative radiotherapy.

Survival prediction score: a simple but age-dependent method predicting prognosis in patients undergoing palliative radiotherapy.

Purpose. Validation of a Canadian three-tiered prognostic model (survival prediction score, SPS) in Norwegian cancer patients referred for palliative radiotherapy (PRT), and evaluation of age-dependent performance of the model. Patients and Methods. We analyzed all 579 PRT courses administered at a dedicated PRT facility between 20.06.07 and 31.12.2009. SPS was assigned as originally described, That is, by taking into consideration three variables: primary cancer type, site of metastases, and performance status. Results. Patients with poor prognosis (non-breast cancer, metastases other than bone, and Karnofsky performance status (KPS) ≤ 60) had median survival of 13 weeks. Those with intermediate prognosis (two of these parameters) survived for a median of 29 weeks, and patients with good prognosis for a median of 114 weeks, P < 0.001. While this model performed well in patients who were 60 years or older, it was less satisfactory in younger patients (no significant difference between the good and intermediate prognosis groups). Conclusion. SPS should mainly be used to predict survival of elderly cancer patients. However, even in this group accuracy is limited because the good prognosis group contained patients with short survival, while the poor prognosis group contained long-term survivors. Thus, improved models should be developed.

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