Prediction of Survival in Patients with Advanced Cancer: A Narrative Review and Future Research Priorities.

Yusuke Hiratsuka, Jun Hamano, Masanori Mori, Isseki Maeda, Tatsuya Morita, Sang-Yeon Suh
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Abstract

This paper aimed to summarize the current situation of prognostication for patients with an expected survival of weeks or months, and to clarify future research priorities. Prognostic information is essential for patients, their families, and medical professionals to make end-of-life decisions. The clinician's prediction of survival is often used, but this may be inaccurate and optimistic. Many prognostic tools, such as the Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and Prognosis in Palliative Care Study, have been developed and validated to reduce the inaccuracy of the clinician's prediction of survival. To date, there is no consensus on the most appropriate method of comparing tools that use different formats to predict survival. Therefore, the feasibility of using prognostic scales in clinical practice and the information wanted by the end users can determine the appropriate prognostic tool to use. We propose four major themes for further prognostication research: (1) functional prognosis, (2) outcomes of prognostic communication, (3) artificial intelligence, and (4) education for clinicians.

晚期癌症患者生存率的预测:叙述性回顾和未来的研究重点。
本文旨在总结预期生存期为数周或数月的患者的预后现状,并明确未来的研究重点。预后信息对于患者、其家人和医疗专业人员做出临终决定至关重要。临床医生对生存率的预测经常被使用,但这可能是不准确和乐观的。许多预后工具,如姑息性能量表、姑息预后指数、姑息预后评分和姑息治疗研究中的预后,已经被开发和验证,以减少临床医生对生存率预测的不准确度。到目前为止,对使用不同格式预测生存率的工具进行比较的最合适方法还没有达成共识。因此,在临床实践中使用预后量表的可行性和最终用户想要的信息可以确定要使用的合适的预后工具。我们提出了进一步预后研究的四个主要主题:(1)功能预后,(2)预后沟通的结果,(3)人工智能,以及(4)临床医生的教育。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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