Suppr超能文献

用于预测软组织肉瘤患者预后的列线图的开发。

Development of a Nomogram to Predict the Outcome for Patients with Soft Tissue Sarcoma.

作者信息

Bray Jonathan P, Munday John S

机构信息

AURA Veterinary, 70 Priestley Road, Surrey Research Park, Guildford GU2 7AJ, UK.

School of Veterinary Science, Massey University, Palmerston North 4410, New Zealand.

出版信息

Vet Sci. 2023 Mar 29;10(4):266. doi: 10.3390/vetsci10040266.

Abstract

Soft tissue sarcomas (STSs) are common cutaneous or subcutaneous neoplasms in dogs. Most STSs are initially treated by surgical excision, and local recurrence may develop in almost 20% of patients. Currently, it is difficult to predict which STS will recur after excision, but this ability would greatly assist patient management. In recent years, the nomogram has emerged as a tool to allow oncologists to predict an outcome from a combination of risk factors. The aim of this study was to develop a nomogram for canine STSs and determine if the nomogram could predict patient outcomes better than individual tumour characteristics. The current study provides the first evidence in veterinary oncology to support a role for the nomogram to assist with predicting the outcome for patients after surgery for STSs. The nomogram developed in this study accurately predicted tumour-free survival in 25 patients but failed to predict recurrence in 1 patient. Overall, the sensitivity, specificity, positive predictive, and negative predictive values for the nomogram were 96%, 45%, 45%, and 96%, respectively (area under the curve: AUC = 0.84). This study suggests a nomogram could play an important role in helping to identify patients who could benefit from revision surgery or adjuvant therapy for an STS.

摘要

软组织肉瘤(STSs)是犬类常见的皮肤或皮下肿瘤。大多数STSs最初通过手术切除进行治疗,近20%的患者可能会出现局部复发。目前,很难预测哪些STSs在切除后会复发,但这种能力将极大地有助于患者管理。近年来,列线图已成为一种工具,使肿瘤学家能够根据多种风险因素预测结果。本研究的目的是为犬类STSs开发一种列线图,并确定该列线图是否比单个肿瘤特征能更好地预测患者预后。本研究提供了兽医肿瘤学中的首个证据,支持列线图在辅助预测STSs手术后患者预后方面的作用。本研究中开发的列线图准确预测了25例患者的无瘤生存期,但未能预测1例患者的复发情况。总体而言,该列线图的敏感性、特异性、阳性预测值和阴性预测值分别为96%、45%、45%和96%(曲线下面积:AUC = 0.84)。本研究表明,列线图在帮助识别可能从STSs翻修手术或辅助治疗中获益的患者方面可能发挥重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88c2/10146366/5d843ab8db80/vetsci-10-00266-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验