Prognostic risk stratification using C-reactive protein, albumin, and associated inflammatory biomarkers in patients with advanced cancer in palliative care

IF 2.5 4区 医学 Q3 ONCOLOGY Current Problems in Cancer Pub Date : 2024-06-28 DOI:10.1016/j.currproblcancer.2024.101115
Geisiane Alves da Silva , Livia Costa de Oliveira , Emanuelly Varea Maria Wiegert , Larissa Calixto-Lima , Gabriella da Costa Cunha , Wilza Arantes Ferreira Peres
{"title":"Prognostic risk stratification using C-reactive protein, albumin, and associated inflammatory biomarkers in patients with advanced cancer in palliative care","authors":"Geisiane Alves da Silva ,&nbsp;Livia Costa de Oliveira ,&nbsp;Emanuelly Varea Maria Wiegert ,&nbsp;Larissa Calixto-Lima ,&nbsp;Gabriella da Costa Cunha ,&nbsp;Wilza Arantes Ferreira Peres","doi":"10.1016/j.currproblcancer.2024.101115","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>To evaluate the prognostic value of C-reactive protein (CRP), albumin, CRP/albumin ratio (CAR), and modified Glasgow Prognostic Score (mGPS) at different thresholds in patients with advanced cancer in palliative care.</p></div><div><h3>Methods</h3><p>Prospective cohort study with patients evaluated at a palliative care unit in Brazil between July 2016 and March 2020. We included patients ≥ 20 years old, both sexes, able to provide the necessary information or accompanied by someone able to do so, and Karnofsky Performance Status ≥ 30 %. The exclusion criteria were the absence of laboratory data and previous diagnosis of autoimmune and infectious diseases. The thresholds analyzed were: CRP &lt; 5 vs. 5-10 vs. &gt; 10 mg/L, albumin &lt; 2.4 vs. 2.4-2.9 vs. 3.0-3.5 vs. &gt; 3.5 g/dL; CAR &lt;1.2 vs. 1.2–2.0 vs. &gt; 2.0, and mGPS equal to 0 vs. 1 vs. 2. Kaplan-Meier curves and Cox regression models (with hazard ratios [HR] and 95% confidence interval [CI]) were used to evaluate prognostic value, and the concordance statistic (C-statistic) was used to evaluate the predictive accuracy of these thresholds to predict death within 90 days.</p></div><div><h3>Results</h3><p>A total of 1,877 patients were included. Median overall survival was 51 (19;124) days and decreased in line with the deterioration of the inflammatory biomarkers. According to the Cox regression models, HR increased as the thresholds worsened (CRP: 1.74 [95% CI, 1.50-2.02] to 2.30 [95% CI, 2.00-2.64]; albumin: 1.77 [95% CI, 1.52-2.07] to 2.60 [95% CI, 2.15-3.14]; CAR: 1.47 [95% CI, 1.21-1.77] to 2.35 [95% CI, 2.05-2.69]; mGPS: 1.78 [95% CI, 1.40-2.23] to 1.89 [95% CI, 1.65-2.15]). All the inflammatory biomarkers evaluated showed discriminatory accuracy for predicting death (C-statistic &gt;0.70), with CAR as the best parameter (C-statistic: 0.80).</p></div><div><h3>Conclusion</h3><p>Our results suggest that CRP, albumin, CAR, and mGPS can be used as clinically meaningful biomarkers to stratify patients with advanced cancer in palliative care according to the severity of these indicators.</p></div>","PeriodicalId":55193,"journal":{"name":"Current Problems in Cancer","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Problems in Cancer","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0147027224000564","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose

To evaluate the prognostic value of C-reactive protein (CRP), albumin, CRP/albumin ratio (CAR), and modified Glasgow Prognostic Score (mGPS) at different thresholds in patients with advanced cancer in palliative care.

Methods

Prospective cohort study with patients evaluated at a palliative care unit in Brazil between July 2016 and March 2020. We included patients ≥ 20 years old, both sexes, able to provide the necessary information or accompanied by someone able to do so, and Karnofsky Performance Status ≥ 30 %. The exclusion criteria were the absence of laboratory data and previous diagnosis of autoimmune and infectious diseases. The thresholds analyzed were: CRP < 5 vs. 5-10 vs. > 10 mg/L, albumin < 2.4 vs. 2.4-2.9 vs. 3.0-3.5 vs. > 3.5 g/dL; CAR <1.2 vs. 1.2–2.0 vs. > 2.0, and mGPS equal to 0 vs. 1 vs. 2. Kaplan-Meier curves and Cox regression models (with hazard ratios [HR] and 95% confidence interval [CI]) were used to evaluate prognostic value, and the concordance statistic (C-statistic) was used to evaluate the predictive accuracy of these thresholds to predict death within 90 days.

Results

A total of 1,877 patients were included. Median overall survival was 51 (19;124) days and decreased in line with the deterioration of the inflammatory biomarkers. According to the Cox regression models, HR increased as the thresholds worsened (CRP: 1.74 [95% CI, 1.50-2.02] to 2.30 [95% CI, 2.00-2.64]; albumin: 1.77 [95% CI, 1.52-2.07] to 2.60 [95% CI, 2.15-3.14]; CAR: 1.47 [95% CI, 1.21-1.77] to 2.35 [95% CI, 2.05-2.69]; mGPS: 1.78 [95% CI, 1.40-2.23] to 1.89 [95% CI, 1.65-2.15]). All the inflammatory biomarkers evaluated showed discriminatory accuracy for predicting death (C-statistic >0.70), with CAR as the best parameter (C-statistic: 0.80).

Conclusion

Our results suggest that CRP, albumin, CAR, and mGPS can be used as clinically meaningful biomarkers to stratify patients with advanced cancer in palliative care according to the severity of these indicators.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用 C 反应蛋白、白蛋白和相关炎症生物标志物对姑息治疗中的晚期癌症患者进行预后风险分层。
目的:评估姑息治疗晚期癌症患者C反应蛋白(CRP)、白蛋白、CRP/白蛋白比值(CAR)和改良格拉斯哥预后评分(mGPS)在不同阈值下的预后价值:前瞻性队列研究:2016 年 7 月至 2020 年 3 月期间在巴西一家姑息治疗机构接受评估的患者。研究对象包括年龄≥ 20 岁的患者,男女均可,能够提供必要信息或由能够提供必要信息的人陪同,卡诺夫斯基表现状态≥ 30%。排除标准是没有化验数据和曾被诊断患有自身免疫性疾病和传染性疾病。分析的临界值为CRP < 5 vs. 5-10 vs. > 10 mg/L,白蛋白 < 2.4 vs. 2.4-2.9 vs. 3.0-3.5 vs. > 3.5 g/dL; CAR 2.0,mGPS 等于 0 vs. 1 vs. 2。卡普兰-梅耶曲线和考克斯回归模型(含危险比[HR]和95%置信区间[CI])用于评估预后价值,一致性统计(C-statistic)用于评估这些阈值预测90天内死亡的准确性:共纳入 1,877 例患者。中位总生存期为 51 (19;124) 天,随着炎症生物标志物的恶化而下降。根据 Cox 回归模型,HR 随着阈值的恶化而增加(CRP:1.74 [95% CI,1.50-2.02] 至 2.30 [95% CI,2.00-2.64];白蛋白:1.77 [95% CI,1.52-2.07]至 2.60 [95% CI,2.15-3.14];CAR:1.47 [95% CI,1.21-1.77]至 2.35 [95% CI,2.05-2.69];mGPS:1.78 [95% CI,1.40-2.23]至 1.89 [95% CI,1.65-2.15])。所有评估的炎症生物标志物都显示出预测死亡的鉴别准确性(C统计量大于0.70),其中CAR是最佳参数(C统计量:0.80):我们的研究结果表明,CRP、白蛋白、CAR 和 mGPS 可作为有临床意义的生物标志物,根据这些指标的严重程度对晚期癌症患者进行姑息治疗分层。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Current Problems in Cancer
Current Problems in Cancer 医学-肿瘤学
CiteScore
5.10
自引率
0.00%
发文量
71
审稿时长
15 days
期刊介绍: Current Problems in Cancer seeks to promote and disseminate innovative, transformative, and impactful data on patient-oriented cancer research and clinical care. Specifically, the journal''s scope is focused on reporting the results of well-designed cancer studies that influence/alter practice or identify new directions in clinical cancer research. These studies can include novel therapeutic approaches, new strategies for early diagnosis, cancer clinical trials, and supportive care, among others. Papers that focus solely on laboratory-based or basic science research are discouraged. The journal''s format also allows, on occasion, for a multi-faceted overview of a single topic via a curated selection of review articles, while also offering articles that present dynamic material that influences the oncology field.
期刊最新文献
Artificial intelligence-based pathological application to predict regional lymph node metastasis in Papillary Thyroid Cancer Four versus six cycles of platinum-based chemotherapy for advanced Urothelial carcinoma in the era of immune checkpoint inhibitors: A retrospective cohort study (FOCUS, KCSG-GU23-08) Metaplastic breast cancer: Experience with ifosfamide based chemotherapy Table of Contents Title Page
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1