Suppr超能文献

癌症 LinQ 发现数据库中多站点队列癌症患者严重急性呼吸综合征冠状病毒 2 感染发生率及其后续死亡率。

Incidence of Severe Acute Respiratory Syndrome Coronavirus 2 and Subsequent Mortality in a Multisite Cohort of Patients With Cancer in the CancerLinQ Discovery Database.

机构信息

Division of Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC.

CancerLinQ, American Society of Clinical Oncology, Alexandria, VA.

出版信息

JCO Oncol Pract. 2022 Aug;18(8):e1265-e1277. doi: 10.1200/OP.22.00064.

Abstract

PURPOSE

Understanding risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent mortality among patients with cancer may help inform treatment decisions during the COVID-19 pandemic.

METHODS

CancerLinQ is an electronic health record database from US oncology practices. We identified a cohort of patients with malignancy and 2+ encounters at CancerLinQ practices in the 12 months before the study period (January 1, 2020-January 31, 2021). We identified a SARS-CoV-2 subcohort as having a positive SARS-CoV-2 test or International Classification of Diseases, 10th Revision, code. We examined predictors of SARS-CoV-2 infection and mortality including sex, race, ethnicity, age, malignancy type, and prior therapy. Unadjusted and adjusted incidence rate ratios (aIRRs) and 95% CIs were estimated from Poisson regression models for SARS-CoV-2 infections and mortality.

RESULTS

The cancer cohort included 629,128 patients, and the SARS-CoV-2 subcohort included 12,300 patients. Higher incidence of SARS-CoV-2 was seen among patients who were male (incidence rate ratio [IRR], 1.14; 95% CI, 1.10 to 1.18), Black (IRR, 1.48; 95% CI, 1.41 to 1.56), Hispanic (IRR, 2.02; 95% CI, 1.91 to 2.14), age < 50 years (IRR, 1.34; 95% CI, 1.26 to 1.42), with hematologic malignancies (IRR, 1.07; 95% CI, 1.02 to 1.12), and with recent chemotherapy (IRR, 1.30, 95% CI, 1.22 to 1.40). In the adjusted analysis, higher incidence was seen in patients who were male (aIRR, 1.17; 95% CI, 1.13 to 1.21), Hispanic (aIRR, 2.01; 95% CI, 1.88 to 2.14), and with recent chemotherapy (aIRR, 1.17; 95% CI, 1.09 to 1.25). There were 182 all-cause deaths within the SARS-CoV-2 subcohort. Higher mortality was seen among patients who were male (IRR, 1.39; 95% CI, 1.04 to 1.86), unknown race (IRR, 2.64; 95% CI, 1.42 to 4.91), other/unknown ethnicity (IRR, 1.99; 95% CI, 1.20 to 3.29), age 60-69 years (IRR, 2.76; 95% CI, 1.23 to 6.19), age 70-79 years (IRR, 5.28; 95% CI, 2.42 to 11.5), age 80+ years (IRR, 7.31; 95% CI, 3.31 to 16.1), or with recent chemotherapy (IRR, 1.52, 95% CI, 1.01 to 2.29). In the adjusted analysis, higher mortality was seen with increased age and receipt of chemotherapy.

CONCLUSION

Patients with increased risk of SARS-CoV-2 infection must balance the competing risks of their cancer diagnosis/treatment and SARS-CoV-2 infection.

摘要

目的

了解癌症患者感染严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)和随后死亡的风险,可能有助于在 COVID-19 大流行期间为治疗决策提供信息。

方法

CancerLinQ 是美国肿瘤学实践中的电子健康记录数据库。我们确定了一个患有恶性肿瘤且在研究期间前 12 个月(2020 年 1 月 1 日-2021 年 1 月 31 日)在 CancerLinQ 实践中有 2 次以上就诊的恶性肿瘤患者队列。我们将 SARS-CoV-2 亚队列确定为 SARS-CoV-2 检测呈阳性或国际疾病分类第 10 次修订版代码。我们研究了包括性别、种族、民族、年龄、恶性肿瘤类型和既往治疗在内的 SARS-CoV-2 感染和死亡率的预测因素。使用泊松回归模型估计了 SARS-CoV-2 感染和死亡率的未调整和调整后的发病率比(aIRR)和 95%置信区间。

结果

癌症队列包括 629128 名患者,SARS-CoV-2 亚队列包括 12300 名患者。男性(发病率比 [IRR],1.14;95%CI,1.10 至 1.18)、黑人(IRR,1.48;95%CI,1.41 至 1.56)、西班牙裔(IRR,2.02;95%CI,1.91 至 2.14)、年龄<50 岁(IRR,1.34;95%CI,1.26 至 1.42)、血液恶性肿瘤(IRR,1.07;95%CI,1.02 至 1.12)和近期化疗(IRR,1.30,95%CI,1.22 至 1.40)患者的 SARS-CoV-2 感染发生率更高。在调整分析中,男性(aIRR,1.17;95%CI,1.13 至 1.21)、西班牙裔(aIRR,2.01;95%CI,1.88 至 2.14)和近期化疗(aIRR,1.17;95%CI,1.09 至 1.25)患者的感染发生率更高。SARS-CoV-2 亚队列中有 182 例全因死亡。男性(IRR,1.39;95%CI,1.04 至 1.86)、未知种族(IRR,2.64;95%CI,1.42 至 4.91)、其他/未知民族(IRR,1.99;95%CI,1.20 至 3.29)、年龄 60-69 岁(IRR,2.76;95%CI,1.23 至 6.19)、年龄 70-79 岁(IRR,5.28;95%CI,2.42 至 11.5)、年龄 80 岁及以上(IRR,7.31;95%CI,3.31 至 16.1)或接受近期化疗(IRR,1.52,95%CI,1.01 至 2.29)患者的死亡率更高。在调整分析中,随着年龄的增加和接受化疗,死亡率更高。

结论

感染 SARS-CoV-2 风险增加的患者必须平衡癌症诊断/治疗和 SARS-CoV-2 感染的竞争风险。

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