一项单中心队列研究的结果表明,血液白细胞、强制肺活量和定量CT的综合测量可高度预测IPF患者的死亡率。

IF 2.8 3区 医学 Q2 RESPIRATORY SYSTEM
Andrew Achaiah, Emily Fraser, Peter Saunders, Rachel Hoyles, Rachel Benamore, Ling-Pei Ho
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引用次数: 0

摘要

背景:特发性肺纤维化(IPF)是一种进行性纤维化疾病。连续FVC监测最常用于评估疾病进展,但FVC并不总是反映IPF的局部CT变化。近年来,人们对IPF的定量CT (qCT)评估越来越感兴趣。在这项研究中,我们比较了疾病进展的不同生理和qCT测量在预测IPF死亡率方面的作用。目的:我们质疑使用qCT和FVC对疾病进展的综合测量是否比单独测量更能预测死亡率,以及血液白细胞水平的增加是否进一步增强了这些疾病进展测量的预测能力。方法:我们对一个IPF队列(n = 71)进行了回顾性分析。计算CT测量肺体积(CTvol)和肺纤维化总评分(TLF)的年化变化(∆)(使用计算机软件CALIPER)以及首次CT后4个月内FVC和血液白细胞水平的年化变化。使用多变量Cox回归对死亡率进行建模。采用不同Cox回归模型的一致性指数(c统计量)来确定死亡率最具预测性和判别性的组合。结果:男性65例,占91.5%。中位(IQR)年龄73.6岁(68.4-79.3岁)。死亡24例(33.8%)。(∆)植被覆盖度的年化变化中位数为- 4.4% (-9.6-0.0),+ 2.9%(0.2-7.0),∆CTvol;-4.3%(0.0 - -10.9)。疾病进展的联合测量(∆CTvol,∆FVC和∆TLF%)在预测IPF的全因死亡率方面优于单变量测量。复合变量[ΔFVC >10%, ΔCTvol >10%或ΔTLF% >10%]最能预测死亡率[HR 7.14 (2.45-20.79), p结论:在该队列中,∆CTvol,∆FVC和∆TLF%的复合终点比单变量测量更能预测死亡率。将血液白细胞纳入风险分层模型进一步改善了所有疾病进展指标的死亡率预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A combined measure of blood leukocytes, forced vital capacity and quantitative CT is highly predictive of mortality in IPF: results of a single-centre cohort study.

A combined measure of blood leukocytes, forced vital capacity and quantitative CT is highly predictive of mortality in IPF: results of a single-centre cohort study.

A combined measure of blood leukocytes, forced vital capacity and quantitative CT is highly predictive of mortality in IPF: results of a single-centre cohort study.

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic condition. Serial FVC monitoring is most commonly used to assess progression of disease but FVC does not always reflect regional CT change in IPF. Recently there has been growing interest in quantitative CT (qCT) assessment of IPF. In this study, we compared different physiological and qCT measurements of disease progression in predicting mortality in IPF.

Aims: We question if a composite measure of disease progression using qCT and FVC is more predictive of mortality than individual measurements, and if addition of blood leukocyte levels further enhance predictive ability of these measurements of disease progression.

Methods: We conducted a retrospective analysis of an IPF cohort (n = 71). Annualised change (∆) in CT-measured lung volume (CTvol) and total lung fibrosis score (TLF) were calculated (using the computer software CALIPER) together with annualised change in FVC and blood leukocyte levels within 4 months of first CT. These were modelled against mortality using multivariate Cox regression. Concordance indexes (C-statistic) of different Cox regression models were used to determine the most predictive and discriminative combination for mortality.

Results: 65 cases (91.5%) were male. Median (IQR) age 73.6 years (68.4-79.3). Death was reported in 24 cases (33.8%). The median annualised change in (∆)FVC was - 4.4% (-9.6-0.0), ∆TLF; + 2.9% (0.2-7.0), and ∆CTvol; -4.3% (0.0-10.9). Combined measurements of disease progression (∆CTvol, ∆FVC and ∆TLF%) out-performed single-variable measurements in predicting all-cause mortality in IPF. The composite variable of [ΔFVC >10%, ΔCTvol >10% or ΔTLF% >10%] was most predictive of mortality [HR 7.14 (2.45-20.79), p <0.001]. Inclusion of blood leukocytes improved C-statistic scores for each multivariate model.

Conclusion: Composite end points of ∆CTvol, ∆FVC and ∆TLF% were more predictive of mortality than single-variable measurements in this cohort. Inclusion of blood leukocytes into risk stratification models further improved mortality prediction for all measures of disease progression.

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来源期刊
BMC Pulmonary Medicine
BMC Pulmonary Medicine RESPIRATORY SYSTEM-
CiteScore
4.40
自引率
3.20%
发文量
423
审稿时长
6-12 weeks
期刊介绍: BMC Pulmonary Medicine is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of pulmonary and associated disorders, as well as related molecular genetics, pathophysiology, and epidemiology.
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