A simplified score to quantify comorbidity in COPD.

A simplified score to quantify comorbidity in COPD.
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DOI:
10.1371/journal.pone.0114438
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Hansel NN
Hansel NN
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Putcha N;Puhan MA;Drummond MB;Han MK;Regan EA;Hanania NA;Martinez CH;Foreman M;Bhatt SP;Make B;Ramsdell J;DeMeo DL;Barr RG;Rennard SI;Martinez F;Silverman EK;Crapo J;Wise RA;Hansel NN

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合并症在COPD中很常见,但难以量化其负担。目前有一个COPD特异性合并症指数来预测死亡率,另一个预测一般生活质量。我们试图开发和验证一种COPD特异性合并症评分,以反映以患者为中心的结局的合并症负担。使用COPDGene研究(GOLD II-IV COPD),我们采用三种技术开发了合并症评分来描述以患者为中心的结局:1)简单计数,2)加权评分,3)基于统计选择程序的加权评分。我们测试了相关性、曲线下面积(AUC)和校准统计量,以内部验证评分与呼吸系统疾病特异性生活质量(圣乔治呼吸问卷,SGRQ)、6分钟步行距离(6 MWD)、改良医学研究理事会(mMRC)呼吸困难评分和加重风险的结局,最终选择一个评分用于SPIROMICS的外部验证。合并症和所有结局之间的相关性在三个评分中具有可比性。所有评分增加了模型的预测能力,包括年龄、性别、种族、当前吸烟状况、吸烟包年数和FEV 1(所有比较p<0.001)。所有三种评分在不同结局之间的曲线下面积(AUC)相似:SGRQ(范围0·7624-0·7676)、MMRC(0·7590-0·7644)、6 MWD(0·7531-0·7560)和加重风险(0·6831-0·6919)。由于相似的性能,合并症计数用于外部验证。在SPIROMICS队列中,合并症计数在预测SGRQ(AUC 0·7891)、MMRC(AUC 0·7611)、6 MWD(AUC 0·7086)和急性加重风险(AUC 0·7341)方面表现良好。量化合并症可以更全面地了解COPD患者以患者为中心的结局风险。合并症计数可很好地量化不同COPD人群中的合并症。
Comorbidities are common in COPD, but quantifying their burden is difficult. Currently there is a COPD-specific comorbidity index to predict mortality and another to predict general quality of life. We sought to develop and validate a COPD-specific comorbidity score that reflects comorbidity burden on patient-centered outcomes. Using the COPDGene study (GOLD II-IV COPD), we developed comorbidity scores to describe patient-centered outcomes employing three techniques: 1) simple count, 2) weighted score, and 3) weighted score based upon statistical selection procedure. We tested associations, area under the Curve (AUC) and calibration statistics to validate scores internally with outcomes of respiratory disease-specific quality of life (St. George's Respiratory Questionnaire, SGRQ), six minute walk distance (6MWD), modified Medical Research Council (mMRC) dyspnea score and exacerbation risk, ultimately choosing one score for external validation in SPIROMICS. Associations between comorbidities and all outcomes were comparable across the three scores. All scores added predictive ability to models including age, gender, race, current smoking status, pack-years smoked and FEV1 (p<0.001 for all comparisons). Area under the curve (AUC) was similar between all three scores across outcomes: SGRQ (range 0·7624–0·7676), MMRC (0·7590–0·7644), 6MWD (0·7531–0·7560) and exacerbation risk (0·6831–0·6919). Because of similar performance, the comorbidity count was used for external validation. In the SPIROMICS cohort, the comorbidity count performed well to predict SGRQ (AUC 0·7891), MMRC (AUC 0·7611), 6MWD (AUC 0·7086), and exacerbation risk (AUC 0·7341). Quantifying comorbidity provides a more thorough understanding of the risk for patient-centered outcomes in COPD. A comorbidity count performs well to quantify comorbidity in a diverse population with COPD.
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