哮喘发作的炎症和临床危险因素（ORACLE2）研究：22项随机试验对照组的患者水平荟萃分析
2025/04/30
摘要
背景：严重哮喘发作的临床危险因素已经确定，但其增量对预后的价值尚不清楚。此外，2型炎症是一种常见的可治疗过程，其增量贡献尚不确定。
目的：本研究旨在量化基线特征和2型炎症生物标志物的预后价值，特别是血液嗜酸性粒细胞计数和呼出气一氧化氮分数（FeNO），以预测哮喘发作。
方法：在这项对随机对照试验（RCTs）牛津哮喘发作风险量表2（ORACLE2）的系统评价和荟萃分析中，我们在MEDLINE上搜索了从1993年1月1日到2021年4月1日期间，研究固定治疗方案对哮喘发作率影响至少6个月的试验，包括基线血液嗜酸性粒细胞计数和FeNO。符合条件的参与者年龄在12岁或以上，患有哮喘（任何严重程度），被随机分配到随机对照试验的对照组。相关试验由两名独立审评员（SC和IDP）手动检索和审评。与五位评审员讨论了分歧。荟萃分析的个体患者数据（IPD）要求研究作者提供。我们调查了对照组参与者至少6个月内严重哮喘发作（≥3天全身性皮质类固醇）的发生率以及基线血液嗜酸性粒细胞计数和FeNO的预后影响。根据经关键变量（包括血液嗜酸性粒细胞计数和FeNO）调整的负二项模型，得出95%置信区间的年化哮喘发作率比率（RR），并探讨了这些2型炎症生物标志物之间的相互作用。证据的确定性使用GRADE进行评估。所纳入研究的异质性和生态偏见的可能性通过一致性统计（C-统计）进行量化。本研究已在PROSPERO注册，CRD42021245337。
结果：我们确定了976项可能符合条件的研究。经过自动筛选，我们手动审查了219篇全文文章。其中，包括23项随机对照试验的19篇出版物符合条件。纳入22项随机对照试验的6513名参与者（4140名[64%]女性；2370名[36%]男性；3名缺失）进行数据分析。6513名患者中有5972名（92%）患有中重度哮喘。在5482人年的随访期间，共发生4615例哮喘发作（年化率为0.84/人年）。更高的血液嗜酸性粒细胞计数或FeNO与更高的哮喘发作风险有关（每增加10倍，血液嗜酸性细胞计数的RR为1.48[95%CI 1.30-1.68]，FeNO为1.44[1.26-1.65]；高确定性证据）。其他预后因素为发作史（是vs否，RR 1.94[1.61-2.32]）；疾病严重程度（重度vs中度，RR 1.57[1.22-2.03]）；预测FEV1百分比（FEV1%；每降低10%，RR 1.11[1.08-1.15]）；5项哮喘控制问卷评分（ACQ-5；每增加0.5，RR 1.10[1.07-1.13]）。高血嗜酸性粒细胞计数和FeNO联合使用比单独使用任何一个预后因素都有更大的风险。支气管扩张剂的可逆性与严重哮喘发作的风险较低有关（每增加10%，RR 0.93[0.90-0.96]），主要在0%至25%之间观察到降低。关于所纳入研究的异质性，C统计范围为0.58至0.95，表明研究之间患者和疾病特征存在重大差异。在每项试验的单变量荟萃分析中，我们发现研究之间的关联存在很大的异质性，I2统计范围为0.56至0.97。
结论：血液嗜酸性粒细胞计数、FeNO、哮喘发作史、疾病严重程度、低肺功能（低FEV1%）和症状（ACQ-5评分）是哮喘发作的关键预测因素。相反，我们发现适度的支气管扩张剂可逆性与风险降低有关。这些来自高质量跨国随机对照试验的发现支持将血液嗜酸性粒细胞和FeNO纳入临床风险分层，以有针对性地降低风险。应探索更个性化的临床决策模型。
Inflammatory and clinical risk factors for asthma attacks (ORACLE2): a patient-level meta-analysis of control groups of 22 randomised trials.
Meulmeester FL, Mailhot-Larouche S, Celis-Preciado C, Lemaire-Paquette S, Ramakrishnan S, Wechsler ME, Brusselle G, Corren J, Hardy J, Diver SE, Brightling CE, Castro M, Hanania NA, Jackson DJ, Martin N, Laugerud A, Santoro E, Compton C, Hardin ME, Holweg CTJ, Subhashini A, Hinks TSC, Beasley RW, Sont JK, Steyerberg EW, Pavord ID, Couillard S.
Abstract
BACKGROUND:Clinical risk factors for severe asthma attacks have been identified, but their incremental prognostic values are unclear. Additionally, the incremental contribution of type 2 inflammation, a common, treatable process, is undetermined.
OBJECTIVE:We aimed to quantify the prognostic value of baseline characteristics and type 2 inflammatory biomarkers, specifically blood eosinophil count and fractional exhaled nitric oxide (FeNO), to predict asthma attacks.
METHODS:In this systematic review and meta-analysis of randomised controlled trials (RCTs), Oxford Asthma Attack Risk Scale 2 (ORACLE2), we searched MEDLINE from Jan 1, 1993, to April 1, 2021, for trials investigating fixed treatment regimen effects on asthma attack rates for at least 6 months with baseline blood eosinophil count and FeNO. Eligible participants were aged 12 years or older with asthma (any severity) who had been randomly assigned to the control group of an RCT. Relevant trials were manually retrieved and reviewed by two independent reviewers (SC and IDP). Disagreements were discussed with five reviewers. Individual patient data (IPD) for meta-analysis were requested from study authors. We investigated the rate of severe asthma attacks (≥3 days of systemic corticosteroids) for at least 6 months and prognostic effects of baseline blood eosinophil count and FeNO in control group participants. Rate ratios (RRs) with 95% CIs were derived for annualised asthma attack rates from negative binomial models adjusted for key variables, including blood eosinophil count and FeNO, and interactions between these type 2 inflammatory biomarkers were explored. Certainty of evidence was assessed using GRADE. The heterogeneity of the included studies and potential for ecological bias were quantified by the concordance statistic (C-statistic). This study was registered with PROSPERO, CRD42021245337.
RESULTS:We identified 976 potentially eligible studies. After automated screening, we manually reviewed 219 full-text articles. Of these, 19 publications comprising 23 RCTs were eligible. 6513 participants (4140 [64%] female; 2370 [36%] male; three missing) spanning 22 RCTs were included for data analysis. 5972 (92%) of 6513 patients had moderate-to-severe asthma. 4615 asthma attacks occurred during 5482 person-years of follow-up (annualised rate 0·84 per person-year). Higher blood eosinophil count or FeNO was linked to higher asthma attack risk (per 10-fold increase, RR 1·48 [95% CI 1·30-1·68] for blood eosinophil count and 1·44 [1·26-1·65] for FeNO; high-certainty evidence). Other prognostic factors were attack history (yes vs no, RR 1·94 [1·61-2·32]); disease severity (severe vs moderate, RR 1·57 [1·22-2·03]); FEV1 percentage predicted (FEV1%; per 10% decrease, RR 1·11 [1·08-1·15]); and 5-item Asthma Control Questionnaire score (ACQ-5; per 0·5 increase, RR 1·10 [1·07-1·13]). High blood eosinophil count and FeNO combined were associated with greater risk than either prognostic factor separately. Bronchodilator reversibility was associated with lower risk of severe asthma attacks (per 10% increase, RR 0·93 [0·90-0·96]), with the reduction observed primarily between 0% and 25%. Regarding heterogeneity of the included studies, the C-statistic ranged from 0·58 to 0·95, indicating major differences in patient and disease characteristics between studies. In the univariable meta-analysis per trial, we found substantial heterogeneity in associations between studies, with I2 statistics ranging from 0·56 to 0·97.
CONCLUSION:Blood eosinophil count, FeNO, asthma attack history, disease severity, low lung function (low FEV1%), and symptoms (ACQ-5 score) are key predictors of asthma attacks. Conversely, we found that moderate bronchodilator reversibility was associated with reduced risk. These findings from high-quality multinational RCTs support incorporation of blood eosinophils and FeNO into clinical risk stratification for targeted risk reduction. More individualised clinical decision-making models should be explored.
背景：严重哮喘发作的临床危险因素已经确定，但其增量对预后的价值尚不清楚。此外，2型炎症是一种常见的可治疗过程，其增量贡献尚不确定。
目的：本研究旨在量化基线特征和2型炎症生物标志物的预后价值，特别是血液嗜酸性粒细胞计数和呼出气一氧化氮分数（FeNO），以预测哮喘发作。
方法：在这项对随机对照试验（RCTs）牛津哮喘发作风险量表2（ORACLE2）的系统评价和荟萃分析中，我们在MEDLINE上搜索了从1993年1月1日到2021年4月1日期间，研究固定治疗方案对哮喘发作率影响至少6个月的试验，包括基线血液嗜酸性粒细胞计数和FeNO。符合条件的参与者年龄在12岁或以上，患有哮喘（任何严重程度），被随机分配到随机对照试验的对照组。相关试验由两名独立审评员（SC和IDP）手动检索和审评。与五位评审员讨论了分歧。荟萃分析的个体患者数据（IPD）要求研究作者提供。我们调查了对照组参与者至少6个月内严重哮喘发作（≥3天全身性皮质类固醇）的发生率以及基线血液嗜酸性粒细胞计数和FeNO的预后影响。根据经关键变量（包括血液嗜酸性粒细胞计数和FeNO）调整的负二项模型，得出95%置信区间的年化哮喘发作率比率（RR），并探讨了这些2型炎症生物标志物之间的相互作用。证据的确定性使用GRADE进行评估。所纳入研究的异质性和生态偏见的可能性通过一致性统计（C-统计）进行量化。本研究已在PROSPERO注册，CRD42021245337。
结果：我们确定了976项可能符合条件的研究。经过自动筛选，我们手动审查了219篇全文文章。其中，包括23项随机对照试验的19篇出版物符合条件。纳入22项随机对照试验的6513名参与者（4140名[64%]女性；2370名[36%]男性；3名缺失）进行数据分析。6513名患者中有5972名（92%）患有中重度哮喘。在5482人年的随访期间，共发生4615例哮喘发作（年化率为0.84/人年）。更高的血液嗜酸性粒细胞计数或FeNO与更高的哮喘发作风险有关（每增加10倍，血液嗜酸性细胞计数的RR为1.48[95%CI 1.30-1.68]，FeNO为1.44[1.26-1.65]；高确定性证据）。其他预后因素为发作史（是vs否，RR 1.94[1.61-2.32]）；疾病严重程度（重度vs中度，RR 1.57[1.22-2.03]）；预测FEV1百分比（FEV1%；每降低10%，RR 1.11[1.08-1.15]）；5项哮喘控制问卷评分（ACQ-5；每增加0.5，RR 1.10[1.07-1.13]）。高血嗜酸性粒细胞计数和FeNO联合使用比单独使用任何一个预后因素都有更大的风险。支气管扩张剂的可逆性与严重哮喘发作的风险较低有关（每增加10%，RR 0.93[0.90-0.96]），主要在0%至25%之间观察到降低。关于所纳入研究的异质性，C统计范围为0.58至0.95，表明研究之间患者和疾病特征存在重大差异。在每项试验的单变量荟萃分析中，我们发现研究之间的关联存在很大的异质性，I2统计范围为0.56至0.97。
结论：血液嗜酸性粒细胞计数、FeNO、哮喘发作史、疾病严重程度、低肺功能（低FEV1%）和症状（ACQ-5评分）是哮喘发作的关键预测因素。相反，我们发现适度的支气管扩张剂可逆性与风险降低有关。这些来自高质量跨国随机对照试验的发现支持将血液嗜酸性粒细胞和FeNO纳入临床风险分层，以有针对性地降低风险。应探索更个性化的临床决策模型。
（中日友好医院呼吸与危重症医学科 张婧媛 摘译 林江涛 审校）
（Lancet Respir Med. 2025 Apr 8:S2213-2600(25)00037-2. doi: 10.1016/S2213-2600(25)00037-2.）
Inflammatory and clinical risk factors for asthma attacks (ORACLE2): a patient-level meta-analysis of control groups of 22 randomised trials.
Meulmeester FL, Mailhot-Larouche S, Celis-Preciado C, Lemaire-Paquette S, Ramakrishnan S, Wechsler ME, Brusselle G, Corren J, Hardy J, Diver SE, Brightling CE, Castro M, Hanania NA, Jackson DJ, Martin N, Laugerud A, Santoro E, Compton C, Hardin ME, Holweg CTJ, Subhashini A, Hinks TSC, Beasley RW, Sont JK, Steyerberg EW, Pavord ID, Couillard S.
Abstract
BACKGROUND:Clinical risk factors for severe asthma attacks have been identified, but their incremental prognostic values are unclear. Additionally, the incremental contribution of type 2 inflammation, a common, treatable process, is undetermined.
OBJECTIVE:We aimed to quantify the prognostic value of baseline characteristics and type 2 inflammatory biomarkers, specifically blood eosinophil count and fractional exhaled nitric oxide (FeNO), to predict asthma attacks.
METHODS:In this systematic review and meta-analysis of randomised controlled trials (RCTs), Oxford Asthma Attack Risk Scale 2 (ORACLE2), we searched MEDLINE from Jan 1, 1993, to April 1, 2021, for trials investigating fixed treatment regimen effects on asthma attack rates for at least 6 months with baseline blood eosinophil count and FeNO. Eligible participants were aged 12 years or older with asthma (any severity) who had been randomly assigned to the control group of an RCT. Relevant trials were manually retrieved and reviewed by two independent reviewers (SC and IDP). Disagreements were discussed with five reviewers. Individual patient data (IPD) for meta-analysis were requested from study authors. We investigated the rate of severe asthma attacks (≥3 days of systemic corticosteroids) for at least 6 months and prognostic effects of baseline blood eosinophil count and FeNO in control group participants. Rate ratios (RRs) with 95% CIs were derived for annualised asthma attack rates from negative binomial models adjusted for key variables, including blood eosinophil count and FeNO, and interactions between these type 2 inflammatory biomarkers were explored. Certainty of evidence was assessed using GRADE. The heterogeneity of the included studies and potential for ecological bias were quantified by the concordance statistic (C-statistic). This study was registered with PROSPERO, CRD42021245337.
RESULTS:We identified 976 potentially eligible studies. After automated screening, we manually reviewed 219 full-text articles. Of these, 19 publications comprising 23 RCTs were eligible. 6513 participants (4140 [64%] female; 2370 [36%] male; three missing) spanning 22 RCTs were included for data analysis. 5972 (92%) of 6513 patients had moderate-to-severe asthma. 4615 asthma attacks occurred during 5482 person-years of follow-up (annualised rate 0·84 per person-year). Higher blood eosinophil count or FeNO was linked to higher asthma attack risk (per 10-fold increase, RR 1·48 [95% CI 1·30-1·68] for blood eosinophil count and 1·44 [1·26-1·65] for FeNO; high-certainty evidence). Other prognostic factors were attack history (yes vs no, RR 1·94 [1·61-2·32]); disease severity (severe vs moderate, RR 1·57 [1·22-2·03]); FEV1 percentage predicted (FEV1%; per 10% decrease, RR 1·11 [1·08-1·15]); and 5-item Asthma Control Questionnaire score (ACQ-5; per 0·5 increase, RR 1·10 [1·07-1·13]). High blood eosinophil count and FeNO combined were associated with greater risk than either prognostic factor separately. Bronchodilator reversibility was associated with lower risk of severe asthma attacks (per 10% increase, RR 0·93 [0·90-0·96]), with the reduction observed primarily between 0% and 25%. Regarding heterogeneity of the included studies, the C-statistic ranged from 0·58 to 0·95, indicating major differences in patient and disease characteristics between studies. In the univariable meta-analysis per trial, we found substantial heterogeneity in associations between studies, with I2 statistics ranging from 0·56 to 0·97.
CONCLUSION:Blood eosinophil count, FeNO, asthma attack history, disease severity, low lung function (low FEV1%), and symptoms (ACQ-5 score) are key predictors of asthma attacks. Conversely, we found that moderate bronchodilator reversibility was associated with reduced risk. These findings from high-quality multinational RCTs support incorporation of blood eosinophils and FeNO into clinical risk stratification for targeted risk reduction. More individualised clinical decision-making models should be explored.
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