Drew D Robinson, Chia-Ying Chiu, Jane I Hampton, George M Solomon, J Michael Wells
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Chi Square and Kruskal-Wallis tests were used for bivariate analyses, generalized linear models for modeling forced expiratory volume in 1-second (FEV1), and logistic regression modeling for healthcare utilization outcomes adjusted for race, age, and sex.</p><p><strong>Results: </strong>1,772 tests were ordered from January 2016 through December 2021. Testing identified 79.5% Pi*MM, 8.4% PI*Z-het, 8.4% Pi*S-het, 3.3% PI*Non-S/Non-Z, and 0.5% PI*ZZ. FEV1 to forced vital capacity (FEV1/FVC) and FEV1 percent predicted were lowest in the PI*Non-S/Non-Z group compared to the other groups. PI*Non-S/Non-Z group had higher mean neutrophil lymphocyte ratio (NLR) compared to the other groups (p=0.021), higher hospitalization for acute respiratory events (27.6%; p=0.019), ICU utilization (15.3%, p=0.011) and death (25.4%, p=0.041) compared to the other groups.</p><p><strong>Conclusion: </strong>AATD PI*typing identified several allelic combinations not previously linked with clinical disease. Compared to other PI*type groups, PI*'Non-S/Non-Z' group had impairments in pulmonary function, elevated inflammatory markers, higher health care utilization, and death. Our results underpin the need to explore relationships between rare allelic combinations and clinical outcomes.</p>","PeriodicalId":51340,"journal":{"name":"Chronic Obstructive Pulmonary Diseases-Journal of the Copd Foundation","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical Characteristics and Health Care Resource Utilization Among Individuals Undergoing Alpha-1 Antitrypsin Testing in a Quaternary Health System.\",\"authors\":\"Drew D Robinson, Chia-Ying Chiu, Jane I Hampton, George M Solomon, J Michael Wells\",\"doi\":\"10.15326/jcopdf.2025.0723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Rationale: </strong>Alpha-1 antitrypsin deficiency (AATD) is a genetically inherited condition that can result in serious lung and liver disease. It is unclear whether testing for common alleles is sufficient or if testing for rare variants is helpful in identifying clinically significant disease.</p><p><strong>Methods: </strong>A retrospective review was performed on adult patients who had AAT phenotyping from January 2016 through December 2021. We recorded clinical characteristics and then grouped patients based on PI*types: Normal, PI*Z-heterozygotes (het), PI*ZZ, PI*S-hets, and defined a PI*Non-S/Non-Z group to include other identified PI*types. Chi Square and Kruskal-Wallis tests were used for bivariate analyses, generalized linear models for modeling forced expiratory volume in 1-second (FEV1), and logistic regression modeling for healthcare utilization outcomes adjusted for race, age, and sex.</p><p><strong>Results: </strong>1,772 tests were ordered from January 2016 through December 2021. Testing identified 79.5% Pi*MM, 8.4% PI*Z-het, 8.4% Pi*S-het, 3.3% PI*Non-S/Non-Z, and 0.5% PI*ZZ. 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引用次数: 0
摘要
原理:α -1抗胰蛋白酶缺乏症(AATD)是一种遗传性疾病,可导致严重的肺部和肝脏疾病。目前尚不清楚检测常见等位基因是否足够,或者检测罕见变异是否有助于识别临床重大疾病。方法:对2016年1月至2021年12月患有AAT表型的成年患者进行回顾性研究。我们记录临床特征,然后根据PI*类型对患者进行分组:正常,PI* z -杂合子(het), PI*ZZ, PI*S-hets,并定义PI*Non-S/Non-Z组,包括其他已确定的PI*类型。采用卡方检验和Kruskal-Wallis检验进行双变量分析,采用广义线性模型模拟1秒用力呼气量(FEV1),采用logistic回归模型对医疗保健利用结果进行种族、年龄和性别调整。结果:从2016年1月到2021年12月订购了1,772个测试。经检测,Pi*MM为79.5%,Pi* z - ht为8.4%,Pi* s - ht为8.4%,Pi* Non-S/Non-Z为3.3%,Pi* ZZ为0.5%。与其他组相比,PI*Non-S/Non-Z组的FEV1/FVC和fev1%预测值最低。PI*Non-S/Non-Z组平均中性粒细胞比(NLR)高于其他组(p=0.021),急性呼吸事件住院率(27.6%,p=0.019)、ICU使用率(15.3%,p=0.011)和死亡率(25.4%,p=0.041)高于其他组(p= 0.041)。结论:AATD PI*分型鉴定出几个先前未与临床疾病相关的等位基因组合。与其他PI*型组相比,PI*'Non-S/Non-Z'组肺功能受损,炎症标志物升高,医疗保健利用率较高,死亡。我们的结果支持了探索罕见等位基因组合与临床结果之间关系的需要。
Clinical Characteristics and Health Care Resource Utilization Among Individuals Undergoing Alpha-1 Antitrypsin Testing in a Quaternary Health System.
Rationale: Alpha-1 antitrypsin deficiency (AATD) is a genetically inherited condition that can result in serious lung and liver disease. It is unclear whether testing for common alleles is sufficient or if testing for rare variants is helpful in identifying clinically significant disease.
Methods: A retrospective review was performed on adult patients who had AAT phenotyping from January 2016 through December 2021. We recorded clinical characteristics and then grouped patients based on PI*types: Normal, PI*Z-heterozygotes (het), PI*ZZ, PI*S-hets, and defined a PI*Non-S/Non-Z group to include other identified PI*types. Chi Square and Kruskal-Wallis tests were used for bivariate analyses, generalized linear models for modeling forced expiratory volume in 1-second (FEV1), and logistic regression modeling for healthcare utilization outcomes adjusted for race, age, and sex.
Results: 1,772 tests were ordered from January 2016 through December 2021. Testing identified 79.5% Pi*MM, 8.4% PI*Z-het, 8.4% Pi*S-het, 3.3% PI*Non-S/Non-Z, and 0.5% PI*ZZ. FEV1 to forced vital capacity (FEV1/FVC) and FEV1 percent predicted were lowest in the PI*Non-S/Non-Z group compared to the other groups. PI*Non-S/Non-Z group had higher mean neutrophil lymphocyte ratio (NLR) compared to the other groups (p=0.021), higher hospitalization for acute respiratory events (27.6%; p=0.019), ICU utilization (15.3%, p=0.011) and death (25.4%, p=0.041) compared to the other groups.
Conclusion: AATD PI*typing identified several allelic combinations not previously linked with clinical disease. Compared to other PI*type groups, PI*'Non-S/Non-Z' group had impairments in pulmonary function, elevated inflammatory markers, higher health care utilization, and death. Our results underpin the need to explore relationships between rare allelic combinations and clinical outcomes.