{"title":"开发一种预测鸟分枝杆菌复杂肺部疾病治疗失败的简单CT评分系统:BCD(支气管扩张和腔分布)评分","authors":"Makoto Hayashi, Hiroyasu Takishima, Hidekazu Cho, Fumihiro Yamaguchi, Takuya Yokoe, Satoshi Matsukura","doi":"10.1093/ofid/ofaf565","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Optimal timing for treatment initiation in <i>Mycobacterium avium</i> complex pulmonary disease (MAC-PD) remains unclear due to lack of established rules for predicting treatment response.</p><p><strong>Methods: </strong>A retrospective observational study was conducted to develop a prediction model for treatment failure at 2 Japanese university hospitals between 2012 and 2023. Participants were 135 patients with MAC-PD who received macrolides and ethambutol-containing regimens over 1 year. Treatment failure was defined as nonachievement culture conversion at 1 year. We selected model components as cavity (categorized by diameter) and bronchiectasis (categorized by modified Reiff score) on pretreatment computed tomography. Their combinations of each category were scored based on number of lobes involved and compared by average areas under the curve calculated using k-fold cross-validation.</p><p><strong>Results: </strong>Forty-three (31.9%) of the 135 patients failed in treatment. Number of lobes with cavities > 2cm or bronchiectasis with varicose or cystic changes was designated as the prediction model, with an average area under the curve of 0.798, and was named the Bronchiectasis and Cavity Distribution score. The representative metrics were sensitivity of 0.907 at the cutoff of 2 and specificity of 0.913 at the cutoff of 4 points. The patients were stratified into low-risk (0-1 points), intermediate-risk (2-3 points), and high-risk (4-6 points) groups. The treatment failure rates were 8.0%, 35.6%, and 69.2% in the respective groups.</p><p><strong>Conclusions: </strong>With simple assessment of computed tomography findings, the Bronchiectasis and Cavity Distribution score predicted treatment failure. Although validation studies are warranted, this score may provide guidance for treatment of MAC-PD.</p>","PeriodicalId":19517,"journal":{"name":"Open Forum Infectious Diseases","volume":"12 9","pages":"ofaf565"},"PeriodicalIF":3.8000,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465108/pdf/","citationCount":"0","resultStr":"{\"title\":\"Developing a Simple Scoring System on CT Findings for Predicting Treatment Failure in <i>Mycobacterium avium</i> Complex Pulmonary Disease: The BCD (Bronchiectasis and Cavity Distribution) Score.\",\"authors\":\"Makoto Hayashi, Hiroyasu Takishima, Hidekazu Cho, Fumihiro Yamaguchi, Takuya Yokoe, Satoshi Matsukura\",\"doi\":\"10.1093/ofid/ofaf565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Optimal timing for treatment initiation in <i>Mycobacterium avium</i> complex pulmonary disease (MAC-PD) remains unclear due to lack of established rules for predicting treatment response.</p><p><strong>Methods: </strong>A retrospective observational study was conducted to develop a prediction model for treatment failure at 2 Japanese university hospitals between 2012 and 2023. Participants were 135 patients with MAC-PD who received macrolides and ethambutol-containing regimens over 1 year. Treatment failure was defined as nonachievement culture conversion at 1 year. We selected model components as cavity (categorized by diameter) and bronchiectasis (categorized by modified Reiff score) on pretreatment computed tomography. Their combinations of each category were scored based on number of lobes involved and compared by average areas under the curve calculated using k-fold cross-validation.</p><p><strong>Results: </strong>Forty-three (31.9%) of the 135 patients failed in treatment. Number of lobes with cavities > 2cm or bronchiectasis with varicose or cystic changes was designated as the prediction model, with an average area under the curve of 0.798, and was named the Bronchiectasis and Cavity Distribution score. The representative metrics were sensitivity of 0.907 at the cutoff of 2 and specificity of 0.913 at the cutoff of 4 points. The patients were stratified into low-risk (0-1 points), intermediate-risk (2-3 points), and high-risk (4-6 points) groups. The treatment failure rates were 8.0%, 35.6%, and 69.2% in the respective groups.</p><p><strong>Conclusions: </strong>With simple assessment of computed tomography findings, the Bronchiectasis and Cavity Distribution score predicted treatment failure. Although validation studies are warranted, this score may provide guidance for treatment of MAC-PD.</p>\",\"PeriodicalId\":19517,\"journal\":{\"name\":\"Open Forum Infectious Diseases\",\"volume\":\"12 9\",\"pages\":\"ofaf565\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465108/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Forum Infectious Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/ofid/ofaf565\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/9/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Forum Infectious Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/ofid/ofaf565","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/9/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Developing a Simple Scoring System on CT Findings for Predicting Treatment Failure in Mycobacterium avium Complex Pulmonary Disease: The BCD (Bronchiectasis and Cavity Distribution) Score.
Background: Optimal timing for treatment initiation in Mycobacterium avium complex pulmonary disease (MAC-PD) remains unclear due to lack of established rules for predicting treatment response.
Methods: A retrospective observational study was conducted to develop a prediction model for treatment failure at 2 Japanese university hospitals between 2012 and 2023. Participants were 135 patients with MAC-PD who received macrolides and ethambutol-containing regimens over 1 year. Treatment failure was defined as nonachievement culture conversion at 1 year. We selected model components as cavity (categorized by diameter) and bronchiectasis (categorized by modified Reiff score) on pretreatment computed tomography. Their combinations of each category were scored based on number of lobes involved and compared by average areas under the curve calculated using k-fold cross-validation.
Results: Forty-three (31.9%) of the 135 patients failed in treatment. Number of lobes with cavities > 2cm or bronchiectasis with varicose or cystic changes was designated as the prediction model, with an average area under the curve of 0.798, and was named the Bronchiectasis and Cavity Distribution score. The representative metrics were sensitivity of 0.907 at the cutoff of 2 and specificity of 0.913 at the cutoff of 4 points. The patients were stratified into low-risk (0-1 points), intermediate-risk (2-3 points), and high-risk (4-6 points) groups. The treatment failure rates were 8.0%, 35.6%, and 69.2% in the respective groups.
Conclusions: With simple assessment of computed tomography findings, the Bronchiectasis and Cavity Distribution score predicted treatment failure. Although validation studies are warranted, this score may provide guidance for treatment of MAC-PD.
期刊介绍:
Open Forum Infectious Diseases provides a global forum for the publication of clinical, translational, and basic research findings in a fully open access, online journal environment. The journal reflects the broad diversity of the field of infectious diseases, and focuses on the intersection of biomedical science and clinical practice, with a particular emphasis on knowledge that holds the potential to improve patient care in populations around the world. Fully peer-reviewed, OFID supports the international community of infectious diseases experts by providing a venue for articles that further the understanding of all aspects of infectious diseases.