Comprehensive Nomograms Using Routine Biomarkers Beyond Eosinophil Levels : Enhancing Predictability of Corticosteroid Treatment Outcomes in AECOPD
© 2024 Feng et al..
Purpose: Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) exhibit heterogeneous responses to corticosteroid treatment. We aimed to determine whether combining eosinophil levels with other routine clinical indicators can enhance the predictability of corticosteroid treatment outcomes and to come up with a scoring system.
Patients and Methods: Consecutive patients admitted with AECOPD receiving corticosteroid treatment between July 2013 and March 2022 at Beijing Chao-Yang Hospital were retrospectively analyzed. Data on patients' demographics, smoking status, hospitalization for AECOPD in the previous year, comorbidities, blood laboratory tests, in-hospital treatment and clinical outcomes were collected. Least absolute shrinkage and selection operator (LASSO) regression and backward logistic regression were used for predictor selection, and predictive nomograms were developed. The discrimination and calibration of the nomograms were assessed using the area under the receiver operating curve (AUC) and calibration plots. Internal validation was performed using the 500-bootstrap method, and clinical utility was evaluated using decision curve analysis (DCA).
Results: Among the 3254 patients included, 804 (24.7%) had treatment failure. A nomogram of eosinophils, platelets, C-reactive protein (CRP), low density lipoprotein cholesterol, prognostic nutritional index (PNI), hospitalization for AECOPD in the previous year, ischemic heart diseases and chronic hepatic disease was developed to predict treatment failure for patients with a smoking history. For patients without a smoking history, a nomogram of CRP, PNI, ischemic heart diseases and chronic hepatic disease was developed. Although the AUCs of these two nomograms were only 0.644 and 0.647 respectively, they were significantly superior to predictions based solely on blood eosinophil levels.
Conclusion: We developed easy-to-use comprehensive nomograms utilizing readily available clinical biomarkers related to inflammation, nutrition and immunity, offering modestly enhanced predictive value for treatment outcomes in corticosteroid-treated patients with AECOPD. Further investigations into novel biomarkers and additional patient data are imperative to optimize the predictive performance.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:17 |
|---|---|
| Enthalten in: |
Journal of inflammation research - 17(2024) vom: 23., Seite 1511-1526 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Feng, Lin [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Chronic obstructive pulmonary disease |
|---|
| Anmerkungen: |
Date Revised 14.03.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.2147/JIR.S450447 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM369661850 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM369661850 | ||
| 003 | DE-627 | ||
| 005 | 20240314235941.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240313s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.2147/JIR.S450447 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1329.xml |
| 035 | |a (DE-627)NLM369661850 | ||
| 035 | |a (NLM)38476472 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Feng, Lin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Comprehensive Nomograms Using Routine Biomarkers Beyond Eosinophil Levels |b Enhancing Predictability of Corticosteroid Treatment Outcomes in AECOPD |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 14.03.2024 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2024 Feng et al. | ||
| 520 | |a Purpose: Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) exhibit heterogeneous responses to corticosteroid treatment. We aimed to determine whether combining eosinophil levels with other routine clinical indicators can enhance the predictability of corticosteroid treatment outcomes and to come up with a scoring system | ||
| 520 | |a Patients and Methods: Consecutive patients admitted with AECOPD receiving corticosteroid treatment between July 2013 and March 2022 at Beijing Chao-Yang Hospital were retrospectively analyzed. Data on patients' demographics, smoking status, hospitalization for AECOPD in the previous year, comorbidities, blood laboratory tests, in-hospital treatment and clinical outcomes were collected. Least absolute shrinkage and selection operator (LASSO) regression and backward logistic regression were used for predictor selection, and predictive nomograms were developed. The discrimination and calibration of the nomograms were assessed using the area under the receiver operating curve (AUC) and calibration plots. Internal validation was performed using the 500-bootstrap method, and clinical utility was evaluated using decision curve analysis (DCA) | ||
| 520 | |a Results: Among the 3254 patients included, 804 (24.7%) had treatment failure. A nomogram of eosinophils, platelets, C-reactive protein (CRP), low density lipoprotein cholesterol, prognostic nutritional index (PNI), hospitalization for AECOPD in the previous year, ischemic heart diseases and chronic hepatic disease was developed to predict treatment failure for patients with a smoking history. For patients without a smoking history, a nomogram of CRP, PNI, ischemic heart diseases and chronic hepatic disease was developed. Although the AUCs of these two nomograms were only 0.644 and 0.647 respectively, they were significantly superior to predictions based solely on blood eosinophil levels | ||
| 520 | |a Conclusion: We developed easy-to-use comprehensive nomograms utilizing readily available clinical biomarkers related to inflammation, nutrition and immunity, offering modestly enhanced predictive value for treatment outcomes in corticosteroid-treated patients with AECOPD. Further investigations into novel biomarkers and additional patient data are imperative to optimize the predictive performance | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a chronic obstructive pulmonary disease | |
| 650 | 4 | |a glucocorticoids | |
| 650 | 4 | |a least absolute shrinkage and selection operator | |
| 650 | 4 | |a prediction model | |
| 700 | 1 | |a Li, Jiachen |e verfasserin |4 aut | |
| 700 | 1 | |a Qian, Zhenbei |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Chenglong |e verfasserin |4 aut | |
| 700 | 1 | |a Gao, Darui |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yongqian |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Wuxiang |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Yutong |e verfasserin |4 aut | |
| 700 | 1 | |a Tong, Zhaohui |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Lirong |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of inflammation research |d 2008 |g 17(2024) vom: 23., Seite 1511-1526 |w (DE-627)NLM197692524 |x 1178-7031 |7 nnns |
| 773 | 1 | 8 | |g volume:17 |g year:2024 |g day:23 |g pages:1511-1526 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.2147/JIR.S450447 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 17 |j 2024 |b 23 |h 1511-1526 | ||