Evidence map›Paper›PMID 32270860›Full record

ArticleBioscience reports2020

Early differential diagnosis model for acute radiation pneumonitis based on multiple parameters.

Zhiwu Wang, Qiong Wu, Liang Dong, Haoyu Fu, Qiwei Liu

Abstract read
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Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zhiwu WangDepartment of Chemoradiotherapy, Tangshan People's Hospital, Tangshan, P.R. China.
Qiong WuDepartment of Chemoradiotherapy, Tangshan People's Hospital, Tangshan, P.R. China.
Liang DongDepartment of Chemoradiotherapy, Tangshan People's Hospital, Tangshan, P.R. China.
Haoyu FuDepartment of Chemoradiotherapy, Tangshan People's Hospital, Tangshan, P.R. China.
Qiwei LiuNuclear Medicine Laboratory, Tangshan People's Hospital, Tangshan, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe present study aimed to construct a diagnosis model for the early differentiation of acute radiation pneumonitis (ARP) and infectious pneumonitis based on multiple parameters.

methodsThe present study included data of 152 patients admitted to the Department of Radiochemotherapy, Tangshan People's Hospital, who developed ARP (91 patients) or infectious pneumonia (IP; 61 patients) after radiotherapy. The radiophysical parameters, imaging characteristics, serological indicators, and other data were collected as independent variables, and ARP was considered as a dependent variable. Logistics univariate analysis and Spearman correlation analysis were used for selecting independent variables. Logistics multivariate analysis was used to fit the variables into the regression model to predict ARP.

resultsThe univariate analysis showed that the positional relation between lesions and V20 area (PRLV), procalcitonin (PCT), C-reactive protein (CRP), mean lung dose (MLD), and lung volume receiving ≥20 Gy (V20) correlated with ARP while the planning target volume (PTV) dose marginally correlated with ARP. The multivariate analysis showed that the PRLV, PCT, white blood cell (WBC), and MLD were independent diagnostic factors. The nomogram was drawn on the basis of the logistics regression model. The area under the curve (AUC) of the model was 0.849, which was significantly better than that of a single indicator and the sensitivity and specificity of the model were high (82.4 and 82.0%, respectively). These results predicted by the model were highly consistent with the actual diagnostic results. The decision curve analysis (DCA) demonstrated a satisfactory positive net benefit of the model.

conclusionThe diagnosis model constructed in the present study is of certain value for the differential diagnosis of ARP and IP.

Indexed as

NomogramsAdultAgedAged, 80 and overC-Reactive ProteinDiagnosis, DifferentialFeasibility StudiesFemaleHumansLeukocyte CountLungLung NeoplasmsMaleMiddle AgedPneumoniaProcalcitoninC-Reactive ProteinProcalcitoninDiagnosis modeldifferential diagnosisinfectious pneumoniaradiation pneumonitisradiotherapy

Identifiers

PMID32270860
PMCPMC7167249

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.