Dataset Information

Prediction of Anthracofibrosis Based on Clinico-Radiographic Findings.

ABSTRACT:

Purpose

Because anthracofibrosis (AF) is associated with tuberculosis (TB), detection of AF is clinically relevant in Korea, a TB endemic region. We thus sought to develop and validate a predictive model for AF using clinical radiographic data.

Materials and methods

Between January 1, 2008 and March 31, 2014, 3849 adult patients who underwent bronchoscopies were retrospectively included from an observational registry. We dichotomized patients based on the presence (n=167) or absence (n=242) of AF. After analyzing their clinico-radiographic characteristics, a logistic prediction model was developed. An area under the curve (AUC) was drawn using the weighted score in logistic regression model. To evaluate the degree of overfitting of the predictive model, a 5-fold cross-validation procedure was performed.

Results

In multivariate logistic regression, clinical findings such as age >70 years, female gender, active TB, and computed tomography findings including atelectasis, stenosis, bronchial wall thickening, enlarged and calcified lymph nodes were significant diagnostic predictors for AF. The weighed score had an AUC of 0.939 [95% confidence interval (CI)=0.911-0.960], similar to the AUC obtained from internal validation (AUC=0.926, 95% CI=0.896-0.949).

Conclusion

The prediction model may be helpful for predicting AF based only on clinical and radiographic findings. However, further external validation is necessary.

SUBMITTER: Park TY

PROVIDER: S-EPMC5290015 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Publications

Prediction of Anthracofibrosis Based on Clinico-Radiographic Findings.

Park Tae Yun TY Heo Eun Young EY Chung Hee Soon HS Jin Kwang Nam KN Kim Deog Kyeom DK

Yonsei medical journal 20170301 2

<h4>Purpose</h4>Because anthracofibrosis (AF) is associated with tuberculosis (TB), detection of AF is clinically relevant in Korea, a TB endemic region. We thus sought to develop and validate a predictive model for AF using clinical radiographic data.<h4>Materials and methods</h4>Between January 1, 2008 and March 31, 2014, 3849 adult patients who underwent bronchoscopies were retrospectively included from an observational registry. We dichotomized patients based on the presence (n=167) or absen ...[more]

PMID: 28120566

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Project description:BackgroundNeurofibroma occurs as isolated or multiple lesions frequently associated with neurofibromatosis type 1 (NF1), a common autosomal dominant disorder affecting 1 in 3500 individuals. It is caused by mutations in the NF1 gene, which comprises 60 exons and is located on chromosome 17q11.2. NF1 is a fully penetrant gene exhibiting a mutation rate some 10-fold higher compared with most other disease genes. As a consequence, a high number of cases (up to 50%) are sporadic. Mutation detection is complex due to the large size of the NF1 gene, the presence of pseudogenes and the great variety of lesions.Methods110 patients with at least two neurofibroma lesions recorded in the files of the Pathology Department of the University of Modena during the period 1999-2010, were included in this study. Through interviews and examination of clinical charts, pedigrees were drawn for all patients who were affected by at least two neurofibromas. We attempted to delineate the clinical features of NF1 and the mutational spectrum in the cohort of 11 NF1 families identified. For each proband, the whole coding sequence and all splice sites were studied for mutations, either by the protein truncation test (PTT), or, more frequently, by denaturing high performance liquid chromatography (DHPLC). Two GIST tumors of NF1 patients were tested for somatic NF1 mutations.ResultsNF1 germline mutations were identified in 7 (68%) patients. A novel mutation, c.3457_3460delCTCA in exon 20, was detected in two unrelated patients and was associated with different clinical features. No NF1 somatic mutations were detected in the GIST tumors. A wide phenotypic and genotypic variability was registered, both in the spectrum of skin lesions and visceral neoplasms, even among members of the same family who had different clinical manifestations. A proclivity to multiple tumors arising in the same subject, and a higher tumor burden per family were the most relevant findings observed in patients affected with the NF1 mutation.ConclusionsWe report a novel NF1 mutation and we contribute data for the refinement of the NF1 genotype-phenotype spectrum.

Dataset Information

Prediction of Anthracofibrosis Based on Clinico-Radiographic Findings.

Purpose

Materials and methods

Results

Conclusion

Publications

Prediction of Anthracofibrosis Based on Clinico-Radiographic Findings.

Similar Datasets

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