Dataset Information

Enteropathy associated T cell lymphoma in celiac disease: a large retrospective study.

ABSTRACT:

Introduction

Prognosis of enteropathy-associated T cell lymphoma is poor but predictors of survival remain ill-defined. How clinical presentation, pathological features and therapies influence outcome was evaluated in 37 thoroughly characterized patients with celiac disease and T-cell lymphoma.

Patients and methods

Medical files were studied retrospectively. Lymphoma and intestinal mucosa were analysed by histopathology, multiplex PCR and intestinal intraepithelial lymphocytes phenotyping. Survival and prognostic factors were analysed using Kaplan-Meier curves with Logrank test and Cox Model.

Results

Lymphoma complicated non clonal enteropathy, celiac disease (n=15) and type I refractory celiac disease (n=2) in 17 patients and clonal type II refractory celiac disease in 20 patients. Twenty-five patients underwent surgery with resection of the main tumour mass in 22 cases. In univariate analysis, non clonal celiac disease, serum albumin level>21.6g/L at diagnosis, chemotherapy and surgical resection predicted good survival (p=0.0007, p<0.0001, p<0.0001, p<0.0001, respectively). In multivariate analysis, serum albumin level>21.6g/L, chemotherapy and reductive surgery were all significantly associated with increased survival (p<0.002, p<0.03, p<0.03, respectively).

Conclusions

Our study underlines the prognostic value of celiac disease type in patients with T-cell lymphoma, and suggests that a combination of nutritional, chemotherapy and reductive surgery may improve survival.

SUBMITTER: Malamut G

PROVIDER: S-EPMC7185558 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Publications

Enteropathy associated T cell lymphoma in celiac disease: a large retrospective study.

Malamut Georgia G Chandesris Olivia O Verkarre Virginie V Meresse Bertrand B Callens Céline C Macintyre Elizabeth E Bouhnik Yoram Y Gornet Jean-Marc JM Allez Matthieu M Jian Raymond R Berger Anne A Châtellier Gilles G Brousse Nicole N Hermine Olivier O Cerf-Bensussan Nadine N Cellier Christophe C

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver 20130110 5

<h4>Introduction</h4>Prognosis of enteropathy-associated T cell lymphoma is poor but predictors of survival remain ill-defined. How clinical presentation, pathological features and therapies influence outcome was evaluated in 37 thoroughly characterized patients with celiac disease and T-cell lymphoma.<h4>Patients and methods</h4>Medical files were studied retrospectively. Lymphoma and intestinal mucosa were analysed by histopathology, multiplex PCR and intestinal intraepithelial lymphocytes phe ...[more]

PMID: 23313469

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Project description:ImportanceDuodenal biopsies from children with enteropathies associated with undernutrition, such as environmental enteropathy (EE) and celiac disease (CD), display significant histopathological overlap.ObjectiveTo develop a convolutional neural network (CNN) to enhance the detection of pathologic morphological features in diseased vs healthy duodenal tissue.Design, setting, and participantsIn this prospective diagnostic study, a CNN consisting of 4 convolutions, 1 fully connected layer, and 1 softmax layer was trained on duodenal biopsy images. Data were provided by 3 sites: Aga Khan University Hospital, Karachi, Pakistan; University Teaching Hospital, Lusaka, Zambia; and University of Virginia, Charlottesville. Duodenal biopsy slides from 102 children (10 with EE from Aga Khan University Hospital, 16 with EE from University Teaching Hospital, 34 with CD from University of Virginia, and 42 with no disease from University of Virginia) were converted into 3118 images. The CNN was designed and analyzed at the University of Virginia. The data were collected, prepared, and analyzed between November 2017 and February 2018.Main outcomes and measuresClassification accuracy of the CNN per image and per case and incorrect classification rate identified by aggregated 10-fold cross-validation confusion/error matrices of CNN models.ResultsOverall, 102 children participated in this study, with a median (interquartile range) age of 31.0 (20.3-75.5) months and a roughly equal sex distribution, with 53 boys (51.9%). The model demonstrated 93.4% case-detection accuracy and had a false-negative rate of 2.4%. Confusion metrics indicated most incorrect classifications were between patients with CD and healthy patients. Feature map activations were visualized and learned distinctive patterns, including microlevel features in duodenal tissues, such as alterations in secretory cell populations.Conclusions and relevanceA machine learning-based histopathological analysis model demonstrating 93.4% classification accuracy was developed for identifying and differentiating between duodenal biopsies from children with EE and CD. The combination of the CNN with a deconvolutional network enabled feature recognition and highlighted secretory cells' role in the model's ability to differentiate between these histologically similar diseases.

Dataset Information

Enteropathy associated T cell lymphoma in celiac disease: a large retrospective study.

Introduction

Patients and methods

Results

Conclusions

Publications

Enteropathy associated T cell lymphoma in celiac disease: a large retrospective study.

Similar Datasets

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