Histological Hyperspectral Glioblastoma Dataset (HistologyHSI-GB).

Hyperspectral (HS) imaging (HSI) technology combines the main features of two existing technologies: imaging and spectroscopy. This allows to analyse simultaneously the morphological and chemical attributes of the objects captured by a HS camera. In recent years, the use of HSI provides valuable insights into the interaction between light and biological tissues, and makes it possible to detect patterns, cells, or biomarkers, thus, being able to identify diseases. This work presents the HistologyHSI-GB dataset, which contains 469 HS images from 13 patients diagnosed with brain tumours, specifically glioblastoma. The slides were stained with haematoxylin and eosin (H&E) and captured using a microscope at 20× power magnification. Skilled histopathologists diagnosed the slides and provided image-level annotations. The dataset was acquired using custom HSI instrumentation, consisting of a microscope equipped with an HS camera covering the spectral range from 400 to 1000 nm.

Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection.

Brain surgery is one of the most common and effective treatments for brain tumour. However, neurosurgeons face the challenge of determining the boundaries of the tumour to achieve maximum resection, while avoiding damage to normal tissue that may cause neurological sequelae to patients. Hyperspectral (HS) imaging (HSI) has shown remarkable results as a diagnostic tool for tumour detection in different medical applications. In this work, we demonstrate, with a robust k-fold cross-validation approach, that HSI combined with the proposed processing framework is a promising intraoperative tool for in-vivo identification and delineation of brain tumours, including both primary (high-grade and low-grade) and secondary tumours. Analysis of the in-vivo brain database, consisting of 61 HS images from 34 different patients, achieve a highest median macro F1-Score result of 70.2 ± 7.9% on the test set using both spectral and spatial information. Here, we provide a benchmark based on machine learning for further developments in the field of in-vivo brain tumour detection and delineation using hyperspectral imaging to be used as a real-time decision support tool during neurosurgical workflows.

Neural Networks-Based On-Site Dermatologic Diagnosis through Hyperspectral Epidermal Images.

Cancer originates from the uncontrolled growth of healthy cells into a mass. Chromophores, such as hemoglobin and melanin, characterize skin spectral properties, allowing the classification of lesions into different etiologies. Hyperspectral imaging systems gather skin-reflected and transmitted light into several wavelength ranges of the electromagnetic spectrum, enabling potential skin-lesion differentiation through machine learning algorithms. Challenged by data availability and tiny inter and intra-tumoral variability, here we introduce a pipeline based on deep neural networks to diagnose hyperspectral skin cancer images, targeting a handheld device equipped with a low-power graphical processing unit for routine clinical testing. Enhanced by data augmentation, transfer learning, and hyperparameter tuning, the proposed architectures aim to meet and improve the well-known dermatologist-level detection performances concerning both benign-malignant and multiclass classification tasks, being able to diagnose hyperspectral data considering real-time constraints. Experiments show 87% sensitivity and 88% specificity for benign-malignant classification and specificity above 80% for the multiclass scenario. AUC measurements suggest classification performance improvement above 90% with adequate thresholding. Concerning binary segmentation, we measured skin DICE and IOU higher than 90%. We estimated 1.21 s, at most, consuming 5 Watts to segment the epidermal lesions with the U-Net++ architecture, meeting the imposed time limit. Hence, we can diagnose hyperspectral epidermal data assuming real-time constraints.

Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.

In recent years, researchers designed several artificial intelligence solutions for healthcare applications, which usually evolved into functional solutions for clinical practice. Furthermore, deep learning (DL) methods are well-suited to process the broad amounts of data acquired by wearable devices, smartphones, and other sensors employed in different medical domains. Conceived to serve the role of diagnostic tool and surgical guidance, hyperspectral images emerged as a non-contact, non-ionizing, and label-free technology. However, the lack of large datasets to efficiently train the models limits DL applications in the medical field. Hence, its usage with hyperspectral images is still at an early stage. We propose a deep convolutional generative adversarial network to generate synthetic hyperspectral images of epidermal lesions, targeting skin cancer diagnosis, and overcome small-sized datasets challenges to train DL architectures. Experimental results show the effectiveness of the proposed framework, capable of generating synthetic data to train DL classifiers.

Endoscopy-Related Bleeding and Thromboembolic Events in Patients on Direct Oral Anticoagulants or Vitamin K Antagonists.

BACKGROUND & AIMS: Few prospective studies have assessed the safety of direct oral anticoagulants (DOACs) in elective endoscopy. Our primary aim was to compare the risks of endoscopy-related gastrointestinal bleeding and thromboembolic events in patients on DOACs or vitamin K antagonists (VKAs) in this setting. Secondarily, we examined the impact of the timing of anticoagulant resumption on the risk of delayed bleeding in high-risk therapeutic procedures. METHODS: We conducted a multicenter, prospective, observational study from January 2018 to March 2020 of 1602 patients on oral anticoagulants (1004 on VKAs and 598 on DOACs) undergoing 1874 elective endoscopic procedures. Our primary outcomes were 90-day thromboembolic events and 30-day endoscopy-related gastrointestinal bleeding. The inverse probability of treatment weighting propensity score method was used for baseline covariate adjustment. RESULTS: The 2 groups had similar risks of endoscopy-related gastrointestinal bleeding (VKAs vs DOACs, 6.2% vs 6.7%; adjusted odds ratio [OR], 1.05; 95% CI, 0.67-1.65) and thromboembolic events (VKAs vs DOACs, 1.3% vs 1.5%; adjusted OR, 0.90; 95% CI, 0.34-2.38). In high bleeding risk procedures (n = 747), delayed anticoagulant resumption (> 48 hours or 24-48 hours vs < 24 hours) did not reduce the risk of postprocedural bleeding (10.3%, 9%, and 5.8%, respectively; adjusted P = .43). Hot and cold snare polypectomy were the most frequent high-risk interventions (41.8% and 39.8%, respectively). CONCLUSION: In a prospective study of patients on DOACs or VKAs undergoing elective endoscopy, endoscopy-related bleeding and thromboembolic events showed similar risk. Our study suggests that early anticoagulant resumption is safe in most patients, but more data are needed for advanced high-risk therapeutic procedures.

Characteristics and outcome of incidental hepatocellular carcinoma after liver transplantation: a cohort study.

INTRODUCTION: despite advances in imaging diagnostic modalities, hepatocellular carcinoma is sometimes incidentally diagnosed on histological examination of the liver explant. The objectives of the study were: a) to compare the characteristics between incidental and known hepatocellular carcinoma; and b) to estimate survival and tumor recurrence after liver transplantation. MATERIAL AND METHODS: a retrospective, single-center study was performed. The inclusion criteria were: a) cirrhotic patients, age ≥ 18 years; b) liver transplantation between 1998 and 2018; and c) hepatocellular carcinoma diagnosed via histopathologic examination of the explanted liver. Cholangiocarcinoma and patients with early retransplantation were excluded. Multivariate analysis was performed using binomial logistic regression to assess the factors associated with incidental hepatocellular carcinoma. Kaplan-Meier curves were plotted to explore the impact on overall survival and recurrence free survival. RESULTS: two hundred and sixty-nine patients were enrolled. The prevalence of incidental hepatocellular carcinoma was 4.18 % (95 % CI: 2.89-6.01 %) of all liver transplants performed in cirrhotic patients. The median diameter of the main nodule was smaller in incidental hepatocellular carcinoma (20 vs 27 mm, p = 0.004), although they were more likely to be beyond the Up-to-Seven criteria on explant examination (22.2 % vs 7.5 %, p = 0.001), with no differences in any other histological features. No differences were found in overall survival rates (incidental 70.2 % vs 70.4 %, p = 0.87) or recurrence-free survival (incidental 100 % vs 83.8 %, p = 0.07) at five years. CONCLUSION: incidental hepatocellular carcinoma are smaller in size and are more frequently found to be beyond the Up-to-Seven criteria. However, no differences were found in overall survival rates or recurrence-free survival, although there was no tumor recurrence in the incidental hepatocellular carcinoma group.

VNIR-NIR hyperspectral imaging fusion targeting intraoperative brain cancer detection.

Currently, intraoperative guidance tools used for brain tumor resection assistance during surgery have several limitations. Hyperspectral (HS) imaging is arising as a novel imaging technique that could offer new capabilities to delineate brain tumor tissue in surgical-time. However, the HS acquisition systems have some limitations regarding spatial and spectral resolution depending on the spectral range to be captured. Image fusion techniques combine information from different sensors to obtain an HS cube with improved spatial and spectral resolution. This paper describes the contributions to HS image fusion using two push-broom HS cameras, covering the visual and near-infrared (VNIR) [400-1000 nm] and near-infrared (NIR) [900-1700 nm] spectral ranges, which are integrated into an intraoperative HS acquisition system developed to delineate brain tumor tissue during neurosurgical procedures. Both HS images were registered using intensity-based and feature-based techniques with different geometric transformations to perform the HS image fusion, obtaining an HS cube with wide spectral range [435-1638 nm]. Four HS datasets were captured to verify the image registration and the fusion process. Moreover, segmentation and classification methods were evaluated to compare the performance results between the use of the VNIR and NIR data, independently, with respect to the fused data. The results reveal that the proposed methodology for fusing VNIR-NIR data improves the classification results up to 21% of accuracy with respect to the use of each data modality independently, depending on the targeted classification problem.

Evaluación del disbalance autonómico en el paciente con serología positiva para enfermedad de Chagas: Score de diagnóstico y tratamiento

La enfermedad de Chagas es una enfermedad parasitaria (Trypanosoma cruzi), endémica en 21 países de América y que las migraciones la han dispersado en distintos continentes. Una de las manifestaciones más precoces de esta enfermedad son las alteraciones disautonómicas o disfunción autonómica. La severidad de este inadecuado funcionamiento del sistema nervioso autónomo resulta mensurable, de modo que la evolución y/o progresión de la enfermedad puede constatarse mediante la alteración de estudios clínicos y detección de anticuerpos antimuscarínicos. Estos anticuerpos están presentes en un 30% de los infectados y aparecen muy precozmente una vez instalada la parasitosis; además otros estudios, como la dispersión del QT (>65 mseg) y la variabilidad de la frecuencia cardíaca (<100 mseg) presentan valores anormales. La utilización de nuevos paradigmas de atención, diagnóstico y tratamientos adecuados son imprescindibles para prevenir el desarrollo de esta cardiopatía.

Chagas disease is a parasitic disease (Trypanosoma cruzi), endemic in 21 countries of America and that migrations have dispersed it in different continents. One of the earliest manifestations of this disease is dysautonomic alterations or autonomic dysfunction. The severity of this inadequate functioning of the autonomic nervous system is measurable, so that the evolution and/or progression of the disease can be verified by altering clinical studies and detecting antimuscarinic antibodies. These antibodies are present in 30% of those infected and appear very early once the parasitosis is installed; In addition, other studies, such as QT dispersion (> 65 ms) and heart rate variability (<100 ms) show abnormal values. The use of new paradigms of care, diagnosis and appropriate treatments are essential to prevent the development of this heart disease.

A doença de Chagas é uma doença parasitária (Trypanosoma cruzi), endêmica em 21 países da América e que as migrações a dispersaram em diferentes continentes. Uma das primeiras manifestações desta doença são as alterações disautonômicas ou disfunção autonômica. A gravidade desse funcionamento inadequado do sistema nervoso autônomo é mensurável, de modo que a evolução e/ou progressão da doença pode ser verificada alterando os estudos clínicos e detectando anticorpos antimuscarínicos. Esses anticorpos estão presentes em 30% dos infectados e aparecem muito cedo, uma vez instalada a parasitose; Além disso, outros estudos, como a dispersão do QT (> 65 mseg) e a variabilidade da freqüência cardíaca (<100 mseg), mostram valores anormais. A utilização de novos paradigmas de atendimento, diagnóstico e tratamentos adequados são essenciais para prevenir o desenvolvimento desta doença cardíaca.

Analysis of Risk Factors in Dementia Through Machine Learning.

BACKGROUND: Sociodemographic data indicate the progressive increase in life expectancy and the prevalence of Alzheimer's disease (AD). AD is raised as one of the greatest public health problems. Its etiology is twofold: on the one hand, non-modifiable factors and on the other, modifiable. OBJECTIVE: This study aims to develop a processing framework based on machine learning (ML) and optimization algorithms to study sociodemographic, clinical, and analytical variables, selecting the best combination among them for an accurate discrimination between controls and subjects with major neurocognitive disorder (MNCD). METHODS: This research is based on an observational-analytical design. Two research groups were established: MNCD group (n = 46) and control group (n = 38). ML and optimization algorithms were employed to automatically diagnose MNCD. RESULTS: Twelve out of 37 variables were identified in the validation set as the most relevant for MNCD diagnosis. Sensitivity of 100%and specificity of 71%were achieved using a Random Forest classifier. CONCLUSION: ML is a potential tool for automatic prediction of MNCD which can be applied to relatively small preclinical and clinical data sets. These results can be interpreted to support the influence of the environment on the development of AD.

Antitumor Necrosis Factor Agents to Treat Endoscopic Postoperative Recurrence of Crohn's Disease: A Nationwide Study With Propensity-Matched Score Analysis.

INTRODUCTION: Patients with Crohn's disease experiencing endoscopic postoperative recurrence (POR) may benefit from antitumor necrosis factor (TNF) agents but scarce data on this are available. Our aim was to assess the efficacy of anti-TNF in improving mucosal lesions in patients with endoscopic POR. METHODS: Multicenter, retrospective, study of patients with Crohn's disease who underwent therapy with anti-TNF agents for endoscopic POR (Rutgeerts score > i1). Treatment outcomes were assessed by the findings in the last ileocolonoscopy performed after anti-TNF therapy was initiated. Endoscopic improvement and remission were defined as any reduction in the baseline Rutgeerts score and by a Rutgeerts score < i2, respectively. RESULTS: A total of 179 patients were included, 83 were treated with infliximab and 96 with adalimumab. Median time on anti-TNF therapy at the last endoscopic assessment was 31 months (interquartile range, 13-54). Endoscopic improvement was observed in 61%, including 42% who achieved endoscopic remission. Concomitant use of thiopurines and treatment with infliximab were associated with endoscopic improvement (odds ratio [OR] 2.15, 95% confidence interval [CI] 1.04-4.46; P = 0.03, and OR 2.34, 95% CI 1.18-4.62; P < 0.01, respectively) and endoscopic remission (OR 3.16, 95% CI 1.65-6.05; P < 0.01, and OR 2.01, 95% CI 1.05-3.88; P = 0.04, respectively) in the multivariable logistic regression analysis. These results were confirmed in a propensity-matched score analysis. DISCUSSION: In patients with endoscopic POR, anti-TNF agents improve mucosal lesions in almost two-thirds of the patients. In this setting, concomitant use of thiopurines and use of infliximab seem to be more effective in improving mucosal lesions.

Non-Invasive Skin Cancer Diagnosis Using Hyperspectral Imaging for In-Situ Clinical Support.

Skin cancer is one of the most common forms of cancer worldwide and its early detection its key to achieve an effective treatment of the lesion. Commonly, skin cancer diagnosis is based on dermatologist expertise and pathological assessment of biopsies. Although there are diagnosis aid systems based on morphological processing algorithms using conventional imaging, currently, these systems have reached their limit and are not able to outperform dermatologists. In this sense, hyperspectral (HS) imaging (HSI) arises as a new non-invasive technology able to facilitate the detection and classification of pigmented skin lesions (PSLs), employing the spectral properties of the captured sample within and beyond the human eye capabilities. This paper presents a research carried out to develop a dermatological acquisition system based on HSI, employing 125 spectral bands captured between 450 and 950 nm. A database composed of 76 HS PSL images from 61 patients was obtained and labeled and classified into benign and malignant classes. A processing framework is proposed for the automatic identification and classification of the PSL based on a combination of unsupervised and supervised algorithms. Sensitivity and specificity results of 87.5% and 100%, respectively, were obtained in the discrimination of malignant and benign PSLs. This preliminary study demonstrates, as a proof-of-concept, the potential of HSI technology to assist dermatologists in the discrimination of benign and malignant PSLs during clinical routine practice using a real-time and non-invasive hand-held device.

The Intracellular Intensity of CD3 on Aberrant Intraepithelial Lymphocytes Is a Prognostic Factor of the Progression to Overt Lymphoma in Refractory Celiac Disease Type II (Pre-Enteropathy-Associated T Cell Lymphoma).

BACKGROUND: Refractory celiac disease type II (RCD-II) is a very rare yet severe complication of celiac disease (CD) with a 50% rate of progression to Enteropathy-associated T-cell lymphoma (EATL). Timely diagnosis and treatment of RCD-II is of the essence and requires the identification of a population of frequently clonal, phenotypically aberrant intraepithelial lymphocytes (IELs). Flow Cytometry of intestinal IELs is the recommended method to identify the aberrant surface CD3-negative (sCD3-) intracytoplasmic CD3-positive (icCD3ε+) IELs, and a proportion of >20% is diagnostic of RCD-II. There is substantial heterogeneity in the clinical course of RCD-II, and insufficient information on prognostic factors. AIM: To establish flow cytometric predictors of the clinical evolution of RCD-II, to help guide treatment approaches. PATIENTS AND METHODS: Retrospective single-center study of clinical and immunological features of 6 RCD-II patients and a control group, both identified from a 2,000-patient cohort over 16 years. IEL subset frequencies and the intensity of staining for surface (s) and intracytoplasmic (ic) CD3ε+ on IEL subsets were quantified and correlated with the clinical outcome. RESULTS: Unexpectedly, the frequency of aberrant sCD3- icCD3ε+ cells at diagnosis did not correlate with histological or clinical affection. However, a higher intensity of icCD3ε+ staining in the aberrant IELs relative to expression on normal IELs correlated with monoclonality and with worse clinical outcomes. CONCLUSION: The ratio of icCD3ε+ on aberrant IELs vs. normal IELs appears to be a useful indicator of prognosis at the time of diagnosis, and may represent a novel tool in the follow-up of RCD-II patients after therapy.

Clinical validation of Endofaster® for a rapid diagnosis of Helicobacter pylori infection.

BACKGROUND: this study aimed to evaluate the diagnostic accuracy of the Endofaster® for the detection of Helicobacter pylori. METHODS: during upper gastrointestinal endoscopy, gastric juice was aspirated to perform an analysis using the Endofaster®. This test was considered as positive when the ammonium concentration was > 67 ppm, negative when < 57 ppm and weakly positive between 57 and 67. Biopsy specimens were also taken as the gold standard. RESULTS: among the 86 patients enrolled in the study, the Endofaster® result was positive in 23.7%, negative in 54.7% and weakly positive in 11.6%, whereas infection was detected via histology in 38.4% of patients. The accuracy was 81.4%, with a Kappa value of 0.57. CONCLUSIONS: the Endofaster® could be useful to perform a rapid diagnosis of Helicobacter pylori infection (area under the curve = 0.81).

Most Relevant Spectral Bands Identification for Brain Cancer Detection Using Hyperspectral Imaging.

Hyperspectral imaging (HSI) is a non-ionizing and non-contact imaging technique capable of obtaining more information than conventional RGB (red green blue) imaging. In the medical field, HSI has commonly been investigated due to its great potential for diagnostic and surgical guidance purposes. However, the large amount of information provided by HSI normally contains redundant or non-relevant information, and it is extremely important to identify the most relevant wavelengths for a certain application in order to improve the accuracy of the predictions and reduce the execution time of the classification algorithm. Additionally, some wavelengths can contain noise and removing such bands can improve the classification stage. The work presented in this paper aims to identify such relevant spectral ranges in the visual-and-near-infrared (VNIR) region for an accurate detection of brain cancer using in vivo hyperspectral images. A methodology based on optimization algorithms has been proposed for this task, identifying the relevant wavelengths to achieve the best accuracy in the classification results obtained by a supervised classifier (support vector machines), and employing the lowest possible number of spectral bands. The results demonstrate that the proposed methodology based on the genetic algorithm optimization slightly improves the accuracy of the tumor identification in ~5%, using only 48 bands, with respect to the reference results obtained with 128 bands, offering the possibility of developing customized acquisition sensors that could provide real-time HS imaging. The most relevant spectral ranges found comprise between 440.5-465.96 nm, 498.71-509.62 nm, 556.91-575.1 nm, 593.29-615.12 nm, 636.94-666.05 nm, 698.79-731.53 nm and 884.32-902.51 nm.

A multicentric Spanish study on the characteristics and survival of gastric adenocarcinoma under the age of 60.

INTRODUCTION: In Europe, gastric adenocarcinoma (GADC) is commonly regarded as a disease of the elderly. This study aims to assess the proportion, characteristics, and survival of patients diagnosed with GADC under the age of 60. MATERIALS AND METHODS: This is a retrospective, multicentric, and analytical study conducted at four tertiary Spanish hospitals. All patients diagnosed with GADC between 2008 and 2015 were included. Demographic, clinical, endoscopic, histologic, and survival data were retrieved. A multivariate analysis was performed to compare GADC in young (age≤60 years) and elderly patients. RESULTS: A total of 1374 patients with GADC were included. The mean age was 74 years (SD:11.1); 62.2% were males. There were 177 patients under the age of 60 (12.9%, 95% CI: 11.2-14.8%). GADC was frequently encountered as a metastatic disease in both young and elderly patients (Stage IV: 45.7% and 41%, respectively). In the multivariate analysis, alcohol abuse, ASA functional status I-II, diffuse subtype, neoadjuvant, and palliative therapy were independently associated (P<0.05) with age ≤60 years. No differences were found in 2-year survival (GADC ≤60: 39% vs. 35%, P=0.45). Curative-intent surgery, TNM stage I-II, body mass index<30kg/m2, and better functional status at diagnosis were independent predictors of survival in GADC under the age of 60. CONCLUSIONS: One out of eight cases of GADC were diagnosed under the age of 60. Metastatic disease was frequent at diagnosis and overall survival was poor regardless of age. Factors associated with localized disease correlated with improved survival in younger patients. Our results underline the need for early diagnosis strategies in our country.

Genetic and flow cytometry analysis of seronegative celiac disease: a cohort study.

Background: Seronegative celiac disease (CD) poses a diagnostic challenge. Aims: Characterize and identify differences between seronegative and seropositive CD. Patients and methods: Retrospective cohort study examining adult patients diagnosed with CD (1980-2017). Clinical, analytical, histological, genetic and immunophenotypic data were compiled. Seronegative CD was defined as a anti-tissue transglutaminase type 2 IgA and endomysial antibodies (EMA) negative and HLA-DQ2 and/or DQ8 positive, showing clinical signs of CD plus an abnormal duodenal biopsy, and responding to a gluten-free diet (GFD). Factors associated with seronegative CD were identified through binomial logistic regression. Results: Of 315 CD patients, 289 were seropositive (91.7%) and 26 seronegative (8.3%). Among the seronegative patients, higher prevalence was observed for autoimmune thyroiditis (26.9% vs. 9.7%, p = .016), HLA-DQ8 heterozygosity (23.1% vs. 2.5%, p ˂ .001) and Marsh I lesion (34.6% vs. 3.7%, p ˂ .001). The two groups showed similar flow cytometry-determined duodenal immunophenotypes and rates of refractory CD. Conclusions: Seronegative CD differs mostly in genetic (more HLA-DQ8) and histologic (milder atrophy) features as compared with seropositive. Intestinal intraepithelial immunophenotype by flow cytometry, similar in both modalities, is a useful tool to diagnose seronegative CD.

Adalimumab or Infliximab for the Prevention of Early Postoperative Recurrence of Crohn Disease: Results From the ENEIDA Registry.

BACKGROUND: Anti-tumor necrosis factor agents (anti-TNFs) are efficacious at preventing the postoperative recurrence (POR) of Crohn disease, as demonstrated in 2 randomized controlled trials. However, real-life data for infliximab or adalimumab in this setting are scarce. Our aim was to assess both the efficiency of anti-TNFs at preventing early POR of Crohn disease in clinical practice and the associated risk factors for POR. METHODS: Patients in whom anti-TNFs were prescribed for the prevention of POR within 3 months after ileocolonic resection and who had an endoscopic assessment within 18 months were identified from the ENEIDA registry. Clinical and endoscopic features were collected within 18 months after surgery. RESULTS: In total, 152 patients were included (55 treated with infliximab, 97 with adalimumab, and 39% with concomitant immunosuppressants). Anti-TNF treatment was started after a median time of 29 days (IQR 13-44) after surgery. Eighty-two percent of patients had at least one risk factor for POR, and 82% had been exposed to anti-TNFs before the index surgery. Overall, 34% had endoscopic POR (as defined using a Rutgeerts endoscopic score > i1); 14% had advanced endoscopic POR (>i2); and 20% had clinical POR, with no differences between infliximab and adalimumab. In the multivariate analysis, only perianal disease (odds ratio 2.73, 95% confidence interval [CI] 1.26-5.91) and rectal involvement (odds ratio 2.79, 95% CI 1.09-7.14) were independent predictors of endoscopic POR. CONCLUSIONS: In clinical practice, anti-TNFs for the prevention of POR of Crohn disease are frequently used in patients experienced with anti-TNFs and with concomitant immunosuppressants. The efficacy of infliximab and adalimumab for POR prevention is similar and in accordance with the results obtained in randomized controlled trials.

Characteristics and consequences of missed gastric cancer: A multicentric cohort study.

BACKGROUND: Missed gastric cancer (MGC) is poorly documented in Mediterranean populations. AIMS: (1) To assess the rate, predictors and survival of MGC. (2) To compare MGC and non-MGC tumors. METHODS: This is a retrospective-cohort study conducted at four centers. MGC was defined as cancer detected within three years after negative esophagogastroduodenoscopy. Gastric adenocarcinomas diagnosed between 2008-2015 were included. Patients with no follow-up were excluded. RESULTS: During the study period 123,395 esophagogastroduodenoscopies were performed, with 1374 gastric cancers being diagnosed (1.1%). A total of 1289 gastric cancers were finally included. The overall rate of MGC was 4.7% (61/1289, 3.7-6%). A negative esophagogastroduodenoscopy in MGC patients was independently associated with PPI therapy (p < 0.001), previous Billroth II anastomosis (p = 0.002), and lack of alarm symptoms (p < 0.001). The most frequent location for MGC was the gastric body(52.4%). MGCs were smaller than non-MGCs (31 vs 41 mm, p = 0.047), more often flat or depressed (p = 0.003) and less likely to be encountered as advanced disease. Overall 2-year survival was similar between MGC (34.1%) and Non-MGC (35.3 %) (p = 0.59). CONCLUSION: MGC accounted for nearly five percent of newly-diagnosed gastric adenocarcinomas. Overall survival was poor and not different between MGC and non-MGC.