Immune-related serious adverse events with immune checkpoint inhibitors: Systematic review and network meta-analysis.

PURPOSE: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, though uncertainty exists regarding their immune-related safety. The objective of this study was to assess the comparative safety profile (odds ratio) of ICIs and estimate the absolute rate of immune-related serious adverse events (irSAEs) in cancer patients undergoing treatment with ICIs. METHODS: We searched for randomized trials till February 2021, including all ICIs for all cancers. Primary outcome was overall irSAEs, and secondary outcomes were pneumonitis, colitis, hepatitis, hypophysitis, myocarditis, nephritis, and pancreatitis. We conducted Bayesian network meta-analyses, estimated absolute rates and ranked treatments according to the surface under the cumulative ranking curve (SUCRA). RESULTS: We included 96 trials (52,811 participants, median age 62 years). Risk of bias was high in most trials. Most cancers were non-small cell lung cancer (28 trials) and melanoma (15 trials). The worst-ranked ICI was ipilimumab (SUCRA 14%; event rate 848/10,000 patients) while the best-ranked ICI was atezolizumab (SUCRA 82%; event rate 119/10,000 patients). CONCLUSION: Each ICI showed a unique safety profile, with certain events more frequently observed with specific ICIs, which should be considered when managing cancer patients.

Partial replacement of mineral fertilisers with animal manures in an apple orchard: Effects on GHG emission.

Partial replacement of mineral fertilisers (MF) with animal manures is a good alternative to reduce MF use and increase both nutrient cycling in agriculture and soil organic matter. However, the adoption of this practice must not lead to increased environmental impacts. In this two-year study conducted in an apple orchard, MF were partially replaced with various animal manures, including cattle slurry (CS), acidified cattle slurry (ACS), solid cattle manure (CsM), or poultry manure (PM), and their impacts on greenhouse gas emission (GHG: CO2, N2O and CH4) were examined. A control (CTRL) receiving only MF served as the baseline, representing the conventional scenario in orchard fertilisation. Overall, replacing MF with manures increased GHG emissions, with the magnitude of the impacts depending on the specific characteristics of the manures and the amount of nutrients and organic matter applied. Comparing to the CTRL, application of ACS and CS led to higher CH4 and N2O emissions, while PM application increased both N2O and CO2 emissions. In contrast, replacement with PM and CsM decreased CH4 emissions. Nevertheless, results varied between the two years, influenced by several factors, including soil conditions. While acidification showed potential to mitigate CH4 emissions, it also led to increased N2O emissions compared to CS, particularly in 2022, suggesting the need for further investigation to avoid emission trade-offs. Replacement with CS (20.49 t CO2-eq ha-1) and CsM (20.30 t CO2-eq ha-1) showed comparable global warming potential (GWP) to the conventional scenario (CTRL, 19.49 t CO2-eq ha-1), highlighting their potential as viable MF substitutes.

Advancements in biliopancreatic endoscopy: a comprehensive review of artificial intelligence in EUS and ERCP.

The development and implementation of artificial intelligence (AI), particularly deep learning (DL) models, has generated significant interest across various fields of gastroenterology. While research in luminal endoscopy has seen rapid translation to clinical practice with approved AI devices, its potential extends far beyond, offering promising benefits for biliopancreatic endoscopy like optical characterization of strictures during cholangioscopy or detection and classification of pancreatic lesions during diagnostic endoscopic ultrasound (EUS). This narrative review provides an up-to-date of the latest literature and available studies in this field. Serving as a comprehensive guide to the current landscape of AI in biliopancreatic endoscopy, emphasizing technological advancements, main applications, ethical considerations, and future directions for research and clinical implementation.

Paraneoplastic or treatment-associated dermatomyositis: a diagnostic challenge.

Dermatomyositis (DM) is a systemic autoimmune disorder characterized by proximal myopathy and dermatological findings. Approximately 15-30% of DM cases emerge as a paraneoplastic syndrome caused by a concomitant malignancy. Although more rare, in cancer patients DM has also been reported as a possible result of toxicity of some antineoplastic agents, such as taxanes and monoclonal antibodies. Herein, we report a 35-year-old woman with metastatic breast cancer who presented with skin lesions after initiation of paclitaxel and anti-HER2 agents. Clinical, laboratory, and histological findings were consistent with the diagnosis of DM.

Deep-Learning and Device-Assisted Enteroscopy: Automatic Panendoscopic Detection of Ulcers and Erosions.

Background and Objectives: Device-assisted enteroscopy (DAE) has a significant role in approaching enteric lesions. Endoscopic observation of ulcers or erosions is frequent and can be associated with many nosological entities, namely Crohn's disease. Although the application of artificial intelligence (AI) is growing exponentially in various imaged-based gastroenterology procedures, there is still a lack of evidence of the AI technical feasibility and clinical applicability of DAE. This study aimed to develop and test a multi-brand convolutional neural network (CNN)-based algorithm for automatically detecting ulcers and erosions in DAE. Materials and Methods: A unicentric retrospective study was conducted for the development of a CNN, based on a total of 250 DAE exams. A total of 6772 images were used, of which 678 were considered ulcers or erosions after double-validation. Data were divided into a training and a validation set, the latter being used for the performance assessment of the model. Our primary outcome measures were sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and an area under the curve precision-recall curve (AUC-PR). Results: Sensitivity, specificity, PPV, and NPV were respectively 88.5%, 99.7%, 96.4%, and 98.9%. The algorithm's accuracy was 98.7%. The AUC-PR was 1.00. The CNN processed 293.6 frames per second, enabling AI live application in a real-life clinical setting in DAE. Conclusion: To the best of our knowledge, this is the first study regarding the automatic multi-brand panendoscopic detection of ulcers and erosions throughout the digestive tract during DAE, overcoming a relevant interoperability challenge. Our results highlight that using a CNN to detect this type of lesion is associated with high overall accuracy. The development of binary CNN for automatically detecting clinically relevant endoscopic findings and assessing endoscopic inflammatory activity are relevant steps toward AI application in digestive endoscopy, particularly for panendoscopic evaluation.

Design of a Convolutional Neural Network as a Deep Learning Tool for the Automatic Classification of Small-Bowel Cleansing in Capsule Endoscopy.

Background and objectives: Capsule endoscopy (CE) is a non-invasive method to inspect the small bowel that, like other enteroscopy methods, requires adequate small-bowel cleansing to obtain conclusive results. Artificial intelligence (AI) algorithms have been seen to offer important benefits in the field of medical imaging over recent years, particularly through the adaptation of convolutional neural networks (CNNs) to achieve more efficient image analysis. Here, we aimed to develop a deep learning model that uses a CNN to automatically classify the quality of intestinal preparation in CE. Methods: A CNN was designed based on 12,950 CE images obtained at two clinical centers in Porto (Portugal). The quality of the intestinal preparation was classified for each image as: excellent, ≥90% of the image surface with visible mucosa; satisfactory, 50-90% of the mucosa visible; and unsatisfactory, <50% of the mucosa visible. The total set of images was divided in an 80:20 ratio to establish training and validation datasets, respectively. The CNN prediction was compared with the classification established by consensus of a group of three experts in CE, currently considered the gold standard to evaluate cleanliness. Subsequently, how the CNN performed in diagnostic terms was evaluated using an independent validation dataset. Results: Among the images obtained, 3633 were designated as unsatisfactory preparation, 6005 satisfactory preparation, and 3312 with excellent preparation. When differentiating the classes of small-bowel preparation, the algorithm developed here achieved an overall accuracy of 92.1%, with a sensitivity of 88.4%, a specificity of 93.6%, a positive predictive value of 88.5%, and a negative predictive value of 93.4%. The area under the curve for the detection of excellent, satisfactory, and unsatisfactory classes was 0.98, 0.95, and 0.99, respectively. Conclusions: A CNN-based tool was developed to automatically classify small-bowel preparation for CE, and it was seen to accurately classify intestinal preparation for CE. The development of such a system could enhance the reproducibility of the scales used for such purposes.

Closed-incision negative-pressure wound therapy (ciNPWT) to minimize wound-related complications in lower limb reconstruction after bone tumor resection: preliminary proof-of-concept study.

AIMS: The purpose of this study was to compare the impact of postoperative closed-incision negative-pressure wound therapy (ciNPWT) and conventional dressings in wound-related complications after bone tumor resection and reconstruction. PATIENTS AND METHODS: A total of 50 patients with bone tumors and clinical indication for wide resection and reconstruction were included and divided into two groups (A and B). Bone defect reconstructions were achieved with modular endoprosthesis or biologic techniques, mainly involving allografts with free vascularized fibula. Group A received ciNPWT, and Group B conventional dressings. Wound-related complications, including wound dehiscence, persistent wound leakage, surgical site infections (SSIs), and causes for surgical revision, were assessed. RESULTS: Nineteen patients were included in Group A and 31 in Group B. No significant differences were found between groups regarding epidemiologic and clinical presentation features, contrarily to reconstructive options, which were significantly different between both (Fisher = 10,100; p = 0.005). Additionally, Group A presented lower wound dehiscence rate (0 vs. 19.4%; χ2(1) = 4.179; p = 0.041), SSI rate (0 vs. 19.4%; χ2(1) = 4.179; p = 0.041), and surgical revision rate (5.3% vs. 32.3%; χ2(1) = 5.003; p = 0.025) compared to Group B. CONCLUSIONS: This is the first study reporting the impact of ciNPWT after bone tumor resection and reconstruction, and its results support a potential role for this technique in diminishing postoperative wound complications and SSIs. A multicentric randomized controlled trial may help clarify the role and impact of ciNPWT after bone tumor resection and reconstruction.

Azacitidine-induced massive pericardial effusion in a child with myelodysplastic syndrome.

INTRODUCTION: Pericardial effusions are rare yet potentially fatal conditions in children. Azacitidine is a DNA-hypomethylating agent used in the treatment of myelodysplastic syndrome. Although seldomly described in adults, no cases of azacitidine-induced pericardial effusion have been reported in children. CASE REPORT: A 7-year-old boy with myelodysplastic syndrome presented with a large pericardial effusion with risk for cardiac tamponade after his first azacitidine cycle. MANAGEMENT & OUTCOME: The patient was admitted to a pediatric ICU, antibiotic and steroid therapy were initiated. Pericardiocentesis was done due to hemodynamic instability. Serum and pericardial fluid complementary evaluation excluded infectious and malignant causes. The pericardial effusion did not reappear and additional pleural and ascitic slight effusions responded well to diuretics. Follow-up azacitidine cycles were administered by tapering daily dosages and using adjunctive steroid therapy, with no additional adverse events. DISCUSSION: We report the first pediatric case of large pericardial effusion secondary to azacitidine therapy in a child with MDS. This adverse reaction has not been described in pediatric patients, in which this therapeutic option has been increasingly used. We seek to raise awareness on the potential life-threatening cardiotoxicity of azacitidine in pediatric patients.

Genomic Profiling of Sarcomas: A Promising Weapon in the Therapeutic Arsenal.

Sarcomas are rare malignant mesenchymal neoplasms, and the knowledge of tumor biology and genomics is scarce. Chemotherapy is the standard of care in advanced disease, with poor outcomes. Identifying actionable genomic alterations may offer effective salvage therapeutic options when previous lines have failed. Here, we report a retrospective cohort study of sarcoma patients followed at our center and submitted to comprehensive genomic profiling between January 2020 and June 2021. Thirty patients were included, most (96.7%) with reportable genomic alterations. The most common alterations were linked to cell cycle regulation (TP53, CDKN2A/B, and RB1 deletions and CDK4, MDM2, and MYC amplifications). Most patients (96.7%) had microsatellite stability and low tumor mutational burden (≤10 muts/megabase (Mb); median 2 Muts/Mb). Two-thirds of patients had actionable mutations for targeted treatments, including five cases with alterations amenable to targeted therapies with clinical benefit within the patient's tumor type, ten cases with targetable alterations with clinical benefit in other tumor types, and five cases with alterations amenable to targeting with drugs under investigation in a clinical trial setting. A significant proportion of cases in this study had actionable genomic alterations with available targeted drugs. Next-generation sequencing is a feasible option for identifying molecular drivers that can provide therapeutic options for individual patients. Molecular Tumor Boards should be implemented in the clinical practice to discuss genomic findings and inform clinically relevant targeted therapies.

On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping.

Soft tissue sarcomas (STS) prognosis is disappointing, with current treatment strategies being based on a "fit for all" principle and not taking distinct sarcoma subtypes specificities and genetic/metabolic differences into consideration. The paucity of precision therapies in STS reflects the shortage of studies that seek to decipher the sarcomagenesis mechanisms. There is an urge to improve STS diagnosis precision, refine STS classification criteria, and increase the capability of identifying STS prognostic biomarkers. Single-omics and multi-omics studies may play a key role on decodifying sarcomagenesis. Metabolomics provides a singular insight, either as a single-omics approach or as part of a multi-omics strategy, into the metabolic adaptations that support sarcomagenesis. Although STS metabolome is scarcely characterized, untargeted and targeted metabolomics approaches employing different data acquisition methods such as mass spectrometry (MS), MS imaging, and nuclear magnetic resonance (NMR) spectroscopy provided important information, warranting further studies. New chromatographic, MS, NMR-based, and flow cytometry-based methods will offer opportunities to therapeutically target metabolic pathways and to monitorize the response to such metabolic targeting therapies. Here we provide a comprehensive review of STS omics applications, comprising a detailed analysis of studies focused on the metabolic landscape of these tumors.

Toxic erythema of chemotherapy induced by liposomal doxorubicin, a clinical case.

A 76-year-old woman presented to the medical oncology outpatient clinic with painful, burning, pruritic erythematous plaques involving both palms and axillae that had suddenly appeared five days before. Examination revealed no additional relevant findings and laboratory studies did not show any alteration. The patient had been recently diagnosed with a high-grade angiosarcoma of the breast (probably radiation induced) and after frequent local recurrences, was being treated with liposomal doxorubicin (three cycles were administered, the last of which was seven days before the appearance of the mentioned lesions). Oral corticosteroids were started, treatment with liposomal doxorubicin was stopped, and cutaneous biopsies performed that revealed features compatible with toxic erythema of chemotherapy induced by liposomal doxorubicin. Complete resolution of the cutaneous lesions was verified one month after. No signs of recurrence of angiosarcoma were documented at follow-up three months later.

Humoral Immune Response of SARS-CoV-2-Infected Patients with Cancer: Influencing Factors and Mechanisms.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients with cancer show worse outcomes compared with patients without cancer. The humoral immune response (HIR) of patients with cancer against SARS-CoV-2 is not well characterized. To better understand it, we conducted a serological study of hospitalized patients with cancer infected with SARS-CoV-2. MATERIALS AND METHODS: This was a unicentric, retrospective study enrolling adult patients with SARS-CoV-2 admitted to a central hospital from March 15 to June 17, 2020, whose serum samples were quantified for anti-SARS-CoV-2 receptor-binding domain or spike protein IgM, IgG, and IgA antibodies. The aims of the study were to assess the HIR to SARS-CoV-2; correlate it with different cancer types, stages, and treatments; clarify the interplay between the HIR and clinical outcomes of patients with cancer; and compare the HIR of SARS-CoV-2-infected patients with and without cancer. RESULTS: We included 72 SARS-CoV-2-positive subjects (19 with cancer, 53 controls). About 90% of controls revealed a robust serological response. Among patients with cancer, a strong response was verified in 57.9%, with 42.1% showing a persistently weak response. Treatment with chemotherapy within 14 days before positivity was the only factor statistically shown to be associated with persistently weak serological responses among patients with cancer. No significant differences in outcomes were observed between patients with strong and weak responses. All IgG, IgM, IgA, and total Ig antibody titers were significantly lower in patients with cancer compared with those without. CONCLUSION: A significant portion of patients with cancer develop a proper HIR. Recent chemotherapy treatment may be associated with weak serological responses among patients with cancer. Patients with cancer have a weaker SARS-CoV-2 antibody response compared with those without cancer. IMPLICATIONS FOR PRACTICE: These results place the spotlight on patients with cancer, particularly those actively treated with chemotherapy. These patients may potentially be more vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, so it is important to provide oncologists further theoretical support (with concrete examples and respective mechanistic correlations) for the decision of starting, maintaining, or stopping antineoplastic treatments (particularly chemotherapy) not only on noninfected but also on infected patients with cancer in accordance with cancer type, stage and prognosis, treatment agents, treatment setting, and SARS-CoV-2 infection risks.

Endoscopic submucosal dissection (ESD): how do Western endoscopists value animal models?

INTRODUCTION: Endoscopic Submucosal Dissection (ESD)was introduced in the West later than in the East. Our aim was to assess how Western endoscopists performing ESD have been trained and how they value animal models for training. MATERIAL AND METHODS: An online survey regarding training in ESD was sent to Western endoscopists who published articles on advanced resection techniques. RESULTS: From 279 endoscopists, 58 (21%) completed the questionnaire, of which 50 confirmed performance of clinical ESD. Endoscopists had a median of 15 years of endoscopic experience (IQR 9.75-20.25) and all of them were performing conventional EMR, before starting ESD. Prior to clinical ESD, 74% (n = 37) underwent training with ex vivo models, 84% (n = 42) with live animal models and 92% (n = 46) with at least, one of the two models. After starting clinical ESD, as trainers, 52% (n = 26) were involved with ex vivo and 60% (n = 30) with live animal models. Personal usefulness of ex vivo and live animal models was rated with a median of 9 (IQR 8-10) and 10 (IQR 8-10), out of 10, respectively. Courses with ex vivo and live animal models were considered a prerequisite before clinical practice by 84% (n = 42) and 78% (n = 39), respectively. CONCLUSIONS: Western endoscopists have extensive endoscopic experience before starting ESD. The majority had pre-clinical training with ex vivo and live animal models and more than half are acting as trainers of other endoscopists with these models. Animal models are considered very useful and deemed a prerequisite before clinical practice by the majority of the endoscopists.

Diaphragmatic eventration as a first sign of Scimitar syndrome.

Diaphragmatic eventration is an anomaly of the diaphragm. In Scimitar syndrome, a curved-shaped anomalous pulmonary venous drainage is seen. Association between these conditions is rare. We present a newborn with diaphragmatic eventration, whose diagnosis of Scimitar syndrome was made after surgical repair. Scimitar syndrome is a congenital disorder often associated with other heart and lungs anomalies. Diagnosis can be fortuitous but with important prognostic features.

Osteosarcoma Pathogenesis Leads the Way to New Target Treatments.

Osteosarcoma (OS) is a rare condition with very poor prognosis in a metastatic setting. Basic research has enabled a better understanding of OS pathogenesis and the discovery of new potential therapeutic targets. Phase I and II clinical trials are already ongoing, with some promising results for these patients. This article reviews OS pathogenesis and new potential therapeutic targets.

Löfgren Syndrome: A Mosaic of Sarcoidosis Phenotypes.

Sarcoidosis is an autoimmune multisystemic granulomatous disease with an unknown etiology. Löfgren syndrome (LS), an infrequent initial presentation of acute sarcoidosis, is characterized by the classic triad of acute arthritis, erythema nodosum (EN), and bilateral hilar lymphadenopathy (BHL). The presence of this triad offers high diagnostic specificity for sarcoidosis, eliminating the need for a confirmatory biopsy. Typically, LS follows a predictable, self-limiting clinical course. However, atypical presentations require early suspicion and closer monitoring. This case report highlights an unusual clinical manifestation of LS, marked by an incomplete presentation with acute panniculitis and joint lesions in the absence of EN. Acute sarcoidosis should be considered among the differential diagnoses when these clinical manifestations are present, and chest radiography should be performed to rule out BHL. In atypical cases, the disease course becomes less predictable, as exemplified in our case, where recurrence of the disease may occur, necessitating consistent monitoring.

Revolutionizing Women's Health: A Comprehensive Review of Artificial Intelligence Advancements in Gynecology.

Artificial intelligence has yielded remarkably promising results in several medical fields, namely those with a strong imaging component. Gynecology relies heavily on imaging since it offers useful visual data on the female reproductive system, leading to a deeper understanding of pathophysiological concepts. The applicability of artificial intelligence technologies has not been as noticeable in gynecologic imaging as in other medical fields so far. However, due to growing interest in this area, some studies have been performed with exciting results. From urogynecology to oncology, artificial intelligence algorithms, particularly machine learning and deep learning, have shown huge potential to revolutionize the overall healthcare experience for women's reproductive health. In this review, we aim to establish the current status of AI in gynecology, the upcoming developments in this area, and discuss the challenges facing its clinical implementation, namely the technological and ethical concerns for technology development, implementation, and accountability.

Artificial Intelligence and Panendoscopy-Automatic Detection of Clinically Relevant Lesions in Multibrand Device-Assisted Enteroscopy.

Device-assisted enteroscopy (DAE) is capable of evaluating the entire gastrointestinal tract, identifying multiple lesions. Nevertheless, DAE's diagnostic yield is suboptimal. Convolutional neural networks (CNN) are multi-layer architecture artificial intelligence models suitable for image analysis, but there is a lack of studies about their application in DAE. Our group aimed to develop a multidevice CNN for panendoscopic detection of clinically relevant lesions during DAE. In total, 338 exams performed in two specialized centers were retrospectively evaluated, with 152 single-balloon enteroscopies (Fujifilm®, Porto, Portugal), 172 double-balloon enteroscopies (Olympus®, Porto, Portugal) and 14 motorized spiral enteroscopies (Olympus®, Porto, Portugal); then, 40,655 images were divided in a training dataset (90% of the images, n = 36,599) and testing dataset (10% of the images, n = 4066) used to evaluate the model. The CNN's output was compared to an expert consensus classification. The model was evaluated by its sensitivity, specificity, positive (PPV) and negative predictive values (NPV), accuracy and area under the precision recall curve (AUC-PR). The CNN had an 88.9% sensitivity, 98.9% specificity, 95.8% PPV, 97.1% NPV, 96.8% accuracy and an AUC-PR of 0.97. Our group developed the first multidevice CNN for panendoscopic detection of clinically relevant lesions during DAE. The development of accurate deep learning models is of utmost importance for increasing the diagnostic yield of DAE-based panendoscopy.

Deep learning and capsule endoscopy: Automatic multi-brand and multi-device panendoscopic detection of vascular lesions.

Background and study aims Capsule endoscopy (CE) is commonly used as the initial exam for suspected mid-gastrointestinal bleeding after normal upper and lower endoscopy. Although the assessment of the small bowel is the primary focus of CE, detecting upstream or downstream vascular lesions may also be clinically significant. This study aimed to develop and test a convolutional neural network (CNN)-based model for panendoscopic automatic detection of vascular lesions during CE. Patients and methods A multicentric AI model development study was based on 1022 CE exams. Our group used 34655 frames from seven types of CE devices, of which 11091 were considered to have vascular lesions (angiectasia or varices) after triple validation. We divided data into a training and a validation set, and the latter was used to evaluate the model's performance. At the time of division, all frames from a given patient were assigned to the same dataset. Our primary outcome measures were sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and an area under the precision-recall curve (AUC-PR). Results Sensitivity and specificity were 86.4% and 98.3%, respectively. PPV was 95.2%, while the NPV was 95.0%. Overall accuracy was 95.0%. The AUC-PR value was 0.96. The CNN processed 115 frames per second. Conclusions This is the first proof-of-concept artificial intelligence deep learning model developed for pan-endoscopic automatic detection of vascular lesions during CE. The diagnostic performance of this CNN in multi-brand devices addresses an essential issue of technological interoperability, allowing it to be replicated in multiple technological settings.