Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammography. We developed and tested an AI model for localizing and characterizing microcalcifications.Three expert radiologists annotated a dataset of mammograms using histology-based ground truth. The dataset was partitioned for training, validation, and testing. Three neural networks  were trained and evaluated using specific metrics including receiver operating characteristics area under the curve (AUC), sensitivity, and specificity. The reported metrics were computed on the test set (10% of the whole dataset).The dataset included 1,000 patients aged 21–73 years and 1,986 mammograms , with 389 malignant and 611 benign groups of microcalcifications. AlexNet achieved the best performance with 0.98 sensitivity, 0.89 specificity of, and 0.98 AUC for microcalcifications detection and 0.85 sensitivity, 0.89 specificity, and 0.94 AUC of for microcalcifications classification. For microcalcifications detection, ResNet18 and ResNet34 achieved 0.96 and 0.97 sensitivity, 0.91 and 0.90 specificity and 0.98 and 0.98 AUC, retrospectively. For microcalcifications classification, ResNet18 and ResNet34 exhibited 0.75 and 0.84 sensitivity, 0.85 and 0.84 specificity, and 0.88 and 0.92 AUC, respectively.The developed AI models accurately detect and characterize microcalcifications on mammography.AI-based systems have the potential to assist radiologists in interpreting microcalcifications on mammograms. The study highlights the importance of developing reliable deep learning models possibly applied to breast cancer screening.• A novel AI tool was developed and tested to aid radiologists in the interpretation of mammography by accurately detecting and characterizing microcalcifications.• Three neural networks  were trained, validated, and tested using an annotated dataset of 1,000 patients and 1,986 mammograms.• The AI tool demonstrated high accuracy in detecting/localizing and characterizing microcalcifications on mammography, highlighting the potential of AI-based systems to assist radiologists in the interpretation of mammograms.The online version contains supplementary material available at 10.1186/s41747-023-00384-3. Breast cancer is the most diagnosed cancer among women worldwide, and early detection is crucial for successful treatment and higher survival rate . AlthougThe introduction of artificial intelligence (AI) in medical image analysis has brought forth a potential revolution in computer-based interpretation of mammography , 5, 7.AI introduction implies technological, ethical, and legal considerations  and different patient’s perspectives on AI integration, ranging from cautious support to concerns about overreliance and potential loss of human interaction , 8. HoweMammography provides a rich domain for scalable clinical AI application. Several studies are currently evaluating how and when AI will be successfully used in clinical practice –14. PartTherefore, the development of a standardized, observer-independent microcalcifications detection and categorization system is warranted. Once trained, the tool can then analyze new mammograms, accurately detect and classify microcalcifications, providing radiologists with a second opinion to improve diagnostic accuracy.Task 1, to detect and localize suspicious microcalcifications in digital mammographyTask 2, to accurately classify microcalcifications into benign or malignant categoriesIn this context, our study aims to develop a deep DL-based network, with the following aims:The Institutional Review Board of the European Institute of Oncology (IEO) approved this study: protocol UID 3052 and date of approval 7 October 2021.The dataset was collected at a single institution, which is an academic hospital and referral centre for breast cancer care. All patients had an interval of less than 1 month between vacuum-assisted breast biopsy and the diagnostic mammography.The patient selection criteria included individuals who had undergone and subsequently had diagnostic mammography performed within an interval of less than 1 month.The dataset contained a total of 1,986 mammography images from 1,000 patients with age 45 ± 10 years (mean ± standard deviation), ranging 21–73 years, including 611 benign lesions and 389 histologically proven breast cancers. Accordingly, the pathological analysis through needle biopsy or surgery was the ground truth reference standard of the microcalcifications included in the region of interest (ROI). To be representative of the population that the model will be applied to, we selected heterogeneous data of patients including women with different breast densities — according to the American College of Radiology (ACR) classification  — medicaEach mammography image in the dataset was meticulously annotated by three expert radiologists from the breast imaging department of a national referral centre for breast cancer care . These aData collection: Two radiologists retrospectively collected cases from a pool of patients who meet the inclusion criteria, namely mammography exams performed at a single institute  containing microcalcifications for which the histology result was available.Anonymization: The selected images, in DICOM format, were made completely anonymous during the extraction phase.Annotation: Three expert radiologists annotated the selected cases. During the annotation phase, the radiologists used a special application made available by Laife Reply, namely the X-RAIS tagging tool , which mAnalysis of annotated data: Data scientists verified the consistency of the annotations made on the images for the purposes of DL algorithm training.Networks training and evaluation: Using the annotated data, the data scientists trained convolutional neural networks (CNNs) to analyze mammographic images towards the two aims of the study.The workflow of the study included the following five different phases, as shown in the flowchart Fig. :Data colThe dataset contains 1,986 full-field digital mammograms, with resolutions variable from 1,912 × 2,294 to 4,700 × 5,800 and a depth of 12 bit. Since the annotated images were too large to be used in their original size, a patch approach was used . The ratThe ROI was then saved and considered from this moment on a patch of “microcalcifications” that, depending on the annotation, could be benign or malignant. Supplementary Fig. SFor the extraction of “non-microcalcifications” patches, the same images are reused, but a different extraction criterion was applied, aimed at obtaining a set composed only of tissue patches without microcalcifications. To guarantee the heterogeneity of the dataset, the number of non-microcalcifications patches to be extracted is similar to the number of microcalcifications patches.To extract non-microcalcifications patches, a point of the image is randomly chosen, and an area of interest of 112 × 112 pixel is built around it. The patch's inclusion is contingent upon satisfying two criteria: first, an average color intensity surpassing a specified threshold (implemented to prevent the extraction of patches unrelated to the tissue); second, avoidance of overlap with annotated regions.At the end of the dataset creation procedure, we obtained the following: 24,237 patches with microcalcifications  and 9,648 non-microcalcifications patches.The dataset was partitioned by assigning 70% of the patches to the training set, 20% to the validation set, and 10% to the test set. Particularly, after splitting, we obtained the following:versus non-microcalcifications)Train split, 23,730 patches, 71% microcalcifications and 29% non-microcalcificationsValidation split, 6,789 patches, 71% microcalcifications and 29% non-microcalcificationsTest split, 3,393 patches, 71% microcalcifications and 29% non-microcalcificationsTask 1 Train split, 16,977 patches, 52% benign and 48% malignantValidation split, 4,859 patches, 53% benign and 47% malignantTest split: 24,26 patches, 54% benign and 46% malignantTask 2  into different subsets. This division of patches aimed to eliminate any possibility of artificially inflated performance by guaranteeing that no identical image regions were utilized across training, validation, and testing sets.After a review of the state of the art , 27–29, Task 1, classification of patches containing microcalcifications or not containing microcalcificationsversus malignant microcalcifications patchesTask 2, classification of benign As reported before, the two tasks of this study are as follows:The training data used in Task 2 is therefore limited to microcalcifications patches only, while training data used in Task 1 includes also non-microcalcifications patches. Accordingly, the localization of microcalcifications was performed through a classification network, whose input is patches extracted from the original image following a sliding window approach. Finally, the dataset underwent pre-processing operations  which allowed obtaining better results.Hyperparameter tuning was performed on each neural network, alongside with early stopping to avoid overfitting. Particularly, following rigorous evaluation, all proposed models were trained from the ground up, employing a cross-entropy loss function, the Adam optimizer, a batch size of 16, and a learning rate of 0.0001.To evaluate the interpretability, we performed a visual assessment of the heatmaps generated from the individual patches. The generation of heatmaps in this study involved a multistep process. Initially, the entire mammogram was partitioned into nonoverlapping patches using a sliding window technique. Each patch was then individually processed through the trained model, which assigned a probability value representing the likelihood of that patch containing microcalcifications. Subsequently, a grid was constructed, where each cell of the grid corresponded to a specific patch and contained the probability associated with the presence of microcalcifications. By the end of the processing, this grid served as a mask, which was superimposed on the mammogram to create a heatmap. The heatmap visually represented the regions with the highest probabilities, indicated as hot patches, suggesting the areas that are most likely to contain microcalcifications. This technique provided a valuable tool for enhancing the interpretability and localization of microcalcifications within the mammogram, facilitating the identification and analysis of potential breast abnormalities. Figure We evaluated the diagnostic performances of DL-based networks using various metrics, including positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity, diagnostic accuracy, and area under the curve at receiver operating characteristics (AUC). Descriptive statistics were computed to summarize the age distribution of the patient population.x is the metric and n is the size of the test set and then rounded.Model metrics are reported with 95% confidence intervals (CIs) computed using the following formula:We assessed the normality assumption of the age variable using the Shapiro–Wilk test. Calculations were performed using a specifically created Python script.The dataset contained a total of 1,986 mammography images from 1,000 patients with age 45 ± 10 years (mean ± standard deviation), ranging 21–73 years. Mammographic breast parenchymal density was categorized as almost entirely fat (ACR category A) in 180 (18%), scattered fibroglandular tissue (ACR category B) in 220 (22%), heterogeneously dense (ACR category C) in 380 (38%), and extremely dense (ACR category D) in 220 (22%) patients. Patient’s medical histories also vary, with 350 (35%) patients having a family history of breast cancer, 110 (11%) patients with previous personal history of breast cancer, 120 (12%) patients had previous breast biopsies, and 75 (7.5%) had previous radiation therapy for breast cancer Table Table Figure In addition, Fig. In this study, we evaluated the performance of CCNs in a dataset that included 1,986 mammography images from 1,000 patients, reflecting diverse demographics. The CCNs results showed AlexNet excelled in detecting and localizing microcalcifications for accuracy, AUC, sensitivity, and NPV, while ResNet18 performed best in specificity and PPV. In the characterization of microcalcifications, AlexNet again led in accuracy and AUC. These findings indicate that AI models can be trained to successfully diagnose malignant microcalcifications and identify mammograms devoid of microcalcifications.Radiologists are already familiar with computer-aided detection systems, which were first introduced in the 1960s for mammography . HoweverIn mammography, DL models can be trained on a large dataset of images, including those with microcalcifications, to learn patterns and features that are characteristic of benign and malignant microcalcifications. However, there is a lack of standardized approaches for data collection, annotation, and evaluation. This hinders the comparability of results from different studies and makes it challenging to establish a consensus on best practices. Our study contributes by following a well-defined workflow for data collection, annotation, and evaluation, ensuring robustness and reproducibility of the results. It was conducted in a cancer referral centre by radiologists with high experience in breast cancer indeed, which ensures that the tool was developed in a context of expert knowledge and clinical expertise. This also increases the likelihood that the tool will be applicable and relevant to real-world clinical practice. While AI models have shown promising results in research settings, their integration into real-world clinical practice poses practical challenges indeed. Implementing AI tools effectively requires seamless integration with existing clinical workflows and regulatory approval, as well as demonstrating their clinical utility.One of the major challenges with AI models in mammography is the lack of interpretability and transparency in their decision-making process as CNNs often act as a “black box”, making it difficult to understand the features or patterns they use to arrive at a diagnosis . Our stuMoreover, we tested the DL networks in a heterogeneous database of population, which increases the generalizability of the results. By including a diverse population, the tool’s ability to detect and classify microcalcifications in a wide range of breast tissue types and patient demographics can be evaluated, providing a more comprehensive assessment of its effectiveness.Regarding the results of our study, high sensitivity and specificity were observed for Task 1 and Task 2, confirming that the proposed CNNs correctly detect and classify microcalcifications, without showing imbalances towards one of the two tasks. Among the three different networks, AlexNet obtained the best results for Task 1 and Task 2  and tasks do not always coincide. However, a few similar studies are reported which allow for a comparison with our results. Cai et al.  used a sOur DL-based tool has some limitations, especially for implementing it in clinical practice.The first limitation is the limited size of the data. This study shows preliminary data, and the number of mammographic images analyzed is constantly increasing to better train AI networks. In the next phase, the amount of data for training, as well as for testing, will be expanded to achieve a higher accuracy. The retrospective testing on internal or external datasets was essential for assessing our new AI tool for clinical imaging . It is pi.e., with a lack of diversity of age or of breast density) and therefore lack the ability to generalize [In the next steps, external testing will limit bias and will also allow for the comparison of multiple algorithms with similar applications . There ineralize . Accordineralize .Another limitation for implementation in clinical practice is that our AI networks are focused on microcalcifications only, while in clinical practice, when reading mammography, the radiologist considers different aspects in addition to microcalcifications, like radiopacities and architectural distortions. Moreover, radiologists rely heavily on the comparison against the contralateral and the prior breast image during their exam interpretation, while current AI networks are not capable of comparing images across time . AdditioFinally, we recognize that a more in-depth analysis of misclassified clusters could provide deeper insights into the model’s weaknesses and potential areas for improvement. The exploration of misclassified areas, as shown in Fig. Despite such limitations, our study contributes to the field of breast cancer diagnosis by evaluating the performance of AI-based neural networks in accurately detecting, localizing, and characterizing microcalcifications on mammography. While there have been previous studies on computer-aided detection systems in mammography , 29, 32,Firstly, we employed advanced DL models, specifically AlexNet, ResNet 18, and ResNet34, which have demonstrated excellent performance in various computer vision tasks. These models were trained on a large dataset of mammography images with microcalcifications, to capture the patterns and features indicative of both benign and malignant microcalcifications. By utilizing these state-of-the-art DL models, our study represents a significant advancement in the application of AI for breast cancer diagnosis. Secondly, we conducted our study in a real-world clinical setting, involving experienced radiologists with high expertise in breast cancer . This enIn conclusion, the current study demonstrates the potential of a DL-based tool to automate detection and discrimination of breast microcalcifications on mammography. The tool achieved high levels of accuracy, sensitivity, and specificity, indicating its potential for clinical use. Once validated, the proposed tool can significantly reduce the time and variability associated with traditional detection and discrimination of microcalcifications, leading to earlier diagnosis and treatment. Finally, this study holds significant implications for improving breast cancer diagnosis and has the potential to enhance the accuracy and efficiency of screening programs, ultimately leading to better patient outcomes. However, further development is required, and additional research is needed to validate the proposed tool on larger datasets and to evaluate its clinical utility.Additional file 1: Supplementary Fig. S1. Example of benign microcalcifications. Cranio-caudal (a) and medio-lateral (b) mammograms show benign microcalcifications (arrows) in the upper-external quadrant of the left breast of a 54 years-old woman. Supplementary Fig. S2. Example of malignant microcalcifications. Cranio-caudal (a) and medio-lateral (b) mammograms show suspicious microcalcifications (arrows) in the lower-external quadrant of the right breast of a 60 years-old woman. A vacuum-assisted breast biopsy was performed under stereotactic guidance and the histological exam results were invasive ductal carcinoma.


Despite causing high morbidity, IgG4-related disease (IgG4-RD) and its gastroenterological manifestations lack better and greater theoretical contributions. Therefore, the objective of this work was to evaluate the clinical–epidemiological, diagnostic and treatment aspects of the gastrointestinal manifestations of this disease. A systematic review was carried out using the PubMed, Scopus and Embase databases between January 2012 and March 2023 with the following descriptors: “Immunoglobulin G4-Related Disease” (MeSH) AND #2 “Gastrointestinal Tract” (MeSH). Our data collection grouped a total of 3607 patients from mostly epidemiological cohort studies and cross-sectional follow-ups. In the subgroup analysis, IgG4-RD was associated with male gender, with an estimated prevalence between 54% and 80%. In our findings, the prevalence by topography was presented in the following ranges: lacrimal glands (17–57%); salivary glands (28–72%); pancreas (19–60%); biliary tract (5–40%); retroperitoneal cavity (9–43%). Longitudinal studies are needed to better map the natural history of the gastrointestinal manifestations of IgG4-RD and enable the formulation of individualized treatments. Immunoglobulin G subclass 4-related disease (IgG4-RD) is a chronic, multisystemic, idiopathic disease characterized by a lymphoplasmacytic inflammatory process that leads to fibrosis of organs and systems. Historically, IgG4-RD was described as a heterogeneous set of diseases with an emphasis on gastrointestinal involvement, especially pancreatitis. Its characterization came from histopathological and immunological studies and mapping of the response to immunosuppressive agents ,2,3.Due to the heterogeneous clinical spectrum of gastroenterological manifestations of IgG4-RD, the diagnosis is challenging, requiring a correlation between clinical, laboratory and imaging aspects ,6. This Despite the high morbidity  and the A qualitative systematic review of the literature was conducted following the PRISMA protocol. Electronic databases including PubMed, Scopus, ScienceDirect (Elsevier) and the Virtual Health Library (VHL) were searched using the following strategy: #1 “Immunoglobulin G4-Related Disease” (MeSH) AND #2 “Gastrointestinal Tract” (MeSH) between January 2012 and June 2023. The year 2012 was chosen as the starting point because it marked the publication of the disease description.The study was carried out with the acronym PICOS, with “P” being patients with IgG4-RD, “I” being the clinical–epidemiological characterization of the gastrointestinal manifestations of IgG4-RD, “C” being the healthy control group and “O” being the outcomes of the gastrointestinal manifestations of IgG4-RD.Data collection took place in June 2023. The articles were pre-analyzed from their titles and abstracts. Two researchers collected data individually, with a third senior researcher responsible for evaluating discrepancies and doubts. After this selection, each article was read in full. The most relevant data from each article are given in https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools, accessed on 15 June 2023) created by the National Heart, Lung and Blood Institute (NHLB) was used. Cohort studies were evaluated using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies and case–control studies were evaluated using the Quality Assessment of Case–Control Studies. These tools classify studies as “good”, “fair” or “poor” based on the presence or absence of relevant methodological elements for each type of study.To analyze the quality of each study, for the convenience of the authors, the Study Quality Assessment tool (n > 100); and prevalence of the topography of involvement due to IgG4-RD. Review articles, brief comments, editorials, communications and letters to the editor were excluded.Articles in English, Portuguese and Spanish that were original, complete and related to the subject of the study were selected. Inclusion criteria considered suitability for the purpose of this review; availability and transparency of data; methodological rigor applied with an emphasis on clinical, comparative and observational studies; number of participants greater than one hundred  dismissed the requirement for approval from a Human Research Ethics Committee.Initially, 1211 articles were identified in the databases searched . After exclusion by title and abstract, 227 articles were selected for full-text analysis . In the Most (91.2%) of the sample comprised cohort studies, while the rest were case–control studies. As for the quality analysis, 41.66% were classified as good, 41.66% as fair and 16.68% as poor.For heuristic reasons, the data were divided as follows: “epidemiology of the gastrointestinal manifestations of IgG4-RD”, “clinical and diagnostic aspects of the gastrointestinal manifestations of IgG4-RD” and “therapeutic approach to the gastrointestinal manifestations of IgG4-RD”.According to our search strategy, 3607 patients had gastrointestinal manifestations of IgG4-RD, and the majority were Asian (mainly Japanese), with a follow-up period between 4 and 5 years of the disease. Survival rates ranged from 95.3% to 89.0% for 5 to 10 years of disease, respectively ,19,20. AThis fact is intriguing as it is not commonly observed in other autoimmune diseases such as systemic lupus erythematosus, rheumatoid arthritis, systemic sclerosis, autoimmune myopathies and sarcoidosis, among others. This could be interesting to consider in the clinical reasoning for the differential diagnoses between the gastrointestinal involvement of IgG4-RD and connective tissue diseases.Individuals affected by IgG4-RD often have other comorbidities, particularly type 2 diabetes mellitus and allergic diseases, such as rhinosinusitis, bronchial asthma and drug allergies . FurtherIgG4-RD is progressive, insidious leading to organ dysfunction or mass effects. It commonly affects glands , the biliary tract, retroperitoneum, lungs, aorta, kidneys, meninges and orbits, and the concomitant involvement of these structures is a strong indication of IgG4-RD . It is sThe main laboratory changes in IgG4-RD are 1) normocytic–normochromic anemia with eosinophilia; 2) increase in immunoglobulin levels such as IgG and IgG4, with 3) polyclonal peak in serum protein electrophoresis; (4) increase in C-reactive protein (CRP) and erythrocyte sedimentation volume; 5) when certain organs are affected, an increase in alkaline phosphatase, gamma-glutamyl transferase (in autoimmune pancreatitis and primary sclerosing cholangitis), salivary amylase (in parotitis) and complement consumption (C3 and C4) may be seen in renal dysfunction [ normocyt increase polyclon when cerHelicobacter pylori, Mycobacterium tuberculosis and Gram-negative bacteria) and immunological factors  that trigger an immune response at the expense of Th-2 lymphocytes, with an increase in interleukins (IL) such as IL-4, IL-5 and IL-13. This immune response is accompanied by the proliferation and maturation of eosinophils, the recruitment of macrophages and differentiation of B lymphocytes, the consumption of complement (C3 and C4) and the increased production of IgG4. The increase in IgG4 is also considered an epiphenomenon. Subsequently, tissue infiltration with lymphoplasmacytic infiltrate occurs, leading to tumors and/or tissue destruction [Regarding the pathophysiology of IgG4-RD, the most widely accepted theory is that there is a relationship between environmental factors . The major pancreatic manifestation of IgG4-RD is type 1 autoimmune pancreatitis (AIP). In type 1 AIP, the clinical manifestations can be acute (obstructive jaundice and/or pancreatic mass) or chronic . The differentiation between them is a challenge for three reasons: (i) imaging tests  may show similar characteristics, including parenchymal enlargement, sometimes resembling a sausage shape, peripancreatic edematous borders and narrowing of the main pancreatic duct without upstream dilation ; (ii) reThree aspects can be used to differentiate type 1 and 2 AIPs: (i) serological abnormalities; (ii) serum IgG4 levels; (iii) histopathological analysis. Histopathological analysis demonstrates a pattern of lymphoplasmacytic infiltration affecting the pancreatic tissue in a diffuse or irregular manner, storiform fibrosis and phlebitis obliterans. Finally, it is possible to observe an increase in serum levels of IgG4 in cases of 1 AIP ,25.Also known as immunoglobulin G4-related hepatobiliary disease, this condition manifests as glucocorticoid-responsive cholangitis of the extrahepatic and perihilar bile ducts, often associated with type 1 AIP. The symptomatology presents as jaundice, pruritus, weight loss and abdominal pain . HoweverThere is an elevation in serum markers of cholestasis, including alkaline phosphatase, gamma-glutamyl transferase and conjugated bilirubin. Histopathological criteria include lymphoplasmacellular infiltrates with more than 10 IgG4-positive plasma cells in the area visible under the microscope, storiform fibrosis and phlebitis obliterans. Minor criteria include eosinophilia and partial obliterative phlebitis .Cholangiographic characteristics are classified into five subtypes based on the involvement of the biliary tree: (i) inferior stenosis of the distal bile duct, (ii) segmental or (iii) diffuse intrahepatic stenosis, (iv) minor stenosis of the distal bile duct or (v) a combination of hilar and inferior stenoses of the distal bile duct or isolated hilar stenoses. The use of therapeutic response to corticosteroids as a diagnostic criterion is controversial . The CT Retroperitoneal fibrosis (RPF) is the process of fibro-inflammation in the peri-aortic and peri-iliac retroperitoneum . It is aRegarding renal involvement, the disease is manifested by typical clinical characteristics such as uremic syndrome or elevation of nitrogenous slags. In histopathological terms, there are lesions similar to tumors, dense infiltration with IgG4-positive plasmocytes and extensive fibrosis. In laboratory terms, it is important to highlight that it is the only manifestation of IgG4-RD that involves complement consumption (C3 and C4). This type of condition is usually related to diagnostic delays that allow the accumulation of involvement in additional organs and increase the risk of permanent damage to these organs ,18.Treatment for IgG4-RD depends on the degree of disease activity, the affected organs and the patient’s symptomatology. In the case of gastrointestinal symptoms, the therapy of choice is glucocorticoid, at a dose of 0.6 to 0.8 mg/kg per day orally for 1 month, aiming to induce remission. Then, the dose should be gradually reduced by 5 mg every 2 weeks, evaluating the disease activity clinically and through laboratory tests during follow-up .Glucocorticoid therapy proved to be the most effective for initial control of the disease, achieving response rates of 97–100%. However, there are not enough studies demonstrating its effectiveness as a maintenance treatment. Even so, about 33% of patients will relapse during weaning from corticosteroid therapy, requiring the reintroduction of the loading dose. There are no known effective means of preventing IgG4-RD relapse. There are recommendations for low-dose maintenance corticosteroid therapy that can last for several years, capable of reducing this chance from 58% to 23%. Furthermore, immunosuppressants can also be used, especially to induce remission in refractory cases, but the combined use with glucocorticoids is initially not a unanimous recommendation [2 of body surface area, weekly, for 4 weeks, followed by infusions every 2–3 months. Studies with immunosuppressants such as azathioprine (2–3 mg/Kg/day), mycophenolate mofetil (2–3 g/day), methotrexate (15–25 mg/week) and calcineurin inhibitors are insufficient. However, it is known that relapses are common when using these medications in medical practice [Currently, in patients with recurrent IgG4-RD, high-dose glucocorticoids can be used, followed or not by rituximab. This biologic is used at a dose of 375 mg/mexate 15– mg/week practice .In the case of involvement of the lacrimal and salivary glands in the head and neck region, treatment usually involves the use of glucocorticoids, such as prednisone. This medication is administered in gradually reduced doses over time, with the aim of reducing the inflammatory process and relieving symptoms. In some more severe cases or refractory to glucocorticoids, immunosuppressants such as azathioprine and rituximab may be used .In specific cases with obstruction of the lacrimal and salivary glands, additional procedures may be required to relieve the obstruction and restore glandular function. This may include performing endoscopic procedures, such as dilation or placement of prostheses, to open obstructed lacrimal or salivary pathways .For the treatment of involvement of the oral cavity, esophagus, stomach and intestines, glucocorticoids are also the first line of treatment. In more severe cases or when symptoms do not respond adequately to glucocorticoids, azathioprine and methotrexate may be considered. When there is an obstruction or stenosis of the digestive tract, it may be necessary to perform dilation or endoscopic clearance ,12.Type 1 AIP has a good response to initial glucocorticoid therapy, yet has high relapse rates. In addition to immunosuppressive therapy, the assessment of nutritional deficiencies is part of the approach, such as (i) liposoluble vitamins  and (ii) trace elements such as zinc, calcium and magnesium. Surgery is generally not indicated for patients with AIP, but may be considered when suspected pancreatic cancer cannot be excluded after diagnostic evaluation. It is important to remember that endocrine insufficiency or pancreatic duct stones may be present, reinforcing the need for longitudinal follow-up in these cases ,26.Involvement of the liver and biliary tract in IgG4-RD can lead to serious complications such as secondary sclerosing cholangitis (SSC). SSC treatment aims to control inflammation and prevent disease progression. The most commonly used medications are glucocorticoids, such as prednisone. In cases of recurrence or relapse, azathioprine, methotrexate or rituximab can be used. In severe cases of SSC with significant obstruction of the bile ducts, surgical intervention or endoscopic procedures to clear bile flow may be performed ,16,25.As in the other organs, in the retroperitoneum, glucocorticoids are first-line drugs followed by immunosuppressive therapy with azathioprine or rituximab in refractory or recurrent cases. A surgical approach or endoscopic procedures may be necessary in specific situations, such as when there is compression of adjacent structures or obstruction of vital organs such as post-renal acute kidney injury. These interventions are aimed at relieving the obstruction and restoring normal function ,17,25.In the analysis of subgroups, IgG4-RD was associated with the male gender with an estimated prevalence ranging from 54 to 80%, while only 20–42% of the involvements were related to females. These results strengthen the association, consistency and analogy to the Bradford–Hill criteria. The literature indicates male predominance in these manifestations, typically occurring between the ages of 50 and 80, except for head and neck involvement. The disease rarely begins before the age of 40, with less than 10% of cases occurring in this age group ,20,27.It is important to understand that most studies are retrospective and were conducted in Asian populations . TherefoRegarding the gastrointestinal manifestations of IgG4-RD, this review found that the most common involvement was observed in the lacrimal glands 17–57%) and salivary glands 28–72%), followed by pancreatic lesions (19–60%), the biliary tract (5–40%) and the retroperitoneum (9–43%). Most of these manifestations were diagnosed postoperatively as a presumed tumor ,26 Figu. Accordi8–72%, fo7% and saThe diagnosis is clinical , and tren > 100, papers with large samples are difficult because IgG4-RD is a rare rheumatic disease. Consequently, data analysis is limited in terms of natural history and treatment approach. In addition, the difficulty of conducting longitudinal and prospective studies should be emphasized.It must be taken into account that the samples in the studies are small . AlthougMore than half of IgG4-RD gastrointestinal manifestations occur in men around the fifth decade of life. The commonly affected organs are the head and neck glands, the pancreas and the hepatobiliary tract. The diagnosis is one of exclusion, with biopsy being the gold standard.There is still a scarcity in the literature to define a better immunosuppressive approach. As limitations of the present study, we can mention (i) the small number of selected articles and, consequently, of samples; (ii) the mostly Asian population; and (iii) data heterogeneity. However, it should be noted that these are elements inherent to the available literature. Thus, longitudinal studies are needed to better map the natural history of gastrointestinal manifestations of IgG4-RD and to allow the development of individualized treatments.


Streptococcus pneumoniae remains a leading cause of morbidity, mortality, and healthcare resource utilization (HRU) among children. This study quantified HRU and cost of acute otitis media (AOM), pneumonia, and invasive pneumococcal disease (IPD).The IBM MarketScan® Commercial Claims and Encounters and Multi-State Medicaid databases from 2014 to 2018 were analyzed. Children with AOM, all-cause pneumonia, or IPD episodes were identified using diagnosis codes in inpatient and outpatient claims. HRU and costs were described for each condition in the commercial and Medicaid-insured populations. National estimates of the number of episodes and total cost  for commercial and $184 (SD $1524) for Medicaid-insured children. A total of 619,876 and 531,095 all-cause pneumonia cases were identified among commercial and Medicaid-insured children, respectively. Mean cost per all-cause pneumonia episode was $2304  in the commercial and $1682  in the Medicaid-insured population. A total of 858 and 1130 IPD episodes were identified among commercial and Medicaid-insured children, respectively. Mean cost per IPD episode was $53,213  for commercial and $23,482  for the Medicaid-insured population. Nationally, there were over 15.8 million cases of AOM annually, with total estimated cost of $4.3 billion, over 1.5 million cases of pneumonia annually, with total cost of $3.6 billion, and about 2200 IPD episodes annually, for a cost of $98 million.The economic burden of AOM, pneumonia, and IPD among US children remains substantial. IPD and its manifestations were associated with higher HRU and costs per episode, compared to AOM and all-cause pneumonia. However, owing to their higher frequencies, AOM and all-cause pneumonia were the main contributors to the economic burden of pneumococcal disease nationally. Additional interventions, such as the development of pneumococcal conjugate vaccinees with sustained protection of existing vaccine type serotypes as well as broader inclusion of additional serotypes, are necessary to further reduce the burden of disease caused by these manifestations.The online version contains supplementary material available at 10.1186/s12913-023-09244-7. Streptococcus pneumoniae is a leading cause of morbidity, mortality, and healthcare resource utilization in children worldwide [S. pneumoniae from a normally sterile site , and has several manifestations, including meningitis, bacteremia, and bacteremic pneumonia. At least 100 serotypes of S. pneumoniae have been identified, which are determined by the surface capsular polysaccharide [orldwide . The cliccharide .S. pneumoniae accounts for up to 25% of bacterial isolates in middle ear fluid of young children with AOM [S. pneumoniae is the most common typical cause of bacterial community acquired pneumonia in children [AOM is a leading cause of acute care visits and antibiotic prescriptions in children, and with AOM –7. Moreochildren –11. AOM,children , 6.The first pneumococcal conjugate vaccine (PCV) was licensed in the US and recommended by the Advisory Committee on Immunization Practices in 2000, as part of the pediatric vaccine schedule . It was Several studies based on real-world data, specifically national surveillance data, have reported substantial healthcare resource use (HRU) and healthcare costs associated with pneumococcal disease. However, these studies were subject to limitations such as lack of recent data and of HRU and cost estimates for individual IPD manifestations , 16, 17.This study was conducted using data from the IBM MarketScan® Commercial Claims and Encounters  and Multi-State Medicaid databases . The CCAE database contains information on enrollment eligibility, demographic data, and medical, surgical and prescription drug utilization and expenditure data for approximately 90 million unique individual employees, their spouses, and dependents covered by employer-sponsored private health insurance. The Multi-State Medicaid database includes similar information for nearly 16 million individuals who were enrolled in Medicaid programs in 12 states. Both databases contain information on inpatient, outpatient, and long-term care services.This was a retrospective observational study of health care utilization and cost associated with AOM, all-cause pneumonia, and IPD episodes using administrative claims data from children < 18 years of age enrolled in commercial or Medicaid plans at any time from January 1, 2014 to December 31, 2018. Children with AOM, all-cause pneumonia, or an IPD episode were identified and defined in each calendar year using inpatient and outpatient claims with International Classification of Diseases 9/10th Revision, Clinical Modification (ICD-9-CM and ICD-10-CM) codes in any position on the claim record. A disease episode was defined as one or more outpatient and/or inpatient claims. For AOM, a gap of at least 14 days with no claims with AOM-related diagnoses was required to define the start of a new episode. For all-cause pneumonia, a gap of at least 90 days with no pneumonia-related diagnoses was required to define the start of a new episode, following prior retrospective studies of administrative records –25. For If there was more than one diagnosis code included on the same claim that fulfilled the definitions for multiple diseases or manifestations, the higher-priority condition took precedent according to the following hierarchy, to avoid double-counting of HRU and costs. IPD episodes received the highest priority, with meningitis first, followed by bacteremia, bacteremic pneumonia, and finally other IPD. All-cause pneumonia was prioritized next, and AOM received the lowest priority. Given that IPD incidence is much lower than pneumonia incidence (approximately 100 times lower) and that pneumonia incidence is much lower than AOM incidence (approximately 10 times lower), the hierarchy is not expected to meaningfully impact the incidence rates of these manifestations. For example, even if 20% of IPD episodes overlap with a pneumonia episode, the calculated IR of pneumonia after applying the hierarchy would only be 0.2% lower than the real value if ignoring the overlapping IPD episodes.IPD was defined as pneumococcal-specific meningitis, bacteremia, bacteremic pneumonia, or other pneumococcal-specific IPDs . All-cause pneumonia was defined as non-invasive pneumonia of any etiology, including bacterial, viral, and of unknown cause. AOM episodes were further categorized as simple or recurrent based on prior history of AOM. Specifically, an AOM episode was categorized as recurrent if a patient had three or more episodes within a six-month period or four or more episodes within a 12-month period, with at least one episode in the preceding six months, based on clinical guidelines , 28. SeeOutcomes measures included the number of children with AOM, all-cause pneumonia, and IPD  by insurance type, as well as mean age, age category, sex, and health plan type; for the commercially insured population, the region and urbanicity was also reported , Exclusive Provider Organization (EPO), Preferred Provider Organization (PPO), High Deductible Health Plan, Fee-for-Service, and Consumer-Directed Health Plans. Capitated plans included Health Maintenance Organizations (HMOs). Healthcare costs of AOM, all-cause pneumonia, and IPD  during the disease episode were assessed.Baseline characteristics  were described among patients with AOM, all-cause pneumonia, and IPD episodes during the study period, for the commercially insured population. For the Medicaid insured population, age, sex, and health plan types were described. Data on reported geographic region and urbanicity were not available in the Medicaid databases.HRU and costs were described for AOM, all-cause pneumonia, and IPD episodes among commercially and Medicaid insured populations. The cost per IP admission, ER visit, OP visit, OP pharmacy prescription, and surgical procedure (AOM only) were calculated among patients who received each service, rather than the total number of episodes. For AOM, HRU and cost were described overall, and further stratified between simple and recurrent AOM episodes, separately. For IPD, HRU and cost were described overall, and further stratified for each manifestation separately. Costs were reported as the total paid amounts for adjudicated claims from payers and out-of-pocket payments by patients, including deductibles, co-payments, and co-insurance. Other patient/family costs (such as transportation and lost productivity) were not included. Costs were reported in 2019 USD; costs incurred prior to 2019 were adjusted for inflation using the Consumer Price Index for medical care .Estimates of the nationally representative number of episodes of each condition were based on the standardization of the disease episode incidence rates observed in the MarketScan database using US Census data by each year, as in prior studies . NationaCensus data for each study year were obtained from the US Census Bureau database , 32. EstDemographic characteristics for the commercially and Medicaid-insured populations with AOM, all-cause pneumonia, and IPD during the period from 2014 to 2018 are shown in Table In the commercially insured population, the majority of children with AOM, all-cause pneumonia, or an IPD episode were insured through a PPO/POS plan . In contrast, in the Medicaid insured population, the majority of children with one of these illnesses were insured through an HMO/EPO plan . In the commercially insured population, the majority of children with AOM, all-cause pneumonia, or an IPD episode resided in an urban area .The HRU and costs associated with AOM in the commercially and Medicaid insured populations from 2014 to 2018 are shown in Table Among children with AOM, hospitalization occurred very rarely regardless of insurance type , with a mean LOS of 3.4 days (SD 7.8) and 3.8 days (SD 13.1), respectively. ER visits occurred less frequently in the commercially insured vs. Medicaid insured population (12.8% vs. 28.2%) but OP visits were more common in the commercially insured population (88.8% vs. 75.0%). OP antibiotics were prescribed in most children with AOM, but less commonly in commercially insured compared with the Medicaid insured population (72.0% vs. 82.2%). In the commercially insured population, recurrent AOM was associated with a lower proportion of ER visits (7.9% vs. 13.8%), a slightly higher proportion of OP visits (93.9% vs. 87.7%), a slightly lower proportion of OP antibiotics (63.3% vs. 73.7%), and a higher proportion of surgical procedures (12.4% vs. 2.1%), compared with simple AOM. In the Medicaid insured population, there was a similar pattern of lower proportion of ER visits (18.9% vs. 30.1%), slightly higher proportion of OP visits (85.1% vs. 72.9%), lower proportion of OP prescriptions (72.8% vs. 84.2%), and higher proportion of surgical procedures (11.4% vs. 2.2%) in children with recurrent vs. simple AOM.The mean total cost per episode of AOM was $329 (SD $1505) in the commercially insured and $184 (SD $1524) in the Medicaid insured population, with higher costs for recurrent vs. simple AOM regardless of insurance type . The costs for IP admission, ER visits, OP visits, and surgical procedures were all higher for commercially insured, compared with Medicaid insured patients, but regardless of insurance type, OP visits comprised about half of the total costs .The HRU and costs associated with all-cause pneumonia in the commercially and Medicaid insured populations from 2014 to 2018 are shown in Table The mean total cost per episode of all-cause pneumonia was $2304  in the commercially insured and $1682  in the Medicaid insured population. The costs for all visit types were higher in commercially insured, compared with Medicaid insured population, including IP admission , ER visits ($1521 vs. $402), and OP visits ($257 vs. $193). Though IP admissions occurred in a small minority of children, they were associated with over half of the total costs for all-cause pneumonia, regardless of insurance type, comprising $1698 (73.7%) of the total cost for commercially insured and $1324 (78.7%) for Medicaid insured children. While we did not investigate the prevalence of comorbidities present in hospitalized children, it is possible that other conditions and risk factors were more common in this population.The HRU and costs associated with IPD and its manifestations in the commercially and Medicaid insured populations are shown in Table The mean total cost per overall IPD episode was $53,213  for the commercially insured and $23,482  for the Medicaid population. All visit costs per overall IPD episode were higher in the commercially insured, compared with the Medicaid population, including IP admission , ER visit ($3032 vs. $633), and OP visits ($2177 vs. $1166). IP admissions comprised the majority of total costs for overall IPD episodes regardless of insurance, including $50,319 (94.6%) of total costs for the commercially insured children, and $22,423 (95.5%) of total costs for children with Medicaid insurance plans. It is noteworthy that this is likely an under-estimate for IP admission costs, because the inpatient IP admission may not have been included in the study period for all children with an IPD episode.In both the commercially insured and the Medicaid insured population, the MarketScan database included the highest proportion of IP admissions for children with bacteremic pneumonia (83.4 and 79.3%) with LOS of 11.1 (SD 16.8) and 9.4 days (SD 12.9), respectively. The total cost per case of bacteremic pneumonia was much higher in the commercially insured, compared with the Medicaid insured population  due to the much higher cost of hospitalization  in those with commercial insurance. IP admissions comprised the majority of total costs for bacteremic pneumonia regardless of insurance, including $84,752 (96.7%) of total costs for the commercially insured children, and $22,784 (97.6%) of total costs for children with Medicaid insurance plans.The MarketScan database identified 97 (51.6%) IP admissions for the 188 children with pneumococcal meningitis and commercial insurance plans, and 130 (53.7%) for the 242 children with Medicaid insurance plans. It is probable that all children with meningitis had an IP admission, but only the post-index episode follow-up care was included in the database during the study period for some children. The duration of IP admission was slightly shorter for the children with commercial insurance, compared with Medicaid insurance plans, with mean LOS of 15.2 days (SD 18.1) vs. 16.1 days (SD 21.7), but the cost per hospitalization was much higher for the children with commercial insurance . IP admissions comprised the majority of total costs for pneumococcal meningitis regardless of insurance, including $52,059 (90.2%) of total costs for the commercially insured children, and $21,345 (87.3%) of total costs for the children with Medicaid insurance plans.The MarketScan database identified 171 (48.3%) IP admissions for the 354 children with pneumococcal bacteremia and commercial insurance plans, and 283 (55.7%) for the 508 children with Medicaid insurance plans. It is probable that the majority of children with pneumococcal bacteremia had an IP admission, but only the post-index episode follow-up care was included in the database during the study period for some children, as for meningitis. The duration of IP admission was shorter for the children with commercial insurance, compared with Medicaid insurance plans, with mean LOS of 8.1 days (SD 12.2) vs. 12.0 days (SD 25.1), but the cost per hospitalization was much higher for the children with commercial insurance . IP admissions comprised the majority of total costs for pneumococcal bacteremia regardless of insurance, including $31,518 (94.6%) of total costs for the commercially insured children, and $23,898 (98.2%) of total costs for the children with Medicaid insurance plans.The nationally representative healthcare costs of AOM, all-cause pneumonia, and IPD are shown in Fig. For all-cause pneumonia, the mean total yearly episodes were 1,506,736 in US children < 18 years of age, with 323,767 episodes among children < 2 years of age, 444,097 episodes among children from 2 to 4 years of age, and 738,872 episodes among children from 5 to 17 years of age. The mean cost of all-cause pneumonia treatment was $2377 per episode at the national level during this time period. Cost per episode was the highest among children < 2 years of age ($5021), followed by those from 5 to 17 years of age ($1858) and 2 to 4 years of age ($1315). Mean costs (SD) per all-cause pneumonia episode for each study calendar year broken down by type of service are shown in Supplemental Table AFor overall IPD, the mean total yearly episodes were 2522 in US children < 18 years of age, with 964 episodes among children < 2 years of age, 566 episodes among children from 2 to 4 years of age, and 992 episodes among children from 5 to 17 years of age. The mean cost of treatment for overall IPD was $38,960 per episode at the national level. Cost per episode was the highest among children from 5 to 17 years of age , followed by those < 2 years of age  and 2 to 4 years of age . Mean costs (SD) per IPD episode for each calendar year by type of service and disease manifestation are shown in Supplemental Table AAmong the specific IPD manifestations, bacteremic pneumonia was associated with highest cost per episode , followed by meningitis , bacteremia , and other IPD ($4958). Among the total yearly cost of $98 million due to IPD, $30.7 million were associated with bacteremic pneumonia, followed by $24.4 million associated with bacteremia, $17.8 million associated with meningitis, and 0.8 million associated with other IPD.This study demonstrates that AOM, pneumonia, and IPD-associated healthcare resource utilization and costs in the US pediatric population remain substantial in recent years. At the national level, there were an estimated 15.8 million episodes of AOM annually among children < 18 years of age from 2014 to 2018, costing an estimated $4.3 billion per year during this period; approximately $2.9 billion were associated with simple AOM and $1.3 billion were with recurrent AOM. Recent incidence estimates suggest that the rates of recurrent AOM episodes and the percentage of recurrent episodes of the total have remained relatively unchanged over the past decade in children of all ages . There wIn the MarketScan database, about 80% of the AOM episodes were associated with OP visits, and about 15% with ER visits. Outpatient antibiotics were prescribed for the majority of cases. Hospitalizations were very rare, but surgical procedures were performed in about 4% of cases (12% for children with recurrent AOM). Hospitalization was also uncommon for children with all-cause pneumonia, occurring in 5 to 9% of the episodes, and outpatient and/or ER visits occurred for nearly all episodes. In contrast, IP admission was common among children with an IPD episode, occurring in about 60% of cases. Even so, this is likely an underestimate, as just over 50% of children with pneumococcal meningitis identified in the MarketScan database had an associated IP admission, and practice guidelines recommend inpatient admission for all patients with bacterial meningitis , 35. We .HRU associated with AOM, all-cause pneumonia, and IPD episodes estimated in this study are consistent with prior real-world studies. As reported by Tong et al., more than 90% of AOM cases were seen in the OP setting only . AlthougThe estimated cost per AOM episode treated from 2014 to 2018 in this analysis is consistent with results from other published studies. Tong et al. reported an average of $344, $338, $248, and $186 per AOM episode among children < 1 year, 1 year, 2 to 4 years, and 5 to 17 years of age, respectively, during the years of 2013 to 2014 . An earlThe costs per pneumonia episode estimated in the current study were about twice as high compared to a prior study. Tong et al. reported an average of $2622, $1255, $923, and $910 per pneumonia episode among children < 1 year of age, 1 year, 2 to 4 years, and 5 to 17 years of age, respectively, in 2013 and 2014 [The national estimates for annual healthcare costs for AOM in this analysis are similar to those from prior studies. Suaya et al. reported costs of $4.4 billion among children < 9 years of age in 2016 and Tong et al. reported costs of $4.3 billion in 2014 , 39. CosTong et al. reported a total cost of $13.4 billion associated with pneumonia among the overall US population, however, costs among the pediatric population were not reported . Zhou etTo our knowledge, no prior studies have specifically estimated healthcare costs associated with the treatment of IPD in the US pediatric population. Huang et al. estimated a direct medical cost of $3.5 billion associated with overall pneumococcal disease, including AOM, pneumonia, and IPD, in the general US population. However, the estimate was based on a micro-costing approach, using annual incidence of disease from CDC’s Active Bacterial Core Surveillance system, HRU associated with pneumococcal disease from literature, and costs of medical services obtained from the public domain based on payment from the payers  [The treatment costs per episode of AOM, all-cause pneumonia, and IPD were much higher in the commercially insured, compared with the Medicaid insured population . The costs for all IP admissions, ER visits, and OP visits were always higher for commercially insured children, but the cost of OP antibiotic prescriptions was generally similar, regardless of insurance type. A recently conducted cross-sectional analysis of a propensity score-matched sample of low-income adults enrolled in health insurance plans also found higher costs in the commercially insured patients, compared with those enrolled in Medicaid insurance plans, with overall health care spending more than 80% higher among those with commercial insurance . A studyS. pneumoniae is associated with greater clinical severity and a higher likelihood of complications in AOM, and studies of antimicrobial susceptibility in middle ear isolates of children with AOM in a primary care setting have demonstrated increasing resistance to penicillin, amoxicillin, fluoroquinolones, third-generation cephalosporins, and carbapenems among nonvaccine serotypes [It is also important to emphasize that erotypes , 46. NeaS. pneumoniae represents only one common bacterial etiology for these conditions [S. pneumoniae were identified using diagnosis codes; however, lab values for pathogen cultures were not available. Therefore, incidence rates of pneumococcal-specific IPD and its manifestations were likely underestimated. Fourth, HRU and costs associated with IPD, particularly meningitis, are likely underestimated, due to the failure to capture all IP admissions, and the HRU and costs of long-term sequelae were not captured as well. In addition, we did not include patient and family costs  for any condition, therefore underestimating the societal cost of these diseases. Fifth, disease episodes were defined with a disease hierarchy based on clinical severity to avoid double counting; however, HRU and costs might be misassigned for episodes where multiple diseases were present. Sixth, bacteremic pneumonia episodes were found to have substantially higher costs than all-cause pneumonia, potentially due to complications requiring chest tube placement or surgical intervention. However, we did not specifically analyze data on chest tube placement or surgical interventions. Seventh, although the MarketScan database is considered representative of commercial health plans in the US, it is based on non-random sampling. The national estimates of disease incidence rates are thus based on the assumption that the study sample accurately reflects the overall commercially insured and Medicaid pediatric populations, respectively. In addition, the national estimates also assume that there are no uninsured children. Eighth, our analysis did not examine costs specifically for different antibiotics used to treat pneumococcal disease. Given the wide range of providers and facilities reporting data for the databases analyzed in this study, many with separate formularies with different unit costs for each drug, reporting the cost data with this level of granularity is outside the scope of this study. Finally, while the disease manifestations analyzed here also affect the adult population, quantifying their burden in the adult population is outside the scope of this study. The study focused on children because they are disproportionately affected by these conditions and have a universal vaccination recommendation, as compared to adults, in whom vaccination is recommended only for those with older age or with risk factors.Though this study used recent data from a large US national representative claims database to comprehensively assess the HRU and costs associated with pneumococcal disease among the US pediatric population, it has several limitations. First, as with any large claims database, miscoding of diagnoses may occur, potentially leading to misclassification and measurement error. Second, we included all etiologies of AOM and pneumonia in this analysis, though nditions , 7, 8. Tnditions  and abounditions . Estimatnditions , 48, 49 nditions  being ofThe economic burden of AOM, pneumonia, and IPD in the US pediatric population remains substantial, even 20 years after the development of PCVs. At the patient level, pneumococcal disease and its manifestations were associated with higher HRU and costs, compared to AOM and all-cause pneumonia, but AOM was associated with the majority of antibiotic prescriptions. At the US pediatric population level, AOM and all-cause pneumonia are the main contributors to the economic burden of pneumococcal disease. Additional interventions, such as the introduction of new PCV vaccinations covering a broader range of serotypes are necessary to decrease the burden of pneumococcal disease, and reduce antibiotic prescriptions. Based on recent estimates, the additional disease burden that could be averted by these new vaccines could reach up to two billion dollars .Additional file 1: Supplemental Table A1. Diagnosis and procedure codes used in the study. Supplemental Table A2. Size of MarketScan commercially insured children population at risk in person-years and estimates of the total US pediatric population with commercial insurance (2014–2018). Supplemental Table A3. Size of MarketScan Medicaid-insured children population at risk in person-years and estimates of the total US pediatric population with Medicaid coverage (2014–2018). Supplemental Table A4. Risk factors for pneumococcal disease among AOM, all-cause pneumonia, and IPD patients aged < 18 years in the 6 months prior to AOM episodes, 2014–2018. Supplemental Table A5. National estimates of healthcare costs of pneumococcal disease in children aged < 18 years in the United States (2014–2018). Supplemental Table A6. Healthcare costs of AOM in commercially insured children aged < 18 years in the United States in 2019 USD, by type (2014–2018). Supplemental Table A7. Healthcare costs of all-cause pneumonia in commercially insured children aged < 18 years in the United States in 2019 USD, by type (2014–2018). Supplemental Table A8. Healthcare costs of IPD manifestations in commercially insured children aged < 18 years in the US in 2019 USD, by type (2014–2018).


Prostate cancer is one of the most common malignant tumors in Chinese men, which is rich in iron metabolic activity and is closely related to all stages of prostate cancer progression. Since the current diagnostic methods are insufficient, we aimed to evaluate the value of quantitative T2 star values from the T2* mapping sequences in multiparametric magnetic resonance imaging (mpMRI) in the diagnosis and grading of PI-RADS 3 prostate cancer (PCa).We prospectively enrolled patients with PCa or benign prostatic hyperplasia (BPH) admitted to our hospital from January 2021 to November 2022. Imaging indicators, including the T2* value and apparent diffusion coefficient (ADC) value, were collected, and enzyme-linked immunosorbent assays (ELISAs) were used to measure the levels of proteins involved in iron metabolism in the patients. ROC curves were drawn to explore whether the T2* value could be used for the diagnosis and grading of PCa.We found that three iron metabolism indexes, ferritin, hepcidin, and the ferric ion (Fe), and the T2* value were significantly different between the PCa group and BPH group and between the low International Society of Urology Pathology (ISUP) group (ISUP ≤ 2) and the high ISUP group (ISUP>2). Additionally, there was a significant correlation between the levels of these three indicators and the T2* value. Further ROC analysis showed that the levels of iron metabolism-related indexes and T2* values performed well in diagnosing and grading PCa.The T2* value has good value in detecting and predicting the grade of prostate cancer and can reflect the iron metabolism of the tumor, which could provide a foundation for the diagnosis and grading of PCa in the future. AccordiTo date, the diagnosis of PCa mainly depends on two methods: the measurement of serum total prostate-specific antigen (TPSA) levels and multiparametric magnetic resonance imaging (mpMRI). In recent years, noninvasive methods, such as PSA measurements, have been developed for evaluating preoperative PCa lesions, and the diagnostic value of these methods for determining progression and prognosis has been evaluated. Although TPSA assays have high sensitivity, their low specificity has led to the overuse of prostate biopsy. Therefore, improving the efficiency of PCa diagnosis and avoiding unnecessary invasive examinations are pivotal components of the diagnosis and treatment of PCa. mpMRI of the prostate is currently another important component of noninvasive PCa diagnosis. mpMRI is not burdened by the economic costs associated with the surgical injury caused by prostate biopsy or false-positive results and can be comprehensively performed before surgery to assess the location, boundaries, and environment of the tumor. The apparent diffusion coefficient (ADC) value has also been discussed with regard to its relation to the pathological stage and prognosis of PCa . PI-RADSWith the in-depth study of iron metabolism, increasing evidence has shown a correlation between iron metabolism and the occurrence and progression of malignant tumors . Iron isHere, we introduce a less-used MR sequence in urology, since the unclear anatomical division, difficulty in parameter adjustment, small prostate volume and so on. The T2* mapping sequence was initially used to assess iron deposition in the heart and spleen . In the 22.1This prospective study was approved by the Medical Ethics Committee of the First Affiliated Hospital of Soochow University . Written informed consent was obtained from all the patients. Patients were included from January 2021 to November 2022. Patients hospitalized in the First Affiliated Hospital of Soochow University diagnosed with prostate diseases were prospectively subjected to mpMRI before prostate biopsy. The sequence included T2, DWI, ADC and T2* mapping. Serum samples were also collected. Two radiologists rescored all patients based on PI-RADS and included patients with PI-RADS3 in this study. Then, retrospective collection of data regarding the clinical indicators of patients in this study, including TPSA levels, prostate volume, pathological grade and others, was performed. The inclusion criteria were as follows: (1) MRI of the prostate, including T2-weighted imaging (T2WI), DWI, and T2* mapping-weighted imaging and surgery-  and postoperative pathology-confirmed PI-RADS 3 PCa or benign prostatic hyperplasia (BPH); (2) MRI examination at our hospital less than six weeks after prostate surgery; and (3) The lack of acute hepatitis or blood diseases affecting iron metabolism. Exclusion criteria were as follows: (1) treatment for PCa before surgery, such as endocrine therapy or radiotherapy; (2) other diseases affecting iron metabolism except PCa; and (3) film reading hampered by MRI artifacts. Based on the primary criteria, our study included 90 patients, including 56 with PCa and 34 with BPH. Ninety-three patients were excluded because of their incorrect PI-RADS score, three patients were excluded because they had received endocrine therapy, one patient was excluded due to an MRI artifact, and one patient was excluded due to reclassification of the PI-RADS score. In accordance with the PCa grading system, patients were divided into five categories. Grades assigned by the ISUP to patients 1, 2, 3, 4, and 5 were 4, 18, 17, 4, and 13, respectively. The PRISMA flow chart was shown in 2.2Preoperative blood was collected from the two groups of patients. Serum and erythrocytes were rapidly and carefully separated by centrifugation at 3000 rpm for 10 minutes. The expression levels of ferritin and hepcidin in serum were measured by enzyme-linked immunosorbent assay (ELISA). After the prostate tissue was acquired after laparoscopic radical prostatectomy or transurethral resection of prostate, the specimens were then mashed with an appropriate amount of normal saline. The supernatant was collected by centrifugation at 3000 rpm for 10 minutes, and the tissue homogenate was detected by ELISA. The process was carried out in strict accordance with the kit instructions.2.3Examinations were performed by using a 3.0 T clinical MR scanner  with a dedicated 16-channel body-phased array coil. All images of 90 patients were assessed by 2 physicians respectively based on the PI-RADS score. Through the former study and following practice , an axia2.4The images obtained from the mpMRI scans were transferred to the Picture Archiving and Communication System (PACS), and the scores were rescored according to the PI-RADS V2.0 by 2 physicians with 10 years of experience in prostate MR diagnosis. The raters knew the patient’s baseline data but were blinded to the pathology results.2.5The slice that showed the greatest extent of the lesion area was selected on the PACS, and the region of interest (ROI) was set. For multiple suspected tumor sites, the one with lowest T2* value was eventually selected for delineating the ROI. Considering the difficulty of sampling, we generally select an area of 1cm*1cm-sized circular area as the ROI. For tumors with too large lesions, we use the area with the lowest T2* value. Each measurement was repeated 3 times, and the average value was taken. After prostatectomy, each prostate pathology image was divided into 5 mm thick slices. Using the corresponding positions on the MR images, experienced pathologists manually marked six points on the prostate pathology images—the basal section, the apex, the peripheral zone, the central gland, the tip and the urinary tract—which were aligned with the corresponding parts on the MRI images. Symbols were used to identify various distinct morphological characteristics and then used to align the images with the step-section slices. For patients with BPH, the prostate was also corresponded to the six positions as described above, and the average value of the 1cm*1cm circular area of the transitional zone of hyperplasia is taken.2.6All data were tested with SPSS 22.0 software . According to the normality test, the baseline data do not fit a normal distribution, and are presented as medians (interquartile range), and group comparisons were made using nonparametric tests. Spearman correlation was used for correlation analysis. Taking the pathological results as the gold standard, the ROC curve was drawn. The difference was considered statistically significant at p<0.05, and applied to all evaluations.33.1The pathological findings of 90 patients were included in this prospective study, including 34 patients with BPH and 56 patients with PCa. To explore differences in patient clinical data, we compared the TPSA, ratio of free to total PSA (F/TPSA), prostate volume, apparent diffusion coefficient (ADC) value, T2* value, ferritin, hepcidin, and Fe between the BPH and Pica groups. The results showed that the differences for all indicators between the two groups were statistically significant  can be selected for ISUP 1 and some ISUP 2 lesions, to avoid unnecessary repeated puncture and radical surgery, we further divided PCa patients into ISUP ≤ 2 and ISUP > 2 Table 2.3.2Next, we analyzed the correlation between the levels of serum markers and prostate volume and TPSA levels or T2* value, and the results showed that in BPH patients, the TPSA level was correlated with the prostate volume p<0.001; Table 3,3.3Next, we further analyzed the correlation between PCa patient indicators and ISUP grade and T2* value, and the results showed that TPSA, ADC value, ferritin, hepcidin, and Fe were all correlated with ISUP grade and T2* value. It is worth noting that the correlation coefficients of the T2* value, ferritin, hepcidin, and Fe with ISUP were -0.661, 0.52, 0.411, and 0.535, respectively ; the AUCs of the other markers are shown in 4Prostate cancer morbidity and mortality are rising in Asia, with current diagnoses mainly relying on PSA, digital rectal exam (DRE) and mpMRI, as as reported above, posing a new challenge to PCa diagnosis. The focus of the diagnosis of PCa is to differentiate it from BPH, which is associated with symptoms that often mask the existence of PCa. With the advancement of MRI technology, mpMRI has become an effective modality for the noninvasive diagnosis of PCa. The existing routine sequence and the general qualitative PI-RADS scoring model are gradually becoming inadequate for meeting current requirements. Whether needle biopsy should be performed for a PI-RADS score of 3 and the positive rate of needle biopsy were not satisfactory. A 2016 multicenter prospective study showed that the detection rates of PCa were 13%, 31%, and 71% for lesions with a PI-RADS score greater than or equal to 3, respectively –19. InteAngiogenesis and tumor metastasis are closely related to cellular iron metabolism. It has been proven that reducing intracellular iron metabolism inhibits tumor cell growth in both hormone-dependent and hormone-resistant cells . As a keWe assessed iron metabolism in prostate disorders using the T2* mapping sequence in mpMRI. We found that the T2* value was lower in the PCa group than in BPH group (p<0.001). In the PCa group, the T2* value was negatively correlated with ISUP grade, and patients with ISUP>2 tended to have a lower T2* value. Compared to the traditional ADC value, the TPSA and T2* values had better performance in distinguishing PCa and BPH and in distinguishing ISUP ≤ 2 and ISUP>2 . As a traditional PCa diagnostic index, TPSA still has good performance in diagnosing PCa (AUC=0.746), but there was no significant difference within the PCa group (p=0.08). The ADC value is used as a quantitative indicator; however, in identifying PCa, the diagnostic performance was not as good as TPSA or the T2* value (AUC=0.647), but it was able to achieve greater diagnostic performance within the PCa group AUC=0.729), which is consistent with previous papers showing that the ADC value can be used to predict PCa staging, grading and prognosis , which i.To verify whether the T2* value can represent iron metabolism, we added three iron metabolism-related indicators, hepcidin, ferritin, and Fe, to our study and found that the levels were significantly different between PCa and BPH (p<0.01). Notably, within the PCa group, the three metrics were still significantly different between the ISUP groups . In further ROC curve analysis, Ferritin (AUC=0.704), Hepcidin (AUC=0.667) and Fe (AUC=0.748) showed good performance in the diagnosis of prostate cancer. When considering the risk stratification of prostate cancer, the diagnostic efficiency of the Ferritin (AUC=0.743), Hepcidin (AUC=0.7) and Fe (AUC=0.771) is further improved, suggesting that even in patients with prostate cancer, different progression often has different iron metabolism. In the PCa group, the three indexes were all negatively correlated with the T2* value, indicating that the T2* mapping sequence could reflect iron metabolism in PCa to a certain extent and reflect the progression of the disease.Through this study, we hope to drive the adoption of radiomics and metabonomics in the management of current PI-RADS3 patients. From a radiological standpoint, it might increase the overall diagnostic efficiency; on the other hand, it might allow us to rule out unnecessary biopsies from a clinical perspective, avoiding the risk of possible complications in selected patients.Inevitably, this article has some limitations. First, the sample size was relatively small, and it is necessary to conduct a multicenter, prospective, large-scale study to confirm the current conclusions. Second, the article lacks prognostic follow-up data, and whether the T2* value can be used as a prognostic indicator remains to be explored. Finally, although the accuracy of sampling was adequate, there are still uncontrollable corresponding errors, and it is necessary to wait for better sampling methods.5In conclusion, the validation of tissue extraction and metabolic analysis based on T2* Mapping sequence could provide a practical basis for non-invasive preoperative evaluation of patients with prostate malignancies using this technology, and could provide the possibility to discover potential iron metabolism-related therapeutic targets in the future.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Medical Ethics Committee of the First Affiliated Hospital of Soochow University . The patients/participants provided their written informed consent to participate in this study.WD analyzed data and wrote the manuscript. YH and XZ developed the project. XW, WZ and GL edited the manuscript. GZL and YL performed MRI examinations. All authors contributed to the article and approved the submitted version.