Advancement study of CancerMath model as prognostic tools for predicting Sentinel lymph node metastasis in clinically negative T1 breast cancer patients

Purpose: Sentinel lymph node biopsy (SLNB) is an invasive surgical procedure and although it has fewer complications and is less severe than axillary lymph node dissection, it is not a risk-free procedure. Large prospective trials have documented SLNB that it is considered non-therapeutic in early stage breast cancer. Methods: Web-calculator CancerMath (CM) allows you to estimate the probability of having positive lymph nodes valued on the basis of tumour size, age, histologic type, grading, expression of estrogen receptor, progesterone receptor. We collected 595 patients referred to our Institute resulting clinically negative T1 breast cancer characterized by sentinel lymph node status, prognostic factors defined by CM and also HER2 and Ki-67. We have compared classification performances obtained by online CM application with those obtained after training its algorithm on our database. Results: By training CM model on our dataset and using the same feature, adding HER2 or ki67 we reached a sensitivity median value of 71.4%, 73%, 70.4%, respectively, whereas the online one was equal to 61%, without losing specificity. The introduction of the prognostic factors Her2 and Ki67 could help improving performances on the classification of particularly type of patients. Conclusions: Although the training of the model on the sample of T1 patients has brought a significant improvement in performance, the general performance does not yet allow a clinical application of the algorithm. However, the experimental results encourage future developments aimed at introducing features of a different nature in the CM model

Accurate Evaluation of Feature Contributions for Sentinel Lymph Node Status Classification in Breast Cancer

The current guidelines recommend the sentinel lymph node biopsy to evaluate the lymph node involvement for breast cancer patients with clinically negative lymph nodes on clinical or radiological examination. Machine learning (ML) models have significantly improved the prediction of lymph nodes status based on clinical features, thus avoiding expensive, time-consuming and invasive procedures. However, the classification of sentinel lymph node status represents a typical example of an unbalanced classification problem. In this work, we developed a ML framework to explore the effects of unbalanced populations on the performance and stability of feature ranking for sentinel lymph node status classification in breast cancer. Our results indicate state-of-the-art AUC (Area under the Receiver Operating Characteristic curve) values on a hold-out set (67%) while providing particularly stable features related to tumor size, histological subtype and estrogen receptor expression, which should therefore be considered as potential biomarkers

The role of immune suppression in COVID-19 hospitalization: clinical and epidemiological trends over three years of SARS-CoV-2 epidemic

Specific immune suppression types have been associated with a greater risk of severe COVID-19 disease and death. We analyzed data from patients >17 years that were hospitalized for COVID-19 at the “Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico” in Milan (Lombardy, Northern Italy). The study included 1727 SARS-CoV-2-positive patients (1,131 males, median age of 65 years) hospitalized between February 2020 and November 2022. Of these, 321 (18.6%, CI: 16.8–20.4%) had at least one condition defining immune suppression. Immune suppressed subjects were more likely to have other co-morbidities (80.4% vs. 69.8%, p < 0.001) and be vaccinated (37% vs. 12.7%, p < 0.001). We evaluated the contribution of immune suppression to hospitalization during the various stages of the epidemic and investigated whether immune suppression contributed to severe outcomes and death, also considering the vaccination status of the patients. The proportion of immune suppressed patients among all hospitalizations (initially stable at <20%) started to increase around December 2021, and remained high (30–50%). This change coincided with an increase in the proportions of older patients and patients with co-morbidities and with a decrease in the proportion of patients with severe outcomes. Vaccinated patients showed a lower proportion of severe outcomes; among non-vaccinated patients, severe outcomes were more common in immune suppressed individuals. Immune suppression was a significant predictor of severe outcomes, after adjusting for age, sex, co-morbidities, period of hospitalization, and vaccination status (OR: 1.64; 95% CI: 1.23–2.19), while vaccination was a protective factor (OR: 0.31; 95% IC: 0.20–0.47). However, after November 2021, differences in disease outcomes between vaccinated and non-vaccinated groups (for both immune suppressed and immune competent subjects) disappeared. Since December 2021, the spread of the less virulent Omicron variant and an overall higher level of induced and/or natural immunity likely contributed to the observed shift in hospitalized patient characteristics. Nonetheless, vaccination against SARS-CoV-2, likely in combination with naturally acquired immunity, effectively reduced severe outcomes in both immune competent (73.9% vs. 48.2%, p < 0.001) and immune suppressed (66.4% vs. 35.2%, p < 0.001) patients, confirming previous observations about the value of the vaccine in preventing serious disease

Neutralizing antibodies to Omicron after the fourth SARS-CoV-2 mRNA vaccine dose in immunocompromised patients highlight the need of additional boosters

IntroductionImmunocompromised patients have been shown to have an impaired immune response to COVID-19 vaccines.MethodsHere we compared the B-cell, T-cell and neutralizing antibody response to WT and Omicron BA.2 SARS-CoV-2 virus after the fourth dose of mRNA COVID-19 vaccines in patients with hematological malignancies (HM, n=71), solid tumors (ST, n=39) and immune-rheumatological (IR, n=25) diseases. The humoral and T-cell responses to SARS-CoV-2 vaccination were analyzed by quantifying the anti-RBD antibodies, their neutralization activity and the IFN-γ released after spike specific stimulation.ResultsWe show that the T-cell response is similarly boosted by the fourth dose across the different subgroups, while the antibody response is improved only in patients not receiving B-cell targeted therapies, independent on the pathology. However, 9% of patients with anti-RBD antibodies did not have neutralizing antibodies to either virus variants, while an additional 5.7% did not have neutralizing antibodies to Omicron BA.2, making these patients particularly vulnerable to SARS-CoV-2 infection. The increment of neutralizing antibodies was very similar towards Omicron BA.2 and WT virus after the third or fourth dose of vaccine, suggesting that there is no preferential skewing towards either virus variant with the booster dose. The only limited step is the amount of antibodies that are elicited after vaccination, thus increasing the probability of developing neutralizing antibodies to both variants of virus.DiscussionThese data support the recommendation of additional booster doses in frail patients to enhance the development of a B-cell response directed against Omicron and/or to enhance the T-cell response in patients treated with anti-CD20

Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography Images

Contrast-enhanced spectral mammography (CESM) is an advanced instrument for breast care that is still operator dependent. The aim of this paper is the proposal of an automated system able to discriminate benign and malignant breast lesions based on radiomic analysis. We selected a set of 58 regions of interest (ROIs) extracted from 53 patients referred to Istituto Tumori “Giovanni Paolo II” of Bari (Italy) for the breast cancer screening phase between March 2017 and June 2018. We extracted 464 features of different kinds, such as points and corners of interest, textural and statistical features from both the original ROIs and the ones obtained by a Haar decomposition and a gradient image implementation. The features data had a large dimension that can affect the process and accuracy of cancer classification. Therefore, a classification scheme for dimension reduction was needed. Specifically, a principal component analysis (PCA) dimension reduction technique that includes the calculation of variance proportion for eigenvector selection was used. For the classification method, we trained three different classifiers, that is a random forest, a naïve Bayes and a logistic regression, on each sub-set of principal components (PC) selected by a sequential forward algorithm. Moreover, we focused on the starting features that contributed most to the calculation of the related PCs, which returned the best classification models. The method obtained with the aid of the random forest classifier resulted in the best prediction of benign/malignant ROIs with median values for sensitivity and specificity of 88.37% and 100%, respectively, by using only three PCs. The features that had shown the greatest contribution to the definition of the same were almost all extracted from the LE images. Our system could represent a valid support tool for radiologists for interpreting CESM images

Immune-Based Combinations versus Sorafenib as First-Line Treatment for Advanced Hepatocellular Carcinoma: A Meta-Analysis

Recent years have observed the emergence of novel therapeutic opportunities for advanced hepatocellular carcinoma (HCC), such as combination therapies including immune checkpoint inhibitors. We performed a meta-analysis with the aim to compare median overall survival (OS), median progression-free survival (PFS), complete response (CR) rate, and partial response (PR) rate in advanced HCC patients receiving immune-based combinations versus sorafenib. A total of 2176 HCC patients were available for the meta-analysis (immune-based combinations = 1334; sorafenib = 842) and four trials were included. Immune-based combinations decreased the risk of death by 27% (HR, 0.73; 95% CI, 0.65–0.83; p p p p < 0.03), respectively. The current study further confirms that first-line immune-based combinations have a place in the management of HCC. The CR rate observed in HCC patients receiving immune-based combinations appears more than twelve times higher compared with sorafenib monotherapy, supporting the long-term benefit of these combinatorial strategies, with even the possibility to cure advanced disease

Second-Generation 3D Automated Breast Ultrasonography (Prone ABUS) for Dense Breast Cancer Screening Integrated to Mammography: Effectiveness, Performance and Detection Rates

In our study, we added a three-dimensional automated breast ultrasound (3D ABUS) to mammography to evaluate the performance and cancer detection rate of mammography alone or with the addition of 3D prone ABUS in women with dense breasts. Our prospective observational study was based on the screening of 1165 asymptomatic women with dense breasts who selected independent of risk factors. The results evaluated include the cancers detected between June 2017 and February 2019, and all surveys were subjected to a double reading. Mammography detected four cancers, while mammography combined with a prone Sofia system (3D ABUS) doubled the detection rate, with eight instances of cancer being found. The diagnostic yield difference was 3.4 per 1000. Mammography alone was subjected to a recall rate of 14.5 for 1000 women, while mammography combined with 3D prone ABUS resulted in a recall rate of 26.6 per 1000 women. We also observed an additional 12.1 recalls per 1000 women screened. Integrating full-field digital mammography (FFDM) with 3D prone ABUS in women with high breast density increases and improves breast cancer detection rates in a significant manner, including small and invasive cancers, and it has a tolerable impact on recall rate. Moreover, 3D prone ABUS performance results are comparable with the performance results of the supine 3D ABUS system

Downstream Signaling of Inflammasome Pathway Affects Patients&rsquo; Outcome in the Context of Distinct Molecular Breast Cancer Subtypes

Inflammasomes are protein complexes involved in the regulation of different biological conditions. Over the past few years, the role of NLRP3 in different tumor types has gained interest. In breast cancer (BC), NLRP3 has been associated with multiple processes including epithelia mesenchymal transition, invasion and metastization. Little is known about molecular modifications of NLRP3 up-regulation. In this study, in a cohort of BCs, the expression levels of NLRP3 and PYCARD were analyzed in combination with CyclinD1 and MYC ones and their gene alterations. We described a correlation between the NLRP3/PYCARD axis and CyclinD1 (p &lt; 0.0001). NLRP3, PYCARD and CyclinD1&rsquo;s positive expression was observed in estrogen receptor (ER) and progesterone receptor (PgR) positive cases (p &lt; 0.0001). Furthermore, a reduction of NLRP3 and PYCARD expression has been observed in triple negative breast cancers (TNBCs) with respect to the Luminal phenotypes (p = 0.017 and p = 0.0015, respectively). The association NLRP3+/CCND1+ or PYCARD+/CCND1+ was related to more aggressive clinicopathological characteristics and a worse clinical outcome, both for progression free survival (PFS) and overall survival (OS) with respect to NLRP3+/CCND1&minus; or PYCARD+/CCND1&minus; patients, both in the whole cohort and also in the subset of Luminal tumors. In conclusion, our study shows that the NLRP3 inflammasome complex is down-regulated in TNBC compared to the Luminal subgroup. Moreover, the expression levels of NLRP3 and PYCARD together with the alterations of CCND1 results in Luminal subtype BC&rsquo;ss poor prognosis

Prevalence of Patients Affected by Fibromyalgia in a Cohort of Women Underwent Mammography Screening

: Fibromyalgia is a widespread condition which is currently underdiagnosed; therefore we conceived this study in order to assess whether a diagnostic suspicion may be assumed during widespread screening procedures, so that patients for which a reasonable diagnostic suspicion exist may be redirected towards rheumatologic evaluation. We analyzed a sample of 1060 patients, all of whom were female and undergoing standard breast cancer screening procedures, and proceeded to evaluate the level of pain they endured during mammographic exam. We also acquired a range of other information which we related to the level of pain endured; we suggested a rheumatologic examination for those patients who endured the highest level of pain and then we evaluated how many patients in this subgroup were actually diagnosed with fibromyalgia. Out of the 1060 patients who participated to our study, 139 presented level 4 pain intensity; One patient did not go for rheumatologic examination; the remaining 138 underwent rheumatologic evaluation, and 50 (36%, 28-44, 95% CI) were diagnosed with fibromyalgia. Our study shows that assessing the level of pain endured by patients during standard widespread screening procedures may be an effective asset in deciding whether or not to suggest specialist rheumatologic evaluation for fibromyalgia

Feasibility, Image Quality and Clinical Evaluation of Contrast-Enhanced Breast MRI Performed in a Supine Position Compared to the Standard Prone Position

Background: To assess the feasibility, image quality and diagnostic value of contrast-enhanced breast magnetic resonance imaging (MRI) performed in a supine compared to a prone position. Methods: One hundred and fifty-one patients who had undergone a breast MRI in both the standard prone and supine position were evaluated retrospectively. Two 1.5 T MR scanners were used with the same image resolution, sequences and contrast medium in all examinations. The image quality and the number and dimensions of lesions were assessed by two expert radiologists in an independent and randomized fashion. Two different classification systems were used. Histopathology was the standard of reference. Results: Two hundred and forty MRIs from 120 patients were compared. The analysis revealed 134 MRIs with monofocal (U), 68 with multifocal (M) and 38 with multicentric (C) lesions. There was no difference between the image quality and number of lesions in the prone and supine examinations. A significant difference in the lesion extension was observed between the prone and supine position. No significant differences emerged in the classification of the lesions detected in the prone compared to the supine position. Conclusions: It is possible to perform breast MRI in a supine position with the same image quality, resolution and diagnostic value as in a prone position. In the prone position, the lesion dimensions are overestimated with a higher wash-in peak than in the supine position