Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint.

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria.

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

penalizedclr: an R package for penalized conditional logistic regression for integration of multiple omics layers.

BACKGROUND: The matched case-control design, up until recently mostly pertinent to epidemiological studies, is becoming customary in biomedical applications as well. For instance, in omics studies, it is quite common to compare cancer and healthy tissue from the same patient. Furthermore, researchers today routinely collect data from various and variable sources that they wish to relate to the case-control status. This highlights the need to develop and implement statistical methods that can take these tendencies into account. RESULTS: We present an R package penalizedclr, that provides an implementation of the penalized conditional logistic regression model for analyzing matched case-control studies. It allows for different penalties for different blocks of covariates, and it is therefore particularly useful in the presence of multi-source omics data. Both L1 and L2 penalties are implemented. Additionally, the package implements stability selection for variable selection in the considered regression model. CONCLUSIONS: The proposed method fills a gap in the available software for fitting high-dimensional conditional logistic regression models accounting for the matched design and block structure of predictors/features. The output consists of a set of selected variables that are significantly associated with case-control status. These variables can then be investigated in terms of functional interpretation or validation in further, more targeted studies.

A Systematic Review of Predictor Composition, Outcomes, Risk of Bias, and Validation of COVID-19 Prognostic Scores.

BACKGROUND: Numerous prognostic scores have been published to support risk stratification for patients with coronavirus disease 2019 (COVID-19). METHODS: We performed a systematic review to identify the scores for confirmed or clinically assumed COVID-19 cases. An in-depth assessment and risk of bias (ROB) analysis (Prediction model Risk Of Bias ASsessment Tool [PROBAST]) was conducted for scores fulfilling predefined criteria ([I] area under the curve [AUC)] ≥ 0.75; [II] a separate validation cohort present; [III] training data from a multicenter setting [≥2 centers]; [IV] point-scale scoring system). RESULTS: Out of 1522 studies extracted from MEDLINE/Web of Science (20/02/2023), we identified 242 scores for COVID-19 outcome prognosis (mortality 109, severity 116, hospitalization 14, long-term sequelae 3). Most scores were developed using retrospective (75.2%) or single-center (57.1%) cohorts. Predictor analysis revealed the primary use of laboratory data and sociodemographic information in mortality and severity scores. Forty-nine scores were included in the in-depth analysis. The results indicated heterogeneous quality and predictor selection, with only five scores featuring low ROB. Among those, based on the number and heterogeneity of validation studies, only the 4C Mortality Score can be recommended for clinical application so far. CONCLUSIONS: The application and translation of most existing COVID scores appear unreliable. Guided development and predictor selection would have improved the generalizability of the scores and may enhance pandemic preparedness in the future.

Clinical Predictors and Outcomes of Invasive Anal Cancer for People With Human Immunodeficiency Virus in an Inception Cohort.

BACKGROUND: Due to the heterogeneity of risk for invasive anal cancer (IAC) among people with human immunodeficiency virus (PWH), we investigated predictors of IAC and described outcomes among those with a cancer diagnosis. METHODS: Using a longitudinal inception cohort of anal cancer screening, we evaluated risk factors and outcome probabilities for incident IAC in Cox models. Screening included anal cytology and digital anorectal examination, and, if results of either were abnormal, high-resolution anoscopy. RESULTS: Between 30 November 2006 and 3 March 2021, a total of 8139 PWH received care at the University of California, San Diego, with 4105 individuals undergoing screening and subsequently followed up over a median of 5.5 years. Anal cancer developed in 33 of them. IAC was more likely to develop in patients with anal high-grade squamous intraepithelial lesions (aHSILs) on initial or subsequent follow-up cytology (hazard ratio, 4.54) and a nadir CD4 cell count ≤200/µL (2.99). The joint effect of aHSILs and nadir CD4 cell count ≤200/µL amplified the hazard of IAC by 9-fold compared with the absence of both. PWH with time-updated cytology aHSIL and CD4 cell counts ≤200/µL had 5- and 10-year probabilities of IAC of 3.40% and 4.27%, respectively. Twelve individuals with cancer died, 7 (21% of the total 33) due to cancer progression, and they had clinical stage IIIA or higher cancer at initial diagnosis. CONCLUSIONS: PWH with both aHSIL and a nadir CD4 cell count ≤200/µL have the highest risk of IAC. PWH who died due to IAC progression had clinical stage IIIA cancer or higher at diagnosis, highlighting the importance of early diagnosis through high-resolution anoscopic screening.

Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens.

Climate change is a threat to sustainable livestock production and livelihoods in the tropics. It has adverse impacts on feed and water availability, disease prevalence, production, environmental temperature, and biodiversity. Unravelling the drivers of local adaptation and understanding the underlying genetic variation in random mating indigenous livestock populations informs the design of genetic improvement programmes that aim to increase productivity and resilience. In the present study, we combined environmental, genomic, and phenotypic information of Ethiopian indigenous chickens to investigate their environmental adaptability. Through a hybrid sampling strategy, we captured wide biological and ecological variabilities across the country. Our environmental dataset comprised mean values of 34 climatic, vegetation and soil variables collected over a thirty-year period for 260 geolocations. Our biological dataset included whole genome sequences and quantitative measurements (on eight traits) from 513 individuals, representing 26 chicken populations spread along 4 elevational gradients (6-7 populations per gradient). We performed signatures of selection analyses ([Formula: see text] and XP-EHH) to detect footprints of natural selection, and redundancy analyses (RDA) to determine genotype-environment and genotype-phenotype-associations. RDA identified 1909 outlier SNPs linked with six environmental predictors, which have the highest contributions as ecological drivers of adaptive phenotypic variation. The same method detected 2430 outlier SNPs that are associated with five traits. A large overlap has been observed between signatures of selection identified by[Formula: see text]and XP-EHH showing that both methods target similar selective sweep regions. Average genetic differences measured by [Formula: see text] are low between gradients, but XP-EHH signals are the strongest between agroecologies. Genes in the calcium signalling pathway, those associated with the hypoxia-inducible factor (HIF) transcription factors, and sports performance (GALNTL6) are under selection in high-altitude populations. Our study underscores the relevance of landscape genomics as a powerful interdisciplinary approach to dissect adaptive phenotypic and genetic variation in random mating indigenous livestock populations.

CD8+CD103+PD1+TIM3+ T cells in glioblastoma microenvironment correlate with prognosis.

Glioblastoma, isocitrate dehydrogenase-wildtype (GB), is the most common and aggressive primary brain malignancy with poor outcome. Immune checkpoint inhibitors (ICIs) have been tested in GB and, despite disappointing results, the identification of a small subgroup of responders underlies the need to improve our understanding of the tumour microenvironment (TME) immunity. This study aimed to determine whether the expression of selected immune checkpoints on tissue-resident memory T cells (Trm) may predict patient outcome. We conducted a single cohort observational study. Tumour samples were collected from 45 patients with histologically confirmed GB (WHO grade 4) and processed to obtain single-cell suspensions. Patients were assessed for the correlation of Trm phenotype with overall survival (OS) or progression-free survival (PFS) using multiparametric flow cytometry and uni/multivariate analyses. Levels of Trm expressing programmed cell death protein 1 (PD1) and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) were found to be linked to clinical outcome. Low frequency of Trm expressing PD1 or TIM3 or both markers defined subgroups as independent positive prognostic factors for patient survival. On multivariate analysis, low CD8+CD103+PD1+TIM3+ Trm and Karnofsky performance status (KPS) ≥70 were confirmed to be the most predictive independent factors associated with longer OS (hazard ratios-HR [95%CI]: 0.14 [0.04-0.52] p < 0.001, 0.39 [0.16-0.96] p = 0.04, respectively). The CD8+CD103+ Trm subgroups were also age-related predictors for survival in GB.

International Multicenter Study of Ultra-Low GRWR Grafts in Adult Living Donor Liver Transplantation.

Decreasing the graft size in living donor liver transplantation (LDLT) increases the risk of early allograft dysfunction. Graft-to-recipient-weight-ratio (GRWR) of 0.8 is considered the threshold. There is evidence that smaller volume grafts may also provide equally good outcomes, the cut-off of which remains unknown. In this retrospective multi-center study, 92 adult LDLT with a final GRWR<=0.6 performed at 12 international liver transplant (LT) centers over a 3-year period were included. Perioperative data including preoperative status, portal flow hemodynamics (PFH) and portal flow modulation (PFM), development of SFSS, morbidity and mortality was collated and analyzed. Thirty-two (36.7%) patients developed SFSS and this was associated with increased 30-day, 90-day and one-year mortality. Pre-operative MELD and inpatient status were independent predictors for SFSS (p<0.05). Pre-LT renal dysfunction was an independent predictor of survival (Hazard ratio- 3.1;95% ci 1.1,8.9, p=0.035). PFH or PFM were not predictive of SFSS or survival. We report the largest ever multi-center study of LDLT outcomes using ultralow-GRWR grafts and for the first-time validate the ILTS-iLDLT-LTSI consensus definition and grading of SFSS. Pre-operative recipient condition rather than GRWR and PFH were independent predictors of SFSS. Algorithms to predict SFSS and LT outcomes should incorporate recipient factors along with GRWR.

Delays in presentation, diagnosis, and treatment in Sudanese women with breast cancer: a cross-sectional study.

BACKGROUND: The poor prognosis of breast cancer in Sudan could be due to delayed treatment and diagnosis at an advanced stage. Our study aimed to assess the extent of delays from onset of symptoms to treatment in Sudanese women with breast cancer, as well as identify factors contributing to these delays. MATERIALS AND METHODS: We conducted a multi-center cross sectional study between March and April 2023. Data were collected from the medical records and interviews with women with breast cancer in the two main oncology centers in Sudan. Linear regression was used to identify the predictors of delayed presentation. RESULTS: We interviewed 601 women with breast cancer. The majority of women (50.1%) were diagnosed at locally advanced or metastatic disease. The median interval from the onset of symptoms to receiving oncologic treatment was 221 days (IQR = 92, 496). The longest delay was the presentation delay 61 (31 244) days. The median duration for diagnosis delay and treatment delay was 21 (10.57) days and 27 (10.64) days, respectively. Predictors of early presentation included, being young (ß = -5.3; 95% CI = 0.06 to 10), married (ß = -264; 95% CI = -427 to -101), divorced (ß = -306; 95% CI = -549 to -63), or widowed (ß = -320; 95% CI = --543 to -97), urban residence (ß = -107; 95% CI = -213 to -2.3), and seeking traditional healer (ß = -204; 95% CI = -383 to -26). CONCLUSION: Most Sudanese women with breast cancer experience significant patient delays, often presenting at advanced stages. Factors like being single, older, and living in rural areas contribute to these delays. Increasing breast cancer education, improving healthcare access and addressing sociodemographic barriers can potentially expedite diagnosis and improve outcomes.

Molecular Markers of Response to Anti-PD1 Therapy in Advanced Hepatocellular Carcinoma.

BACKGROUND & AIMS: Single-agent anti-PD1 checkpoint inhibitors convey outstanding clinical benefits in a small fraction (∼20%) of patients with advanced hepatocellular carcinoma (aHCC) but the molecular mechanisms determining response are unknown. To fill this gap, we herein analyze the molecular and immune traits of aHCC in patients treated with anti-PD1. METHODS: Overall, 111 tumor samples from patients with aHCC were obtained from 13 centers before systemic therapies. We performed molecular analysis and immune deconvolution using whole-genome expression data (n = 83), mutational analysis (n = 72), and histologic evaluation with an endpoint of objective response. RESULTS: Among 83 patients with transcriptomic data, 28 were treated in frontline, whereas 55 patients were treated after tyrosine kinase inhibitors (TKI) either in second or third line. Responders treated in frontline showed upregulated interferon-γ signaling and major histocompatibility complex II-related antigen presentation. We generated an 11-gene signature (IFNAP), capturing these molecular features, which predicts response and survival in patients treated with anti-PD1 in frontline. The signature was validated in a separate cohort of aHCC and >240 patients with other solid cancer types where it also predicted response and survival. Of note, the same signature was unable to predict response in archival tissue of patients treated with frontline TKIs, highlighting the need for fresh biopsies before immunotherapy. CONCLUSION: Interferon signaling and major histocompatibility complex-related genes are key molecular features of HCCs responding to anti-PD1. A novel 11-gene signature predicts response in frontline aHCC, but not in patients pretreated with TKIs. These results must be confirmed in prospective studies and highlights the need for biopsies before immunotherapy to identify biomarkers of response.

Facial emotion recognition in individuals with mild cognitive impairment: An exploratory study.

Understanding facial emotions is fundamental to interact in social environments and modify behavior accordingly. Neurodegenerative processes can progressively transform affective responses and affect social competence. This exploratory study examined the neurocognitive correlates of face recognition, in individuals with two mild cognitive impairment (MCI) etiologies (prodromal to dementia - MCI, or consequent to Parkinson's disease - PD-MCI). Performance on the identification and memorization of neutral and emotional facial expressions was assessed in 31 individuals with MCI, 26 with PD-MCI, and 30 healthy controls (HC). Individuals with MCI exhibited selective impairment in recognizing faces expressing fear, along with difficulties in remembering both neutral and emotional faces. Conversely, individuals with PD-MCI showed no differences compared with the HC in either emotion recognition or memory. In MCI, no significant association emerged between the memory for facial expressions and cognitive difficulties. In PD-MCI, regression analyses showed significant associations with higher-level cognitive functions in the emotional memory task, suggesting the presence of compensatory mechanisms. In a subset of participants, voxel-based morphometry revealed that the performance on emotional tasks correlated with regional changes in gray matter volume. The performance in the matching of negative expressions was predicted by volumetric changes in brain areas engaged in face and emotional processing, in particular increased volume in thalamic nuclei and atrophy in the right parietal cortex. Future studies should leverage on neuroimaging data to determine whether differences in emotional recognition are mediated by pathology-specific atrophic patterns.

Degree of COVID-19 severity and mortality in stroke: correlation of clinical and laboratory parameters.

BACKGROUND: Stroke is one of the neurological manifestations of COVID-19, leading to a significant risk of morbidity and mortality. Clinical manifestations and laboratory parameters were investigated to determine mortality predictors in this case. METHOD: The case control study was conducted at Dr. Sardjito General Hospital,Yogyakarta, Indonesia, with data collected between July 2020 and August 2021. All recorded clinical and laboratory data from acute stroke patients with confirmed COVID-19 were collected. Baseline characteristics, bivariate, and multivariate analyses were assessed to determine significant predictors for mortality. RESULT: This study involved 72 subjects with COVID-19 and stroke. The majority experienced ischemic stroke, with hypertension as the most prevalent comorbidity. Notably, 45.8% of subjects (p < 0.05) loss of consciousness and 72.2% of exhibited motor deficits (p < 0.05). Severe degree of COVID-19 was observed in 52.8% of patients, with respiratory distress and death rates of 56.9% and 58.3%. Comparison of surviving and deceased groups highlighted significant differences in various clinical and laboratory characteristics differences. Hazard ratio (HR) analysis identified loss of consciousness (HR = 2.68; p = 0.01), motor deficit (HR = 2.34; p = 0.03), respiratory distress (HR = 81.51; p < 0.001), and monocyte count (HR:1.002; p = 0.04) as significant predictors of mortality. CONCLUSION: Mortality in COVID-19 patients with stroke was significantly associated with loss of consciousness, motor deficit, respiratory distress, and raised monocyte count. The risk of mortality is heightened when multiple factors coexist.

Exome and genome sequencing in a heterogeneous population of patients with rare disease: Identifying predictors of a diagnosis.

PURPOSE: Exome (ES) and genome sequencing (GS) are increasingly being utilized for individuals with rare and undiagnosed diseases; however, guidelines on their use remain limited. This study aimed to identify factors associated with diagnosis by ES and/or GS in a heterogeneous population of patients with rare and undiagnosed diseases. METHODS: In this case control study, we reviewed data from 400 diagnosed and 400 undiagnosed randomly selected participants in the Undiagnosed Diseases Network, all of whom had undergone ES and/or GS. We analyzed factors associated with receiving a diagnosis by ES and/or GS. RESULTS: Factors associated with a decreased odds of being diagnosed included adult symptom onset, singleton sequencing, and having undergone ES and/or GS before acceptance to the Undiagnosed Diseases Network (48%, 51%, and 32% lower odds, respectively). Factors that increased the odds of being diagnosed by ES and/or GS included having primarily neurological symptoms and having undergone prior chromosomal microarray testing (44% and 59% higher odds, respectively). CONCLUSION: We identified several factors that were associated with receiving a diagnosis by ES and/or GS. This will ideally inform the utilization of ES and/or GS and help manage expectations of individuals and families undergoing these tests.

Risk factors for invasive pulmonary aspergillosis in patients with severe fever with thrombocytopenia syndrome: A multicenter retrospective study.

Invasive pulmonary aspergillosis (IPA) is a life-threatening complication in patients with severe fever with thrombocytopenia syndrome (SFTS), yet SFTS-associated IPA (SAPA)'s risk factors remain undefined. A multicenter retrospective cohort study across Hubei and Anhui provinces (May 2013-September 2022) utilized least absolute shrinkage and selection operator (LASSO) regression for variable selection. Multivariable logistic regression identified independent predictors of SAPA, Cox regression highlighted mortality-related risk factors. Of the 1775 screened SFTS patients, 1650 were included, with 169 developing IPA, leading to a 42-day mortality rate of 26.6% among SAPA patients. Multivariable logistic regression revealed SAPA risk factors including advanced age, petechia, hemoptysis, tremor, low albumin levels, elongated activated partial thromboplastin time (APTT), intensive care unit (ICU) admission, glucocorticoid usage, intravenous immunoglobulin (IVIG) and prolonged hospital stays. Cox regression identified predictors of 42-day mortality, including ecchymosis at venipuncture sites, absence of ICU admission, elongated prothrombin time (PT), vasopressor and glucocorticoid use, non-antifungals. Nomograms constructed on these predictors registered concordance indexes of 0.855 (95% CI: 0.826-0.884) and 0.778 (95% CI: 0.702-0.854) for SAPA onset and 42-day mortality, respectively. Lower survival rates for SAPA patients treated with glucocorticoids (p < 0.001) and improved 14-day survival with antifungal therapy (p = 0.036). Improving IPA management in SFTS-endemic areas is crucial, with effective predictive tool.

Osteoarthritis year in review 2023: Epidemiology & therapy.

OBJECTIVE: To highlight some important findings from osteoarthritis (OA) epidemiology and therapy research undertaken over the past year. METHODS: Search of MEDLINE and EMBASE databases between April 1, 2022 to March 3, 2023 using "exp *Osteoarthritis/" as the preliminary search term. The search was limited to articles published in English and including human subjects. Final inclusions were based on perceived importance and results that may inform improved identification of risk factors or OA treatments, as well as OA subgroups of potential relevance to risk factors or treatment approaches. RESULTS: 3182 studies were screened, leaving 208 eligible for inclusion. This narrative review of thirty-three selected studies was arranged into: a) OA predictors - population-based studies, b) Specific predictors of OA and OA outcome; c) Intra-articular injections, and d) OA phenotypes. There was some suggestion of sex differences in predictors of incidence or outcomes. Body mass index changes appear largely to affect knee OA outcomes. Evidence points to a lack of benefit of viscosupplementation in knee OA; findings were variable for other injectables. Studies of OA phenotypes reveal potentially relevant clinical and pathophysiological differences. CONCLUSIONS: Identifying risk factors for the incidence/progression of OA represents an ongoing and important area of OA research. Sex may play a role in this understanding and bears consideration and further study. For knee injectables other than viscosupplementation, additional high-quality trials appear warranted. Continued investigation and application of phenotyping across the OA disease, illness and care spectrum may be key to developing disease-modifying agents and their appropriate selection for individuals.

Predictors of DAPSA28 remission in patients with psoriatic arthritis initiating a first TNF inhibitor: results from 13 European registries.

OBJECTIVES: In bio-naïve patients with PsA initiating a TNF inhibitor (TNFi), we aimed to identify baseline predictors of Disease Activity index for PsA in 28 joints (DAPSA28) remission (primary objective) and DAPSA28 moderate response at 6 months, as well as drug retention at 12 months across 13 European registries. METHODS: Baseline demographic and clinical characteristics were retrieved and the three outcomes investigated per registry and in pooled data, using logistic regression analyses on multiply imputed data. In the pooled cohort, selected predictors that were either consistently positive or negative across all three outcomes were defined as common predictors. RESULTS: In the pooled cohort (n = 13 369), 6-month proportions of remission, moderate response and 12-month drug retention were 25%, 34% and 63% in patients with available data (n = 6954, n = 5275 and n = 13 369, respectively). Five common baseline predictors of remission, moderate response and 12-month drug retention were identified across all three outcomes. The odds ratios (95% CIs) for DAPSA28 remission were: age, per year: 0.97 (0.96-0.98); disease duration, years (<2 years as reference): 2-3 years: 1.20 (0.89-1.60), 4-9 years: 1.42 (1.09-1.84), ≥10 years: 1.66 (1.26-2.20); men vs women: 1.85 (1.54-2.23); CRP of >10 vs ≤10 mg/l: 1.52 (1.22-1.89) and 1 mm increase in patient fatigue score: 0.99 (0.98-0.99). CONCLUSION: Baseline predictors of remission, response and adherence to TNFi therapy were identified, of which five were common for all three outcomes, indicating that the predictors emerging from our pooled cohort may be considered generalizable from country level to disease level.

A nomogram based on clinical factors and CT radiomics for predicting anti-MDA5+ DM complicated by RP-ILD.

OBJECTIVES: Anti-melanoma differentiation-associated gene 5 antibody-positive (anti-MDA5+) DM complicated by rapidly progressive interstitial lung disease (RP-ILD) has a high incidence and poor prognosis. The objective of this study was to establish a model for the prediction and early diagnosis of anti-MDA5+ DM-associated RP-ILD based on clinical manifestations and imaging features. METHODS: A total of 103 patients with anti-MDA5+ DM were included. The patients were randomly split into training and testing sets of 72 and 31 patients, respectively. After image analysis, we collected clinical, imaging and radiomics features from each patient. Feature selection was performed first with the minimum redundancy and maximum relevance algorithm and then with the best subset selection method. The final remaining features comprised the radscore. A clinical model and imaging model were then constructed with the selected independent risk factors for the prediction of non-RP-ILD and RP-ILD. We also combined these models in different ways and compared their predictive abilities. A nomogram was also established. The predictive performances of the models were assessed based on receiver operating characteristics curves, calibration curves, discriminability and clinical utility. RESULTS: The analyses showed that two clinical factors, dyspnoea (P = 0.000) and duration of illness in months (P = 0.001), and three radiomics features (P = 0.001, 0.044 and 0.008, separately) were independent predictors of non-RP-ILD and RP-ILD. However, no imaging features were significantly different between the two groups. The radiomics model built with the three radiomics features performed worse than the clinical model and showed areas under the curve (AUCs) of 0.805 and 0.754 in the training and test sets, respectively. The clinical model demonstrated a good predictive ability for RP-ILD in MDA5+ DM patients, with an AUC, sensitivity, specificity and accuracy of 0.954, 0.931, 0.837 and 0.847 in the training set and 0.890, 0.875, 0.800 and 0.774 in the testing set, respectively. The combination model built with clinical and radiomics features performed slightly better than the clinical model, with an AUC, sensitivity, specificity and accuracy of 0.994, 0.966, 0.977 and 0.931 in the training set and 0.890, 0.812, 1.000 and 0.839 in the testing set, respectively. The calibration curve and decision curve analyses showed satisfactory consistency and clinical utility of the nomogram. CONCLUSION: Our results suggest that the combination model built with clinical and radiomics features could reliably predict the occurrence of RP-ILD in MDA5+ DM patients.

Clinicopathological Predictors of Positive Resection Margins in Breast-Conserving Surgery.

BACKGROUND: Ductal carcinoma in situ (DCIS) is associated with risk of positive resection margins following breast-conserving surgery (BCS) and subsequent reoperation. Prior reports grossly underestimate the risk of margin positivity with IBC containing a DCIS component (IBC + DCIS) due to patient-level rather than margin-level analysis. OBJECTIVE: The aim of this study was to delineate the relative risk of IBC + DCIS compared with pure IBC (without a DCIS component) on margin positivity through detailed margin-level interrogation. METHODS: A single institution, retrospective, observational cohort study was conducted in which pathology databases were evaluated to identify patients who underwent BCS over 5 years (2014-2019). Margin-level interrogation included granular detail into the extent, pathological subtype and grade of disease at each resection margin. Predictors of a positive margin were computed using multivariate regression analysis. RESULTS: Clinicopathological details were examined from 5454 margins from 909 women. The relative risk of a positive margin with IBC + DCIS versus pure IBC was 8.76 (95% confidence interval [CI] 6.64-11.56) applying UK Association of Breast Surgery guidelines, and 8.44 (95% CI 6.57-10.84) applying the Society of Surgical Oncology/American Society for Radiation Oncology guidelines. Independent predictors of margin positivity included younger patient age (0.033, 95% CI 0.006-0.060), lower specimen weight (0.045, 95% CI 0.020-0.069), multifocality (0.256, 95% CI 0.137-0.376), lymphovascular invasion (0.138, 95% CI 0.068-0.208) and comedonecrosis (0.113, 95% CI 0.040-0.185). CONCLUSIONS: Compared with pure IBC, the relative risk of a positive margin with IBC + DCIS is approximately ninefold, significantly higher than prior estimates. This margin-level methodology is believed to represent the impact of DCIS more accurately on margin positivity in IBC.

Determination of Factors Associated with Upstage in Atypical Ductal Hyperplasia to Identify Low-Risk Patients Where Active Surveillance May be an Alternative.

BACKGROUND: Excision is routinely recommended for atypical ductal hyperplasia (ADH) found on core biopsy given cancer upstage rates of near 20%. Identifying a cohort at low-risk for upstage may avoid low-value surgery. Objectives were to elucidate factors predictive of upstage in ADH, specifically near-complete core sampling, to potentially define a group at low upstage risk. PATIENTS AND METHODS: This retrospective, cross-sectional, multi-institutional study from 2015 to 2019 of 221 ADH lesions in 216 patients who underwent excision or active observation (≥ 12 months imaging surveillance, mean follow-up 32.6 months) evaluated clinical, radiologic, pathologic, and procedural factors for association with upstage. Radiologists prospectively examined imaging for lesional size and sampling proportion. RESULTS: Upstage occurred in 37 (16.7%) lesions, 25 (67.6%) to ductal carcinoma in situ (DCIS) and 12 (32.4%) to invasive cancer. Factors independently predictive of upstage were lesion size ≥ 10 mm (OR 5.47, 95% CI 2.03-14.77, p < 0.001), pathologic suspicion for DCIS (OR 12.29, 95% CI 3.24-46.56, p < 0.001), and calcification distribution pattern (OR 8.08, 95% CI 2.04-32.00, p = 0.003, "regional"; OR 19.28, 95% CI 3.47-106.97, p < 0.001, "linear"). Near-complete sampling was not correlated with upstage (p = 0.64). All three significant predictors were absent in 65 (29.4%) cases, with a 1.5% upstage rate. CONCLUSIONS: The upstage rate among 221 ADH lesions was 16.7%, highest in lesions ≥ 10 mm, with pathologic suspicion of DCIS, and linear/regional calcifications on mammography. Conversely, 30% of the cohort exhibited all low-risk factors, with an upstage rate < 2%, suggesting that active surveillance may be permissible in lieu of surgery.

Clinical impact of left atrial remodeling pattern in patients with atrial fibrillation: Comparison of volumetric, electrical, and combined remodeling.

INTRODUCTION: Atrial fibrillation (AF) is accompanied by various types of remodeling, including volumetric enlargement and histological degeneration. Electrical remodeling reportedly reflects histological degeneration. PURPOSE: To clarify the differences in determinants and clinical impacts among types of remodeling. METHODS: This observational study included 1118 consecutive patients undergoing initial ablation for AF. Patients were divided into four groups: minimal remodeling (left atrial volume index [LAVI] < mean value and no low-voltage area [LVA], n = 477); volumetric remodeling (LAVI ≥ mean value and no LVA, n = 361); electrical remodeling (LAVI < mean value and LVA presence, n = 96); and combined remodeling (LAVI ≥ mean value and LVA presence, n = 184). AF recurrence and other clinical outcomes were followed up for 2 and 5 years, respectively. RESULTS: Major determinants of each remodeling pattern were high age for electrical (odds ratio = 2.32, 95% confidence interval = 1.68-3.25) and combined remodeling (2.57, 1.88-3.49); female for electrical (3.85, 2.21-6.71) and combined remodeling (4.92, 2.90-8.25); persistent AF for combined remodeling (7.09, 3.75-13.4); and heart failure for volumetric (1.71, 1.51-2.53) and combined remodeling (2.21, 1.30-3.75). Recurrence rate after initial ablation increased in the order of minimal remodeling (20.1%), volumetric (27.4%) or electrical remodeling (36.5%), and combined remodeling (50.0%, p < .0001). A composite endpoint of heart failure, stroke, and death occurred in the order of minimal (3.4%), volumetric (7.5%) or electrical (8.3%), and combined remodeling (15.2%, p < .0001). CONCLUSION: Volumetric, electrical, and combined remodeling were each associated with a unique patient background, and defined rhythm and other clinical outcomes.