Fully Automated Measurement of the Insall-Salvati Ratio with Artificial Intelligence

Patella alta (PA) and patella baja (PB) affect 1-2% of the world population, but are often underreported, leading to potential complications like osteoarthritis. The Insall-Salvati ratio (ISR) is commonly used to diagnose patellar height abnormalities. Artificial intelligence (AI) keypoint models show promising accuracy in measuring and detecting these abnormalities.An AI keypoint model is developed and validated to study the Insall-Salvati ratio on a random population sample of lateral knee radiographs. A keypoint model was trained and internally validated with 689 lateral knee radiographs from five sites in a multi-hospital urban healthcare system after IRB approval. A total of 116 lateral knee radiographs from a sixth site were used for external validation. Distance error (mm), Pearson correlation, and Bland-Altman plots were used to evaluate model performance. On a random sample of 2647 different lateral knee radiographs, mean and standard deviation were used to calculate the normal distribution of ISR. A keypoint detection model had mean distance error of 2.57 ± 2.44 mm on internal validation data and 2.73 ± 2.86 mm on external validation data. Pearson correlation between labeled and predicted Insall-Salvati ratios was 0.82 [95% CI 0.76-0.86] on internal validation and 0.75 [0.66-0.82] on external validation. For the population sample of 2647 patients, there was mean ISR of 1.11 ± 0.21. Patellar height abnormalities were underreported in radiology reports from the population sample. AI keypoint models consistently measure ISR on knee radiographs. Future models can enable radiologists to study musculoskeletal measurements on larger population samples and enhance our understanding of normal and abnormal ranges.

A 20-year Follow-up of the International Early Lung Cancer Action Program (I-ELCAP)

Background The low-dose CT (≤3 mGy) screening report of 1000 Early Lung Cancer Action Program (ELCAP) participants in 1999 led to the International ELCAP (I-ELCAP) collaboration, which enrolled 31 567 participants in annual low-dose CT screening between 1992 and 2005. In 2006, I-ELCAP investigators reported the 10-year lung cancer-specific survival of 80% for 484 participants diagnosed with a first primary lung cancer through annual screening, with a high frequency of clinical stage I lung cancer (85%). Purpose To update the cure rate by determining the 20-year lung cancer-specific survival of participants diagnosed with first primary lung cancer through annual low-dose CT screening in the expanded I-ELCAP cohort. Materials and Methods For participants enrolled in the HIPAA-compliant prospective I-ELCAP cohort between 1992 and 2022 and observed until December 30, 2022, Kaplan-Meier survival analysis was used to determine the 10- and 20-year lung cancer-specific survival of participants diagnosed with first primary lung cancer through annual low-dose CT screening. Eligible participants were aged at least 40 years and had current or former cigarette use or had never smoked but had been exposed to secondhand tobacco smoke. Results Among 89 404 I-ELCAP participants, 1257 (1.4%) were diagnosed with a first primary lung cancer (684 male, 573 female; median age, 66 years; IQR, 61-72), with a median smoking history of 43.0 pack-years (IQR, 29.0-60.0). Median follow-up duration was 105 months (IQR, 41-182). The frequency of clinical stage I at pretreatment CT was 81% (1017 of 1257). The 10-year lung cancer-specific survival of 1257 participants was 81% (95% CI: 79, 84) and the 20-year lung cancer-specific survival was 81% (95% CI: 78, 83), and it was 95% (95% CI: 91, 98) for 181 participants with pathologic T1aN0M0 lung cancer. Conclusion The 10-year lung cancer-specific survival of 80% reported in 2006 for I-ELCAP participants enrolled in annual low-dose CT screening and diagnosed with a first primary lung cancer has persisted, as shown by the updated 20-year lung cancer-specific survival for the expanded I-ELCAP cohort. © RSNA, 2023 See also the editorials by Grenier and by Sequist and Olazagasti in this issue.

Deep Learning for Multi-Tissue Segmentation and Fully Automatic Personalized Biomechanical Models from BACPAC Clinical Lumbar Spine MRI

STUDY DESIGN

In vivo retrospective study of fully automatic quantitative imaging feature extraction from clinically acquired lumbar spine magnetic resonance imaging (MRI).

OBJECTIVE

To demonstrate the feasibility of substituting automatic for human-demarcated segmentation of major anatomic structures in clinical lumbar spine MRI to generate quantitative image-based features and biomechanical models.

SETTING

Previous studies have demonstrated the viability of automatic segmentation applied to medical images; however, the feasibility of these networks to segment clinically acquired images has not yet been demonstrated, as they largely rely on specialized sequences or strict quality of imaging data to achieve good performance.

METHODS

Convolutional neural networks were trained to demarcate vertebral bodies, intervertebral disc, and paraspinous muscles from sagittal and axial T1-weighted MRIs. Intervertebral disc height, muscle cross-sectional area, and subject-specific musculoskeletal models of tissue loading in the lumbar spine were then computed from these segmentations and compared against those computed from human-demarcated masks.

RESULTS

Segmentation masks, as well as the morphological metrics and biomechanical models computed from those masks, were highly similar between human- and computer-generated methods. Segmentations were similar, with Dice similarity coefficients of 0.77 or greater across networks, and morphological metrics and biomechanical models were similar, with Pearson R correlation coefficients of 0.69 or greater when significant.

CONCLUSIONS

This study demonstrates the feasibility of substituting computer-generated for human-generated segmentations of major anatomic structures in lumbar spine MRI to compute quantitative image-based morphological metrics and subject-specific musculoskeletal models of tissue loading quickly, efficiently, and at scale without interrupting routine clinical care.

Pathophysiologic mechanism for MYOcarditis in COVID-19 VAccinations ("MYOVAx" Study)

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NMRC COVID-19 Research Fund

Objective

This is the first prospective cohort study in Singapore to investigate the COVID-19 vaccine-associated myocarditis to understand its pathophysiology.

Introduction

Acute myocarditis and other cardiovascular symptoms have been observed to be associated with the two mRNA-based coronavirus disease 2019 (COVID-19) vaccines—namely Pfizer-BioNTech BNT162b2 and Moderna mRNA-1273)—currently in-use in Singapore. The mechanisms through which myocarditis occurs are unknown, hence our study aims to understand the pathophysiology of myocarditis associated with COVID-19 vaccines.

Methods

Patients with onset of cardiac manifestations were recruited from multiple hospital outpatient clinics between November 2021 and September 2022. Clinical history and physical examination data was collected with blood sample collection, echocardiography, 12-lead electrocardiogram (ECG), coronary angiography and magnetic resonance imaging (MRI) at recruitment and 6-month follow-up. Analysis of biomarkers, genetic, serological and MRI data was conducted.

Results

As of 6 September 2022, a total of 5 patients have been enrolled (4 males, 1 female). The most commonly reported symptoms across all patients were chest pain/discomfort (80%), followed by palpitations (40%). MRI evidence of myocarditis has been detected in 2 (50%) of the male patients, of which both reported two or more symptoms occurring 1-2 days post-vaccination. Both patients have each received at least two doses of either the Pfizer-BioNTech BNT162b2 vaccine or Moderna mRNA-1273 vaccine. Their MRI findings were consistent with myocarditis. On late gadolinium enhancement (LGE) imaging, epicardial enhancement at the basal inferolateral segment and mid-wall enhancement at the apical anterior, lateral and inferior walls were observed in one patient. Patchy, mid-wall LGE in the basal inferior/inferolateral wall was observed in the other patient. No MRI evidence of myocarditis was available for the sole female patient.

Conclusion

While more data is needed to definitively prove the association of the two mRNA-based Pfizer-BioNTech BNT162b2 and Moderna mRNA-1273 COVID-19 vaccines with post-vaccination myocarditis, we believe our findings may support further investigations to enable risk stratification for vaccine-associated myocarditis and identify potential preventative strategies accordingly.

NIMG-15. INTEGRATED RADIOGRAPHIC AND PATHOLOGICAL ANALYSIS OF MALIGNANT PERIPHERAL NERVE SHEATH TUMORS (MPNSTS) REVEALS IMAGING CORRELATES OF MOLECULAR ALTERATIONS AND CLINICAL OUTCOME

Malignant peripheral nerve sheath tumors (MPNSTs) are the most common cause of death in patients with neurofibromatosis type 1 (NF-1) yet non-invasive diagnosis and risk stratification of NF-1-associated peripheral nerve tumors remains challenging. Moreover, the relationship between radiographic features and pathologic measures such as mitotic index and necrosis, or molecular markers of malignant transformation such as H3K27 trimethylation and Schwann cell marker (S100B, SOX10) expression remain unknown. Here, we integrate positron emission tomography (PET) (n=32 studies from 18 patients) and magnetic resonance imaging (MRI) (n=20 studies from 20 patients) with immunohistochemical analysis and clinical follow-up in a total of 20 patients with pathologically confirmed MPNST diagnosis. The median age was 33 years (range 5-74 years), n = 11 were male (55%) and n=13 (65%) harbored a clinical diagnosis of NF-1. Anatomically, n=6 (30%) tumors arose near the spine, n=5 (25%) arose in the extremities, and n=4 (20%) arose in the sacrum. By PET, the average preoperative SUVmax was 8.53 with a trend toward increased SUVmax in Ki-67 high tumors (SUVmax 10.58 vs. 6.47, p=0.08). No significant differences in SUVmax based on H3K27 trimethylation, SOX10, or S100B expression was noted. The appearance of cystic necrosis by MRI was significantly associated with H3K27 trimethylation loss (Chi-square p=0.04) with a trend toward increased KI-67 labeling (43% vs. 24%, p = 0.07), suggesting cystic necrosis identifies aggressive lesions. No other features were correlated with H3K27 trimethylation status or Ki-67 labeling index. With regard to clinical outcome, dichotomized SUVmax identified patient subgroups with significant differences in overall survival (OS), with high SUVmax tumors demonstrating improved survival (median OS: 250 months vs. 60 months, log-rank test p=0.02). Our data support a relationship between radiographic features, histopathologic characteristics and clinical outcomes. Future work will include longitudinal analysis, validation in larger, multi-institutional cohorts and incorporation of radiomic approaches.

Institution-wide shape analysis of 3D spinal curvature and global alignment parameters

The spine is an articulated, 3D structure with 6 degrees of translational and rotational freedom. Clinical studies have shown spinal deformities are associated with pain and functional disability in both adult and pediatric populations. Clinical decision making relies on accurate characterization of the spinal deformity and monitoring of its progression over time. However, Cobb angle measurements are time-consuming, are limited by interobserver variability, and represent a simplified 2D view of a 3D structure. Instead, spine deformities can be described by 3D shape parameters, addressing the limitations of current measurement methods. To this end, we develop and validate a deep learning algorithm to automatically extract the vertebral midline (from the upper endplate of S1 to the lower endplate of C7) for frontal and lateral radiographs. Our results demonstrate robust performance across datasets and patient populations. Approximations of 3D spines are reconstructed from the unit normalized midline curves of 20,118 pairs of full spine radiographs belonging to 15,378 patients acquired at our institution between 2008 and 2020. The resulting 3D dataset is used to describe global imbalance parameters in the patient population and to build a statistical shape model to describe global spine shape variations in preoperative deformity patients via eight interpretable shape parameters. The developed method can identify patient subgroups with similar shape characteristics without relying on an existing shape classification system.

Plasma desmosine as a biomarker in acute aortic syndrome

Introduction

Acute aortic syndromes (AAS) include aortic dissection, intramural haematoma and penetrating aortic ulcer, all of which are caused by aortic wall failure and associated with significant mortality. Although, treatment options currently include early surgical intervention or aggressive medical management, disease progression and devastating complications remain commonplace. Early diagnosis of AAS as well as ability to predict those at the highest risk of disease progression would represent significant progress in the care these patients receive. Desmosine is the cross-link component in the elastin molecule and is exclusively released from mature elastin breakdown, thus is a physiologically relevant biomarker of aortic elastin degradation. The aim of the study was to test the hypothesis that plasma desmosine (pDES) concentrations are elevated in AAS and has prognostic value in indentifying those at risk of significant disease progression.

Method

Patients over 25 years old with radiologically confirmed acute aortic syndrome were recruited as part of a prospective observational study (NCT03647566). Demographic details, AAS sub-category, time from index acute aortic syndrome event and pDES concentrations measured by stable isotope dilution LC-MS/MS were recorded at baseline. Baseline and follow up maximal aortic diameters were measured on contrast-enhanced computed tomography (CT) and change in aortic diameter over time was calculated. Control plasma desmosine samples were obtained at a 2:1 ratio control subjects participating in the United Kingdom Aneurysm Growth Study. Data presented as mean±standard deviation or median [interquartile range].

Results

Plasma desmosine concentrations were measured in 53 patients (64 [53 to 71] years) with acute aortic syndromes and 106 control subjects (53 [44 to 60] years). In patients with AAS, pDES concentrations were almost twice those of control subjects (0.58±0.26 vs 0.27±0.07, p<0.001). In those with AAS, plasma desmosine concentrations were seen to be highest at presentation, and reduced over time from the aortic syndrome event (R=0.51, p=0.003). Plasma desmosine concentration was the only variable associated with increasing aortic diameter over time (R=0.34, p=0.014).

Conclusion

Plasma desmosine concentrations are elevated in patients with AAS, peak at the time of presentation and represents a promising biomarker for early identification and risk stratification in patients with AAS.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): British Heart FoundationTenovus Scotland Major Research GrantChief Scientist Office Catalytic Grant Plasma desmosine, time and expansionBaseline characteristics

Exaggerated elastin turnover in childhood and adolescence in Marfan syndrome – correlation with age – new insights from the AIMS trial

Background

Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder caused by mutations in the Fibrillin1 gene (FBN1) that leads to impaired elastin formation and extra-cellular matrix homeostasis. Elastin synthesis and related lamellae formation in the aorta is completed in the newborn. Thereafter further elastin turnover is thought to be minimal during life. Elastin homeostasis is little studied in patients with MFS who have been reported to have reduced elastin in their aorta and are at risk of aortic dilatation and consequent life-threatening dissection. It is not clear if elastin loss is due to reduced elastin formation in utero or accelerated degradation during life. However, aortopathy develops early in MFS with 70% of patients developing aortic dilatation by the age of 20 years. Therefore, the longitudinal and circumferential aortic growth that occurs in childhood may involve elastic lamellae remodelling that is impaired in MFS. Desmosine is the cross-link component in the elastin molecule and is exclusively released from mature elastin breakdown, thus is a physiologically relevant biomarker of elastin turnover. We hypothesise that physiologic aortic growth is associated with elastic lamellae remodelling and increased elastin turnover, detected by elevated plasma desmosine (pDES), and that elastin turnover is exaggerated during the fast-growing period in MFS.

Purpose

The aims of this study were 1. To investigate the relationship between elastin turnover and age in the control subjects, and 2. To compare the elastin turnover in MFS with control subjects.

Methods

pDES was measured by stable isotope dilution LC-MS/MS in 113 MFS subjects (48% male, mean age 18.2±9.4 (SD) years), mean aortic root 33.8±2.1mm and Z-score 3.4±2.1 in the AIMS trial at baseline before intervention, and in 109 healthy controls (46% male, mean age 26.1±9.5 years).

Results

pDES levels were associated positively with age, body surface area and negatively with diastolic BP in the control group (p=0.05 and 0.21 respectively after correcting for age). In MFS subjects pDES also positively correlated with age and male sex (p<0.05). Interestingly, the age-dependent association with pDES showed a peak distribution in both control and MFS groups (Figure 1) where teenage children expressed the highest pDES levels. MFS subjects had significantly higher pDES compared to controls before the age of 20 (p=0.01) but in adulthood, there was no difference (Figure 2).

Conclusion

Elastin turnover is highly dynamic before early adulthood, and peaks in adolescence and is exaggerated in MFS, suggesting that this period of growth is critical in developing aortopathy.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): British Heart FoundationTENOVUS Scotland Figure 1Figure 2

Echocardiographic global longitudinal strain as a marker of myocardial fibrosis predicts outcomes in aortic stenosis

Background

Left ventricular global longitudinal strain (LV-GLS) by speckle tracking echocardiography (STE) reflects intrinsic myocardial function, influenced by interstitial abnormalities. Cardiovascular magnetic resonance (CMR) detects myocardial fibrosis non-invasively, but it is limited for widespread use. We aim to establish LV-GLS as a marker of replacement myocardial fibrosis on CMR and validate the prognostic value of LV-GLS thresholds associated with fibrosis.

Methods

LV-GLS thresholds of replacement fibrosis were established in the derivation cohort: 151 patients (57±10 years; 58% males) with hypertension who underwent STE to measure LV-GLS and CMR for replacement myocardial fibrosis. Prognostic value of the thresholds was validated in a separate outcome cohort: 261 patients with moderate-severe aortic stenosis (AS; 71±12 years; 58% males; NYHA functional class I-II) and preserved LVEF ≥50%. Primary outcome was a composite of cardiovascular mortality, heart failure hospitalization, myocardial infarction and cerebrovascular events.

Results

In the derivation cohort, LV-GLS demonstrated good discrimination (c-statistics 0.74; 95% confidence interval: 0.66–0.83; P<0.001) and calibration (Hosmer-Lemeshow X2=6.37; P=0.605) for replacement fibrosis. In the outcome cohort, 52 events occurred over 16 [3.1, 42.0] months of follow-up. Patients with LV-GLS >−15.0% (corresponding to 95% specificity to rule-in myocardial fibrosis) had the worst outcomes compared to patients with LV-GLS <−21.0% (corresponding to 95% sensitivity to rule-out myocardial fibrosis) and those between −21.0 and −15.0% (log-rank P<0.001; Figure 1). Furthermore, LV-GLS offered independent prognostic value over clinical variables, AS severity, echocardiographic LVEF and E/e' (hazard ratio 1.18; 95% confidence interval: 1.07 to 1.30; P=0.001).

Conclusions

LV-GLS thresholds associated with replacement myocardial fibrosis is a novel approach to risk-stratify patients with AS and preserved LVEF (Figure 2).

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Medical Research Council Figure 1Figure 2

POS0456 EXTERNAL VALIDATION OF A MULTI-BIOMARKER-BASED CARDIOVASCULAR DISEASE RISK PREDICTION SCORE FOR RHEUMATOID ARTHRITIS PATIENTS

Background:

A novel score for predicting 3-year risk for CVD events in RA patients combines age, four traditional CVD risk factors (diabetes, hypertension, smoking, history of high-risk CVD event), a personalized assessment of RA-related inflammation based on the multi-biomarker disease activity (MBDA) score and, individually, 3 of its 12 biomarkers, TNF-R1, MMP-3 and leptin (log-transformed). This score was developed and internally validated using patient data from the Medicare database.

Objectives:

The purpose of this analysis was to externally validate the MBDA-based CVD risk prediction score in a younger cohort from the Symphony claims database.

Methods:

A cohort of patients greater than or equal to 18 years old with RA diagnosis from a rheumatologist and evidence of an RA-specific treatment, excluding patients with malignancy, past myocardial infarction (MI) or stroke, was created by a third party (Symphony) by matching medical and pharmaceutical claims and linking them to MBDA scores from a database of tests done for routine care. Medicare patients were excluded to avoid overlap with the internal validation cohort. Only the first MBDA test was used for each patient. The study endpoint was time from MBDA testing to first CVD event within a 3-year time horizon. CVD event was defined as MI or stroke, based on ICD-9 or ICD-10 diagnosis codes in hospital claims. Analyses focused on relative risk, not absolute risk, because CVD event data in Symphony may be incomplete. A univariate Cox proportional hazards regression model was fit with the MBDA-based CVD risk score as the sole predictor of time to CVD event to obtain a hazard ratio (HR) estimate (95% CI) and p-values from a likelihood ratio test (LRT). Sensitivity analyses determined HR for patient subgroups, with p-values determined for the interaction between subgroups and the MBDA-based CVD risk score. Using a multivariate Cox proportional hazard regression model, the MBDA-based CVD risk score was compared to a simpler model that included only age, sex, diabetes, hypertension, history of other CVD, smoking and CRP (log-transformed) for ability to predict time to a CVD event.

Results:

48,868 patients with 337 CVD events met eligibility criteria and had linked biomarker data. Mean age was 54.4 years. 81.7% were female (Table 1). Mean follow-up was 24.4 months. The MBDA-based CVD risk score (mean 3.3, IQR 2.8–3.8) was highly significant in univariate analysis, with HR = 3.99 (95% CI: 3.52-4.51, p = 4.4×10-95); i.e., for every 1-unit increase in risk score, the CVD event rate in this cohort was ~4 times as high. Similar results were seen in the subset of 44,379 patients <65 years old, with HR=4.26 (95% CI: 3.53-5.14, p = 1.2×10-47). In sensitivity analyses, after adjusting for multiple comparisons, there were no significant differences between HR of complementary subgroups (Figure 1). The MBDA-based CVD risk score added significant prognostic information to a simpler, clinical model (HR=2.28 [95% CI: 1.69-3.08, p = 1.6×10-7] after accounting for all other factors).

Conclusion:

The MBDA-based CVD risk prediction score has been externally validated in a cohort that is younger than and independent of the Medicare cohort used previously for test development and internal validation.

Table 1.

Cohort characteristics of RA patients with linked biomarker data and at risk for CVD events.

VariableMedian (IQR) or N (%)Total patients48,868()Age, years54 (46-60)Sex, male8,940 (18.3%)Diabetes7,974 (16.3%)Hypertension19,132 (39.2%)History of high-risk CVD event6,713 (13.7%)Smoking7,487 (15.3%)CRP, mg/L4.1 (1.4-11.5)Leptin, ng/mL24.3 (10.6-47.1)MMP-3, ng/mL21.1 (14.3-36.2)TNF-RI, ng/mL1.4 (1.1-1.7)MBDA score40 (31-48)MBDA-based CVD risk score3.3 (2.8-3.8)

Disclosure of Interests:

Jeffrey Curtis Grant/research support from: Abbvie, Amgen, BMS, Corrona, Eli Lilly, Jannsen, Myriad Genetics, Inc., Pfizer, Regeneron, Roche, and UCB., Eric Sasso Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Autoimmune, Elena Hitraya Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Autoimmune, Cheryl Chin Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Autoimmune, Richard Bamford Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Autoimmune, Rotem Ben-Shachar Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Alexander Gutin Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Darl Flake Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Brent Mabey Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Jerry Lanchbury Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc.

Assessing automated CMR contouring algorithms using systematic contour quality scoring analysis

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): SmartHeart EPSRC programme grant (www.nihr.ac.uk), London Medical Imaging and AI Centre for Value-Based Healthcare

Background

Quality measures for machine learning algorithms include clinical measures such as end-diastolic (ED) and end-systolic (ES) volume, volumetric overlaps such as Dice similarity coefficient and surface distances such as Hausdorff distance. These measures capture differences between manually drawn and automated contours but fail to capture the trust of a clinician to an automatically generated contour.

Purpose

We propose to directly capture clinicians’ trust in a systematic way. We display manual and automated contours sequentially in random order and ask the clinicians to score the contour quality. We then perform statistical analysis for both sources of contours and stratify results based on contour type.

Data

The data selected for this experiment came from the National Health Center Singapore. It constitutes CMR scans from 313 patients with diverse pathologies including: healthy, dilated cardiomyopathy (DCM), hypertension (HTN), hypertrophic cardiomyopathy (HCM), ischemic heart disease (IHD), left ventricular non-compaction (LVNC), and myocarditis. Each study contains a short axis (SAX) stack, with ED and ES phases manually annotated. Automated contours are generated for each SAX image for which manual annotation is available. For this, a machine learning algorithm trained at Circle Cardiovascular Imaging Inc. is applied and the resulting predictions are saved to be displayed in the contour quality scoring (CQS) application.

Methods: The CQS application displays manual and automated contours in a random order and presents the user an option to assign a contour quality score

1: Unacceptable, 2: Bad, 3: Fair, 4: Good. The UK Biobank standard operating procedure is used for assessing the quality of the contoured images. Quality scores are assigned based on how the contour affects clinical outcomes. However, as images are presented independent of spatiotemporal context, contour quality is assessed based on how well the area of the delineated structure is approximated. Consequently, small contours and small deviations are rarely assigned a quality score of less than 2, as they are not clinically relevant. Special attention is given to the RV-endo contours as often, mostly in basal images, two separate contours appear. In such cases, a score of 3 is given if the two disjoint contours sufficiently encompass the underlying anatomy; otherwise they are scored as 2 or 1.

Results

A total of 50991 quality scores (24208 manual and 26783 automated) are generated by five expert raters. The mean score for all manual and automated contours are 3.77 ± 0.48 and 3.77 ± 0.52, respectively. The breakdown of mean quality scores by contour type is included in Fig. 1a while the distribution of quality scores for various raters are shown in Fig. 1b.

Conclusion

We proposed a method of comparing the quality of manual versus automated contouring methods. Results suggest similar statistics in quality scores for both sources of contours.

Abstract Figure 1

Interaction of stroke volume and myocardial phenotype in patients with severe aortic stenosis referred for intervention: outcome data from the BSCMR AS700 study

Funding Acknowledgements

Type of funding sources: None.

onbehalf

The BSCMR Valve Consortium

Background

 Patients with low-flow aortic stenosis (LF-AS) have higher mortality than those with high-flow severe AS.  The conventional echocardiographic definition of LF-AS is an indexed stroke volume (SVi) &lt;35ml/m2. Whether this cut-off translates to cardiac magnetic resonance (CMR), and how CMR SVi associates with myocardial remodelling (volume/function/scar) and survival is unclear.

Purpose

 To determine the association between CMR SVi, myocardial remodelling and survival in severe symptomatic AS. 

Methods

  In a multi-centre longitudinal outcome study of patients with severe AS listed for either surgical (SAVR) or transcatheter aortic valve intervention (TAVI) at six cardiothoracic centres, survival was assessed and stratified by SVi. Patients underwent preprocedural echocardiography and CMR between January 2003 and May 2015.  Standardised core-lab analyses on pre-procedural CMR for biventricular volumes, function and scar quantification were performed. All-cause and cardiovascular mortality were tracked for a minimum of two years after AVR.

Results

 A total of 674 patients with severe AS (age 75 ± 14years; 63% male, aortic valve area 0.4 ± 0.1 cm2/m2) were included.  Patients with low SVi by CMR &lt;35ml/m2 were older and had a greater burden of comorbidities (atrial fibrillation [AF], diabetes, high BMI). Independent predictors of SVi were age, AF, increased left atrial volume, aortic valve regurgitant fraction and left ventricular mass (LV) mass index (by CMR). There was no difference in SVi with choice of intervention (TAVI vs SAVR) or presence of late gadolinium enhancement. In multivariate analysis (Table 1), SVi was associated with cardiovascular mortality in the whole cohort (HR 0.97, 95%CI 0.95-0.99, p = 0.02), and all-cause mortality after TAVI (HR 0.97, 95%CI 0.95-0.99, p = 0.006) but not SAVR (p = 0.6). Adjusted mortality hazard increases below 50ml/m2 and plateaus between 35-40ml/m2 (Figure 1A), adjusted for LGE, STS score (Society of Thoracic Surgery score) and wall thickness.

Conclusion

SVi by CMR is an independent predictor of cardiovascular mortality. Mortality hazard increases progressively below a SVi of 50mL/m2.

Abstract Figure 1

Stratifying the prognostic capability of cardiovascular magnetic resonance in severe aortic stenosis: a machine learning approach

Background

Cardiovascular magnetic resonance (CMR) demonstrates promise in improving patient risk stratification in aortic stenosis (AS). We explored whether machine learning might provide further insights into the prognostic capability of CMR parameters.

Methods

Severe AS patients (n=440) undergoing AVR were prospectively enrolled across 10 international sites, and CMR performed prior to AVR. A machine learning prediction model using a random survival forest (RSF) was trained with 29 variables, including 13 CMR, 4 echocardiography, and 12 clinical parameters, using post-AVR mortality as an outcome. The impact of the important variables on the outcome (partial dependency) was examined.

Results

The most predictive CMR parameters in the RSF model were the extracellular volume fraction (ECV%), followed by right ventricular ejection fraction (RVEF), late gadolinium enhancement (LGE%), and indexed left ventricular end-diastolic volume (LVEDVi). Regarding the partial effects, the predicted mortality increased strongly once the ECV% exceeded 26.5% (Figure 1A). The LGE% was associated with an increased risk of mortality, which reached a plateau beyond the level of 2% (Figure 1C). There were U-shaped relationships between mortality and both RVEF and LVEDVi, with the lowest mortality seen at RVEF 70% and LVEDVi 68ml/m2 (Figure 1B, D). These trends of predicted outcomes by each variable were verified in the Kaplan-Meier curves and Cox analyses (Table). In both Cox and RSF models, the predictability was substantially increased when these four CMR parameters were added to conventional clinical risk factors. An AS-CMR risk score comprised of these four parameters presented a stepwise increase in mortality with increasing adverse CMR features (p&lt;0.001).

Conclusions

Our machine learning analysis using RSF has identified ECV%, RVEF, LGE%, and LVEDVi as key prognostic markers in severe AS with a nonlinear influence of each parameter on mortality post-AVR.

Figure 1

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): This study was supported by grants from the Korean Health Technology R & D Project, Ministry of Health, Welfare & Family Affairs, Republic of Korea (HI16C0225 and HI15C0399) and the National Institute for Health Research (NIHR) infrastructure at Leeds.

Physiological performance and inflammatory markers as indicators of complications after oesophageal cancer surgery

BACKGROUND

The extent to which physiological factors influence outcome following oesophageal cancer surgery is poorly understood. This study aimed to evaluate the extent to which cardiorespiratory fitness and selected metabolic factors predicted complications after surgery for carcinoma.

METHODS

Two hundred and twenty-five consecutive patients underwent preoperative cardiopulmonary exercise testing to determine peak oxygen uptake ( V ˙ o_2peak ), anaerobic threshold and the ventilatory equivalent for carbon dioxide ( V ˙ e/ V ˙ co₂ ). Cephalic venous blood was assayed for serum C-reactive protein (CRP) and albumin levels, and a full blood count was done. The primary outcome measure was the Morbidity Severity Score (MSS).

RESULTS

One hundred and ninety-eight patients had anatomical resection. A high MSS (Clavien-Dindo grade III or above) was found in 48 patients (24·2 per cent) and was related to an increased CRP concentration (area under the receiver operating characteristic (ROC) curve (AUC) 0·62, P = 0·001) and lower V ˙ o_2peak (AUC 0·36, P = 0·003). Dichotomization of CRP levels (above 10 mg/l) and V ˙ o_2peak (below 18·6 ml per kg per min) yielded adjusted odds ratios (ORs) for a high MSS of 2·86 (P = 0·025) and 2·92 (P = 0·002) respectively. Compared with a cohort with a low Combined Inflammatory and Physiology Score (CIPS), the OR was 1·70 (95 per cent c.i. 0·85 to 3·39) for intermediate and 27·47 (3·12 to 241·69) for high CIPS (P < 0·001).

CONCLUSION

CRP and V ˙ o_2peak were independently associated with major complications after potentially curative oesophagectomy for cancer. A composite risk score identified a group of patients with a high risk of developing complications.

FRI0553 DEVELOPMENT AND VALIDATION OF A BIOMARKER-BASED CARDIOVASCULAR RISK PREDICTION SCORE IN RHEUMATOID ARTHRITIS

Background:

Rheumatoid arthritis (RA) patients are at elevated risk for cardiovascular (CV) events, but risk stratification based on CV prediction models is not part of routine rheumatology practice.

Objectives:

To develop and validate a biomarker-based CV risk prediction model and compare it to alternative risk prediction models.

Methods:

We constructed a cohort of RA patients - age ≥40 with ≥1 RA diagnosis from a rheumatologist, excluding patients with malignancy, past myocardial infarction (MI) or stroke - by linking Medicare administrative data from 2006-2016 to multi-biomarker disease activity (MBDA) test results obtained as part of routine care. The cohort was split 2:1 to create training and internal validation datasets. The composite CV outcome was MI, stroke or CV death occurring within 3 years. Clinical predictors examined were: age, sex, race, traditional CV risk factors (e.g. diabetes, hypertension, hyperlipidemia, high-risk CV conditions [e.g. angina]), RA-related factors (e.g. glucocorticoid use, MTX, number of prior biologics), adjusted MBDA score1and its 12 biomarkers, log-transformed. Backward elimination was used to remove predictors with p ≥0.05. The resulting CV risk score was compared to four prediction models (age+sex; age+sex+CRP; age+sex+diabetes+hypertension+ smoking+high risk CV [±CRP]) in the validation dataset. We evaluated: 1) incremental improvement in the likelihood ratio test (LRT) statistic, 2) discrimination (AUROC), and 3) goodness-of-fit (predicted vs. observed, based on Kaplan-Meier estimates). Validation analyses were prespecified.

Results:

30,751 RA patients with 904 CV events were linked to MBDA test results and eligible for analysis. Patient characteristics were mean (SD) age 68.7 (9.5) years; 23.4% age <65; 82% women. Comorbidities included diabetes (39%), hypertension (78%), smoking (24%) and history of high-risk CV condition (37%). RA-related features included use of glucocorticoids (58%), MTX (60%), TNFi (33%) and other biologics (16%). Mean (SD) MBDA score was 41 (14). The final covariates included in the MBDA-based CV risk score were age, diabetes, hypertension, smoking, history of high-risk CV conditions, adjusted MBDA score, leptin, TNFRI and MMP-3. Median (IQR) of the predicted 3-year CV risk was 3.4% (2.1%, 5.6%). Based on extrapolation to 10-year risk, 9.4% of patients would be considered low, 10.2% borderline, 52.2% intermediate, and 28.2% high risk per 2019 ACC/AHA guidelines.

Compared to four simpler CV prediction models, significant improvement in the LRT statistic was observed with the addition of the biomarker-based CV risk score (Figure 1). Model fit was good across deciles (Figure 2). The AUROC was 0.70. The MBDA-based model reclassified 28.5% of patients vs. the model based on age+sex+diabetes+hypertension +smoking+high risk CV+CRP.

Figure 1.

Incremental Improvement of MBDA-based CV Risk Score Compared to Other CV Risk Prediction Models

Figure 2.

MBDA-Based CV Risk Score Calibration for Composite CV Outcome at 3 Years

Conclusion:

A biomarker-based prediction score incorporating a few clinical risk factors appears to have good accuracy to predict CV risk in RA. Additional validation in independent cohorts will help verify its performance characteristics.

References:

[1] Curtis et al.,Rheumatology2018;58:874.

Disclosure of Interests:

Jeffrey Curtis Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Fenglong Xie: None declared, Cynthia S. Crowson Grant/research support from: Pfizer research grant, Brent Mabey Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Darl Flake Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Richard Bamford Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Cheryl Chin Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Eric Sasso Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Elena Hitraya Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Rotem Ben-Shachar Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Alexander Gutin Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Jerry Lanchbury Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc.

Neutrophil to lymphocyte ratio as a predictor of response to neoadjuvant chemotherapy and survival in oesophageal adenocarcinoma

BACKGROUND

Inflammation has an important role in cancer survival, yet whether serum markers of inflammation predict response to potentially curative neoadjuvant chemotherapy (NAC) in oesophageal adenocarcinoma (OAC) is controversial. This study aimed to determine whether the systemic inflammatory response (SIR) is associated with response to NAC and survival.

METHODS

Consecutive patients with OAC planned for surgery with curative intent received blood neutrophil and lymphocyte measurements at diagnosis to calculate the neutrophil to lymphocyte ratio (NLR). Pathological variables including pTNM stage, differentiation, vascular invasion and Mandard tumour regression grade (TRG) were recorded. TRGs 1 and 2 were taken to represent a good response, and the primary outcome was overall survival.

RESULTS

During follow-up of 136 patients, 36 patients (26·5 per cent) had recurrence and 69 (50·7 per cent) died. Receiver operating characteristic (ROC) curve analysis of NLR before NAC predicted poor TRG (area under the ROC curve 0·71, 95 per cent c.i. 0·58 to 0·83; P = 0·002). In univariable analysis, pT category (P < 0·001), pN category (P < 0·001), poor differentiation (P = 0·006), margin positivity (P = 0·001), poor TRG (P = 0·014) and NLR (dichotomized at 2·25; P = 0·017) were associated with poor overall survival, and NLR retained independent significance in multivariable analysis (hazard ratio 2·26, 95 per cent c.i. 1·03 to 4·93; P = 0·042).

CONCLUSION

The pretreatment NLR was associated with a pathological response to NAC and overall survival in patients with OAC.

ANTECEDENTES

La inflamación juega un importante papel en la supervivencia por cáncer, aunque aún no se sabe si los marcadores séricos de inflamación predicen la respuesta a la quimioterapia neoadyuvante (neoadjuvant chemotherapy, NAC) potencialmente curativa en el adenocarcinoma de esófago (oesophageal adenocarcinoma, OAC). Este estudio se propuso determinar si la respuesta inflamatoria sistémica (systemic inflammatory response, SIR) estaba asociada con la respuesta a la NAC y a la supervivencia. MÉTODOS: A pacientes consecutivos con OAC en los que se planificó cirugía con intención curativa se les determinó neutrófilos y linfocitos en sangre en el momento del diagnóstico para calcular la tasa neutrófilo-linfocito (neutrophil-lymphocyte ratio, NLR). Se registraron variables patológicas que incluían el estadio pTNM, diferenciación tumoral, invasión vascular y grado de regresión tumoral (tumour regression grade, TRG) de Mandard. Los grados TRG 1 y 2 fueron considerados como una buena respuesta y el resultado primario fue la supervivencia global (overall survival, OS).

RESULTADOS

Durante el seguimiento de 136 pacientes, 36 pacientes (26,5%) presentaron recidiva y 69 pacientes (50,7%) fallecieron. El análisis de las características operativas del receptor (receiver-operator-characteristic, ROC) de NLR antes de la NAC predijo una pobre TRG (área bajo la curva ROC, AUC 0,71, i.c. del 95% 0,58-0,83, P = 0,002). En el análisis univariable, el estadio pT (P < 0,001), el estadio pN (P < 0,001), una pobre diferenciación tumoral (P = 0,006), un margen positivo (P = 0,001), una pobre TRG (P = 0,014) y la NLR (dicotomizada a 2,25, P = 0,017) se asociaron con una pobre OS, pero solamente la NLR (cociente de riesgos instantáneos, hazard ratio, HR 2,28, i.c. del 95% 1,03-4,93, P = 0,042) conservó la significación estadística como variable independiente en el análisis multivariable. CONCLUSIÓN: La NLR antes del tratamiento se asoció con respuesta patológica del OAC a la NAC y OS.

480Right ventricular dysfunction is associated with late mortality in severe aortic stenosis: results from a multi-centre outcome study in patients undergoing aortic valve replacement

Background

The right ventricle (RV) is relatively understudied and often not routinely assessed in aortic stenosis (AS). However, there are several potential reasons for its importance. RV function is sensitive to left-sided afterload changes which can result in pulmonary hypertension (PH) in severe AS. PH is also a recognised predictor of poor prognosis in AS, but RV afterload and function can be difficult to assess. Cardiovascular magnetic resonance (CMR) may reveal unrecognised RV dysfunction and simultaneously evaluate other prognostic markers in AS.

Purpose

To investigate preoperative RV function assessed by CMR in severe AS and its association with mortality after aortic valve replacement (AVR).

Methods

674 severe AS patients listed for either surgical or percutaneous AVR at six cardiothoracic centres underwent preoperative CMR (for ventricular function, mass and scar) along with echocardiography for valve severity. Scans were core-lab analysed for LV and RV volumes, function and scar quantification. Eight patients were excluded due to inadequate RV image quality for a total of 666 patients finally included. All-cause mortality was tracked for a minimum of 2 years after AVR.

Results

107 (16%) of severe AS undergoing invasive AVR had a RV ejection fraction (RVEF) <55%. CMR detected overt RV dysfunction (RVEF <50%) in 61 (9%) patients. During a median 3.6 years follow-up, 145 (22%) patients died. Baseline RV dysfunction was the most powerful predictor of all-cause mortality (hazard ratio [HR] 2.5, 95% CI 1.6–3.9, p<0.0001). RV function was independent from other clinical characteristics but associated with signs of LV maladaptation (LV ejection fraction [LVEF] and late gadolinium enhancement [LGE]). The strongest Cox multivariable model for all-cause mortality accounted for RV dysfunction, age and LGE (adjusted HRs 1.7, 1.1, 2.2, respectively). Even early stages of pre-procedural RV dysfunction (RVEF 45–50%) were associated with reduced long-term survival.

Cox and Kaplan-Meier for all-cause death

Conclusion

One out of 6 patients with severe AS undergoing valve replacement manifests a reduction in RV function detectable by CMR. Those with RV dysfunction (RVEF<50%) have a 2.5-fold increase in all-cause mortality after AVR at 3.6 years. Whilst RV dysfunction is associated with LV maladaptation (LGE, LVEF), it is a powerful independent factor associated with all-cause mortality and impacts survival even at early stages. Thus, the RV appears to be important in cardiac adaptation to AS and longevity after AS intervention.

Acknowledgement/Funding

British Heart Foundation and National Institute of Health Research

P6505Urinary desmosine, an elastin-specific degradation product is associated with maximum aortic root size and aortic z-scores in patients with bicuspid aortic valve

Background

Bicuspid aortic valve (BAV) is the commonest congenital cardiac abnormality affecting up to 2% of the general population. BAV is highly diverse in phenotype however a common feature is its inherent risk of morbidity and mortality from aortic root dilatation and dissection. Aortic dilatation involves elastin degradation and desmosine is an amino acid cross-link that is released into the bloodstream and urine following elastin degradation. It is known from an earlier pilot study (DESMA) of desmosine in Marfan Syndrome (MFS) patients that plasma desmosine among patients with MFS is significantly elevated and correlates with aortic size however whether this same observation is seen in other forms of inherited aortopathies such as BAV is unclear.

Objectives

1. To investigate whether patients with BAV have higher elastin degradation as indicated by plasma desmosine and urinary desmosine levels.

2. To explore the relationship between plasma and urinary desmosine levels with aortic root size in patients with BAV.

Methods

We measured urinary (ng/mg creatinine) and plasma desmosine (ng/mL) in 20 patients with BAV and healthy control subjects using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Aortic root size and corresponding Z-scores were measured on echocardiogram. Correlation was analysed with Spearman's rank test.

Results

The patients with BAV were predominantly male (n=15, 75%) with a mean age of 50.5 years ± 17.6 [SD]. All the BAV patients had normal LV systolic function and none had prior aortic root surgery or were current smokers. Nine BAV patients had treated hypertension. Compared to controls, both plasma desmosine (0.30±0.10 vs 0.26±0.075 ng/mL, p=0.01) and urinary desmosine (15.9±4.6 vs 7.2±2.8 ng/mg creatinine, p<0.001) were significantly elevated in patients with BAV. Urinary and plasma desmosine (Figure 1) were also significantly correlated (r=0.55, p=0.01). There was a significant association between urinary desmosine and maximal aortic root size and Z-scores in the BAV cohort (Figure 2) compared to controls (p=0.02), however this was not seen with plasma desmosine.

Conclusions

Urinary and plasma desmosine levels are significantly higher in patients with BAV compared to controls. Urinary desmosine is also significantly associated with maximal aortic root size, reflecting higher elastin degradation. This suggests a potential use of desmosine as a biomarker to monitor disease progression in patients with BAV.

Acknowledgement/Funding

Anonymous Trust

1337Myocardial extracellular volume in patients with aortic stenosis undergoing valve intervention - A multicentre T1 mapping study

Background

The development of myocardial fibrosis is a key mechanism in the transition from compensated hypertrophy to heart failure in aortic stenosis (AS). Focal and diffuse fibrosis can be quantified using cardiac magnetic resonance (CMR) imaging late gadolinium-enhanced (LGE) and T1 mapping techniques.

Purpose

To assess T1 mapping measures of fibrosis in patients with severe AS referred for aortic valve intervention, and determine their associations with clinical characteristics, disease severity and long-term clinical outcome.

Methods

In this international prospective cohort study, patients with severe AS underwent contrast enhanced CMR with T1 mapping and LGE prior to aortic valve intervention. Image analysis was performed by a single core laboratory and the extracellular volume fraction [ECV%] calculated from T1 mapping images. The presence of LGE was determined visually and quantified using the full-width-at-half-maximum technique.

Results

Four-hundred and forty patients (70±10 years, 59% male) from ten international centres were enrolled. Aortic valve intervention was performed 15 [4 to 58] days following CMR. Within a follow-up of 3.8 [2.8 to 4.6] years, 52 patients died.

ECV% (mean 27.7±3.6%) correlated with increasing age, Society of Thoracic Surgeons Predicted Risk of Mortality score, known coronary artery disease, lower peak aortic-jet velocity, larger left ventricular (LV) mass, lower LV ejection fraction, and presence of LGE (P<0.05 for all). Following adjustment for all demographic and clinical variables, ECV% remained associated with age (P=0.028), LV ejection fraction (P<0.001) and presence of LGE (P=0.035).

Univariable predictors of all-cause mortality included age, male sex, impaired LV ejection fraction and presence of LGE (all P<0.05). A progressive increase in all-cause mortality was seen across tertiles of ECV% (17.3, 31.6 and 52.7 deaths per 1000 patient-years; log-rank test, P=0.009). ECV% was independently associated with all-cause mortality following adjustment for age, sex, impaired LV ejection fraction and presence of LGE (HR per unit increase in ECV: 1.10, 95%, (1.02–1.19), P=0.013).

ECV440 abstract iamge

Conclusion

In patients with severe aortic stenosis scheduled for aortic valve intervention, extracellular volume-based T1 mapping correlates with LV decompensation. ECV% is a strong independent predictor of late all-cause mortality and is a potential therapeutic target.

A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk

OBJECTIVE

We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.

RESEARCH DESIGN AND METHODS

We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.

RESULTS

Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002).

CONCLUSIONS

The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.

Concurrent use of capecitabine with radiation therapy and survival in breast cancer (BC) after neoadjuvant chemotherapy

PURPOSE

Capecitabine has been studied as a radiosensitizer, and our study seeks to examine the association of concurrent capecitabine/radiation therapy (RT) on event-free- (EFS) and overall survival (OS) in women with breast cancer (BC) with residual disease after neoadjuvant chemotherapy (NAC).

METHODS/PATIENTS

In a retrospective study of women with BC who received adriamycin/taxane-based NAC from 2004-2016, we identified 21 women administered concurrent capecitabine/RT. To assess differences in survival, we selected a clinical control cohort (n = 57) based on criteria used to select patients for capecitabine/RT. We also created a matched cohort (2:1), matching on tumor subtype, pathological stage and age (< 50 or 50+ years). Differences in EFS, using STEEP criteria, and OS, using all-cause mortality, between those who received capecitabine/RT and controls were assessed.

RESULTS

Of the 21 women who received capecitabine/RT, median age was 52 years. The majority were pathologic stage III (n = 15) and hormone receptor-positive/HER2-negative BC (n = 20). In those receiving capecitabine/RT, there were 9 events, compared with 14 events in clinical and 10 events in matched controls. Capecitabine/RT was associated with worse OS in clinical (HR 3.83 95% CI 1.12-13.11, p = 0.03) and matched controls (HR 3.71 95% CI 1.04-13.18, p = 0.04), after adjusting for clinical size, pathological stage and lymphovascular invasion. Capecitabine/RT was also associated with a trend towards worse EFS in clinical (HR 2.41 95% CI 0.86-6.74, p = 0.09) and matched controls (HR 2.68 95% CI 0.91-7.90, p = 0.07) after adjustment.

CONCLUSION

Concurrent capecitabine/RT after NAC is associated with worse survival and should be carefully considered in BC.