An investigation of the clinical impact and therapeutic relevance of a DNA damage immune response (DDIR) signature in patients with advanced gastroesophageal adenocarcinoma

BACKGROUND

An improved understanding of which gastroesophageal adenocarcinoma (GOA) patients respond to both chemotherapy and immune checkpoint inhibitors (ICI) is needed. We investigated the predictive role and underlying biology of a 44-gene DNA damage immune response (DDIR) signature in patients with advanced GOA.

MATERIALS AND METHODS

Transcriptional profiling was carried out on pretreatment tissue from 252 GOA patients treated with platinum-based chemotherapy (three dose levels) within the randomized phase III GO2 trial. Cross-validation was carried out in two independent GOA cohorts with transcriptional profiling, immune cell immunohistochemistry and epidermal growth factor receptor (EGFR) fluorescent in situ hybridization (FISH) (n = 430).

RESULTS

In the GO2 trial, DDIR-positive tumours had a greater radiological response (51.7% versus 28.5%, P = 0.022) and improved overall survival in a dose-dependent manner (P = 0.028). DDIR positivity was associated with a pretreatment inflamed tumour microenvironment (TME) and increased expression of biomarkers associated with ICI response such as CD274 (programmed death-ligand 1, PD-L1) and a microsatellite instability RNA signature. Consensus pathway analysis identified EGFR as a potential key determinant of the DDIR signature. EGFR amplification was associated with DDIR negativity and an immune cold TME.

CONCLUSIONS

Our results indicate the importance of the GOA TME in chemotherapy response, its relationship to DNA damage repair and EGFR as a targetable driver of an immune cold TME. Chemotherapy-sensitive inflamed GOAs could benefit from ICI delivered in combination with standard chemotherapy. Combining EGFR inhibitors and ICIs warrants further investigation in patients with EGFR-amplified tumours.

Fatigue in children who have recently completed treatment for acute lymphoblastic leukemia: a longitudinal study

BACKGROUND

This study examined fatigue in patients treated for childhood acute lymphoblastic leukemia (ALL) over a 2-year period (3- to 27-months post-treatment completion), from the perspective of children and parent caregivers, compared to a healthy comparison group.

METHODS

Eighty-three patients (4-16 years at enrolment) and their parents, reported on the child's fatigue using the Pediatric Quality of Life Inventory- Multidimensional Fatigue Scale (PedsQL-MFS), at 3- 15- and 27-months post-treatment completion, and 53 healthy children and their parents reported on fatigue across the same timepoints.

RESULTS

Parent proxy-reporting showed that parents of ALL patients reported more total fatigue than parents of the comparison group at all time points, with all subscales elevated (general, cognitive, and sleep/rest fatigue). In contrast, patient self-report of fatigue over this period differed from the comparison children for the general fatigue subscale only. Self-reported total fatigue was worse than the comparison group at the 27-month timepoint, with cognitive and sleep/rest fatigue symptoms contributing to this difference. Expected improvements in fatigue over time were not evident in either patient or parent report and no demographic risk factors were identified. Parents and children from both groups reported significantly more fatigue at all time points compared to commonly utilised normative population data.

CONCLUSIONS

Patients treated for childhood ALL are impacted by fatigue symptoms in the post-treatment and early survivorship period. These findings highlight that patients in the 2-years following treatment require increased symptom surveillance and may benefit particularly from interventions that target cognitive and sleep/rest fatigue.

Reduction in re-rupture rates following implementation of return-to-sport testing after anterior cruciate ligament reconstruction in 313 patients with a mean follow-up of 50 months

OBJECTIVES

The objective of this study was to assess the mid-term effectiveness of a return to sport (RTS) test in relation to preventing anterior cruciate ligament (ACL) re-rupture and contralateral ACL injury following ACL reconstruction (ACLR). Furthermore, this study aimed to assess the timing of passing a, RTS-test after surgery, and the effect age has on RTS outcomes.

METHODS

Patients undergoing ACLR between August 2014 and December 2018 took an RTS-test following rehabilitation. The RTS-test consisted of the Anterior Cruciate Ligament Return to Sport After Injury Scale, a single-leg hop, a single-leg triple hop, a single-leg triple cross-over hop, a box-drop vertical jump down, a single-leg 4-rep max-incline leg press, and a modified agility T test. RTS-passing criteria were ≥90% limb symmetry index in addition to defined takeoff and landing parameters. Mid-term review assessed sporting level, ACL re-injury, and contralateral ACL injury.

RESULTS

A total of 352 patients underwent RTS-testing, following ACLR with 313 (89%) contactable at follow-up, a mean of 50 months (standard deviation: 11.41, range: 28-76) after surgery. The re-rupture rate was 6.6% after passing the RTS-test and 10.3% following failure (p ​= ​0.24), representing a 36% reduction. Contralateral ACL injury rate after surgery was 6% and was 19% lower in those passing the RTS test. The mean age of patients passing their first RTS-test was significantly higher than that of those who failed (p ​= ​0.0027). Re-ruptures in those who passed the RTS test first time occurred late (>34 months), compared to those who failed first time, which all occurred early (<33 months) (p ​= ​0.0015). The mean age of re-rupture was significantly less than those who did not sustain a re-rupture (p ​= ​0.025).

CONCLUSION

Passing a RTS-test following ACLR reduces ACL re-rupture by 36.21% and contralateral ACL injury by 19.15% at mid-term follow-up. Younger patients are more likely to fail a RTS-test and are at higher risk of contralateral ACL rupture.

LEVEL III EVIDENCE

Are Population-Level Approaches to Dementia Risk Reduction Under-Researched? A Rapid Review of the Dementia Prevention Literature

Dementia is forecast to become increasingly prevalent, particularly in low- and middle-income countries, and is associated with high human and economic costs. Primary prevention of dementia -preventing risk factors leading to disease development - is an emerging global public health priority. Primary prevention can be achieved in two ways: individual-level or population-level. In this rapid review, we quantify the proportion of contributing interventional evidence to the dementia primary prevention literature that is concerned with either approach. We searched Medline, the National Institute for Health and Care Excellence, Cochrane, the World Health Organization, and Google to identify systematic reviews that described primary prevention interventions for dementia. We used search terms related to dementia risk reduction, intervention/policy, and review. We analysed reference lists of included dementia prevention reviews to identify contributing primary prevention evidence, and categorised these as either individual-level or population-level. Additionally, we examined search strategies to investigate the likelihood of reviews identifying available population-level interventions. We included twelve of the 527 articles retrieved. Population-level evidence was summarised by only two reviews. In these two reviews, <2.5% of the interventions described where population-level interventions. Most search strategies were weighted towards identifying individual-level evidence. Existing systematic reviews of dementia primary prevention interventions include almost no population-level evidence. Correction of this imbalance is needed to ensure that dementia prevention policies can achieve meaningful reductions in the prevalence of, and inequalities in, dementia.

Baduanjin Mind-Body Exercise for Cancer-Related Fatigue: Protocol for a Remotely Delivered Randomized Wait-List Controlled Feasibility Study

BACKGROUND

People living with a cancer diagnosis often experience cancer-related fatigue (CRF). Between 9% and 45% of people report CRF as moderate to severe, negatively impacting their quality-of-life (QOL). The evidence-base for managing CRF recommends exercise-related therapies over pharmaceutical interventions. One such exercise-like therapy is Baduanjin mind-body exercise (MBE), which has additional benefits. A remotely delivered program may further benefit people with CRF. The primary objective of this pilot will test study feasibility of a remotely delivered Baduanjin MBE exercise program for people living with CRF.

METHODS

This is a randomized wait-list controlled pilot study and will take place in Sydney, Australia. Subject to informed consent, 40 adults with moderate CRF levels and receiving or previously received adjuvant chemotherapy, will undertake a home-based 8-week Baduanjin MBE program supported by online resources and instructors. The primary feasibility outcomes are recruitment, enrollment, retention, and adherence rates; and safety as measured by tolerance and adverse-event frequency. Clinical outcomes (eg, changes in CRF, QOL, and participant perceptions) are assessed at pre-intervention, week 1, week 4, week 8, and post-intervention. Analyses follows the Intent-to-Treat (all participants as per randomization) and per-protocol (participants adhering to the protocol). Missing data will be imputed from previous data entries and regression models may be tested to predict missing outcomes.

DISCUSSION

To our knowledge, this is the first study evaluating the feasibility and effects of Baduanjin MBE on CRF using a remote delivery method. These feasibility data will inform a fully powered future trial investigating evidence of effect on CRF and QOL.Trial registration: Australian and New Zealand Clinical Trials Registry (ANZCTR 12623000177651).Ringgold ID: 651498 Chinese Medicine Centre.

What is a population-level approach to prevention, and how could we apply it to dementia risk reduction?

The World Health Organisation's 2022 'blueprint for dementia research' highlights the need for more research into population-level risk reduction. However, definitions of population-level prevention vary, and application to dementia is challenging because of its multi-factorial aetiology and a maturing prevention evidence base. This paper compares and contrasts key concepts of 'population-level prevention' from the literature, explores related theoretical models and policy frameworks, and applies this to dementia risk reduction. We reach a proposed definition of population-level risk reduction of dementia, which focusses on the need to change societal conditions such that the population is less likely to develop modifiable risk factors known to be associated with dementia, without the need for high-agency behaviour change by individuals. This definition, alongside identified policy frameworks, can inform synthesis of existing evidence and help to co-ordinate the generation of new evidence.

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

INTRODUCTION

The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures.

METHODS

In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025.

FINDINGS

Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation.

INTERPRETATION

After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification.

FUNDING

UK Research and Innovation and National Institute for Health Research.

A novel approach using electroacupuncture for erectile dysfunction after radical prostatectomy: A case report

INTRODUCTION

Research shows that electrical stimulation to damaged peripheral nerves has promising effects on nerve regeneration and recovery of function.

DESCRIPTION

A 71 yr. old male, who was 12 months post left intrafacial and right incremental nerve sparing robotic radical prostatectomy received 6 sessions of sacral electroacupuncture/acupuncture at weekly intervals, commencing 12 months post operatively.

METHODS

CARE guidelines informed the case study report. Positive changes in erectile function after electroacupuncture was recorded using validated scores (IIEF-5 and EHS). Qualitative information was collected via a feedback box.

DISCUSSION

Given that current treatments for post radical prostatectomy erectile dysfunction are invasive and largely unsuccessful, further investigation into electroacupuncture for this population should be pursued.

External validation of a radiomic signature to predict p16 (HPV) status from standard CT images of anal cancer patients

The paper deals with the evaluation of the performance of an existing and previously validated CT based radiomic signature, developed in oropharyngeal cancer to predict human papillomavirus (HPV) status, in the context of anal cancer. For the validation in anal cancer, a dataset of 59 patients coming from two different centers was collected. The primary endpoint was HPV status according to p16 immunohistochemistry. Predefined statistical tests were performed to evaluate the performance of the model. The AUC obtained here in anal cancer is 0.68 [95% CI (0.32-1.00)] with F1 score of 0.78. This signature is TRIPOD level 4 (57%) with an RQS of 61%. This study provides proof of concept that this radiomic signature has the potential to identify a clinically relevant molecular phenotype (i.e., the HPV-ness) across multiple cancers and demonstrates potential for this radiomic signature as a CT imaging biomarker of p16 status.

Post-acute phase and sequelae management of epidermal necrolysis: an international, multidisciplinary DELPHI-based consensus

BACKGROUND

Long-term sequelae are frequent and often disabling after epidermal necrolysis (Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN)). However, consensus on the modalities of management of these sequelae is lacking.

OBJECTIVES

We conducted an international multicentric DELPHI exercise to establish a multidisciplinary expert consensus to standardize recommendations regarding management of SJS/TEN sequelae.

METHODS

Participants were sent a survey via the online tool "Survey Monkey" consisting of 54 statements organized into 8 topics: general recommendations, professionals involved, skin, oral mucosa and teeth, eyes, genital area, mental health, and allergy workup. Participants evaluated the level of appropriateness of each statement on a scale of 1 (extremely inappropriate) to 9 (extremely appropriate). Results were analyzed according to the RAND/UCLA Appropriateness Method.

RESULTS

Fifty-two healthcare professionals participated. After the first round, a consensus was obtained for 100% of 54 initially proposed statements (disagreement index < 1). Among them, 50 statements were agreed upon as 'appropriate'; four statements were considered 'uncertain', and ultimately finally discarded.

CONCLUSIONS

Our DELPHI-based expert consensus should help guide physicians in conducting a prolonged multidisciplinary follow-up of sequelae in SJS-TEN.

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci

PURPOSE

Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often requiring further investigations. Deep learning (DL) - a machine learning technique designed to mimic human neuronal interactions- has shown promise in the field of medical imaging analysis for different purposes, including segmentation and classification of lesions. In this study, we aim to develop a DL algorithm that can classify areas of increased uptake on bone scintigraphy scans.

METHODS

We collected 2365 BS from three European medical centres. The model was trained and validated on 1203 and 164 BS scans respectively. Furthermore we evaluated its performance on an external testing set composed of 998 BS scans. We further aimed to enhance the explainability of our developed algorithm, using activation maps. We compared the performance of our algorithm to that of 6 nuclear medicine physicians.

RESULTS

The developed DL based algorithm is able to detect MBD on BSs, with high specificity and sensitivity (0.80 and 0.82 respectively on the external test set), in a shorter time compared to the nuclear medicine physicians (2.5 min for AI and 30 min for nuclear medicine physicians to classify 134 BSs). Further prospective validation is required before the algorithm can be used in the clinic.

89 DIAGNOSIS AND TREATMENT OF SUSPECTED OBSTRUCTIVE SLEEP APNOEA (OSA) IN OLDER PEOPLE: A RETROSPECTIVE COMPARATIVE ANALYSIS

Background

Obstructive Sleep Apnoea (OSA) is common yet often undiagnosed in older people as symptoms of fatigue and poor sleep are common and non-specific. OSA screening tools also lack validity in older patients. This study aims to review the clinical presentation, use of screening tools and treatment adherence in older people.

Methods

A retrospective cohort study of patients &gt;65 years attending a tertiary sleep clinic who underwent polysomnography for suspected OSA was performed. Electronic patient records were reviewed to obtain information on clinical presentation, screening scores, polysomnography reports and treatment initiated. Correlation between variables was performed using Pearson’s correlation co-efficient and represented using R-score. To compare CPAP usage with younger people, a cohort of controls &lt;65 years were matched in 2:1 ratio for OSA severity (mild, moderate or severe) at diagnosis. Comparison of adherence rates was performed using Mann-Whitney U-test and represented using Z-scores.

Results

A convenience sample of 100 consecutive older patients were included. Fatigue was present in 53% and witness reported snoring in 86% and apnoeas in 56%. Moderate or severe OSA was confirmed by polysomnography in 91% cases. BMI and the STOP-BANG questionnaire were positively correlated with OSA severity as measured by Apnoea Hypopnea Index, while ESS and Berlin Questionnaire were not. Positive pressure ventilation was initiated in 90% patients. CPAP was extremely effective with the median AHI falling to within normal range on follow up. CPAP usage was significantly higher in older patients compared with younger matched control (85% vs 66% p=013).

Conclusion

Older people with OSA present with classical symptoms. STOP -BANG questionnaire and BMI were positively correlated with AHI values while other screening tools lacked validity. Treatment with CPAP was highly efficacious in older people with high usage rates and should be considered as first-line treatment for moderate and severe OSA in older patients.

293 PRE-ADMISSION POTENTIALLY INAPPROPRIATE PRESCRIBING PREVALENCE ON A CARE OF THE OLDER ADULT MEDICAL WARD

Background

Potentially Inappropriate Prescribing (PIP) is a common but critical issue in care of the older adult. It is estimated that between 50 and 70% of those over 65 years are receiving at least one potentially inappropriate medication. Polypharmacy is a good indicator of PIP as it can indicate over- and inappropriate prescribing through prescribing cascade, exposing patients to risks of drug interactions and Adverse Drug Events (ADEs). 10-20% of hospital admissions of older adults are directly related to ADE of inappropriately prescribed drugs.

Methods

Point prevalence study using the ‘Screening Tool of Older Persons Prescriptions’ (STOPP) to identify PIPs on a geriatric medicine ward. Patients over 65 years of age admitted from home were included in the study. Patients’ pre-admission medications and changes made to these were assessed using STOPP.

Results

Sixteen patients out of 22 met the inclusion criteria. The average age of the patients included in the study was 82.3 years with a range from 70 to 88 years. 75% were female. 94% had polypharmacy prior to admission with an average of 2.25 PIPs (range 0 to 5). 43% (n=7) had all their PIPs addressed by a geriatrician as per STOPP, with a further 18% (n=3) having some of their PIPs altered. 25% (n=4) did not have any alterations to their PIPs.

Conclusion

Despite widely known impacts of PIPs on older adults, PIP remains highly prevalent in those admitted to hospital. PIP and polypharmacy can increase incident frailty two-fold and polypharmacy and frailty can lead to a 6-fold increase in mortality within two and a half years. We must actively educate all those involved in prescribing for this cohort of patients to reduce PIPs and their adverse effects.

250 AUDIT INTO THE USE AND COMPLICATIONS OF MAINTENANCE INHALER THERAPY IN MEDICALLY ADMITTED PATIENTS OVER THE AGE OF 65 YEARS

Background

Adequate maintenance inhaler use is associated with improved symptom control and reduced exacerbation rates, however, cognitive impairment and limitations in dexterity can be a barrier to inhaled therapy.

Methods

Between the 20th of April and 30th May 2022 patients admitted to our ward over the age of 65 years had their maintenance inhaler technique assessed using the National Asthma Council of Australia checklist. Symptom control was assessed by either the Asthma Control Test (ACT) or the Chronic Obstructive Pulmonary Disease (COPD) assessment tool (CAT). The 4 AT score was used to screen for neurocognitive impairment.

Results

20 patients were recruited to the study. 40% were male. Mean age 81.5 years +- 6.8years. The respiratory diagnosis was COPD in 70%, Asthma 20%, Interstitial Lung Disease 5% and bronchiectasis 5%. 65 % had pulmonary function testing performed. Asthma symptom control was within target in 75% of the asthma patients (ACT score &gt;20). Mean score 21 +- 2.5. COPD symptom control was within target in 31% of patients (CAT score &lt;10) . Mean CAT score of 19.3 +- 8. 4. 20% had a pre-admission diagnosis of neurocognitive impairment. The mean 4AT score of the cohort was 1.2. 35% had audible wheeze at the time of review. 80% of inhalers were prescribed for the licensed indication. 35% had potential complications of inhaler therapy – 25% pneumonia and 10% oral candidiasis. Notably all pneumonias were associated with fluticasone. Inhaler technique was associated with errors in almost a quarter of all patients (24%). Increasing 4AT score correlated with high likelihood of inhaler errors, R = 0.63.

Conclusion

Poor inhaler technique is correlated with neurocognitive impairment. Pneumonia is a potential complication of inhaler therapy and represents an opportunity for deprescribing in patients with COPD.

Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run

We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2  M_{⊙} and 1.0  M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14  yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200]  Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2  M_{⊙}<m_{PBH}<1.0  M_{⊙} is f_{PBH}≡Ω_{PBH}/Ω_{DM}≲6%. This improves existing constraints on primordial black hole abundance by a factor of ∼3. The other is a dissipative dark matter model, in which fermionic dark matter can collapse and form black holes. The upper limit on the fraction of dark matter black holes depends on the minimum mass of the black holes that can be formed: the most constraining result is obtained at M_{min}=1  M_{⊙}, where f_{DBH}≡Ω_{DBH}/Ω_{DM}≲0.003%. These are the first constraints placed on dissipative dark models by subsolar-mass analyses.

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

BACKGROUND

No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.

METHODS

The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.

FINDINGS

2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.

INTERPRETATION

The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Total neoadjuvant chemotherapy: a silver lining during the COVID pandemic for a patient with locally advanced diffuse distal gastric adenocarcinoma

Perioperative oncological therapies resulting in pathological complete response (pCR) in diffuse-type distal gastric adenocarcinoma are extremely rare. We report a case of locally advanced (cT3 N2 M0) diffuse-type distal gastric adenocarcinoma treated with 'total neoadjuvant' FLOT (eight cycles), due to the COVID-19 pandemic, and laparoscopic radical subtotal gastrectomy with D2 lymphadenectomy. The patient demonstrated a progressive radiological response on positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-d-glucose integrated with computed tomography (¹⁸F-FDG PET-CT) and pCR in the resected specimen (ypT0 N0). As far as we are aware, this is the first case of pCR in locally advanced T3 N2 diffuse distal gastric cancer to be reported in the literature. It introduces a novel approach of total neoadjuvant chemotherapy with ¹⁸F-FDG PET-CT to assess response, combined with radical minimally invasive surgical management to provide optimal care for patients with gastric cancer.

The Role of Imaging in the Detection of Non-COVID-19 Pathologies during the Massive Screening of the First Pandemic Wave

During the COVID-19 pandemic induced by the SARS-CoV-2, numerous chest scans were carried out in order to establish the diagnosis, quantify the extension of lesions but also identify the occurrence of potential pulmonary embolisms. In this perspective, the performed chest scans provided a varied database for a retrospective analysis of non-COVID-19 chest pathologies discovered de novo. The fortuitous discovery of de novo non-COVID-19 lesions was generally not detected by the automated systems for COVID-19 pneumonia developed in parallel during the pandemic and was thus identified on chest CT by the radiologist. The objective is to use the study of the occurrence of non-COVID-19-related chest abnormalities (known and unknown) in a large cohort of patients having suffered from confirmed COVID-19 infection and statistically correlate the clinical data and the occurrence of these abnormalities in order to assess the potential of increased early detection of lesions/alterations. This study was performed on a group of 362 COVID-19-positive patients who were prescribed a CT scan in order to diagnose and predict COVID-19-associated lung disease. Statistical analysis using mean, standard deviation (SD) or median and interquartile range (IQR), logistic regression models and linear regression models were used for data analysis. Results were considered significant at the 5% critical level (p < 0.05). These de novo non-COVID-19 thoracic lesions detected on chest CT showed a significant prevalence in cardiovascular pathologies, with calcifying atheromatous anomalies approaching nearly 35.4% in patients over 65 years of age. The detection of non-COVID-19 pathologies was mostly already known, except for suspicious nodule, thyroid goiter and the ascending thoracic aortic aneurysm. The presence of vertebral compression or signs of pulmonary fibrosis has shown a significant impact on inpatient length of stay. The characteristics of the patients in this sample, both from a demographic and a tomodensitometric point of view on non-COVID-19 pathologies, influenced the length of hospital stay as well as the risk of intra-hospital death. This retrospective study showed that the potential importance of the detection of these non-COVID-19 lesions by the radiologist was essential in the management and the intra-hospital course of the patients.

Lesion-specific radiomics analysis shows promising results for early-stage efficacy assessment of IOA-244 in uveal melanoma

3068

Background: Radiomics is an image based approach that allows for characterization and quantification of tumor lesions in cancer patients. Radiomics has been proven capable of potentially adding value in the diagnostic and prognostic patient managment. In this study we evaluated the potential of Radiomics to bring additional insight also in early drug development. Methods: All the visible malignant lung and liver metastasis lesions of 7 uveal melanoma patients (86% of women, 60±11y) treated with IOA-244 (EudraCT 2019-000686-20) were manually segmented and analyzed in their size and shape via a radiomics approach. The CT scans at baseline and first follow-up (8 weeks) were included in the study and compared. Descriptive statistics and linear mixed effect (LME) models were used to quantify volumetric lesion-specific response to treatment. Response has been defined both as continuous variable and in three discrete categories (lesion shrinkage, stable and progressive disease for a volume change of [-100%;-0%];[0%-+25%] and > 25%, respectively). The influence of lesion shape at baseline (e.g. compactness, elongation or surface roughness among others) on the treatment response has been explore through LME models as well. Results: We identified and segmented 126 metastatic lesions (70 lung and 56 liver) from baseline scans and 122 lesions (71 lung and 51 liver) from post treatment scans. Of those, 64% could be consistently mapped between visits, resulting in a total of 147 matching lesions on which the radiomics analysis was performed. We found 19% of complete response and 16% of new lesions appearing. 8 weeks after treatment start, we observed non progressive disease in 61% of all lesions, of which 42% was shrinking. LME did not show a significant change in lesion volume between visits, but the mean difference between visits was negative. LME did show that lesion shape is significantly different between progressors and non-progressors at baseline for lung lesions (compact and irregular lesions are more likely to respond), and that there are moderate correlations (0.4-0.7) between tumor shape and volume change for liver lesions (compact lesions have a larger volume drop). Conclusions: This work demonstrates both the clinical potential of IOA-244 for treatment of Uveal Melanoma patients with lesions in the lung and in the liver and the potential of radiomics individual lesion analysis for clinical research in the very early stages of drug development. Lesion evolution volumetric assessment has allowed a more accurate and sensitive understanding of IOA-244 efficacy and impact across different lesions, in both lung and liver. Radiomics showed a promising response of selected population to IOA-244 over the first time point (W0-W8). A further radiomics analysis on next follow-up scans would allow a radiological proof of treatment-induced changes and long-term patient outcome prediction.

Nodule vascularity as novel radiomics imaging endpoint for lung cancer diagnosis and prognosis

e20580

Background: The vascularization of lung nodules has been proven as severe risk factor for malignancy, and in lung cancer, indication of worse prognosis (1,2). For this reason, we developed a novel imagining endpoint based on the vasculature surrounding a lung mass and we tested this endpoint for the prediction of malignancy for lung nodules. Methods: The vasculature of the nodules (both arteries and veins) has been computed using the surface intersection between the nodule and the vascular structure 3D meshes. Both 3D structures were obtained by converting the segmentations of the nodule and of the vessels to meshes with a marching cubes algorithm. Nodule and vessels segmentation has been obtained with an in-house deep learning segmentation model. The features considered are the numbers of intersections, the total area of intersection and the mean area of intersection. These features have been used to predict nodule malignancy on thoracic CT scans from the Lung Image Database Consortium image collection (3). Quality controls on clinical data completeness and imaging parameters resulted in a cohort of 894 scans (715 for training and 179 for testing), from the original 1018 cases. The malignancy status is defined as high risk and low risk, based on the consensus classification of a panel of four radiologists. Firstly, an univariate analysis is performed to assess the variability of the features grouped by the malignancy score by using Mann-Whitney and ANOVA tests. After, seven combinations of features have been used to train generalized linear models (GLM) to predict nodule malignancy. To compare the models, the Area Under the Curve (AUC) is used as the main performance metric. Results: Univariate analysis of each feature grouped by the malignancy outcome showed that all the three features have good univariate discriminative power between high risk and low risk categories ( p value ≤ 0.05), with nb_connections as the most predictive singular feature ( p value of 1.343277 × 10-36). All the GLM models developed showed a good performance (AUC equal or higher than 0.7), with the best model in testing based on the combination of mean_area and sum_area (AUC of 0.84). Conclusions: The radiomics vascularity endpoint has been proven capable of predicting nodule malignancy with very good performance. The singular feature that is most related to malignancy is the number of vessels intersecting the nodule while the total area of intersection followed by the number of intersections are the most useful to model risk of malignancy. Wang et al., Lung Cancer 114: 38–43, 2017. Hamanaka et al., Diagn Pathol 10,17, 2015. G. Armato et al., Med. Phys., 38: 915-931, 2011.

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Risk factors for local atypical fibroxanthoma recurrence and progression to pleomorphic dermal sarcoma: A meta-analysis of individualized participant data

Background

Risk factors for local atypical fibroxanthoma (AFX) recurrence and progression to pleomorphic dermal sarcoma (PDS) have not previously been identified.

Objective

To identify risk factors and provide follow‐up suggestions for local AFX recurrence and progression to PDS.

Methods and Materials

A literature search was performed in the PubMed, EMBASE, and Cochrane databases. The PRISMA and MOOSE guidelines were followed. The risks of local AFX recurrence and progression to PDS were presented as Kaplan–Meier plots and risk factors were presented as hazard ratios (HRs) calculated with univariate and multivariate Cox regression.

Results

Five hundred and ninety‐eight patients with AFX from 14 studies were included. Age >74 years and male sex significantly increased the risk of local recurrence (HR: 7.31 [95% confidence interval [CI]: 1.78–30.0], p < 0.01 and HR: 2.89 [95% CI: 1.04–8.01], p < 0.05, respectively). There was no difference when comparing wide local excision and Mohs' micrographic surgery (p = 0.89). The risks of local AFX recurrence and progression to PDS after 2 years were <1%.

Conclusion

A more intensive follow‐up regimen could be considered in patients >74 years old and males due to the higher risk of local AFX recurrence.

An externally validated fully automated deep learning algorithm to classify COVID-19 and other pneumonias on chest CT

Purpose

In this study, we propose an artificial intelligence (AI) framework based on three-dimensional convolutional neural networks to classify computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19), influenza/community-acquired pneumonia (CAP), and no infection, after automatic segmentation of the lungs and lung abnormalities.

Methods

The AI classification model is based on inflated three-dimensional Inception architecture and was trained and validated on retrospective data of CT images of 667 adult patients (no infection n=188, COVID-19 n=230, influenza/CAP n=249) and 210 adult patients (no infection n=70, COVID-19 n=70, influenza/CAP n=70), respectively. The model's performance was independently evaluated on an internal test set of 273 adult patients (no infection n=55, COVID-19 n= 94, influenza/CAP n=124) and an external validation set from a different centre (305 adult patients: COVID-19 n=169, no infection n=76, influenza/CAP n=60).

Results

The model showed excellent performance in the external validation set with area under the curve of 0.90, 0.92 and 0.92 for COVID-19, influenza/CAP and no infection, respectively. The selection of the input slices based on automatic segmentation of the abnormalities in the lung reduces analysis time (56 s per scan) and computational burden of the model. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) score of the proposed model is 47% (15 out of 32 TRIPOD items).

Conclusion

This AI solution provides rapid and accurate diagnosis in patients suspected of COVID-19 infection and influenza.

A fully automated artificial intelligence-based network is proposed to classify CT volumes of patients affected with COVID-19 or influenza/CAP, and in the uninfectedhttps://bit.ly/3MJrVRi

A cross-sectional analysis of psychological distress among higher education students in Ireland

OBJECTIVES

To examine levels of psychological distress among higher education students in Ireland overall and across a range of personal, higher education, and socioeconomic characteristics, prior to the COVID-19 pandemic.

METHODS

A cross-sectional online survey of college students in Ireland was undertaken in 2018. Data on 5201 students from 13 higher education institutions (HEIs) were analyzed. Stress, anxiety, and depression symptom scores based on the Depression, Anxiety and Stress Scale (DASS-21) were calculated and reported, with statistical testing used to compare across groups.

RESULTS

Overall, 29.6% and 19.1% of respondents were classified in the mild to moderate and severe to extremely severe range for depression respectively. The corresponding proportions were 25.9% and 20.7% for anxiety, and 24.5% and 14.8% for stress. Differences across groups included higher levels of psychological distress for transgender and female students compared to males (p < 0.01), for gay/lesbian/bisexual students compared to heterosexuals (p < 0.01), for undergraduates compared to postgraduates (p < 0.01), for students from intermediate/technical/service/unskilled social classes compared to professional/self-employed social classes (p < 0.01), and for those with financial difficulties compared to those without financial difficulties (p < 0.01).

CONCLUSIONS

Rates of psychological distress were high amongst college students in Ireland prior to the COVID-19 pandemic, with substantial differences across groups. Due to study limitations, such as possible selection bias, the findings need replication. Further research is needed to determine the impact of the pandemic on the prevalence of mental illness in this population.

Demonstrating the processes and outcomes of a rural Community Mental Health Rehabilitation Service: A realist evaluation

BACKGROUND

As part of significant mental health reform, the Community Mental Health Rehabilitation Service (CMHRS) was implemented in rural South Australia. The CMHRS is a 10-bed mental health residential program offering rehabilitative mental health support to rural residents.

AIM

To analyse the CMHRS service delivery model and its impact on recovery outcomes for consumers.

METHODS

A mixed method, realist evaluation approach was utilised. A purposive sample of CMHRS staff (n = 6) and consumers (n = 8) were recruited. Consumer recovery was measured using the RAS-DS (on admission and discharge). Participants' perspectives of the service were gained via one staff focus group (n = 6) and individual semi-structured interviews (consumers n = 6; staff n = 2). Pre-post RAS-DS scores were analysed using paired t-tests/Wilcoxon paired-signed rank test, with qualitative data analysed thematically.

RESULTS

Significant positive increases in RAS-DS total scores were observed at discharge, supported by the qualitative themes of (re)building relationships and social connections and recovering health and wellbeing. Contextual factors (e.g. staffing) and program mechanisms (e.g. scheduling) impacting on service implementation were identified.

CONCLUSION

Maintaining a rehabilitation recovery-focused approach, balanced with an appropriately trained multi-disciplinary team, are vital for maximising positive consumer outcomes.

SIGNIFICANCE

This realist evaluation identifies critical factors impacting rural mental health rehabilitation service delivery.

Association between social deprivation status, age of presentation, and survival following ST-segment elevation myocardial infarction

Introduction

Many factors influence age of presentation with and survival following ST-segment myocardial infarction (STEMI). These include age, mode of, and time-delay to emergency treatment, diabetes and smoking. We sought to assess whether overall social deprivation status is associated with age of presentation and mortality following STEMI patients treated with primary PCI.

Methods

All patients treated emergently for STEMI in a large Northern Irish tertiary hospital from 2013 – 2017 were reviewed. Social deprivation is determined as a composite score relating to income, crime etc, and assigned to small geographical regions by the Northern Ireland Statistics and Research Agency. Deprivation score was assigned to patients based on their postcode. The database was ranked by social deprivation score and divided in to quintiles. The most (Grp 1) and least (Grp 5) deprived quintiles were compared. Mortality was determined from a national electronic health record.

Results

1,192 patients were included in the analysis. Mean follow up was 52.5 months (SD 15.6), minimum follow up was 35.6 months. There was no difference in gender: 70.1% male in Grp 1 vs 75.2% male in Grp 5 (p=0.68); no difference in ECG to balloon time: mean 89.9mins (95% CI 84.9–94.9) Grp 1 vs 90.5mins (95% CI 86.2–94.9) Grp 5 (p=0.86). The more deprived group was younger: mean age 60.6 (95% CI 59.5–61.6) vs 65.2 (95% CI 64.2–66.3) (p&lt;0.000). Crude survival measured by Log-rank test was the same between the groups (p=0.52). Following Cox-regression adjustment for age, survival was longer in the least deprived group (p=0.042).

Conclusion

Social deprivation is associated with both a younger age of presentation with, and a higher mortality following STEMI. This is important variable is often overlooked in medical literature and should be further studied.

Funding Acknowledgement

Type of funding sources: None.

Privacy preserving distributed learning classifiers - Sequential learning with small sets of data

BACKGROUND

Artificial intelligence (AI) typically requires a significant amount of high-quality data to build reliable models, where gathering enough data within a single institution can be particularly challenging. In this study we investigated the impact of using sequential learning to exploit very small, siloed sets of clinical and imaging data to train AI models. Furthermore, we evaluated the capacity of such models to achieve equivalent performance when compared to models trained with the same data over a single centralized database.

METHODS

We propose a privacy preserving distributed learning framework, learning sequentially from each dataset. The framework is applied to three machine learning algorithms: Logistic Regression, Support Vector Machines (SVM), and Perceptron. The models were evaluated using four open-source datasets (Breast cancer, Indian liver, NSCLC-Radiomics dataset, and Stage III NSCLC).

FINDINGS

The proposed framework ensured a comparable predictive performance against a centralized learning approach. Pairwise DeLong tests showed no significant difference between the compared pairs for each dataset.

INTERPRETATION

Distributed learning contributes to preserve medical data privacy. We foresee this technology will increase the number of collaborative opportunities to develop robust AI, becoming the default solution in scenarios where collecting enough data from a single reliable source is logistically impossible. Distributed sequential learning provides privacy persevering means for institutions with small but clinically valuable datasets to collaboratively train predictive AI while preserving the privacy of their patients. Such models perform similarly to models that are built on a larger central dataset.

A review in radiomics: Making personalized medicine a reality via routine imaging

Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can be performed by extracting hand-crafted radiomics features or via deep learning algorithms. Radiomics has evolved tremendously in the last decade, becoming a bridge between imaging and precision medicine. Radiomics exploits sophisticated image analysis tools coupled with statistical elaboration to extract the wealth of information hidden inside medical images, such as computed tomography (CT), magnetic resonance (MR), and/or Positron emission tomography (PET) scans, routinely performed in the everyday clinical practice. Many efforts have been devoted in recent years to the standardization and validation of radiomics approaches, to demonstrate their usefulness and robustness beyond any reasonable doubts. However, the booming of publications and commercial applications of radiomics approaches warrant caution and proper understanding of all the factors involved to avoid "scientific pollution" and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decision-making, from oncology and respiratory medicine to pharmacological and genotyping studies.

Constraints on Cosmic Strings Using Data from the Third Advanced LIGO-Virgo Observing Run

We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO-Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10^{-15}. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.

Constraints on Cosmic Strings Using Data from the Third Advanced LIGO-Virgo Observing Run

We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO-Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10^{-15}. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.

External validation of a radiomic signature to predict HPV (p16) status from standard CT images of anal and vulvar cancer patients

e15502

Background: HPV status of anal and vulvar cancers cannot be predicted by visual inspection as well as for oropharyngeal cancers. Radiomics applied on computed tomography images can extract features that may better characterize the structure and the underlying biology of the tumor. Methods: In this multi-center study, we validated a CT based radiomic signature to predict HPV (p16) status, developed in head & neck cancer, in anal and vulvar cancer patients. The patients cohort was composed of 68 anal cancer patients and 7 vulvar cancer patients, with p16 status determined by immunohistochemistry, while a control cohort was composed of 422 lung cancer patients. The patient cohorts come from 4 different centers (Maastro Clinic - the Netherlands, CHU Liege – Belgium, St Luke’s Hospital – Ireland, Cork University Hospital - Ireland). The primary tumor volume was manually delineated for each patient on axial CT images. Prior to analysis, all images were resampled to isotropic voxels of 2 mm, using linear interpolation. A total of 37 radiomics features were calculated from five groups: tumor intensity, shape, texture, Wavelet and Laplacian of Gaussian. The signature was built using regularized logistic regression [1]. The signature was evaluated according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) and the Radiomics Quality Score (RQS). Results: The signature classified anal and vulvar cancers based on their HPV status (positive or negative), with an AUROC of 0.760 comparable to the performance of the original signature developed in oropharyngeal squamous cell carcinomas (AUROC of 0.764) [1]. The model, tested in the control cohort of lung cancer patients, predicted the HPV positive status of 1% of the patients which is in line with expected European prevalence (0 – 10%). This signature is TRIPOD level 4 (57%) with an RQS of 61%. Conclusions: This study supplies an additional insight into HPV imaging phenotype, providing a proof of concept that molecular information can be inferred from standard medical images by means of radiomics. These preliminary but encouraging results may pave the road for further generalization of CT image features of HPV-related tumors and aid in the optimization of future therapy developments [2]. Reference [1] Ralph TH Leijenaar et al., The British Journal of Radiology 2018 91:1086 [2] Immunotherapy Drug with Two Targets Shows Promise against HPV-Related Cancers - accessed on 12/02/2021 - https://www.cancer.gov/

Supportive care in the acute phase of Stevens-Johnson syndrome and toxic epidermal necrolysis: an international, multidisciplinary Delphi-based consensus

BACKGROUND

Supportive care is the cornerstone of management of adult and paediatric Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). However, consensus on the modalities of supportive care is lacking.

OBJECTIVES

Our aim in this international multicentric Delphi exercise was to establish a multidisciplinary expert consensus to standardize recommendations regarding supportive care in the acute phase of SJS/TEN.

METHODS

Participants were sent a survey via the online tool SurveyMonkey, consisting of 103 statements organized into 11 topics: multidisciplinary team composition, suspect drug management, infection prevention, fluid resuscitation and prevention of hypothermia, nutritional support, pain and psychological distress management, management of acute respiratory failure, local skincare, ophthalmological management, management of other mucosa, and additional measures. Participants evaluated the level of appropriateness of each statement on a scale of 1 (extremely inappropriate) to 9 (extremely appropriate). The results were analysed according to the RAND/UCLA Appropriateness Method.

RESULTS

Forty-five participants from 13 countries (on three continents) participated. After the first round, a consensus was obtained for 82.5% of the 103 initially proposed statements. After the second round, a final consensus was obtained for 102 statements.

CONCLUSIONS

We have reached an international Delphi-based consensus on best supportive care practice for SJS/TEN. Our expert consensus should help guide physicians in treating patients with SJS/TEN and thereby improve short-term prognosis and the risk of sequelae.