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Background: Breast cancer brain metastasis (BCBM) represents an area of unmet clinical need. We previously demonstrated the genomic differences between primary BC and BCBM. In this study we examined the genomic differences between BCBM by BC subtypes and the potential actionable targets that might be taken forward for each subtype in clinical trials. Material and Methods: A total of 761 BCBMs were analyzed by comprehensive genomic profiling (CGP) for alterations in up to 395 genes (Foundation Medicine, USA). The samples were classified by immunohistochemistry (IHC) of the BCBM to ER+ (ER+/HER2-, ER+/HER2+), ER-/HER2+ and ER-/HER2-. Homologous recombination deficiency (HRD-gLOH; cutoff 16%), tumour mutational burden (TMB; cutoff 10 mutations/Mb), microsatellite instability (MSI) and PD-L1 prevalence and expression by IHC using the VENTANA SP142 assay (Immune Cell Score [IC] cutoff 1%) were also investigated. Results: For all BC subtypes the most enriched gene alterations in BCBM (>20% prevalence) were: TP53, MYC and PIK3CA. ESR1 and ERBB2 were more prevalent in ER+ and HER2+ tumours respectively, with ESR1 alterations significantly enriched in ER+/HER2- BCBMs (p< 0.0001). Frequently altered genes by BCBM subtype were: ER+/HER2-: CDH1 (8%) and BRCA2 (7%); ER+/HER2+: PIK3C2B (11%), MDM4 (11%), TBX3 (9%) and AKT2 (8%); ER-/HER2+: LYN (9%). Significantly enriched genes (p< 0.01) by BCBM subtype were: HER2+: CDK12 (15%); ER-/HER2-: BRCA1 (14%), CCND3 (9%), VEGFA, JAK2 (8% each) and the immune checkpoint inhibition (ICPI) biomarkers PDCD1LG2 (PDL2), CD274 (PDL1) (7% each). HRD-gLOH was high in ER+/HER2-: (43%) and ER-/HER2-: (70%). TMB and MSI were present in 10%-21% and 1-3% of BCBM respectively, whereas PDL1 protein expression by subtypes was: ER+/HER2- 23%, ER+/HER2+ 27%, ER-/HER2+ 57% , ER-/HER2- 48%. Table 1 summarizes the proportion of BCBMs with actionable alterations and selected clinical trials in BCBM. Conclusion: Clinically-relevant genomic alterations were identified across all BCBM subtypes. High HRD-gLOH, TMB and MSI were observed across all the BCBMs subtypes whereas PDL1/PDL2 alterations were a distinctive feature of ER-/HER2- BCBM. These data highlight the need to assess the genomic landscape of BCBM to enable rational treatment decisions with targeted agents, as well as to enable enrichment of relevant populations within clinical trials. Table 1. Selected studies with targeted therapy and/or immunotherapy in breast cancer brain metastases. The percentage (%) of actionable alterations by ER and HER2 status is summarized. ND: Not Detectable. Citation Format: Athina Giannoudis, Ethan Sokol, Shakti Ramkissoon, Talvinder Bhogal, Jeff Ross, Kimberly McGregor, Evangelia Razis, Rupert Bartsch, Richard S. Huang, Carlo Palmieri. Targetable alterations and genomic signatures within breast cancer brain metastases: Data from comprehensive genomic profiling of 761 breast cancer brain metastases [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-14-10.

Background: Central nervous system (CNS) disease secondary to breast cancer (BC) is a growing clinical problem and a cause of significant morbidity and mortality. A better understanding of the genomic landscape is key to understanding its cause and to developing novel treatments. In this study, we examined the genomic landscape of a large cohort of breast cancer brain metastases (BMs) and compared them to a cohort of local breast cancers (BCs) and non-CNS metastases (N-CNS). Material and Methods: We analyzed 822 BMs and compared them to 11,988 local, breast-biopsied BCs and 15,516 N-CNS (unpaired samples) with comprehensive genomic profiling (CGP) for all classes of alterations in at least 324 genes (Foundation Medicine, Cambridge, MA, USA). Homologous recombination deficiency detected by genome-wide loss of heterozygosity (HRD-gLOH; cutoff 16%), tumour mutation burden (TMB; cutoff 10 mutations/Mb), microsatellite instability (MSI) and PD-L1 prevalence and expression by VENTANA SP142 immune cell immunohistochemistry (IHC; cutoff 1%) was also investigated within and across the cohorts. Results: As compared to local BCs, 31 genes were significantly enriched for genomic alterations in BMs with BM prevalence >3% and false-discovery rate (FDR) Table 1.Prevalence (%) of the genomic signatures HRD-gLOH, TMB, MSI and PD-L1+ expression.Site% HRD-gLOH% TMB-H% MSI-H% PDL1+ALLlocal BC33.70%. (2573/7636)5.04%. (527/10464)0.37%. (39/10464)54.25%. (1092/2013)BM52.01%. (362/696)15.51%. (116/748)2.01%. (15/748)38.73%. (55/142)N-CNS31.55%. (3237/10260)9.82%. (1395/14210)0.23%. (32/14210)26.21%. (615/2346)ER+/HER2-local BC31.48%. (119/378)3.41%. (19/557)0.36%. (2/557)40.00%. (14/35)BM43.17%. (79/183)11.40%. (22/193)1.04%. (2/193)23.08%. (9/39)N-CNS29.65%. (126/425)8.92%. (51/572)0.17%. (1/572)12.99%. (10/77)ER+/HER2+local BC19.57%. (9/46)2.78%. (2/72)0.00%. (0/72)42.86%. (3/7)BM26.67%. (16/60)9.68%. (6/62)0.00%. (0/62)27.27%. (3/11)N-CNS47.37%. (18/38)19.57%. (9/46)0.00%. (0/46)14.29%. (1/7)ER-/HER2+local BC32.26%. (10/31)8.70%. (4/46)0.00%. (0/46)100.00%. (5/5)BM33.33%. (23/69)21.33%. (16/75)2.67%. (2/75)57.14%. (4/7)N-CNS34.38%. (11/32)4.26%. (2/47)0.00%. (0/47)42.86%. (3/7)ER-/HER2-local BC52.25%. (186/356)2.70%. (14/518)0.19%. (1/518)50.00%. (30/60)BM70.45%. (174/247)17.41%. (47/270)2.59%. (7/270)48.33%. (29/60)N-CNS43.52%. (84/193)10.04%. (27/269)0.74%. (2/269)21.43%. (6/28) Citation Format: Athina Giannoudis, Ethan Sokol, Shakti H Ramkissoon, Talvinder Bhogal, Kimberly McGregor, Allison Clark, Evangelia D Razis, Rupert Bartsch, Richard SP Huang, Carlo Palmieri. Comprehensive assessment of the genomic landscape of breast cancer brain metastases reveals targetable alterations and genomic signatures relevant to immune-checkpoint and PARP inhibitors [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD4-09.

Understanding the genomic landscape of breast cancer brain metastases (BCBMs) is key to elucidating their cause and developing novel treatments. In this study, comprehensive genomic profiling was performed on 822 BCBMs, 11,988 local breast cancer (BC) biopsies and 15,516 non-central nervous system (N-CNS) metastases (all unpaired samples). Clinically-relevant genomic alterations were significantly enriched in BCBMs compared to local BCs and N-CNS metastases. Homologous recombination deficiency as measured by BRCA1/2alteration prevalence and loss-of-heterozygosity and immune checkpoint inhibitor (ICI) biomarkers [Tumour mutation burden (TMB)-High, Microsatellite instability (MSI)-High, PD-L1/L2)] were significantly more prevalent in BCBM than local BC and N-CNS. High PD-L1 protein expression was observed in ER-negative/HER2-negative BCBMs (48.3% vs 50.0% in local BCs, 21.4% in N-CNS). Collectively, our data highlights that a high proportion of BCBMs are potentially amenable to treatment with targeted therapeutic agents including PARP inhibitors and ICIs.

Introduction:. Breast cancer (BC) brain metastases (BM) are a growing clinical problem as survival for metastatic BC improves. Genomic analyses of BM are key to developing more targeted therapeutic interventions. In this study we explored the gene rearrangements of BM and compared these to a cohort of non-paired local breast cancers (BCs) and non-CNS metastasis (N-CNS). Methods:. We analyzed 822 BMs and compared them to 11,988 local, breast-biopsied BCs and 15,516 N-CNS (samples unpaired) profiled with comprehensive genomic profiling (CGP) (Foundation Medicine, Cambridge, MA, USA) examining all classes of alterations in at least 324 genes. The prevalence of individual gene rearrangements within the BM was compared to those within BC and N-CNS cases. Further analysis was undertaken by classifying BM, BC and N-CNS specimens with respect to their oestrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status, available for a subset of samples. Results:. CGP identified 307 rearrangement events in BMs impacting 169 genes. Twenty genes exhibited recurrent rearrangement events with a prevalence greater than 0.5% in either the BM, BC or N-CNS. 10 of these 20 genes were significantly more prevalent within the BM specimens vs. BC and N-CNS (p The prevalence of CDK12 rearrangements within BM, BCs, and other N-CNS in different sub-types of BC.SubtypePrevalenceP-valueBM BCN-CNSBM vs. BCBM vs. . N-CNSAll3.53%. (29/822)0.86%. (103/11,988)0.68%. (105/15,516)3.55x10-91.85x10-11HER2+(irrespective of ER status)14.59%. (27/185)7.80%. (86/1,102)7.87%. (94/1,194)0.00460.0048HER2+, ER-15.29%. (13/85)10.53%. (6/57)1.96%. (1/51)0.460.02HER2+, ER+13.64%. (9/66)7.14%. (6/84)10.20%. (5/49)0.270.77HER2-, ER-0.67%. (2/298)0.17%. (1/585)0.69%. (2/291)0.261.00HER2-, ER+0.00%. (0/212)0.16%. (1/641)0.00%. (0/634)1.001.00 Citation Format: Talvinder Bhogal, Ethan Sokol, Shakti Ramkissoon, Athina Giannoudis, Kimberly McGregor, Allison Clark, Evangelia Razis, Rupert Bartsch, Richard Huang, Carlo Palmieri. Comprehensive analysis of the gene rearrangements within 822 breast cancer brain metastases reveals an enrichment of cyclin dependent kinase 12 rearrangements in HER2-positive brain metastases [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-07-04.

International audience; Simple Summary There have been huge improvements in both vaccination and the management of COVID-19 in patients with cancer. In addition, different variants may be associated with different presentations. Therefore, we examined whether indicators of the severity of COVID-19 in patients with cancer who present to hospital varied during different waves of the pandemic and we showed that these indicators remained predictive. We validated that the COVID-19 Risk in Oncology Evaluation Tool (CORONET), which predicts the severity of COVID-19 in cancer patients presenting to hospital, performed well in all waves. In addition, we examined patient outcomes and the factors that influence them and found that there was increased vaccination uptake and steroid use for patients requiring oxygen in later waves, which may be associated with improvements in outcome. Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

BackgroundAmong patients with breast carcinoma who have metastatic disease, 15%–30% will eventually develop brain metastases. We examined the genomic landscape of a large cohort of patients with breast carcinoma brain metastases (BCBMs) and compared it with a cohort of patients with primary breast carcinomas (BCs).Material and MethodsWe retrospectively analyzed 733 BCBMs tested with comprehensive genomic profiling (CGP) and compared them with 10,772 primary breast carcinomas (not-paired) specimens. For a subset of 16 triple-negative breast carcinoma (TNBC)–brain metastasis samples, programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) was performed concurrently.ResultsA total of 733 consecutive BCBMs were analyzed. Compared with primary BCs, BCBMs were enriched for genomic alterations in TP53 (72.0%, 528/733), ERBB2 (25.6%, 188/733), RAD21 (14.1%, 103/733), NF1 (9.0%, 66/733), BRCA1 (7.8%, 57/733), and ESR1 (6.3%,46/733) (p < .05 for all comparisons). Immune checkpoint inhibitor biomarkers such as high tumor mutational burden (TMB-high; 16.2%, 119/733); high microsatellite instability (1.9%, 14/733); CD274 amplification (3.6%, 27/733); and apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like mutational signature (5.9%, 43/733) were significantly higher in the BCBM cohort compared with the primary BC cohort (p < .05 for all comparisons). When using both CGP and PD-L1 IHC, 37.5% (6/16) of patients with TNBC brain metastasis were eligible for atezolizumab based on PD-L1 IHC, and 18.8% (3/16) were eligible for pembrolizumab based on TMB-high status.ConclusionWe found a high prevalence of clinically relevant genomic alterations in patients with BCBM, suggesting that tissue acquisition (surgery) and/or cerebrospinal fluid for CGP in addition to CGP of the primary tumor may be clinically warranted.Implications for PracticeThis study found a high prevalence of clinically relevant genomic alterations in patients with breast carcinoma brain metastasis (BCBM), suggesting that tissue acquisition (surgery) and/or cerebrospinal fluid for comprehensive genomic profiling (CGP) in addition to CGP of the primary tumor may be clinically warranted. In addition, this study identified higher positive rates for FDA-approved immunotherapy biomarkers detected by CGP in patients with BCBM, opening a possibility of new on-label treatments. Last, this study noted limited correlation between tumor mutational burden and PD-L1 immunohistochemistry (IHC), which shows the importance of testing patients with triple-negative BCBM for immune checkpoint inhibitor eligibility with both PD-L1 IHC and CGP.

The COVID-19 pandemic has been a disruptive event for cancer patients, especially those with haematological malignancies (HM). They may experience a more severe clinical course due to impaired immune responses. This multi-center retrospective UK audit identified cancer patients who had SARS-CoV-2 infection between 1 March and 10 June 2020 and collected data pertaining to cancer history, COVID-19 presentation and outcomes. In total, 179 patients were identified with a median age of 72 (IQR 61, 81) and follow-up of 44 days (IQR 42, 45). Forty-one percent were female and the overall mortality was 37%. Twenty-nine percent had HM and of these, those treated with chemotherapy in the preceding 28 days to COVID-19 diagnosis had worse outcome compared with solid malignancy (SM): 62% versus 19% died [HR 8.33 (95% CI, 2.56-25), p p = 0.001). Patients with haematological malignancies and those who acquire nosocomial transmission are at increased risk of death. Therefore, there is an urgent need to reassess shielding advice, reinforce stringent infection control, and ensure regular patient and staff testing to prevent nosocomial transmission.

Background: Patients with cancer are at increased risk of severe COVID-19, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET). Methods: Patients with active cancer (stage I-IV) and laboratory confirmed COVID-19 presenting to hospitals worldwide were included. Discharge (within 24hrs), admission (≥24hrs inpatient), oxygen requirement (O2) and death were combined in a 0-3 point severity scale. Association of features with outcome were investigated using Lasso regression and Random Forest (RF) combined with SHapley Additive exPlanations (SHAP). RF was further validated in 4 cohorts, split by geography. The CORONET model was then examined in the entire cohort to build an online CORONET decision-support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Findings: The dataset comprised 920 patients; median age 70 (range 5-99), 56% males, 44% females, 81% solid vs. 19% haematological cancers. In derivation, RF demonstrated superior performance over Lasso with lower mean squared error (0.801 vs. 0.807) and was selected for development. During validation, RF achieved mean AUROC 0.77, 0.80 and 0.75 for prediction of admission, O 2 and death, respectively. Using the entire cohort, CORONET cut-offs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died. SHAP explanations revealed National-Early-Warning-Score-2, C-reactive protein and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. Interpretation: CORONET, a decision-support tool validated in healthcare systems worldwide can aid admission decisions and predict COVID-19 severity in patients with cancer. Funding Information: R. Lee and T. Robinson and J. Weaver are supported by the National Institute for Health Research as Clinical Lecturers. T. Bhogal is supported by the National Institute for Health Research as an academic clinical fellow. U. Khan is an MRC Clinical Training Fellow based at the University of Liverpool supported by the North West England Medical Research Council Fellowship Scheme in Clinical Pharmacology and Therapeutics, which is funded by the Medical Research Council (Award Ref. MR/N025989/1). The Liverpool Experimental Cancer Medicine Centre for providing infrastructure support (Grant Reference: C18616/A25153) and The Clatterbridge Cancer charity (North West Cancer Research). C. Dive is funded by CRUK Core funding to Manchester Institute (C5757/A27412) and is supported by the CRUK Manchester Centre Award (C5759/A25254), and by the NIHR Manchester Biomedical Research Centre. C. Zhou is funded by the CRUK Manchester Centre Award (C5759/A25254), J. Stevenson and P. Fitzpatrick are funded by the CRUK Accelerator Award (29374). This research was funded in part, by the Wellcome Trust [205228/Z/16/Z]. LT is also supported by the National Institute for Health Research Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections (NIHR200907) at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford. LT is based at University of Liverpool. MS is supported by a grant from the Ministry of Science and Higher Education of the Russian Federation for the state support for the creation and development of World Class Research Centers "Digital biodesign and personalized healthcare” N.075-15-2020-926. Declaration of Interests: R Lee research funding (institution) BMS and speaker fees Astrazeneca. A. Croitoru Consulting or Advisory Role: Lilly, Merck, Roche, Bayer, Novartis, Ipsen, Research Funding me and my hospital: Gilead Sciences, Pfizer, Canfite, NanoCarrier, Bristol-Myers Squibb, Merck, Amgen, Servier, Five Prime Therapeutics, Travel Accommodations: Pfizer, Genekor, and oz, Merck, Pfizer, Servier, Roche. O. Michielin reports personal fees from Bristol-Myers Squibb, personal fees from MSD, personal fees from Novartis, personal fees from Roche, personal fees from Amgen, personal fees from NeraCare GmbH, outside the submitted work. E. Romano institutional research grants from Amgen, Astra Zeneca, Bristol-Myers Squibb. G. Pentheroudakis advisory board for Amgen, Astra Zeneca, Bristol-Myers Squibb, Lilly, Merck, MSD, Roche, Abbvie, institutional research grants from Amgen, Astra Zeneca, Boehringer Ingelheim, Bristol Myers Squibb, Debbio, Enorasis, Genekor, Ipsen, Janssen, Lilly, Merck, MSD, Pfizer, Roche, Sanofi, Servier. Solange Peters reports consultation/advisory role: AbbVie, Amgen, AstraZeneca, Bayer, Beigene, Biocartis, Bio Invent, Blueprint Medicines, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, Elsevier, F. Hoffmann-La Roche/Genentech, Foundation Medicine, Illumina, Incyte, IQVIA, Janssen, Medscape, Merck Sharp and Dohme, Merck Serono, Merrimack, Mirati, Novartis, Pharma Mar, Phosplatin Therapeutics, Pfizer, Regeneron, Sanofi, Seattle Genetics, Takeda, Vaccibody, talk in a company’s organized public event: AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, e-cancer, Eli Lilly, F. Hoffmann-La Roche/Genentech, Illumina, Medscape, Merck Sharp and Dohme, Novartis, PER, Pfizer, Prime, RTP, Sanofi, Takeda, receipt of grants/research supports: (Sub)investigator in trials (institutional financial support for clinical trials) sponsored by Amgen, AstraZeneca, Biodesix, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, F. Hoffmann-La Roche/Genentech, GSK, Illumina, Lilly, Merck Sharp and Dohme, Merck Serono, Mirati, Novartis, and Pfizer, Phosplatin Therapeutics. M Rowe honoraria from Astellas Pharma, speaker fees MSD and Servier. C. Wilson consultancy and speaker fees Pfizer, Amgen, Novartis, A Armstrong conference fee Merck, spouse shares in Astrazeneca. T Robinson financial support to attend educational workshops from Amgen and Daiichi-Sankyo. C Dive, outside of this scope of work, has received research funding from AstraZeneca, Astex Pharmaceuticals, Bioven, Amgen, Carrick Therapeutics, Merck AG, Taiho Oncology, Clearbridge Biomedics, Angle PLC, Menarini Diagnostics, GSK, Bayer, Boehringer Ingelheim, Roche, BMS, Novartis, Celgene, Thermofisher. C Dive is on advisory boards for, and has received consultancy fees/honoraria from, AstraZeneca, Biocartis and Merck KGaA. No other authors have nothing to declare. Ethics Approval Statement: Approval (reference 20/WA/0269) was granted from the UK Research Ethics Committee for the study. Information regarding governance/regulatory approvals for each international cohort are available in the Supp. Methods.

BackgroundCancer patients are at increased risk of severe COVID-19. As COVID-19 presentation and outcomes are heterogeneous in cancer patients, decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical.ObjectiveTo identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET)MethodData was obtained for consecutive patients with active cancer with laboratory confirmed COVID-19 presenting in 12 hospitals throughout the United Kingdom (UK). Univariable logistic regression was performed on pre-specified features to assess their association with admission (≥24 hours inpatient), oxygen requirement and death. Multivariable logistic regression and random forest models (RFM) were compared with patients randomly split into training and validation sets. Cost function determined cut-offs were defined for admission/death using RFM. Performance was assessed by sensitivity, specificity and Brier scores (BS). The CORONET model was then assessed in the entire cohort to build the online CORONET tool.ResultsTraining and validation sets comprised 234 and 66 patients respectively with median age 69 (range 19-93), 54% males, 46% females, 71% vs 29% had solid and haematological cancers. The RFM, selected for further development, demonstrated superior performance over logistic regression with AUROC predicting admission (0.85 vs. 0.78) and death (0.76 vs. 0.72). C-reactive protein was the most important feature predicting COVID-19 severity. CORONET cut-offs for admission and mortality of 1.05 and 1.8 were established. In the training set, admission prediction sensitivity and specificity were 94.5% and 44.3% with BS 0.118; mortality sensitivity and specificity were 78.5% and 57.2% with BS 0.364. In the validation set, admission sensitivity and specificity were 90.7% and 42.9% with BS 0.148; mortality sensitivity and specificity were 92.3% and 45.8% with BS 0.442. In the entire cohort, the CORONET decision support tool recommended admission of 99% of patients requiring oxygen and of 99% of patients who died.Conclusions and RelevanceCORONET, a decision support tool validated in hospitals throughout the UK showed promise in aiding decisions regarding admission and predicting COVID-19 severity in patients with cancer presenting to hospital. Future work will validate and refine the tool in further datasets.

To investigate the effect of sarcopenia on postoperative mortality in patients undergoing emergency abdominal procedures and to compare postoperative mortality in patients with sarcopenia undergoing emergency abdominal procedures with those undergoing elective abdominal procedures.A search of electronic information sources was conducted to identify all observational studies comparing sarcopenia with no sarcopenia in a) emergency abdominal surgery and b) elective abdominal surgery. We also identified the available cohort of patients in the literature with sarcopenia undergoing abdominal procedures and divided the entire cohort into two groups based on exposure to emergency surgery or elective surgery. The primary outcome measure of this study was postoperative 30-day mortality.Overall, 4 studies, enrolling a total of 734 patients, were eligible for the comparison in emergency setting and 16 studies, enrolling a total of 4590 patients, were eligible for the comparison in elective setting. Sarcopenia is associated with significantly higher risk of 30-day mortality (RR: 2.15, P 0.0001), 1-year mortality (RR:1.97, P 0.0001), total complications (RR:2.07, P = 0.0008), and need for ICU admission (RR:1.38, P = 0.003) and significantly longer length of ICU stay (MD:2.26, P = 0.006) and length of hospital stay (MD:2.46, P 0.00001) compared to no sarcopenia in patients undergoing emergency abdominal procedures. Sarcopenia was also associated with significantly higher risk of 30-day mortality in patients undergoing elective abdominal procedures (RR:2.15, P = 0.002). Emergency abdominal surgery in patients with sarcopenia was associated with significantly higher risk of 30-day mortality compared to elective surgery (OR:12.00, P 0.00001).Sarcopenia is an independent predictor of postoperative mortality in emergency abdominal surgery.