Outcomes of the SARS-CoV-2 omicron (B.1.1.529) variant outbreak among vaccinated and unvaccinated patients with cancer in Europe: results from the retrospective, multicentre, OnCovid registry study

BACKGROUND: The omicron (B.1.1.529) variant of SARS-CoV-2 is highly transmissible and escapes vaccine-induced immunity. We aimed to describe outcomes due to COVID-19 during the omicron outbreak compared with the prevaccination period and alpha (B.1.1.7) and delta (B.1.617.2) waves in patients with cancer in Europe. METHODS: In this retrospective analysis of the multicentre OnCovid Registry study, we recruited patients aged 18 years or older with laboratory-confirmed diagnosis of SARS-CoV-2, who had a history of solid or haematological malignancy that was either active or in remission. Patient were recruited from 37 oncology centres from UK, Italy, Spain, France, Belgium, and Germany. Participants were followed up from COVID-19 diagnosis until death or loss to follow-up, while being treated as per standard of care. For this analysis, we excluded data from centres that did not actively enter new data after March 1, 2021 (in France, Germany, and Belgium). We compared measures of COVID-19 morbidity, which were complications from COVID-19, hospitalisation due to COVID-19, and requirement of supplemental oxygen and COVID-19-specific therapies, and COVID-19 mortality across three time periods designated as the prevaccination (Feb 27 to Nov 30, 2020), alpha-delta (Dec 1, 2020, to Dec 14, 2021), and omicron (Dec 15, 2021, to Jan 31, 2022) phases. We assessed all-cause case-fatality rates at 14 days and 28 days after diagnosis of COVID-19 overall and in unvaccinated and fully vaccinated patients and in those who received a booster dose, after adjusting for country of origin, sex, age, comorbidities, tumour type, stage, and status, and receipt of systemic anti-cancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974, and is ongoing. FINDINGS: As of Feb 4, 2022 (database lock), the registry included 3820 patients who had been diagnosed with COVID-19 between Feb 27, 2020, and Jan 31, 2022. 3473 patients were eligible for inclusion (1640 [47·4%] were women and 1822 [52·6%] were men, with a median age of 68 years [IQR 57–77]). 2033 (58·5%) of 3473 were diagnosed during the prevaccination phase, 1075 (31·0%) during the alpha-delta phase, and 365 (10·5%) during the omicron phase. Among patients diagnosed during the omicron phase, 113 (33·3%) of 339 were fully vaccinated and 165 (48·7%) were boosted, whereas among those diagnosed during the alpha-delta phase, 152 (16·6%) of 915 were fully vaccinated and 21 (2·3%) were boosted. Compared with patients diagnosed during the prevaccination period, those who were diagnosed during the omicron phase had lower case-fatality rates at 14 days (adjusted odds ratio [OR] 0·32 [95% CI 0·19–0·61) and 28 days (0·34 [0·16–0·79]), complications due to COVID-19 (0·26 [0·17–0·46]), and hospitalisation due to COVID-19 (0·17 [0·09–0·32]), and had less requirements for COVID-19-specific therapy (0·22 [0·15–0·34]) and oxygen therapy (0·24 [0·14–0·43]) than did those diagnosed during the alpha-delta phase. Unvaccinated patients diagnosed during the omicron phase had similar crude case-fatality rates at 14 days (ten [25%] of 40 patients vs 114 [17%] of 656) and at 28 days (11 [27%] of 40 vs 184 [28%] of 656) and similar rates of hospitalisation due to COVID-19 (18 [43%] of 42 vs 266 [41%] of 652) and complications from COVID-19 (13 [31%] of 42 vs 237 [36%] of 659) as those diagnosed during the alpha-delta phase. INTERPRETATION: Despite time-dependent improvements in outcomes reported in the omicron phase compared with the earlier phases of the pandemic, patients with cancer remain highly susceptible to SARS-CoV-2 if they are not vaccinated against SARS-CoV-2. Our findings support universal vaccination of patients with cancer as a protective measure against morbidity and mortality from COVID-19. FUNDING: National Institute for Health and Care Research Imperial Biomedical Research Centre and the Cancer Treatment and Research Trust

Face recognition based on Kinect

In this paper, we present a new algorithm that utilizes low-quality red, green, blue and depth (RGB-D) data from the Kinect sensor for face recognition under challenging conditions. This algorithm extracts multiple features and fuses them at the feature level. A Finer Feature Fusion technique is developed that removes redundant information and retains only the meaningful features for possible maximum class separability. We also introduce a new 3D face database acquired with the Kinect sensor which has released to the research community. This database contains over 5,000 facial images (RGB-D) of 52 individuals under varying pose, expression, illumination and occlusions. Under the first three variations and using only the noisy depth data, the proposed algorithm can achieve 72.5 % recognition rate which is significantly higher than the 41.9 % achieved by the baseline LDA method. Combined with the texture information, 91.3 % recognition rate has achieved under illumination, pose and expression variations. These results suggest the feasibility of low-cost 3D sensors for real-time face recognition

Statistical shape modelling for expression-invariant face analysis and recognition

Paper introduces a 3-D shape representation scheme for automatic face analysis and identification, and demonstrates its invariance to facial expression. The core of this scheme lies on the combination of statistical shape modelling and non-rigid deformation matching. While the former matches 3-D faces with facial expression, the latter provides a low-dimensional feature vector that controls the deformation of model for matching the shape of new input, thereby enabling robust identification of 3-D faces. The proposed scheme is also able to handle the pose variation without large part of missing data. To assist the establishment of dense point correspondences, a modified freeform-deformation based on B-spline warping is applied with the help of extracted landmarks. The hybrid iterative closest point method is introduced for matching the models and new data. The feasibility and effectiveness of the proposed method was investigated using standard publicly available Gavab and BU-3DFE datasets, which contain faces with expression and pose changes. The performance of the system was compared with that of nine benchmark approaches. The experimental results demonstrate that the proposed scheme provides a competitive solution for face recognition

Genome-wide association study identifies novel loci predisposing to cutaneous melanoma

We performed a multistage genome-wide association study of melanoma. In a discovery cohort of 1804 melanoma cases and 1026 controls, we identified loci at chromosomes 15q13.1 (HERC2/OCA2 region) and 16q24.3 (MC1R) regions that reached genome-wide significance within this study and also found strong evidence for genetic effects on susceptibility to melanoma from markers on chromosome 9p21.3 in the p16/ARF region and on chromosome 1q21.3 (ARNT/LASS2/ANXA9 region). The most significant single-nucleotide polymorphisms (SNPs) in the 15q13.1 locus (rs1129038 and rs12913832) lie within a genomic region that has profound effects on eye and skin color; notably, 50% of variability in eye color is associated with variation in the SNP rs12913832. Because eye and skin colors vary across European populations, we further evaluated the associations of the significant SNPs after carefully adjusting for European substructure. We also evaluated the top 10 most significant SNPs by using data from three other genome-wide scans. Additional in silico data provided replication of the findings from the most significant region on chromosome 1q21.3 rs7412746 (P = 6 x 10(-10)). Together, these data identified several candidate genes for additional studies to identify causal variants predisposing to increased risk for developing melanoma