A population-scale temporal case-control evaluation of COVID-19 disease phenotype and related outcome rates in patients with cancer in England (UKCCP).

Patients with cancer are at increased risk of hospitalisation and mortality following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, the SARS-CoV-2 phenotype evolution in patients with cancer since 2020 has not previously been described. We therefore evaluated SARS-CoV-2 on a UK populationscale from 01/11/2020-31/08/2022, assessing case-outcome rates of hospital assessment(s), intensive care admission and mortality. We observed that the SARS-CoV-2 disease phenotype has become less severe in patients with cancer and the non-cancer population. Case-hospitalisation rates for patients with cancer dropped from 30.58% in early 2021 to 7.45% in 2022 while case-mortality rates decreased from 20.53% to 3.25%. However, the risk of hospitalisation and mortality remains 2.10x and 2.54x higher in patients with cancer, respectively. Overall, the SARS-CoV-2 disease phenotype is less severe in 2022 compared to 2020 but patients with cancer remain at higher risk than the non-cancer population. Patients with cancer must therefore be empowered to live more normal lives, to see loved ones and families, while also being safeguarded with expanded measures to reduce the risk of transmission.

Spatial and temporal intra-tumoral heterogeneity in advanced HGSOC: Implications for surgical and clinical outcomes.

Limited evidence exists on the impact of spatial and temporal heterogeneity of high-grade serous ovarian cancer (HGSOC) on tumor evolution, clinical outcomes, and surgical operability. We perform systematic multi-site tumor mapping at presentation and matched relapse from 49 high-tumor-burden patients, operated up front. From SNP array-derived copy-number data, we categorize dendrograms representing tumor clonal evolution as sympodial or dichotomous, noting most chemo-resistant patients favor simpler sympodial evolution. Three distinct tumor evolutionary patterns from primary to relapse are identified, demonstrating recurrent disease may emerge from pre-existing or newly detected clones. Crucially, we identify spatial heterogeneity for clinically actionable homologous recombination deficiency scores and for poor prognosis biomarkers CCNE1 and MYC. Copy-number signature, phenotypic, proteomic, and proliferative-index heterogeneity further highlight HGSOC complexity. This study explores HGSOC evolution and dissemination across space and time, its impact on optimal surgical cytoreductive effort and clinical outcomes, and its consequences for clinical decision-making.

COVID-19: Third dose booster vaccine effectiveness against breakthrough coronavirus infection, hospitalisations and death in patients with cancer: A population-based study.

PURPOSE: People living with cancer and haematological malignancies are at an increased risk of hospitalisation and death following infection with acute respiratory syndrome coronavirus 2. Coronavirus third dose vaccine boosters are proposed to boost waning immune responses in immunocompromised individuals and increase coronavirus protection; however, their effectiveness has not yet been systematically evaluated. METHODS: This study is a population-scale real-world evaluation of the United Kingdom's third dose vaccine booster programme for cancer patients from 8th December 2020 to 7th December 2021. The cancer cohort comprises individuals from Public Health England's national cancer dataset, excluding individuals less than 18 years. A test-negative case-control design was used to assess the third dose booster vaccine effectiveness. Multivariable logistic regression models were fitted to compare risk in the cancer cohort relative to the general population. RESULTS: The cancer cohort comprised of 2,258,553 tests from 361,098 individuals. Third dose boosters were evaluated by reference to 87,039,743 polymerase chain reaction coronavirus tests. Vaccine effectiveness against breakthrough infections, symptomatic infections, coronavirus hospitalisation and death in cancer patients were 59.1%, 62.8%, 80.5% and 94.5%, respectively. Lower vaccine effectiveness was associated with a cancer diagnosis within 12 months, lymphoma, recent systemic anti-cancer therapy (SACT) or radiotherapy. Patients with lymphoma had low levels of protection from symptomatic disease. In spite of third dose boosters, following multivariable adjustment, individuals with cancer remain at an increased risk of coronavirus hospitalisation and death compared to the population control (OR 3.38, 3.01, respectively. p < 0.001 for both). CONCLUSIONS: Third dose boosters are effective for most individuals with cancer, increasing protection from coronavirus. However, their effectiveness is heterogenous and lower than the general population. Many patients with cancer will remain at the increased risk of coronavirus infections even after 3 doses. In the case of patients with lymphoma, there is a particularly strong disparity of vaccine effectiveness against breakthrough infection and severe disease. Breakthrough infections will disrupt cancer care and treatment with potentially adverse consequences on survival outcomes. The data support the role of vaccine boosters in preventing severe disease, and further pharmacological intervention to prevent transmission and aid viral clearance to limit the disruption of cancer care as the delivery of care continues to evolve during the coronavirus pandemic.

Vaccine effectiveness against COVID-19 breakthrough infections in patients with cancer (UKCCEP): a population-based test-negative case-control study.

BACKGROUND: People with cancer are at increased risk of hospitalisation and death following infection with SARS-CoV-2. Therefore, we aimed to conduct one of the first evaluations of vaccine effectiveness against breakthrough SARS-CoV-2 infections in patients with cancer at a population level. METHODS: In this population-based test-negative case-control study of the UK Coronavirus Cancer Evaluation Project (UKCCEP), we extracted data from the UKCCEP registry on all SARS-CoV-2 PCR test results (from the Second Generation Surveillance System), vaccination records (from the National Immunisation Management Service), patient demographics, and cancer records from England, UK, from Dec 8, 2020, to Oct 15, 2021. Adults (aged ≥18 years) with cancer in the UKCCEP registry were identified via Public Health England's Rapid Cancer Registration Dataset between Jan 1, 2018, and April 30, 2021, and comprised the cancer cohort. We constructed a control population cohort from adults with PCR tests in the UKCCEP registry who were not contained within the Rapid Cancer Registration Dataset. The coprimary endpoints were overall vaccine effectiveness against breakthrough infections after the second dose (positive PCR COVID-19 test) and vaccine effectiveness against breakthrough infections at 3-6 months after the second dose in the cancer cohort and control population. FINDINGS: The cancer cohort comprised 377 194 individuals, of whom 42 882 had breakthrough SARS-CoV-2 infections. The control population consisted of 28 010 955 individuals, of whom 5 748 708 had SARS-CoV-2 breakthrough infections. Overall vaccine effectiveness was 69·8% (95% CI 69·8-69·9) in the control population and 65·5% (65·1-65·9) in the cancer cohort. Vaccine effectiveness at 3-6 months was lower in the cancer cohort (47·0%, 46·3-47·6) than in the control population (61·4%, 61·4-61·5). INTERPRETATION: COVID-19 vaccination is effective for individuals with cancer, conferring varying levels of protection against breakthrough infections. However, vaccine effectiveness is lower in patients with cancer than in the general population. COVID-19 vaccination for patients with cancer should be used in conjunction with non-pharmacological strategies and community-based antiviral treatment programmes to reduce the risk that COVID-19 poses to patients with cancer. FUNDING: University of Oxford, University of Southampton, University of Birmingham, Department of Health and Social Care, and Blood Cancer UK.

Evaluation of a novel communication and consultation skills model (WISE COACH) on dog owner perceptions of veterinarians and projected spending on veterinary care.

OBJECTIVE: To assess the impact of a novel communication and consultation skills model (WISE COACH [WC]) on dog owner perceptions of veterinarians and projected spending on veterinary care. SAMPLE: 1,200 US dog owners who had visited a veterinarian within the prior 18 months. PROCEDURES: Video recordings of 2 staged client consultations were made, with the veterinarian following the WC recommendations in one video and not following them in the other (control). Participants were randomly assigned to view one of the videos and completed an online survey to assess their perceptions and projected spending. Qualitative responses were coded to identify themes. RESULTS: The veterinarian was rated significantly higher in the WC video than in the control video for the characteristics first impression, skilled and knowledgeable, cares about me, cares about my pet, and communicates clearly, and was rated significantly lower for the characteristic rushed or abrupt. Participants who viewed the WC video were significantly more likely to follow the veterinarian's recommendations, return to see the veterinarian, and recommend the veterinarian. They were also approximately 1.4 times as likely to approve the full recommended treatment plan, and their projected total spending was approximately 15% higher than projected spending for participants who viewed the control video. CLINICAL RELEVANCE: Results showed improved client perceptions, client retention, quality of patient care, and financial metrics when the veterinarian followed the WC recommendations. Further study is needed to determine whether this model may also improve veterinarian well-being by improving client relationships and decreasing resistance to recommendations.

Towards a Machine Vision-Based Yield Monitor for the Counting and Quality Mapping of Shallots.

In comparison to field crops such as cereals, cotton, hay and grain, specialty crops often require more resources, are usually more sensitive to sudden changes in growth conditions and are known to produce higher value products. Providing quality and quantity assessment of specialty crops during harvesting is crucial for securing higher returns and improving management practices. Technical advancements in computer and machine vision have improved the detection, quality assessment and yield estimation processes for various fruit crops, but similar methods capable of exporting a detailed yield map for vegetable crops have yet to be fully developed. A machine vision-based yield monitor was designed to perform size categorization and continuous counting of shallots in-situ during the harvesting process. Coupled with a software developed in Python, the system is composed of a video logger and a global navigation satellite system. Computer vision analysis is performed within the tractor while an RGB camera collects real-time video data of the crops under natural sunlight conditions. Vegetables are first segmented using Watershed segmentation, detected on the conveyor, and then classified by size. The system detected shallots in a subsample of the dataset with a precision of 76%. The software was also evaluated on its ability to classify the shallots into three size categories. The best performance was achieved in the large class (73%), followed by the small class (59%) and medium class (44%). Based on these results, the occasional occlusion of vegetables and inconsistent lighting conditions were the main factors that hindered performance. Although further enhancements are envisioned for the prototype system, its modular and novel design permits the mapping of a selection of other horticultural crops. Moreover, it has the potential to benefit many producers of small vegetable crops by providing them with useful harvest information in real-time.

Treatment of gestational trophoblastic disease in the 2020s.

PURPOSE OF REVIEW: This review demonstrates the evidence for new systemic anticancer treatments and how they integrate within conventional management for gestational trophoblastic neoplasia (GTN). We present the evidence on atypical placental site nodules, and how they incorporate within the GTN spectrum, as well as updates regarding GTN staging and follow-up. RECENT FINDINGS: First-line treatment for GTN still lies in conventional chemotherapy, although the introduction of anti-PD1/PD-L1 immune checkpoint inhibitors has shown significant promise in management of relapsed disease, with responses reported in multiple relapsed choriocarcinomas as well as epithelioid trophoblastic tumours and placental site trophoblastic tumours (ETT/PSTT). Following completion of treatment, ETT/PSTT still require life-long surveillance but for other GTN, no recurrences have been detected after 7 years. SUMMARY: Checkpoint inhibitors are likely to play an increasing role in the future management of GTN management. Further refinement of prognostic factors to identify those most at risk of GTN recurrence is warranted so that surveillance can be focussed on those most at risk, whilst minimizing unnecessary intervention for those at lower risk.

Advances in cyclin-dependent kinase inhibitors for the treatment of melanoma.

Introduction: Despite the recent advances in the treatment of malignant melanoma with immunotherapy and BRAF/MEK targeted agents, advanced disease still beholds a poor prognosis for a significant proportion of patients. Cyclin-dependent kinase (CDK) inhibitors have been investigated as novel melanoma therapeutics throughout a range of phase 1 and 2 trials, as single agents and in combination with established treatments. Areas covered: This article summarizes the rationale for, and development of CDK inhibitors in melanoma, with their evolution from pan-CDK inhibitors to highly specific agents, throughout clinical trials and finally their potential future use. Expert opinion: Whilst CDK inhibitors have been practice changing in breast cancer management, their efficacy is yet to be proven in melanoma. Combination with BRAF/MEK inhibitors has been hindered by dose-limiting toxicities, but their role may yet to be found within the spectrum of biomarker-derived personalized melanoma management. The effect that CDK inhibitors can have as an adjunct to immunotherapy also remains to be seen.

The effect of clinical decision making for initiation of systemic anticancer treatments in response to the COVID-19 pandemic in England: a retrospective analysis.

BACKGROUND: Cancer services worldwide had to adapt in response to the COVID-19 pandemic to minimise risk to patients and staff. We aimed to assess the national impact of COVID-19 on the prescribing of systemic anticancer treatment in England, immediately after lockdown and after the introduction of new treatments to reduce patient risk. METHODS: We did a retrospective analysis using data from a central National Health Service England web database mandated for clinicians to register intention to start all new systemic anticancer treatments approved for use in England since 2016. We analysed the monthly number of treatment registrations in April, 2020, after the implementation of societal lockdown on March 23, 2020, and after implementation of treatment options to reduce patient risk such as oral or less immunosuppressive drugs, in May and June, 2020. We compared the number of registrations in April-June, 2020, with the mean number of registrations and SD during the previous 6 months of unaffected cancer care (September, 2019, to February, 2020). We calculated the percentage change and absolute difference in SD units for the number of registrations overall, by tumour type, and by type and line of therapy. FINDINGS: In April, 2020, 2969 registrations were recorded, representing 1417 fewer registrations than in the control period (monthly mean 4386; 32% reduction, absolute difference 4·2 SDs, p<0·0001). In May, 2020, total registrations increased to 3950, representing a 10% reduction compared with the control period (absolute difference 1·3 SDs, p<0·0001). In June, 2020, 5022 registrations were recorded, representing a 15% increase compared with the control period (absolute difference 1·9 SDs; p<0·0001]). INTERPRETATION: After the onset of the COVID-19 pandemic, there was a reduction in systemic anticancer treatment initiation in England. However, following introduction of treatment options to reduce patient risk, registrations began to increase in May, 2020, and reached higher numbers than the pre-pandemic mean in June, 2020, when other clinical and societal risk mitigation factors (such as telephone consultations, facemasks and physical distancing) are likely to have contributed. However, outcomes of providing less treatment or delaying treatment initiation, particularly for advanced cancers and neoadjuvant therapies, require continued assessment. FUNDING: None.

Developmental impairments in moral competence as mitigation in capital cases.

In this article we propose a mitigation approach in those capital murder cases where traditional mitigation themes such as mental illness or low IQ are not present. To avoid prosecution characterization of these defendants as simply evil or antisocial personalities, we suggest reframing the issue as one of moral incompetence, based not on character defect but rather stemming from profoundly neglectful or abusive parenting. Under this reframing, defense teams would present evidence about the many antecedents of poor moral competence, its origins in neglect or abuse, its neurophysiological basis, and, most importantly, its potential for change. Evaluation in such cases would pay close attention to early childhood and family characteristics. We also recommend presentation of research findings showing how moral competence can be improved in adulthood, given appropriate guidance and support. This approach to mitigation is consistent with much of the developmental literature. But juror responses to these mitigation themes are as yet unknown.

The status of research ethics in social work.

Research ethics provide important and necessary standards related to the conduct and dissemination of research. To better understand the current state of research ethics discourse in social work, a systematic literature search was undertaken and numbers of publications per year were compared between STEM, social science, and social work disciplines. While many professions have embraced the need for discipline-specific research ethics subfield development, social work has remained absent. Low publication numbers, compared to other disciplines, were noted for the years (2006-2016) included in the study. Social work published 16 (1%) of the 1409 articles included in the study, contributing 3 (>1%) for each of the disciplines highest producing years (2011 and 2013). Comparatively, psychology produced 75 (5%) articles, psychiatry produced 64 (5%) articles, and nursing added 50 (4%) articles. The STEM disciplines contributed 956 (68%) articles between 2006 and 2016, while social science produced 453 (32%) articles. Examination of the results is provided in an extended discussion of several misconceptions about research ethics that may be found in the social work profession. Implications and future directions are provided, focusing on the need for increased engagement, education, research, and support for a new subfield of social work research ethics.

Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

Health Behavior Decision-making in African-American Adults Diagnosed with Schizophrenia.

Little is known about the factors that influence health behavior decision-making among people with schizophrenia. The purpose of this qualitative study was to describe the processes used by 10 African-American adults with schizophrenia when making health behavior decisions and identification of perceived barriers and facilitators to health. Three phases of health behavior decision-making were identified: Recognizing Complex Components of Health, Personalizing Components of Health, and Tracking Health Status. Findings may guide clinicians' efforts to improve the health status of patients, as well as influence future research in understanding health behavior decision-making among vulnerable populations.

An inverse Yarbus process: predicting observers' task from eye movement patterns.

In this paper we develop a probabilistic method to infer the visual-task of a viewer given measured eye movement trajectories. This method is based on the theory of hidden Markov models (HMM) that employs a first order Markov process to predict the coordinates of fixations given the task. The prediction confidence level of each task-dependent model is used in a Bayesian inference formulation, whereby the task with the maximum a posteriori (MAP) probability is selected. We applied this technique to a challenging dataset consisting of eye movement trajectories obtained from subjects viewing monochrome images of real scenes tasked with answering questions regarding the scenes. The results show that the HMM approach, combined with a clustering technique, can be a reliable way to infer visual-task from eye movements data.

A computational model for task inference in visual search.

We develop a probabilistic framework to infer the ongoing task in visual search by revealing what the subject is looking for during a search process. Based on the level of difficulty, two types of tasks, easy and difficult, are investigated in this work, and individual models are customized for them according to their specific dynamics. We use Hidden Markov Models (HMMs) to serve as a model for the human cognitive process that is responsible for directing the center of gaze (COG) according to the task at hand during visual search and generating task-dependent eye trajectories. This generative model, then, is used to estimate the likelihood term in a Bayesian inference formulation to infer the task given the eye trajectory. In the easy task, focus of attention (FOA) often lands on targets, whereas in the difficult one, in addition to the on-target foci of attention, deployment of attention on nontarget objects happens very often. Therefore, we suggest a single-state and a multi-state HMM to serve as the cognitive process model of attention for the easy and difficult tasks, respectively.

Implementation issues in an innovative rural substance misuser treatment program.

This article is essentially the story of the development, implementation, and testing of a treatment protocol designed specifically for rural individuals who are substance misusers. Although the treatment protocol that emerged from this process seemed to be valuable for clients, the researchers were not able to establish with statistical significance that it was better than conventional treatment. In some ways, this was a failure. This article explores some of the possible reasons why new treatment approaches, tested in real clinical situations, may have difficulty establishing their effectiveness. The factors involved are many and complex.

A brief personal meditation about failure and defeat.

Failure and defeat create despair, but can also create new ways to imagine our therapeutic work with people. This essay explores one approach to understanding this idea.

'Better than nothing' is not good enough: challenges to introducing evidence-based approaches for traumatized populations.

RATIONALE: Focus group data were generated by a larger, mixed-methods investigation on treatment practices among therapists working with significantly traumatized populations in a primarily rural, underdeveloped region of the USA. This paper explores reasons behind low utilization of evidence-based practices (EBPs) that putatively would benefit poor communities where these behavioural health care providers serve. METHODS: Eight focus groups of 45 licensed and certified behavioural health professionals were conducted over a 6-month period of time in 2006. Sites were selected based on Beale code designations with representation from urban, rural, and rural with urban influence providers. Potential respondents were selected from licensing board membership rosters and invited to participate in the study. Focus groups were facilitated by trained interviewers using a semi-structured interview schedule that focused on how participants defined, assessed, and understood trauma, as well as the information therapists utilized to determine interventions for clients with trauma histories. RESULTS: Focus group transcripts were analysed using qualitative data reduction methods and six major themes emerged regarding the limited use of EBPs: complexity of trauma identification, issues with manualized assessment, role of treatment settings, conditions for innovation success and failure, untangling cultural effects, and defining successful treatment outcomes. CONCLUSION: These findings shed light on the endurance of insufficient behavioural health infrastructures despite therapists' access to scientifically validated treatments for trauma spectrum and co-morbid mental disorders suffered by children and adults. Such insights have implications for the success of global dissemination of validated behavioural health interventions.