How head and neck consultants manage patients’ emotional distress during cancer follow-up consultations : a multilevel study

Head and neck cancer (HNC) patients suffer substantial emotional problems. This study aimed to explore how utterance-level variables (source, type and timing of emotional cues) and patient-level variables (e.g. age, gender and emotional well-being) relate to consultants’ responses (i.e. reducing or providing space) to patient expressions of emotional distress. Forty-three HNC outpatient follow-up consultations were audio recorded and coded, for patients’ expressions of emotional distress and consultants’ responses, using the Verona Coding Definitions of Emotional Sequence. Multilevel logistic regression modelled the probability of the occurrence of consultant reduce space response as a function of patient distress cue expression, controlling for consultation and patient-related variables. An average of 3.5 cues/concerns (range 1–20) was identified per consultation where 84 out of 152 total cues/concerns were responded by reducing space. Cue type did not impact on response; likewise for the quality of patient emotional well-being. However, consultants were more likely to reduce space to cues elicited by patients, as opposed to those initiated by themselves. This reduced space response was more pronounced as the consultation continued. However, about 6 min into the consultation, this effect (i.e. tendency to block patients) started to weaken. Head and neck consultants’ responses to negative emotions depended on source and timing of patient emotional expressions. The findings are useful for training programme development to encourage consultants to be more flexible and open in the early stages of the consultation.PostprintPeer reviewe

Chromatin Regulation and Gene Centrality Are Essential for Controlling Fitness Pleiotropy in Yeast

There are a wide range of phenotypes that are due to loss-of-function or null mutations. Previously, the functions of gene products that distinguish essential from nonessential genes were characterized. However, the functions of products of non-essential genes that contribute to fitness remain minimally understood.Using data from Saccharomyces cerevisiae, we investigated several gene characteristics, which we are able to measure, that are significantly associated with a gene's fitness pleiotropy. Fitness pleiotropy is a measurement of the gene's importance to fitness. These characteristics include: 1) whether the gene's product functions in chromatin regulation, 2) whether the regulation of the gene is influenced by chromatin state, measured by chromatin regulation effect (CRE), 3) whether the gene's product functions as a transcription factor (TF) and the number of genes a TF regulates, 4) whether the gene contains TATA-box, and 5) whether the gene's product is central in a protein interaction network. Partial correlation analysis was used to study how these characteristics interact to influence fitness pleiotropy. We show that all five characteristics that were measured are statistically significantly associated with fitness pleiotropy. However, fitness pleiotropy is not associated with the presence of TATA-box when CRE is controlled. In particular, two characteristics: 1) whether the regulation of a gene is more likely to be influenced by chromatin state, and 2) whether the gene product is central in a protein interaction network measured by the number of protein interactions were found to play the most important roles affecting a gene's fitness pleiotropy.These findings highlight the significance of both epigenetic gene regulation and protein interaction networks in influencing the fitness pleiotropy

Which Head and Neck Cancer Patients Are Most at Risk of High Levels of Fear of Cancer Recurrence

Background: Fear of cancer recurrence (FCR) is recognized as a common concern for patients with head and neck cancer (HNC). The aim of this study is to describe in greater detail the demographic and clinical characteristics of HCN patients who indicate a high level of FCR in their review consultation. Methods: A pragmatic cluster-controlled trial was conducted between January 2017 and December 2018 at two UK HNC centers (Leeds and Liverpool) to test the efficacy of a prompt tool called the Patient Concerns Inventory (PCI). Patients completed the PCI and the UW-QOLv4 which included a single 5 category rating of FCR. Secondary statistical analyses focused on variables associated with high FCR. Results: Two hundred and eighty-eight trial patients were recruited in this trial. At a median of 194 days after diagnosis and 103 days after the end of treatment 8% stated (n = 24) “I get a lot of fears of recurrence and these can really preoccupy my thoughts” and 3% (n = 8) “I am fearful all the time that my cancer might return, and I struggle with this.” Thus, 11% (n = 32) responded in the worst two categories, 95% Confidence interval 7.7–15.3% for high FCR. Stepwise logistic regression resulted in female gender (p < 0.001), age (p = 0.007), and receiving financial benefits (p = 0.01) as independent predictors. Conclusions: Around one in ten HNC patients attending routine outpatient follow-up consultations report high FCR, however for female patients under the age of 55 the rate was one in three. This group requires specialist attention and could be the focus of a multicenter intervention trial

Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures

The presence of Long Distance Dependencies (LDDs) in sequential data poses significant challenges for computational models. Various recurrent neural architectures have been designed to mitigate this issue. In order to test these state-of-the-art architectures, there is growing need for rich benchmarking datasets. However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs. This lack of control limits the analysis of model performance in relation to the specific challenge posed by LDDs. One way to address this is to use synthetic data having the properties of subregular languages. The degree of LDDs within the generated data can be controlled through the k parameter, length of the generated strings, and by choosing appropriate forbidden strings. In this paper, we explore the capacity of different RNN extensions to model LDDs, by evaluating these models on a sequence of SPk synthesized datasets, where each subsequent dataset exhibits a longer degree of LDD. Even though SPk are simple languages, the presence of LDDs does have significant impact on the performance of recurrent neural architectures, thus making them prime candidate in benchmarking tasks.Comment: International Conference of Artificial Neural Networks (ICANN) 201

Factors that affect quality of life for older people with head and neck cancer: A systematic review

Purpose: Quality of life is a critical aspect in the management of older head and neck cancer patients. It needs to be considered alongside survival benefit, treatment burden, and longer-term outcomes. The purpose was to undertake a systematic review of empirical peer-reviewed studies with a primary focus on factors impacting quality of life for older head and neck cancer patients. Methods: A systematic review, searching 5 electronic databases (PsychoINFO, MEDLINE, CINHAL, Embase, and Scopus) using PRISMA methodology was conducted. Data was appraised using the Newcastle-Ottawa scale and a narrative synthesis performed. Results: Only 10 papers fulfilled the inclusion criteria. Two main themes emerged: 1) Impact of head and neck cancer on quality of life domains and 2) quality of life in treatment decision-making. Conclusions: In an era of progressive personalised care, there is an evident need for more qualitative and quantitative studies focusing on quality of life for older head and neck cancer patients. However, older head and neck cancer patients experience notable differences, especially with poorer physical functioning and greater eating and drinking challenges. Quality of life impacts older patients decision-making, treatment planning and intensifies post-treatment support

Concerns raised by people treated for head and neck cancer : a secondary analysis of audiotaped consultations in a health services follow-up clinic

Purpose People treated for head and neck cancer (HNC) face various barriers in communicating concerns with consultants. Our aim was to investigate the number of concerns raised between patients using the Patient Concerns Inventory (PCI) and those who did not. The PCI is a 57-item prompt list used in routine HNC follow-up clinics. Additionally, we aimed to examine whether who initiated the concerns differed between groups and the factors that may predict this initiation. Methods   Secondary data analysis included 67 participants across 15 HNC consultants from specialist cancer centres in Liverpool and Leeds. Seven consultants utilised the PCI and eight did not, assigned by preferential and random assignment. Results   Patients in the PCI group raised on average 2.5 more concerns than patients in the non-PCI group (p < .001). There was no significant relationship between group and who initiated the first concern (p = .28). A mixed-effects logistic regression was found to significantly predict who initiated the first concern in consultations (p < .05). Discussion   The number of concerns raised by patients increased when the PCI was introduced pre-HNC consultation. A number of factors were shown to predict the number of concerns raised in consultations by both patient and consultant. As concerns may not be raised further following the concern mentioned, we propose that the discussion of concerns needs to be maintained by the clinician throughout the consultation and not solely at the start. Conclusion   The PCI promoted the sharing of concerns in follow-up consultations between patient and consultant.Publisher PDFPeer reviewe

A low stellar obliquity for WASP-47, a compact multiplanet system with a hot Jupiter and an ultra-short period planet

We have detected the Rossiter-Mclaughlin effect during a transit of WASP-47b, the only known hot Jupiter with close planetary companions. By combining our spectroscopic observations with Kepler photometry, we show that the projected stellar obliquity is $\lambda = 0^\circ \pm 24^\circ$. We can firmly exclude a retrograde orbit for WASP-47b, and rule out strongly misaligned prograde orbits. Low obliquities have also been found for most of the other compact multiplanet systems that have been investigated. The Kepler-56 system, with two close-in gas giants transiting their subgiant host star with an obliquity of at least 45$^\circ$, remains the only clear counterexample.Comment: 5 pages, 2 figures, Accepted for publication on ApJL, comments welcom

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation