Tezepelumab decreases airway epithelial IL-33 and T2-inflammation in response to viral stimulation in patients with asthma.

BACKGROUND: Respiratory virus infections are main triggers of asthma exacerbations. Tezepelumab, an anti-TSLP mAb, reduces exacerbations in patients with asthma, but the effect of blocking TSLP on host epithelial resistance and tolerance to virus infection is not known. AIM: To examine effects of blocking TSLP in patients with asthma on host resistance (IFNß, IFNλ, and viral load) and on the airway epithelial inflammatory response to viral challenge. METHODS: Bronchoalveolar lavage fluid (BALF, n = 39) and bronchial epithelial cells (BECs) were obtained from patients with uncontrolled asthma before and after 12 weeks of tezepelumab treatment (n = 13) or placebo (n = 13). BECs were cultured in vitro and exposed to the viral infection mimic poly(I:C) or infected by rhinovirus (RV). Alarmins, T2- and pro-inflammatory cytokines, IFNß IFNλ, and viral load were analyzed by RT-qPCR and multiplex ELISA before and after stimulation. RESULTS: IL-33 expression in unstimulated BECs and IL-33 protein levels in BALF were reduced after 12 weeks of tezepelumab. Further, IL-33 gene and protein levels decreased in BECs challenged with poly(I:C) after tezepelumab whereas TSLP gene expression remained unaffected. Poly(I:C)-induced IL-4, IL-13, and IL-17A release from BECs was also reduced with tezepelumab whereas IFNß and IFNλ expression and viral load were unchanged. CONCLUSION: Blocking TSLP with tezepelumab in vivo in asthma reduced the airway epithelial inflammatory response including IL-33 and T2 cytokines to viral challenge without affecting anti-viral host resistance. Our results suggest that blocking TSLP stabilizes the bronchial epithelial immune response to respiratory viruses.

Potential for using simulated altitude as a means of prehabilitation: a physiology study.

The current pandemic of surgical complications necessitates urgent and pragmatic innovation to reduce postoperative morbidity and mortality, which are associated with poor pre-operative fitness and anaemia. Exercise prehabilitation is a compelling strategy, but it has proven difficult to establish that it improves outcomes either in isolation or as part of a multimodal approach. Simulated altitude exposure improves performance in athletes and offers a novel potential means of improving cardiorespiratory and metabolic fitness and alleviating anaemia within the prehabilitation window. We aimed to provide an initial physiological foundation for 'altitude prehabilitation' by determining the physiological effects of one week of simulated altitude (FI O2 15%, equivalent to approximately 2438 m (8000 ft)) in older sedentary volunteers. The study used a randomised, double-blind, sham-controlled crossover design. Eight participants spent counterbalanced normoxic and hypoxic weeks in a residential hypoxia facility and underwent repeated cardiopulmonary exercise tests. Mean (SD) age of participants was 64 (7) y and they were unfit, with mean (SD) baseline anaerobic threshold 12 (2) ml.kg-1 .min-1 and mean (SD) peak V̇O2 15 (3) ml.kg-1 .min-1 . Hypoxia was mild (mean (SD) Sp O2 93 (2) %, p < 0.001) and well-tolerated. Despite some indication of greater peak exercise capacity following hypoxia, overall there was no effect of simulated altitude on anaerobic threshold or peak V̇O2 . However, hypoxia induced a substantial increase in mean (SD) haemoglobin of 1.5 (2.7) g.dl-1 (13% increase, p = 0.028). This study has established the concept and feasibility of 'altitude prehabilitation' and demonstrated specific potential for improving haematological fitness. Physiologically, there is value in exploring a possible role for simulated altitude in pre-operative optimisation.

The interplay between susceptibility and vaccine effectiveness control the timing and size of an emerging seasonal influenza wave in England.

Relaxing social distancing measures and reduced level of influenza over the last two seasons may lead to a winter 2022 influenza wave in England. We used an established model for influenza transmission and vaccination to evaluate the rolled out influenza immunisation programme over October to December 2022. Specifically, we explored how the interplay between pre-season population susceptibility and influenza vaccine efficacy control the timing and the size of a possible winter influenza wave. Our findings suggest that susceptibility affects the timing and the height of a potential influenza wave, with higher susceptibility leading to an earlier and larger influenza wave while vaccine efficacy controls the size of the peak of the influenza wave. With pre-season susceptibility higher than pre-COVID-19 levels, under the planned vaccine programme an early influenza epidemic wave is possible, its size dependent on vaccine effectiveness against the circulating strain. If pre-season susceptibility is low and similar to pre-COVID levels, the planned influenza vaccine programme with an effective vaccine could largely suppress a winter 2022 influenza outbreak in England.

Identification of the Neural Correlates Underlying Conflict Resolution Performance Using a Rodent Analogue of the Stroop Tests.

The Stroop test is a widely used neuropsychological test measuring attention and conflict resolution, which shows sensitivity across a range of diseases, including Alzheimer's, Parkinson's and Huntington's diseases. A rodent analogue of the Stroop test, the Response-Conflict task (rRCT), allows for systematic investigation of the neural systems underpinning performance in this test. Little is known about the involvement of the basal ganglia in this neural process. The aim of this study was to use the rRCT to determine whether striatal subregions are recruited during conflict resolution processing. To achieve this, rats were exposed to Congruent or Incongruent stimuli in the rRCT and the expression patterns of the immediate early gene Zif268 were analysed throughout cortical, hippocampal and basal ganglia subregions. The results confirmed the previously reported involvement of prefrontal cortical and hippocampal regions, as well as identifying a specific role for the dysgranular (but not granular) retrosplenial cortex in conflict resolution. Finally, performance accuracy correlated significantly with reduced neural activation in the dorsomedial striatum. Involvement of the basal ganglia in this neural process has not previously been reported. These data demonstrate that the cognitive process of conflict resolution requires not only prefrontal cortical regions, but also recruits the dysgranular retrosplenial cortex and the medial region of the neostriatum. These data have implications for understanding the neuroanatomical changes that underpin impaired Stroop performance in people with neurological disorders.

A randomised controlled trial of compression therapies for the treatment of venous leg ulcers (VenUS 6): study protocol for a pragmatic, multicentre, parallel-group, three-arm randomised controlled trial.

BACKGROUND: Venous leg ulcer(s) are common, recurring, open wounds on the lower leg, resulting from diseased or damaged leg veins impairing blood flow. Wound healing is the primary treatment aim for venous leg ulceration, alongside the management of pain, wound exudate and infection. Full (high) compression therapy delivering 40 mmHg of pressure at the ankle is the recommended first-line treatment for venous leg ulcers. There are several different forms of compression therapy available including wraps, two-layer hosiery, and two-layer or four-layer bandages. There is good evidence for the clinical and cost-effectiveness of four-layer bandage and two-layer hosiery but more limited evidence for other treatments (two-layer bandage and compression wraps). Robust evidence is required to compare clinical and cost-effectiveness of these and to investigate which is the best compression treatment for reducing time to healing of venous leg ulcers whilst offering value for money. VenUS 6 will therefore investigate the clinical and cost-effectiveness of evidence-based compression, two-layer bandage and compression wraps for time to healing of venous leg ulcers. METHODS: VenUS 6 is a pragmatic, multi-centre, three-arm, parallel-group, randomised controlled trial. Adult patients with a venous leg ulcer will be randomised to receive (1) compression wraps, (2) two-layer bandage or (3) evidence-based compression (two-layer hosiery or four-layer bandage). Participants will be followed up for between 4 and 12 months. The primary outcome will be time to healing (full epithelial cover in the absence of a scab) in days since randomisation. Secondary outcomes will include key clinical events (e.g. healing of the reference leg, ulcer recurrence, ulcer/skin deterioration, amputation, admission/discharge, surgery to close/remove incompetent superficial veins, infection or death), treatment changes, adherence and ease of use, ulcer related pain, health-related quality of life and resource use. DISCUSSION: VenUS 6 will provide robust evidence on the clinical and cost-effectiveness of the different forms of compression therapies for venous leg ulceration. VenUS 6 opened to recruitment in January 2021 and is currently recruiting across 30 participating centres. TRIAL REGISTRATION: ISRCTN67321719 . Prospectively registered on 14 September 2020.

Time-resolved Coulomb collision of single electrons.

A series of recent experiments have shown that collision of ballistic electrons in semiconductors can be used to probe the indistinguishability of single-electron wavepackets. Perhaps surprisingly, their Coulomb interaction has not been seen due to screening. Here we show Coulomb-dominated collision of high-energy single electrons in counter-propagating ballistic edge states, probed by measuring partition statistics while adjusting the collision timing. Although some experimental data suggest antibunching behaviour, we show that this is not due to quantum statistics but to strong repulsive Coulomb interactions. This prevents the wavepacket overlap needed for fermionic exchange statistics but suggests new ways to utilize Coulomb interactions: microscopically isolated and time-resolved interactions between ballistic electrons can enable the use of the Coulomb interaction for high-speed sensing or gate operations on flying electron qubits.

Willingness to vaccinate children against COVID-19 declined during the pandemic.

OBJECTIVES: To document the level of vaccine hesitancy in caregivers' of children younger than 12 years of age over the course of the pandemic in Pediatric Emergency Departments (ED). Study design Ongoing multicenter, cross-sectional survey of caregivers presenting to 19 pediatric EDs in the USA, Canada, Israel, and Switzerland during first months of the pandemic (phase1), when vaccines were approved for adults (phase2) and most recently when vaccines were approved for children (phase3). RESULTS: Willingness to vaccinate rate declined over the study period (59.7%, 56.1% and 52.1% in the three phases). Caregivers who are fully vaccinated, who have higher education, and those worried their child had COVID-19 upon arrival to the ED, were more likely to plan to vaccinate in all three phases. Mothers were less likely to vaccinate early in the pandemic, but this hesitancy attenuated in later phases. Older caregivers were more willing to vaccinate, and caregivers of older children were less likely to vaccinate their children in phase 3. During the last phase, willingness to vaccinate was lowest in those who had a primary care provider but did not rely on their advice for medical decisions (34%). Those with no primary care provider and those who do and rely on their medical advice, had similar rates of willingness to vaccinate (55.1% and 52.1%, respectively). CONCLUSIONS: COVID-19 vaccine hesitancy is widespread and growing over time, and public health measures should further try to leverage identified factors associated with hesitancy in order to enhance vaccination rates among children.

Phenotyping Superagers Using Resting-State fMRI.

BACKGROUND AND PURPOSE: Superagers are defined as older adults with episodic memory performance similar or superior to that in middle-aged adults. This study aimed to investigate the key differences in discriminative networks and their main nodes between superagers and cognitively average elderly controls. In addition, we sought to explore differences in sensitivity in detecting these functional activities across the networks at 3T and 7T MR imaging fields. MATERIALS AND METHODS: Fifty-five subjects 80 years of age or older were screened using a detailed neuropsychological protocol, and 31 participants, comprising 14 superagers and 17 cognitively average elderly controls, were included for analysis. Participants underwent resting-state-fMRI at 3T and 7T MR imaging. A prediction classification algorithm using a penalized regression model on the measurements of the network was used to calculate the probabilities of a healthy older adult being a superager. Additionally, ORs quantified the influence of each node across preselected networks. RESULTS: The key networks that differentiated superagers and elderly controls were the default mode, salience, and language networks. The most discriminative nodes (ORs > 1) in superagers encompassed areas in the precuneus posterior cingulate cortex, prefrontal cortex, temporoparietal junction, temporal pole, extrastriate superior cortex, and insula. The prediction classification model for being a superager showed better performance using the 7T compared with 3T resting-state-fMRI data set. CONCLUSIONS: Our findings suggest that the functional connectivity in the default mode, salience, and language networks can provide potential imaging biomarkers for predicting superagers. The 7T field holds promise for the most appropriate study setting to accurately detect the functional connectivity patterns in superagers.

Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions.

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and the agent-based model Covasim, in June 2021, to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. Using these estimates in Covasim (calibrated 1 September 2020 to 20 June 2021), in June 2021, we found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

The Royal Society RAMP modelling initiative.

Normally, science proceeds following a well-established set of principles. Studies are done with an emphasis on correctness, are submitted to a journal editor who evaluates their relevance, and then undergo anonymous peer review by experts before publication in a journal and acceptance by the scientific community via the open literature. This process is slow, but its accuracy has served all fields of science well. In an emergency situation, different priorities come to the fore. Research and review need to be conducted quickly, and the target audience consists of policymakers. Scientists must jostle for the attention of non-specialists without sacrificing rigour, and must deal not only with peer assessment but also with media scrutiny by journalists who may have agendas other than ensuring scientific correctness. Here, we describe how the Royal Society coordinated efforts of diverse scientists to help model the coronavirus epidemic. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Compositional modelling of immune response and virus transmission dynamics.

Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they do not allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Technical challenges of modelling real-life epidemics and examples of overcoming these.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the importance of mathematical modelling in informing and advising policy decision-making. Effective practice of mathematical modelling has challenges. These can be around the technical modelling framework and how different techniques are combined, the appropriate use of mathematical formalisms or computational languages to accurately capture the intended mechanism or process being studied, in transparency and robustness of models and numerical code, in simulating the appropriate scenarios via explicitly identifying underlying assumptions about the process in nature and simplifying approximations to facilitate modelling, in correctly quantifying the uncertainty of the model parameters and projections, in taking into account the variable quality of data sources, and applying established software engineering practices to avoid duplication of effort and ensure reproducibility of numerical results. Via a collection of 16 technical papers, this special issue aims to address some of these challenges alongside showcasing the usefulness of modelling as applied in this pandemic. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Modelling the impact of reopening schools in the UK in early 2021 in the presence of the alpha variant and with roll-out of vaccination against SARS-CoV-2.

Following the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the alpha (also known as B117) variant of the SARS-CoV-2 virus, a third national lockdown was imposed from January 4, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, the question of when and how to reopen schools became an increasingly pressing one in early 2021. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. We used our previously published agent-based model, Covasim, to model the emergence of the alpha variant over September 1, 2020 to January 31, 2021 in presence of Test, Trace and Isolate (TTI) strategies. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, with 200,000 daily vaccine doses prioritised by age starting with people 75 years or older, assuming vaccination offers a 95% reduction in disease acquisition risk and a 30% reduction in transmission risk. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (years 11 and 13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2021. Our calibration across different scenarios is consistent with alpha variant being around 60% more transmissible than the wild type. We find that strict social distancing measures, i.e. national lockdowns, were essential in containing the spread of the virus and controlling hospitalisations and deaths during January and February 2021. We estimated that a national lockdown over January and February 2021 would reduce the number of cases by early March to levels similar to those seen in October 2020, with R also falling and remaining below 1 over this period. We estimated that infections would start to increase when schools reopened, but found that if other parts of society remain closed, this resurgence would not be sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas was estimated to lead to lower increases in cases and R than if all schools opened. Without an increase in vaccination above the levels seen in January and February, we estimate that R could have increased above 1 following the reopening of society, simulated here from April 19, 2021. Our findings suggest that stringent measures were integral in mitigating the increase in cases and bringing R below 1 over January and February 2021. We found that it was plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 would keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, without an increase in vaccination levels, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

Kelp detritus: Unutilized productivity or an unacknowledged trophic resource?

Kelp beds are one of the most productive marine systems and, while little of this production is directly consumed, there is growing evidence that kelp detritus is an essential food source for many detrital and suspension feeders, and forms an important component of offshore sedimentary carbon pools. However, the extent of the contribution of kelp detritus to the nutrition of coastal fauna is not well resolved. In this study, we compare the contribution of phytoplankton, kelp detritus, and waste from fish cages to the diet of a sentinel suspension feeder, the blue mussel (Mytilus edulis) using stable isotopes. We found a significant depletion in both 13C and 15N in kelp tissue with age (distance from stipe to the deteriorating distal end of the kelp frond) which may have biased dietary estimates in previous studies which have applied isotopic source values derived from fresh kelp. Our mixing models indicate that macroalgal detritus formed 59% of the diet of the mussels in Berehaven, Bantry Bay, Ireland. We support the isotopic mixing model results by modelling the relative production of phytoplankton, kelp, and salmon farm waste, and found the supply of C and N from kelp and phytoplankton far exceeded the requirements of the mussels with much less coming from the nearby fish cages. Monthly chlorophyll measurements indicated there was only sufficient phytoplankton density to support mussel growth during the spring and autumn, explaining our observation of patterns in the relative importance of utilization of kelp detritus. Where there is pressure to harvest kelp beds, this study highlights the supporting ecosystem service they provide as an important dietary source in coastal food webs and emphasises the need for appropriate management measures for this resource.

Electrically Controllable Kondo Correlation in Spin-Orbit-Coupled Quantum Point Contacts.

Integrating the Kondo correlation and spin-orbit interactions, each of which have individually offered unprecedented means to manipulate electron spins, in a controllable way can open up new possibilities for spintronics. We demonstrate electrical control of the Kondo correlation by coupling the bound spin to leads with tunable Rashba spin-orbit interactions, realized in semiconductor quantum point contacts. We observe a transition from single to double peak zero-bias anomalies in nonequilibrium transport-the manifestation of the Kondo effect-indicating a controlled Kondo spin reversal using only spin-orbit interactions. Universal scaling of the Kondo conductance is demonstrated, implying that the spin-orbit interactions could enhance the Kondo temperature. A theoretical model based on quantum master equations is also developed to calculate the nonequilibrium quantum transport.

Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis.

Molecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8-12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal-ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and development.

Rule-based epidemic models.

Rule-based models generalise reaction-based models with reagents that have internal state and may be bound together to form complexes, as in chemistry. An important class of system that would be intractable if expressed as reactions or ordinary differential equations can be efficiently simulated when expressed as rules. In this paper we demonstrate the utility of the rule-based approach for epidemiological modelling presenting a suite of seven models illustrating the spread of infectious disease under different scenarios: wearing masks, infection via fomites and prevention by hand-washing, the concept of vector-borne diseases, testing and contact tracing interventions, disease propagation within motif-structured populations with shared environments such as schools, and superspreading events. Rule-based models allow to combine transparent modelling approach with scalability and compositionality and therefore can facilitate the study of aspects of infectious disease propagation in a richer context than would otherwise be feasible.

Modelling the potential impact of mask use in schools and society on COVID-19 control in the UK.

As the UK reopened after the first wave of the COVID-19 epidemic, crucial questions emerged around the role for ongoing interventions, including test-trace-isolate (TTI) strategies and mandatory masks. Here we assess the importance of masks in secondary schools by evaluating their impact over September 1-October 23, 2020. We show that, assuming TTI levels from August 2020 and no fundamental changes in the virus's transmissibility, adoption of masks in secondary schools would have reduced the predicted size of a second wave, but preventing it would have required 68% or 46% of those with symptoms to seek testing (assuming masks' effective coverage 15% or 30% respectively). With masks in community settings but not secondary schools, the required testing rates increase to 76% and 57%.

The Prognosis in Palliative care Study II (PiPS2): A prospective observational validation study of a prognostic tool with an embedded qualitative evaluation.

BACKGROUND: Prognosis in Palliative care Study (PiPS) models predict survival probabilities in advanced cancer. PiPS-A (clinical observations only) and PiPS-B (additionally requiring blood results) consist of 14- and 56-day models (PiPS-A14; PiPS-A56; PiPS-B14; PiPS-B56) to create survival risk categories: days, weeks, months. The primary aim was to compare PIPS-B risk categories against agreed multi-professional estimates of survival (AMPES) and to validate PiPS-A and PiPS-B. Secondary aims were to assess acceptability of PiPS to patients, caregivers and health professionals (HPs). METHODS AND FINDINGS: A national, multi-centre, prospective, observational, cohort study with nested qualitative sub-study using interviews with patients, caregivers and HPs. Validation study participants were adults with incurable cancer; with or without capacity; recently referred to community, hospital and hospice palliative care services across England and Wales. Sub-study participants were patients, caregivers and HPs. 1833 participants were recruited. PiPS-B risk categories were as accurate as AMPES [PiPS-B accuracy (910/1484; 61%); AMPES (914/1484; 61%); p = 0.851]. PiPS-B14 discrimination (C-statistic 0.837) and PiPS-B56 (0.810) were excellent. PiPS-B14 predictions were too high in the 57-74% risk group (Calibration-in-the-large [CiL] -0.202; Calibration slope [CS] 0.840). PiPS-B56 was well-calibrated (CiL 0.152; CS 0.914). PiPS-A risk categories were less accurate than AMPES (p<0.001). PiPS-A14 (C-statistic 0.825; CiL -0.037; CS 0.981) and PiPS-A56 (C-statistic 0.776; CiL 0.109; CS 0.946) had excellent or reasonably good discrimination and calibration. Interviewed patients (n = 29) and caregivers (n = 20) wanted prognostic information and considered that PiPS may aid communication. HPs (n = 32) found PiPS user-friendly and considered risk categories potentially helpful for decision-making. The need for a blood test for PiPS-B was considered a limitation. CONCLUSIONS: PiPS-B risk categories are as accurate as AMPES made by experienced doctors and nurses. PiPS-A categories are less accurate. Patients, carers and HPs regard PiPS as potentially helpful in clinical practice. STUDY REGISTRATION: ISRCTN13688211.

Prognostic tools or clinical predictions: Which are better in palliative care?

PURPOSE: The Palliative Prognostic (PaP) score; Palliative Prognostic Index (PPI); Feliu Prognostic Nomogram (FPN) and Palliative Performance Scale (PPS) have all been proposed as prognostic tools for palliative cancer care. However, clinical judgement remains the principal way by which palliative care professionals determine prognoses and it is important that the performance of prognostic tools is compared against clinical predictions of survival (CPS). METHODS: This was a multi-centre, cohort validation study of prognostic tools. Study participants were adults with advanced cancer receiving palliative care, with or without capacity to consent. Key prognostic data were collected at baseline, shortly after referral to palliative care services. CPS were obtained independently from a doctor and a nurse. RESULTS: Prognostic data were collected on 1833 participants. All prognostic tools showed acceptable discrimination and calibration, but none showed superiority to CPS. Both PaP and CPS were equally able to accurately categorise patients according to their risk of dying within 30 days. There was no difference in performance between CPS and FPN at stratifying patients according to their risk of dying at 15, 30 or 60 days. PPI was significantly (p<0.001) worse than CPS at predicting which patients would survive for 3 or 6 weeks. PPS and CPS were both able to discriminate palliative care patients into multiple iso-prognostic groups. CONCLUSIONS: Although four commonly used prognostic algorithms for palliative care generally showed good discrimination and calibration, none of them demonstrated superiority to CPS. Prognostic tools which are less accurate than CPS are of no clinical use. However, prognostic tools which perform similarly to CPS may have other advantages to recommend them for use in clinical practice (e.g. being more objective, more reproducible, acting as a second opinion or as an educational tool). Future studies should therefore assess the impact of prognostic tools on clinical practice and decision-making.