Colorectal cancer care and patients’ perceptions before and during COVID-19: implications for subsequent SARS-CoV-2 infection waves

BACKGROUND: Changes in colorectal cancer (CRC) care planning due to the coronavirus disease 2019 (COVID-19) pandemic and associated health-related quality of life (HRQoL) and well-being of patients with CRC are unknown. We report changes in CRC care and patient-reported outcomes (PROs) including HRQoL, distress, and loneliness during the first wave of SARS-CoV-2. METHODS: In April 2020, 4,984 patients included in the nationwide Prospective Dutch Colorectal Cancer cohort were invited to complete a COVID-19-specific questionnaire, together with the validated EORTC QLQ-C30, De Jong Gierveld, and HADS. Clinical data were obtained from the Netherlands Cancer Registry. Scores were compared with the year prior to COVID-19, and with an age- and sex-matched control population during COVID-19. RESULTS: In total, 3,247 (65.1%) patients responded between April and June 2020. Seventeen percent of patients had cancelled/postponed/changed hospital visits into a telephone- or video consult while 5.3% had adjusted/postponed/cancelled treatment. Compared to controls, patients reported worse HRQoL, but comparable distress and less social loneliness (patients = 21.2%; controls = 32.9%). Compared to pre-COVID-19, clinically meaningful deterioration of HRQoL was more prevalent in patients with changes in cancer care planning than in patients without changes. Prior to undergoing or currently undergoing treatment, and infection worries were associated with lower HRQoL. CONCLUSIONS: CRC patients reported equal anxiety and depression, but worse HRQoL than the control population. Changes in care planning were associated with deterioration of HRQoL and increased anxiety. In case of one or more risk factors, healthcare specialists should discuss (mental) health status and possible support during future SARS-CoV-2 infection waves or comparable pandemics

Impact of the COVID-19 Pandemic on Colorectal Cancer Care in the Netherlands: A Population-based Study

Contains fulltext : 283493.pdf (Publisher’s version ) (Open Access)INTRODUCTION: The COVID-19 pandemic disrupted health care services worldwide. In the Netherlands, the first confirmed COVID-19 infection was on February 27, 2020. We aimed to investigate the impact of the pandemic on colorectal cancer care in the Netherlands. METHODS: Colorectal cancer patients who were diagnosed in 25 hospitals in weeks 2 to 26 of the year 2020 were selected from the Netherlands Cancer Registry (NCR) and divided in 4 periods. The average number of patients treated per type of initial treatment was analyzed by the Mantel-Haenszel test adjusted for age. Median time between diagnosis and treatment and between (neo)adjuvant therapy and surgery were analyzed by the Mann Whitney test. Percentages of (acute) resection, stoma and (neo)adjuvant therapy were compared using the Chi-squared test. RESULTS: In total, 1,653 patients were included. The patient population changed during the COVID-19 pandemic regarding higher stage and more clinical presentation with ileus at time of diagnosis. Slight changes were found regarding type of initial treatment. Median time between diagnosis and treatment decreased on average by 4.5 days during the pandemic. The proportion of colon cancer patients receiving a stoma significantly increased with 6.5% during the pandemic. No differences were found in resection rate and treatment with (neo)adjuvant therapy. CONCLUSION: Despite the disruptive impact of the COVID-19 pandemic on global health care, the impact on colorectal cancer care in the Netherlands was limited

UV Spectropolarimetry with Polstar: Massive Star Binary Colliding Winds

The winds of massive stars are important for their direct impact on the interstellar medium, and for their influence on the final state of a star prior to it exploding as a supernova. However, the dynamics of these winds is understood primarily via their illumination from a single central source. The Doppler shift seen in resonance lines is a useful tool for inferring these dynamics, but the mapping from that Doppler shift to the radial distance from the source is ambiguous. Binary systems can reduce this ambiguity by providing a second light source at a known radius in the wind, seen from orbitally modulated directions. From the nature of the collision between the winds, a massive companion also provides unique additional information about wind momentum fluxes. Since massive stars are strong ultraviolet (UV) sources, and UV resonance line opacity in the wind is strong, UV instruments with a high resolution spectroscopic capability are essential for extracting this dynamical information. Polarimetric capability also helps to further resolve ambiguities in aspects of the wind geometry that are not axisymmetric about the line of sight, because of its unique access to scattering direction information. We review how the proposed MIDEX-scale mission Polstar can use UV spectropolarimetric observations to critically constrain the physics of colliding winds, and hence radiatively-driven winds in general. We propose a sample of 20 binary targets, capitalizing on this unique combination of illumination by companion starlight, and collision with a companion wind, to probe wind attributes over a range in wind strengths. Of particular interest is the hypothesis that the radial distribution of the wind acceleration is altered significantly, when the radiative transfer within the winds becomes optically thick to resonance scattering in multiple overlapping UV lines.Comment: 26 pages, 12 figures, Review in a topical collection series of Astrophysics and Space Sciences on the proposed Polstar satellite. arXiv admin note: substantial text overlap with arXiv:2111.1155

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim: To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods: A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results: Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion: This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.Financial support for this study was provided by a grant from ZonMw (Grant number: 848015007). ZonMw had no role in designing the study, interpreting the data, writing the manuscript, and publishing the report

Ultraviolet spectropolarimetry: conservative and nonconservative mass transfer in OB interacting binaries

peer reviewe

Ultraviolet spectropolarimetry: conservative and nonconservative mass transfer in OB interacting binaries

peer reviewe

UV spectropolarimetry with Polstar: massive star binary colliding winds

peer reviewe

The Prospective Dutch Colorectal Cancer (PLCRC) cohort: real-world data facilitating research and clinical care

Real-world data (RWD) sources are important to advance clinical oncology research and evaluate treatments in daily practice. Since 2013, the Prospective Dutch Colorectal Cancer (PLCRC) cohort, linked to the Netherlands Cancer Registry, serves as an infrastructure for scientific research collecting additional patient-reported outcomes (PRO) and biospecimens. Here we report on cohort developments and investigate to what extent PLCRC reflects the “real-world”. Clinical and demographic characteristics of PLCRC participants were compared with the general Dutch CRC population (n = 74,692, Dutch-ref). To study representativeness, standardized differences between PLCRC and Dutch-ref were calculated, and logistic regression models were evaluated on their ability to distinguish cohort participants from the Dutch-ref (AU-ROC 0.5 = preferred, implying participation independent of patient characteristics). Stratified analyses by stage and time-period (2013–2016 and 2017–Aug 2019) were performed to study the evolution towards RWD. In August 2019, 5744 patients were enrolled. Enrollment increased steeply, from 129 participants (1 hospital) in 2013 to 2136 (50 of 75 Dutch hospitals) in 2018. Low AU-ROC (0.65, 95% CI: 0.64–0.65) indicates limited ability to distinguish cohort participants from the Dutch-ref. Characteristics that remained imbalanced in the period 2017–Aug’19 compared with the Dutch-ref were age (65.0 years in PLCRC, 69.3 in the Dutch-ref) and tumor stage (40% stage-III in PLCRC, 30% in the Dutch-ref). PLCRC approaches to represent the Dutch CRC population and will ultimately meet the current demand for high-quality RWD. Efforts are ongoing to improve multidisciplinary recruitment which will further enhance PLCRC’s representativeness and its contribution to a learning healthcare system

SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway

Vaccines based on the spike protein of SARS-CoV-2 are a cornerstone of the public health response to COVID-19. The emergence of hypermutated, increasingly transmissible variants of concern (VOCs) threaten this strategy. Omicron (B.1.1.529), the fifth VOC to be described, harbours multiple amino acid mutations in spike, half of which lie within the receptor-binding domain. Here we demonstrate substantial evasion of neutralization by Omicron BA.1 and BA.2 variants in vitro using sera from individuals vaccinated with ChAdOx1, BNT162b2 and mRNA-1273. These data were mirrored by a substantial reduction in real-world vaccine effectiveness that was partially restored by booster vaccination. The Omicron variants BA.1 and BA.2 did not induce cell syncytia in vitro and favoured a TMPRSS2-independent endosomal entry pathway, these phenotypes mapping to distinct regions of the spike protein. Impaired cell fusion was determined by the receptor-binding domain, while endosomal entry mapped to the S2 domain. Such marked changes in antigenicity and replicative biology may underlie the rapid global spread and altered pathogenicity of the Omicron variant