Barriers to healthcare access and experiences of stigma: Findings from a coproduced Long Covid case-finding study.

BACKGROUND AND AIM: Long Covid is often stigmatised, particularly in people who are disadvantaged within society. This may prevent them from seeking help and could lead to widening health inequalities. This coproduced study with a Community Advisory Board (CAB) of people with Long Covid aimed to understand healthcare and wider barriers and stigma experienced by people with probable Long Covid. METHODS: An active case finding approach was employed to find adults with probable, but not yet clinically diagnosed, Long Covid in two localities in London (Camden and Merton) and Derbyshire, England. Interviews explored the barriers to care and the stigma faced by participants and were analysed thematically. This study forms part of the STIMULATE-ICP Collaboration. FINDINGS: Twenty-three interviews were completed. Participants reported limited awareness of what Long Covid is and the available pathways to management. There was considerable self-doubt among participants, sometimes reinforced by interactions with healthcare professionals (HCPs). Participants questioned their deservedness in seeking healthcare support for their symptoms. Hesitancy to engage with healthcare services was motivated by fear of needing more investigation and concerns regarding judgement about the ability to carry out caregiving responsibilities. It was also motivated by the complexity of the clinical presentation and fear of all symptoms being attributed to poor mental health. Participants also reported trying to avoid overburdening the health system. These difficulties were compounded by experiences of stigma and discrimination. The emerging themes reaffirmed a framework of epistemic injustice in relation to Long Covid, where creating, interpreting and conveying knowledge has varied credibility based on the teller's identity characteristics and/or the level of their interpretive resources. CONCLUSION: We have codeveloped recommendations based on the findings. These include early signposting to services, dedicating protected time to listening to people with Long Covid, providing a holistic approach in care pathways, and working to mitigate stigma. Regardless of the diagnosis, people experiencing new symptoms must be encouraged to seek timely medical help. Clear public health messaging is needed among communities already disadvantaged by epistemic injustice to raise awareness of Long Covid, and to share stories that encourage seeking care and to illustrate the adverse effects of stigma. PATIENT OR PUBLIC CONTRIBUTION: This study was coproduced with a CAB made up of 23 members including HCPs, people with lived experience of Long Covid and other stakeholders.

Combining measures of immune infiltration shows additive effect on survival prediction in high-grade serous ovarian carcinoma.

BACKGROUND: In colorectal and breast cancer, the density and localisation of immune infiltrates provides strong prognostic information. We asked whether similar automated quantitation and combined analysis of immune infiltrates could refine prognostic information in high-grade serous ovarian carcinoma (HGSOC) and tested associations between patterns of immune response and genomic driver alterations. METHODS: Epithelium and stroma were semi-automatically segmented and the infiltration of CD45RO+, CD8+ and CD68+ cells was automatically quantified from images of 332 HGSOC patient tissue microarray cores. RESULTS: Epithelial CD8 [p = 0.027, hazard ratio (HR) = 0.83], stromal CD68 (p = 3 × 10-4, HR = 0.44) and stromal CD45RO (p = 7 × 10-4, HR = 0.76) were positively associated with survival and remained so when averaged across the tumour and stromal compartments. Using principal component analysis, we identified optimised multiparameter survival models combining information from all immune markers (p = 0.016, HR = 0.88). There was no significant association between PTEN expression, type of TP53 mutation or presence of BRCA1/BRCA2 mutations and immune infiltrate densities or principal components. CONCLUSIONS: Combining measures of immune infiltration provided improved survival modelling and evidence for the multiple effects of different immune factors on survival. The presence of stromal CD68+ and CD45RO+ populations was associated with survival, underscoring the benefits evaluating stromal immune populations may bring for prognostic immunoscores in HGSOC.

Maintaining, masking, and mimicking selection: the interplay of cell-intrinsic and cell-extrinsic effects upon eco-evolutionary dynamics.

Evolution is a stochastic yet inevitable process that lies at the heart of biology yet in the multi-cellular environments within patients, ecological complexities arise via heterogeneity and microenvironments. The interplay of ecology and mutation is thus fundamental to predicting the evolution of complex diseases and engineering optimal treatment solutions. As experimental evidence of ecological interactions between disease agents continues to grow, so does the need for evolutionary theory and modeling that incorporates these interaction effects. Inspired by experimental cell biology, we transform the variables in the interaction payoff matrix to encode cell-cell interactions in our mathematical approach as growth-rate modifying, frequency-dependent interactions. In this way, we can show the extent to which the presence of these cell-extrinsic ecological interactions can modify the evolutionary trajectories that would be predicted from cell-intrinsic properties alone. To do this we form a Fokker-Planck equation for a genetic population undergoing diffusion, drift, and interactions and generate a novel, analytic solution for the stationary distribution. We use this solution to determine when these interactions can modify evolution in such ways as to maintain, mask, or mimic mono-culture fitness differences. This work has implications for the interpretation and understanding of experimental and patient evolution and is a result that may help to explain the abundance of apparently neutral evolution in cancer systems and heterogeneous populations in general. In addition, the derivation of an analytical result for stochastic, ecologically dependent evolution paves the way for treatment approaches requiring knowledge of a stationary solution for the development of control protocols.

Long Covid active case finding study protocol: A co-produced community-based pilot within the STIMULATE-ICP study (Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways).

BACKGROUND AND AIM: Long Covid is a significant public health concern with potentially negative implications for health inequalities. We know that those who are already socially disadvantaged in society are more exposed to COVID-19, experience the worst health outcomes and are more likely to suffer economically. We also know that these groups are more likely to experience stigma and have negative healthcare experiences even before the pandemic. However, little is known about disadvantaged groups' experiences of Long Covid, and preliminary evidence suggests they may be under-represented in those who access formal care. We will conduct a pilot study in a defined geographical area in London, United Kingdom to test the feasibility of a community-based approach of identifying Long Covid cases that have not been clinically diagnosed and have not been referred to Long Covid specialist services. We will explore the barriers to accessing recognition, care, and support, as well as experiences of stigma and perceived discrimination. METHODS: This protocol and study materials were co-produced with a Community Advisory Board (CAB) made up primarily of people living with Long Covid. Working with voluntary organisations, a study leaflet will be distributed in the local community to highlight Long Covid symptoms and invite those experiencing them to participate in the study if they are not formally diagnosed. Potential participants will be assessed according to the study's inclusion criteria and offered the opportunity to participate if they fit them. Awareness of Long Covid and associated symptoms, experiences of trying to access care, as well as stigma and discrimination will be explored through qualitative interviews with participants. Upon completion of the interviews, participants will be offered a referral to the local social prescribing team to receive support that is personalised to them potentially including, but not restricted to, liaising with their primary care provider and the regional Long Covid clinic.

Clinical Nomogram Using Novel Computed Tomography-Based Radiomics Predicts Survival in Patients With Non-Small-Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy.

PURPOSE: Improved survival prediction and risk stratification in non-small-cell lung cancer (NSCLC) would lead to better prognosis counseling, adjuvant therapy selection, and clinical trial design. We propose the persistent homology (PHOM) score, the radiomic quantification of solid tumor topology, as a solution. MATERIALS AND METHODS: Patients diagnosed with stage I or II NSCLC primarily treated with stereotactic body radiation therapy (SBRT) were selected (N = 554). The PHOM score was calculated for each patient's pretreatment computed tomography scan (October 2008-November 2019). PHOM score, age, sex, stage, Karnofsky Performance Status, Charlson Comorbidity Index, and post-SBRT chemotherapy were predictors in the Cox proportional hazards models for OS and cancer-specific survival. Patients were split into high- and low-PHOM score groups and compared using Kaplan-Meier curves for overall survival (OS) and cumulative incidence curves for cause-specific death. Finally, we generated a validated nomogram to predict OS, which is publicly available at Eashwarsoma.Shinyapps. RESULTS: PHOM score was a significant predictor for OS (hazard ratio [HR], 1.17; 95% CI, 1.07 to 1.28) and was the only significant predictor for cancer-specific survival (1.31; 95% CI, 1.11 to 1.56) in the multivariable Cox model. The median survival for the high-PHOM group was 29.2 months (95% CI, 23.6 to 34.3), which was significantly worse compared with the low-PHOM group (45.4 months; 95% CI, 40.1 to 51.8; P < .001). The high-PHOM group had a significantly greater chance of cancer-specific death at post-treatment month 65 (0.244; 95% CI, 0.192 to 0.296) compared with the low-PHOM group (0.171; 95% CI, 0.123 to 0.218; P = .029). CONCLUSION: The PHOM score is associated with cancer-specific survival and predictive of OS. Our developed nomogram can be used to inform clinical prognosis and assist in making post-SBRT treatment considerations.