Pan-cancer analyses of the associations between 109 pre-existing conditions and cancer treatment patterns across 19 adult cancers.

Comorbidities present considerable challenges to cancer treatment and care. However, little is known about the effect of comorbidity on cancer treatment decisions across a wide range of cancer types and treatment modalities. Harnessing a cohort of 280,543 patients spanning 19 site-specific cancers, we explored pan-cancer frequencies of 109 comorbidities. Multinomial logistic regression was used to analyse the relationship between comorbidities and cancer treatment types, while binomial logistic regression examined the association between comorbidities and chemotherapy drug types, adjusting for demographic and clinical factors. Patients with comorbidity exhibited lower odds of receiving chemotherapy and multimodality treatment. End-stage renal disease was significantly associated with a decreased odds of receiving chemotherapy and surgery. Patients with prostate cancer who have comorbid non-acute cystitis, obstructive and reflux uropathy, urolithiasis, or hypertension were less likely to receive chemotherapy. Among patients with breast cancer, dementia, left bundle branch block, peripheral arterial disease, epilepsy, Barrett's oesophagus, ischaemic stroke, unstable angina and asthma were associated with lower odds of receiving multimodal chemotherapy, radiotherapy and surgery. Comorbidity is also consistently associated with the lower odds of receiving chemotherapy when comparing across 10 drug classes. Patients with comorbid dementia, intracerebral haemorrhage, subarachnoid haemorrhage, oesophageal varices, liver fibrosis sclerosis and cirrhosis and secondary pulmonary hypertension were less likely to receive antimetabolites. Comorbidity can influence the effectiveness and tolerability of cancer treatment and ultimately, prognosis. Multi-specialty collaborative care is essential for the management of comorbidity during cancer treatment, including prophylactic measures to manage toxicities.

Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England.

OBJECTIVE: To describe hospital admissions associated with SARS-CoV-2 infection in children and adolescents. DESIGN: Cohort study of 3.2 million first ascertained SARS-CoV-2 infections using electronic health care record data. SETTING: England, July 2020 to February 2022. PARTICIPANTS: About 12 million children and adolescents (age <18 years) who were resident in England. MAIN OUTCOME MEASURES: Ascertainment of a first SARS-CoV-2 associated hospital admissions: due to SARS-CoV-2, with SARS-CoV-2 as a contributory factor, incidental to SARS-CoV-2 infection, and hospital acquired SARS-CoV-2. RESULTS: 3 226 535 children and adolescents had a recorded first SARS-CoV-2 infection during the observation period, and 29 230 (0.9%) infections involved a SARS-CoV-2 associated hospital admission. The median length of stay was 2 (interquartile range 1-4) days) and 1710 of 29 230 (5.9%) SARS-CoV-2 associated admissions involved paediatric critical care. 70 deaths occurred in which covid-19 or paediatric inflammatory multisystem syndrome was listed as a cause, of which 55 (78.6%) were in participants with a SARS-CoV-2 associated hospital admission. SARS-CoV-2 was the cause or a contributory factor in 21 000 of 29 230 (71.8%) participants who were admitted to hospital and only 380 (1.3%) participants acquired infection as an inpatient and 7855 (26.9%) participants were admitted with incidental SARS-CoV-2 infection. Boys, younger children (<5 years), and those from ethnic minority groups or areas of high deprivation were more likely to be admitted to hospital (all P<0.001). The covid-19 vaccination programme in England has identified certain conditions as representing a higher risk of admission to hospital with SARS-CoV-2: 11 085 (37.9%) of participants admitted to hospital had evidence of such a condition, and a further 4765 (16.3%) of participants admitted to hospital had a medical or developmental health condition not included in the vaccination programme's list. CONCLUSIONS: Most SARS-CoV-2 associated hospital admissions in children and adolescents in England were due to SARS-CoV-2 or SARS-CoV-2 was a contributory factor. These results should inform future public health initiatives and research.

Cumulative burden of 144 conditions, critical care hospitalisation and premature mortality across 26 adult cancers.

A comprehensive evaluation of the total burden of morbidity endured by cancer survivors remains unavailable. This study quantified the burden of 144 health conditions and critical care admissions across 26 adult cancers and treatment modalities in 243,767 adults. By age 60, top conditions ranked by fold difference (cumulative burden in survivors divided by cumulative burden in controls) were haematology, immunology/infection and pulmonary conditions. Patients who had all three forms of treatment (chemotherapy, radiotherapy and surgery) experienced a high cumulative burden of late morbidities compared with patients who received radiotherapy alone. The top five cancers with the highest cumulative burden of critical care admissions by age 60 were bone (12.4 events per 100 individuals [CI: 11.6-13.1]), brain (9.0 [7.5-10.5]), spinal cord and nervous system (7.2 [6.7-7.8]), testis (6.7 [4.9-8.4]) and Hodgkin lymphoma (4.4 [3.6-5.1]). Conditions that were associated with high excess years-of-life-lost were haematological conditions (9.6 years), pulmonary conditions (8.6 years) and immunological conditions or infections (7.8 years). As the population of cancer survivors continues to grow, our results indicate that it is important to tackle long-term health consequences through enacting data-driven policies.

Injury primes mutation-bearing astrocytes for dedifferentiation in later life.

Despite their latent neurogenic potential, most normal parenchymal astrocytes fail to dedifferentiate to neural stem cells in response to injury. In contrast, aberrant lineage plasticity is a hallmark of gliomas, and this suggests that tumor suppressors may constrain astrocyte dedifferentiation. Here, we show that p53, one of the most commonly inactivated tumor suppressors in glioma, is a gatekeeper of astrocyte fate. In the context of stab-wound injury, p53 loss destabilized the identity of astrocytes, priming them to dedifferentiate in later life. This resulted from persistent and age-exacerbated neuroinflammation at the injury site and EGFR activation in periwound astrocytes. Mechanistically, dedifferentiation was driven by the synergistic upregulation of mTOR signaling downstream of p53 loss and EGFR, which reinstates stemness programs via increased translation of neurodevelopmental transcription factors. Thus, our findings suggest that first-hit mutations remove the barriers to injury-induced dedifferentiation by sensitizing somatic cells to inflammatory signals, with implications for tumorigenesis.

Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry.

BACKGROUND: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. METHODS: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. RESULTS: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10-6) and AC058822.1 (P = 1.47 × 10-4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. CONCLUSIONS: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10-5), demonstrating the importance of diversifying study cohorts.

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19-a data-driven retrospective cohort study.

OBJECTIVES: To use national, pre- and post-pandemic electronic health records (EHR) to develop and validate a scenario-based model incorporating baseline mortality risk, infection rate (IR) and relative risk (RR) of death for prediction of excess deaths. DESIGN: An EHR-based, retrospective cohort study. SETTING: Linked EHR in Clinical Practice Research Datalink (CPRD); and linked EHR and COVID-19 data in England provided in NHS Digital Trusted Research Environment (TRE). PARTICIPANTS: In the development (CPRD) and validation (TRE) cohorts, we included 3.8 million and 35.1 million individuals aged ≥30 years, respectively. MAIN OUTCOME MEASURES: One-year all-cause excess deaths related to COVID-19 from March 2020 to March 2021. RESULTS: From 1 March 2020 to 1 March 2021, there were 127,020 observed excess deaths. Observed RR was 4.34% (95% CI, 4.31-4.38) and IR was 6.27% (95% CI, 6.26-6.28). In the validation cohort, predicted one-year excess deaths were 100,338 compared with the observed 127,020 deaths with a ratio of predicted to observed excess deaths of 0.79. CONCLUSIONS: We show that a simple, parsimonious model incorporating baseline mortality risk, one-year IR and RR of the pandemic can be used for scenario-based prediction of excess deaths in the early stages of a pandemic. Our analyses show that EHR could inform pandemic planning and surveillance, despite limited use in emergency preparedness to date. Although infection dynamics are important in the prediction of mortality, future models should take greater account of underlying conditions.

Comparing clinical trial population representativeness to real-world populations: an external validity analysis encompassing 43 895 trials and 5 685 738 individuals across 989 unique drugs and 286 conditions in England.

BACKGROUND: Randomised controlled trials (RCTs) inform prescription guidelines, but stringent eligibility criteria exclude individuals with vulnerable characteristics, which we define as comorbidities, concomitant medication use, and vulnerabilities due to age. Poor external validity can result in inadequate treatment decision information. Our first aim was to quantify the extent of exclusion of individuals with vulnerable characteristics from RCTs for all prescription drugs. Our second aim was to quantify the prevalence of individuals with vulnerable characteristics from population electronic health records who are actively prescribed such drugs. In tandem, these two aims will allow us to assess the representativeness between RCT and real-world populations and identify vulnerable populations potentially at risk of inadequate treatment decision information. When a vulnerable population is highly excluded from RCTs but has a high prevalence of individuals actively being prescribed the same medication, there is likely to be a gap in treatment decision information. Our third aim was to investigate the use of real-world evidence in contributing towards quantifying missing treatment risk or benefit through an observational study. METHODS: We extracted RCTs from ClinicalTrials.gov from its inception to April 28, 2021, and primary care records from the Clinical Practice Research Datalink Gold database from Jan 1, 1998, to Dec 31, 2020. We referred to the British National Formulary to classify prescription drugs into drug categories. We conducted descriptive analyses and quantified RCT exclusion and prevalence of individuals with vulnerable characteristics for comparison to identify populations without treatment decision information. Exclusion and prevalence were assessed separately for different age groups, individual clinical specialities, and for quantities of concomitant conditions by clinical specialities, where multimorbidity was defined as having two or more clinical specialties, and medications prescribed, where polypharmacy was defined as having five or more medications prescribed. Population trends of individuals with multimorbidity or polypharmacy were assessed separately by age group. We conducted an observational cohort study to validate the use of real-world evidence in contributing towards quantifying treatment risk or benefit for patients with dementia on anti-dementia drugs with and without a contraindicated clinical speciality. To do so, we identified the clinical specialities that anti-dementia drug RCTs highly excluded yet had corresponding high prevalence in the real-world population, forming the groups with highest risk of having scarce treatment decision information. Cox regression was used to assess if the risk of mortality outcomes differs between both groups. FINDINGS: 43 895 RCTs from ClinicalTrials.gov and 5 685 738 million individuals from primary care records were used. We considered 989 unique drugs and 286 conditions across 13 drug-category cohorts. For the descriptive analyses, the median RCT exclusion proportion across 13 drug categories was 81·5% (IQR 76·7-85·5) for adolescents (aged <18 years), 26·3% (IQR 21·0-29·5) for individuals older than 60 years, 40·5% (IQR 33·7-43·0) for individuals older than 70 years, and 52·9% (IQR 47·1-56·0) for individuals older than 80 years. Multimorbidity had a median exclusion proportion of 91·1% (IQR 88·9-91·8) and median prevalence of 41·0% (IQR 34·9-46·0). Concomitant medication use had a median exclusion proportion of 52·5% (IQR 50·0-53·7) and a median prevalence of 94·3% (IQR 84·3-97·2), and polypharmacy had a median prevalence of 47·7% (IQR 38·0-56·1). Population trends show increasing multimorbidity with age and consistently high polypharmacy across age groups. Populations with cardiovascular or otorhinolaryngological comorbidities had the highest risk of having scarce treatment decision information. For the observational study, populations with cardiovascular or psychiatric comorbidities had highest risk of having scarce treatment decision information. Patients with dementia with an anti-dementia prescription and contraindicated cardiovascular condition had a higher risk of mortality (hazard ratio [HR] 1·20 [95% CI 1·13-1·28 ; p<0·0001]) compared with patients with dementia without a contraindicated cardiovascular condition. Patients with dementia with comorbid delirium (HR 1·25 [95% CI 1·06-1·48]; p<0·0088), intellectual disability (HR 2·72 [95% CI 1·53-4·81]; p=0·0006), and schizophrenia and schizotypal delusional disorders (HR 1·36 [95% CI 1·02-1·82]; p=0·036) had a higher risk of mortality compared with patients with dementia without these conditions. INTERPRETATION: Overly stringent RCT exclusion criteria do not appropriately account for the heterogeneity of vulnerable characteristics observed in real-world populations. Treatment decision information is scarce for such individuals, which might affect health outcomes. We discuss the challenges facing the inclusivity of such individuals and highlight the strength of real-world evidence as an integrative solution in complementing RCTs and increasing the completeness of evidence-based medicine assessments in evaluating the effectiveness of treatment decisions. FUNDING: Wellcome Trust, National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre, NIHR Great Ormond Street Hospital Biomedical Research Centre, Academy of Medical Sciences, and the University College London Overseas Research Scholarship.

Depression, anxiety, substance misuse and self-harm in children and young people with rare chronic liver disease.

The burden of mental illness in young people with chronic liver disease is not known. In this population cohort study in England, we identified 358 individuals (aged ≤25 years) diagnosed with autoimmune hepatitis or liver disease related to cystic fibrosis and 1541 propensity-score-matched controls. By the first year of follow-up, the cumulative burden of psychiatric events in participants with liver disease was high compared with controls: anxiety disorder (6.87 per 100 individuals [95% CI 4.00-9.73] v. 2.22 [95% CI 1.37-3.07]), depression (5.10 [95% CI 2.83-7.37] v. 0.86 [95% CI 0.53-1.19]), substance misuse (10.61 [95% CI 9.50-11.73] v. 1.23 [95% CI 0.71-1.75]) and self-harm (3.09 [95% CI 1.12-5.05] v. 0.20 [95% CI 0.07-0.33]). Participants with liver disease had a 2-fold increase (OR = 1.94, 95% CI 1.45-2.58), a 2.5-fold increase (OR = 2.59, 95% CI 1.91-3.50) and 4.4-fold increase (OR = 4.44; 95% CI 3.46-5.71) in the risk of anxiety, depression and substance misuse, respectively. These findings highlight the need for effective intervention in psychiatric disorders in young people with rare liver disease.

Multimorbidity patterns and risk of hospitalisation in children: A population cohort study of 3.6 million children in England, with illustrative examples from childhood cancer survivors.

Background: Population-level estimates of hospitalisation risk in children are currently limited. The study aims to characterise morbidity patterns in all children, focusing on childhood cancer survivors versus children without cancer. Methods: Employing hospital records of children aged <19 years between 1997 to 2018 in England, we characterised morbidity patterns in childhood cancer survivors compared with children without cancer. The follow-up began on the 5th anniversary of the index hospitalisation and the primary outcome was the incidence of comorbidities. Findings: We identified 3,559,439 eligible participants having 12,740,666 hospital admissions, with a mean age at study entry of 11.2 years. We identified 32,221 patients who survived for at least 5 years since their initial cancer diagnosis. During the follow-up period and within the whole population of 3.6 million children, the leading conditions for admission were (i) metabolic, endocrine, digestive renal and genitourinary conditions (84,749, 2.5%), (ii) neurological (35,833, 1.0%) and (iii) musculoskeletal or skin conditions (23,574, 0.7%), fever, acute respiratory and sepsis (22,604, 0.7%). Stratified analyses revealed that females and children from socioeconomically deprived areas had a higher cumulative incidence for morbidities requiring hospitalisation (p < 0.001). At baseline (5 years after the initial cancer diagnosis or initial hospitalisation for survivors and population comparisons, respectively), cancer survivors experienced a higher prevalence of individual conditions and multimorbidity (≥ 2 morbidities) compared with children without cancer. Cox regression analyses showed that survivors had at least a 4-fold increase in the risk of hospitalisation for conditions such as chronic eye conditions (hazard ration (HR):4.0, 95% confidence interval (CI): 3.5-4.7), fever requiring hospitalisation (HR: 4.4, 95% CI: 3.8-5.0), subsequent neoplasms (HR: 5.7, 95% CI:5.0-6.5), immunological disorders (HR: 6.5, 95% CI:4.5-9.3) and metabolic conditions (HR: 7.1, 95% CI:5.9-8.5). Interpretation: The overall morbidity burden among children was low in general; however, childhood cancer survivors experienced a higher prevalence and subsequent risk of hospitalisation for a range of morbidities. Targeted policies may be required to promote awareness on health vulnerabilities and gender disparity and to improve advocacy for healthcare in deprived communities. Funding: Wellcome Trust, National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre, NIHR Great Ormond Street Hospital Biomedical Research Centre and Academy of Medical Sciences. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK.

Pan-cancer prognostic genetic mutations and clinicopathological factors associated with survival outcomes: a systematic review.

Cancer is a leading cause of death, accounting for almost 10 million deaths annually worldwide. Personalised therapies harnessing genetic and clinical information may improve survival outcomes and reduce the side effects of treatments. The aim of this study is to appraise published evidence on clinicopathological factors and genetic mutations (single nucleotide polymorphisms [SNPs]) associated with prognosis across 11 cancer types: lung, colorectal, breast, prostate, melanoma, renal, glioma, bladder, leukaemia, endometrial, ovarian. A systematic literature search of PubMed/MEDLINE and Europe PMC was conducted from database inception to July 1, 2021. 2497 publications from PubMed/MEDLINE and 288 preprints from Europe PMC were included. Subsequent reference and citation search was conducted and a further 39 articles added. 2824 articles were reviewed by title/abstract and 247 articles were selected for systematic review. Majority of the articles were retrospective cohort studies focusing on one cancer type, 8 articles were on pan-cancer level and 6 articles were reviews. Studies analysing clinicopathological factors included 908,567 patients and identified 238 factors, including age, gender, stage, grade, size, site, subtype, invasion, lymph nodes. Genetic studies included 210,802 patients and identified 440 gene mutations associated with cancer survival, including genes TP53, BRCA1, BRCA2, BRAF, KRAS, BIRC5. We generated a comprehensive knowledge base of biomarkers that can be used to tailor treatment according to patients' unique genetic and clinical characteristics. Our pan-cancer investigation uncovers the biomarker landscape and their combined influence that may help guide health practitioners and researchers across the continuum of cancer care from drug development to long-term survivorship.

Cumulative burden of psychiatric disorders and self-harm across 26 adult cancers.

Cancer is a life-altering event causing considerable psychological distress. However, information on the total burden of psychiatric disorders across all common adult cancers and therapy exposures has remained scarce. Here, we estimated the risk of self-harm after incident psychiatric disorder diagnosis in patients with cancer and the risk of unnatural deaths after self-harm in 459,542 individuals. Depression was the most common psychiatric disorder in patients with cancer. Patients who received chemotherapy, radiotherapy and surgery had the highest cumulative burden of psychiatric disorders. Patients treated with alkylating agent chemotherapeutics had the highest burden of psychiatric disorders, whereas those treated with kinase inhibitors had the lowest burden. All mental illnesses were associated with an increased risk of subsequent self-harm, where the highest risk was observed within 12 months of the mental illness diagnosis. Patients who harmed themselves were 6.8 times more likely to die of unnatural causes of death compared with controls within 12 months of self-harm (hazard ratio (HR), 6.8; 95% confidence interval (CI), 4.3-10.7). The risk of unnatural death after 12 months was markedly lower (HR, 2.0; 95% CI, 1.5-2.7). We provide an extensive knowledge base to help inform collaborative cancer-psychiatric care initiatives by prioritizing patients who are most at risk.

Increased burden of cardiovascular disease in people with liver disease: unequal geographical variations, risk factors and excess years of life lost.

BACKGROUND: People with liver disease are at increased risk of developing cardiovascular disease (CVD), however, there has yet been an investigation of incidence burden, risk, and premature mortality across a wide range of liver conditions and cardiovascular outcomes. METHODS: We employed population-wide electronic health records (EHRs; from 1998 to 2020) consisting of almost 4 million adults to assess regional variations in disease burden of five liver conditions, alcoholic liver disease (ALD), autoimmune liver disease, chronic hepatitis B infection (HBV), chronic hepatitis C infection (HCV) and NAFLD, in England. We analysed regional differences in incidence rates for 17 manifestations of CVD in people with or without liver disease. The associations between biomarkers and comorbidities and risk of CVD in patients with liver disease were estimated using Cox models. For each liver condition, we estimated excess years of life lost (YLL) attributable to CVD (i.e., difference in YLL between people with or without CVD). RESULTS: The age-standardised incidence rate for any liver disease was 114.5 per 100,000 person years. The highest incidence was observed in NAFLD (85.5), followed by ALD (24.7), HCV (6.0), HBV (4.1) and autoimmune liver disease (3.7). Regionally, the North West and North East regions consistently exhibited high incidence burden. Age-specific incidence rate analyses revealed that the peak incidence for liver disease of non-viral aetiology is reached in individuals aged 50-59 years. Patients with liver disease had a two-fold higher incidence burden of CVD (2634.6 per 100,000 persons) compared to individuals without liver disease (1339.7 per 100,000 persons). When comparing across liver diseases, atrial fibrillation was the most common initial CVD presentation while hypertrophic cardiomyopathy was the least common. We noted strong positive associations between body mass index and current smoking and risk of CVD. Patients who also had diabetes, hypertension, proteinuric kidney disease, chronic kidney disease, diverticular disease and gastro-oesophageal reflex disorders had a higher risk of CVD, as do patients with low albumin, raised C-reactive protein and raised International Normalized Ratio levels. All types of CVD were associated with shorter life expectancies. When evaluating excess YLLs by age of CVD onset and by liver disease type, differences in YLLs, when comparing across CVD types, were more pronounced at younger ages. CONCLUSIONS: We developed a public online app ( https://lailab.shinyapps.io/cvd_in_liver_disease/ ) to showcase results interactively. We provide a blueprint that revealed previously underappreciated clinical factors related to the risk of CVD, which differed in the magnitude of effects across liver diseases. We found significant geographical variations in the burden of liver disease and CVD, highlighting the need to devise local solutions. Targeted policies and regional initiatives addressing underserved communities might help improve equity of access to CVD screening and treatment.

Late effects of cancer in children, teenagers and young adults: Population-based study on the burden of 183 conditions, in-patient and critical care admissions and years of life lost.

BACKGROUND: Children, teenagers and young adults who survived cancer are prone to developing late effects. The burden of late effects across a large number of conditions, in-patient hospitalisation and critical care admissions have not been described using a population-based dataset. We aim to systematically quantify the cumulative burden of late effects across all cancer subtypes, treatment modalities and chemotherapy drug classes. METHODS: We employed primary care records linked to hospitals, the death registry and cancer registry from 1998-2020. CTYA survivors were 25 years or younger at the time of cancer diagnosis had survived ≥5 years post-diagnosis. Year-of-birth and sex-matched community controls were used for comparison. We considered nine treatment types, nine chemotherapy classes and 183 physical and mental health late effects. Cumulative burden was estimated using mean cumulative count, which considers recurring events. Multivariable logistic regression was used to investigate the association between treatment exposures and late effects. Excess years of life lost (YLL) attributable to late effects were estimated. FINDINGS: Among 4,063 patients diagnosed with cancer, 3,466 survived ≥ 5 years (85%); 13,517 matched controls were identified. The cumulative burden of late effects at age 35 was the highest in survivors of leukaemia (23.52 per individual [95% CI:19.85-29.33]) and lowest in survivors of germ cell tumours (CI:6.04 [5.32-6.91]). In controls, the cumulative burden was 3.99 (CI:3.93-4.08) at age 35 years. When survivors reach age 45, the cumulative burden for immunological conditions and infections was the highest (3.27 [CI:3.01-3.58]), followed by cardiovascular conditions (3.08 [CI:1.98-3.29]). Survivors who received chemotherapy and radiotherapy had the highest disease burden compared to those who received surgery only. These patients also had the highest burden of hospitalisation (by age 45: 10.43 [CI:8.27-11.95]). Survivors who received antimetabolite chemotherapy had the highest disease and hospitalisation burden, while the lowest burden is observed in those receiving antitumour antibiotics. Regression analyses revealed that survivors who received only surgery had lower odds of developing cardiovascular (adjusted odds ratio 0.73 [CI:0.56-0.94]), haematological (aOR 0.51 [CI:0.37-0.70]), immunology and infection (aOR 0.84 [CI:0.71-0.99]) and renal (aOR 0.51 [CI:0.39-0.66]) late effects. By contrast, the opposite trend was observed in survivors who received chemo-radiotherapy. High antimetabolite chemotherapy cumulative dose was associated with increased risks of subsequent cancer (aOR 2.32 [CI:1.06-4.84]), metastatic cancer (aOR 4.44 [CI:1.29-11.66]) and renal (aOR 3.48 [CI:1.36-7.86]) conditions. Patients who received radiation dose of ≥50 Gy experienced higher risks of developing metastatic cancer (aOR 5.51 [CI:2.21-11.86]), cancer (aOR 3.77 [CI:2.22-6.34]), haematological (aOR 3.43 [CI:1.54-6.83]) and neurological (aOR 3.24 [CI:1.78-5.66]) conditions. Similar trends were observed in survivors who received more than three teletherapy fields. Cumulative burden analyses on 183 conditions separately revealed varying dominance of different late effects across cancer types, socioeconomic deprivation and treatment modalities. Late effects are associated with excess YLL (i.e., the difference in YLL between survivors with or without late effects), which was the most pronounced among survivors with haematological comorbidities. INTERPRETATION: To our knowledge, this is the first study to dissect and quantify the importance of late morbidities on subsequent survival using linked electronic health records from multiple settings. The burden of late effects is heterogeneous, as is the risk of premature mortality associated with late effects. We provide an extensive knowledgebase to help inform treatment decisions at the point of diagnosis, future interventional trials and late-effects screening centred on the holistic needs of this vulnerable population.

'What is the risk to me from COVID-19?': Public involvement in providing mortality risk information for people with 'high-risk' conditions for COVID-19 (OurRisk.CoV).

Patients and public have sought mortality risk information throughout the pandemic, but their needs may not be served by current risk prediction tools. Our mixed methods study involved: (1) systematic review of published risk tools for prognosis, (2) provision and patient testing of new mortality risk estimates for people with high-risk conditions and (3) iterative patient and public involvement and engagement with qualitative analysis. Only one of 53 (2%) previously published risk tools involved patients or the public, while 11/53 (21%) had publicly accessible portals, but all for use by clinicians and researchers.Among people with a wide range of underlying conditions, there has been sustained interest and engagement in accessible and tailored, pre- and postpandemic mortality information. Informed by patient feedback, we provide such information in 'five clicks' (https://covid19-phenomics.org/OurRiskCoV.html), as context for decision making and discussions with health professionals and family members. Further development requires curation and regular updating of NHS data and wider patient and public engagement.

Antithrombotic therapy in patients with liver disease: population-based insights on variations in prescribing trends, adherence, persistence and impact on stroke and bleeding.

BACKGROUND: Patients with liver disease have complex haemostasis and due to such contraindications, landmark randomised controlled trials investigating antithrombotic medicines have often excluded these patients. As a result, there has been limited consensus on the safety, efficacy and monitoring practices of anticoagulant and antiplatelet therapy in patients with liver disease. This study aims to investigate prescribing prevalence, adherence, persistence and impact of adherence on bleeding and stroke risk in people with and without liver disease taking anticoagulants and antiplatelets. METHODS: We employed a population-based cohort consisting of person-level linked records from primary care, secondary care and the death registry. The cohort consisted of 3,929,596 adults aged ≥ 30 years during the study period of 1998 to 2020 and registered with an NHS general practitioner in England. The primary outcome was prescribing prevalence, adherence to and persistence with anticoagulant and antiplatelet therapy comparing patients with and without liver disease. Risk factors for non-adherence and non-persistence were analysed using multivariable logistic regression and Cox regression. Impact of adherence on bleeding and ischaemic stroke was assessed. FINDINGS: Among patients with any of the six liver diseases (ALD, autoimmune liver disease, cirrhosis, HBV, HCV and NAFLD), we identified 4,237 individuals with incident atrial fibrillation (indication for anticoagulants) and 4,929 individuals with incident myocardial infarction, transient ischaemic attack, unstable angina or peripheral arterial disease (indication for antiplatelets). Among patients without liver disease, 321,510 and 386,643 individuals were identified as having indications for anticoagulant and antiplatelet therapy, respectively. Among drug-naïve individuals, prescribing prevalence was lower in patients with liver disease compared with individuals without liver disease: anticoagulants (20.6% [806/3,921] vs. 33.5% [103,222/307,877]) and antiplatelets (56.2% [2,207/3,927] vs. 71.1% [249,258/350,803]). Primary non-adherence rates (stopping after one prescription) were higher in patients with liver disease, compared with those without liver disease: anticoagulants (7.9% [64/806] vs. 4.7% [4,841/103,222]) and antiplatelets (6.2% [137/2,207] vs. 4.4% [10,993/249,258]). Among individuals who were not primary non-adherent and had at least 12 months of follow-up, patients with liver disease however had a higher one-year adherence rate: anticoagulants (33.1% [208/628] vs. 29.4% [26,615/90,569]) and antiplatelets (40.9% [743/1,818] vs. 34.4% [76,834/223,154]). Likelihood of non-adherence was lower in apixaban and rivaroxaban (relative to warfarin) and lower in clopidogrel (relative to aspirin). Increased comorbidity burden (by CHA2DS2VASc score) was associated with decreased risk of non-adherence and non-persistence with anticoagulants. Overall rates of 'non-adherent, non-persistent' were highest in warfarin (compared with apixaban and rivaroxaban) and aspirin (compared with clopidogrel or dipyridamole) in patients with and without liver disease. Among patients without liver disease, not taking antithrombotic medications for >3 months was associated with a higher risk of stroke, however, adherence to these medications was also associated with a small increase in risk of bleeding. Patients with liver disease (when compared with those without liver disease) had higher risks of stroke, especially when they stopped taking antiplatelets for >3 months. Patients with liver disease who were adherent to antiplatelets, however, had a higher risk of bleeding compared with patients without liver disease. INTERPRETATION: Use of antithrombotic medicines in patients with and without liver disease is suboptimal with heterogeneity across medicines. As patients with liver disease are excluded from major randomised trials for these drugs, our results provide real-world evidence that may inform medicine optimisation strategies. We outline challenges and opportunities for tackling non-adherence, which begins with understanding patients' views of medicines to help them make informed decisions about appropriate use. FUNDING: AGL is supported by funding from the Wellcome Trust (204841/Z/16/Z), National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre (BRC714/HI/RW/101440), NIHR Great Ormond Street Hospital Biomedical Research Centre (19RX02), the Health Data Research UK Better Care Catalyst Award (CFC0125) and the Academy of Medical Sciences (SBF006\1084). The funders have no role in the writing of the manuscript or the decision to submit it for publication.