Dr Agnieszka Lemanska

Background Healthcare across all sectors, in the UK and globally, was negatively affected by the COVID-19 pandemic. We analysed healthcare services delivered to people with pancreatic cancer from January 2015 to March 2023 to investigate the effect of the COVID-19 pandemic. Methods With the approval of NHS England, and drawing from a nationally representative OpenSAFELY-TPP dataset of 24 million patients (over 40% of the English population), we undertook a cohort study of people diagnosed with pancreatic cancer. We queried electronic healthcare records for information on the provision of healthcare services across the pancreatic cancer pathway. To estimate the effect of the COVID-19 pandemic, we predicted the rates of healthcare services if the pandemic had not happened. We used generalised linear models (GLM) and the pre-pandemic data from January 2015 to February 2020 to predict rates in March 2020 to March 2023. The 95% confidence intervals of the predicted values were used to estimate the significance of the difference between the predicted and observed rates. Results The rate of pancreatic cancer and diabetes diagnoses in the cohort was not affected by the pandemic. There were 26,840 people diagnosed with pancreatic cancer from January 2015 to March 2023. The mean age at diagnosis was 72 (±11 SD), 48% of people were female, 95% were of White ethnicity and 40% were diagnosed with diabetes. We found a reduction in surgical resections by 25% to 28% during the pandemic. In addition, 20%, 10% and 4% fewer people received BMI, HbA1c and liver function tests respectively before they were diagnosed with pancreatic cancer. There was no impact of the pandemic on the number of people making contact with primary care, but the number of contacts increased on average by 1 to 2 per person amongst those who made contact. Reporting of jaundice decreased by 28%, but recovered within twelve months into the pandemic. Emergency department visits, hospital admissions and deaths were not affected. Conclusions The pandemic affected healthcare in England across the pancreatic cancer pathway. Positive lessons could be learnt from the services that were resilient and those that recovered quickly. The reductions in healthcare experienced by people with cancer have the potential to lead to worse outcomes. Current efforts should focus on addressing the unmet needs of people with cancer.

Introduction Worldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients’ age, blood glucose and weight changes to provide pancreatic cancer risk scores. These values are routinely collected in primary care in the UK. Primary care’s central role in cancer diagnosis makes it an ideal setting to implement ENDPAC but it has yet to be used in clinical settings. This study aims to determine the feasibility of applying ENDPAC to data held by UK primary care practices. Methods and analysis This will be a multicentre observational study with a cohort design, determining the feasibility of applying ENDPAC in UK primary care. We will develop software to search, extract and process anonymised data from 20 primary care providers’ electronic patient record management systems on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥48 mmol/mol (6.5%) and no previous abnormal HbA1c results. Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort’s demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC’s effectiveness for the early detection of pancreatic cancer. Ethics and dissemination This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating primary care practices, clinical leads and policy makers will be provided with summaries of the findings.

Tackling inequities in cancer outcomes is a global health priority. One avenue for improving early diagnosis of cancer is to ensure people know when and how to seek help for cancer symptoms and that this knowledge (and behaviour) is equitably distributed across the population. In this perspective piece we highlight the challenges in understanding sociodemographic differences in help-seeking behaviour (for example, how help-seeking is defined / conceptualised and subsequently assessed), as well as challenges with using existing datasets that are now more readily accessible than ever. Addressing these will strengthen methodological approaches to understand inequities in help-seeking and ways to tackle them.

There is a global emergency in relation to mental health (MH) and healthcare. In the UK each year, 1 in 4 people will experience MH problems. Healthcare services are increasingly oversubscribed, and COVID-19 has deepened the healthcare gap. We investigated the effect of COVID-19 on waiting times for MH services in Scotland. We used national registers of MH services provided by Public Health Scotland. The results show that waiting times for adults and children increased drastically during the pandemic. This was seen nationally and across most of the administrative regions of Scotland. We find, however, that child and adolescent services were comparatively less impacted by the pandemic than adult services. This is potentially due to prioritisation of paediatric patients, or due to an increasing demand on adult services triggered by the pandemic itself.

Background Randomised controlled trials (RCTs) are the gold standard for evidence-based practice. However, RCTs can have limitations. For example, translation of findings into practice can be limited by design features, such as inclusion criteria, not accurately reflecting clinical populations. In addition, it is expensive to recruit and follow-up participants in RCTs. Linkage with routinely collected data could offer a cost-effective way to enhance the conduct and generalisability of RCTs. The aim of this study is to investigate how primary care data can support RCTs. Methods Secondary analysis following linkage of two datasets: 1) multicentre CHHiP radiotherapy trial (ISRCTN97182923) and 2) primary care database from the Royal College of General Practitioners Research and Surveillance Centre. Comorbidities and medications recorded in CHHiP at baseline, and radiotherapy-related toxicity recorded in CHHiP over time were compared with primary care records. The association of comorbidities and medications with toxicity was analysed with mixed-effects logistic regression. Results Primary care records were extracted for 106 out of 2811 CHHiP participants recruited from sites in England (median age 70, range 44 to 82). Complementary information included longitudinal body mass index, blood pressure and cholesterol, as well as baseline smoking and alcohol usage but was limited by the considerable missing data. In the linked sample, 9 (8%) participants were recorded in CHHiP as having a history of diabetes and 38 (36%) hypertension, whereas primary care records indicated incidence prior to trial entry of 11 (10%) and 40 (38%) respectively. Concomitant medications were not collected in CHHiP but available in primary care records. This indicated that 44 (41.5%) men took aspirin, 65 (61.3%) statins, 14 (13.2%) metformin and 46 (43.4%) phosphodiesterase-5-inhibitors at some point before or after trial entry. Conclusions We provide a set of recommendations on linkage and supplementation of trials. Data recorded in primary care are a rich resource and linkage could provide near real-time information to supplement trials and an efficient and cost-effective mechanism for long-term follow-up. In addition, standardised primary care data extracts could form part of RCT recruitment and conduct. However, this is at present limited by the variable quality and fragmentation of primary care data.

Purpose: To identify symptom clusters and predisposing factors associated with long-term symptoms and health-related quality of life (HRQOL) following radiotherapy in men with prostate cancer. Methods: Patient-reported outcomes (PROs) data from the Medical Research Council RT01 radiotherapy with neoadjuvant androgen deprivation therapy (ADT) trial of 843 patients were used. PROs were collected over 5 years with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI) and the 36-Item Short-Form Health Survey (SF-36). Symptom clusters were explored using hierarchical cluster analysis (HCA). The association of treatment dose, baseline patient characteristics and early symptom clusters with the change in severity of PROs over three years was investigated with multivariate linear mixed effects models. Results: Seven symptom clusters of three or more symptoms were identified. The clusters were stable over time. The longitudinal profiles of symptom clusters showed the onset of acute symptoms during treatment for all symptom clusters and significant recovery by six months. Some clusters such as Physical Health and Sexual Function were adversely affected more than others by ADT, and were less likely to return to pre-treatment levels over time. Older age was significantly associated with decreased long-term Physical Function, Physical Health and Sexual Function (p

We have analysed mental health data for in-patient admissions from 1997 to 2021 in Scotland. The number of patient admissions for mental health patients is declining despite population numbers increasing. This is driven by the adult population; child and adolescent numbers are consistent. We find that mental health in-patients are more likely to be from deprived areas: 33 % of patients are from the most deprived areas, compared to only 11 % from the least deprived. The average length of stay for a mental health in-patient is decreasing, with a rise in stays lasting less than a day. The number of mental health patients who have been readmitted within a month fell from 1997 to 2011, then increased to 2021. Despite the average stay length decreasing, the number of overall readmissions is increasing, suggesting patients are having more, shorter stays.

To develop a non-invasive management strategy for men with lower urinary tract symptoms (LUTS) after treatment for pelvic cancer, that is suitable for use in a primary healthcare context. PubMed literature searches of LUTS management in this patient group were carried out, together with obtaining a consensus of management strategies from a panel of authors for the management of LUTS from across the UK. Data from 41 articles were investigated and collated. Clinical experience was sought from authors where there was no clinical evidence. The findings discussed in this paper confirm that LUTS after the cancer treatment can significantly impair men's quality of life. While many men recover from LUTS spontaneously over time, a significant proportion require long-term management. Despite the prevalence of LUTS, there is a lack of consensus on best management. This article offers a comprehensive treatment algorithm to manage patients with LUTS following pelvic cancer treatment. Based on published research literature and clinical experience, recommendations are proposed for the standardisation of management strategies employed for men with LUTS after the pelvic cancer treatment. In addition to implementing the algorithm, understanding the rationale for the type and timing of LUTS management strategies is crucial for clinicians and patients.

Objectives: To assess the feasibility and acceptability of a community pharmacy lifestyle intervention to improve physical activity and cardiovascular health of men with prostate cancer. To refine the intervention. Design: Phase II feasibility study of a complex intervention. Setting: Nine community pharmacies in the UK. Intervention: Community pharmacy teams were trained to deliver a health assessment including fitness, strength and anthropometric measures. A computer algorithm generated a personalised lifestyle prescription for a homebased programme accompanied by supporting resources. The health assessment was repeated 12 weeks later and support phone calls were provided at weeks 1 and 6. Participants: 116 men who completed treatment for prostate cancer. Outcome measures: The feasibility and acceptability of the intervention and the delivery model were assessed by evaluating study processes (rate of participant recruitment, consent, retention and adverse events), by analysing delivery data and semi-structured interviews with participants and by focus groups with pharmacy teams. Physical activity (measured with accelerometry at baseline, 3 and 6 months) and patient reported outcomes (activation, dietary intake and quality of life) were evaluated. Change in physical activity was used to inform the sample size calculations for a future trial. Results: Out of 403 invited men, 172 (43%) responded and 116 (29%) participated. Of these, 99 (85%) completed the intervention and 88 (76%) completed the 6-month follow-up (attrition 24%). Certain components of the intervention were feasible and acceptable (eg, community pharmacy delivery), while others were more challenging (eg, fitness assessment) and will be refined for future studies. By 3 months, moderate to vigorous physical activity increased on average by 34 min (95% CI 6 to 62, p=0.018), but this was not sustained over 6 months. Conclusions: The community pharmacy intervention was feasible and acceptable. Results are encouraging and warrant a definitive trial to assess the effectiveness of the refined intervention.

Background Assessing fitness and promoting regular physical activity can improve health outcomes and early recovery in prostate cancer. This is however, underutilised in clinical practice. The cardiopulmonary exercise test (CPET) is increasingly being used pre-treatment to measure aerobic capacity and peak oxygen consumption (VO2peak - a gold standard in cardiopulmonary fitness assessment). However, CPET requires expensive equipment and may not always be appropriate. The Siconolfi step test (SST) is simpler and cheaper, and could provide an alternative. The aim of this study was to evaluate the validity and reliability of SST for predicting cardiopulmonary fitness in men with prostate cancer. Men were recruited to this two-centre study (Surrey and Newcastle, United Kingdom) after treatment for locally advanced prostate cancer. They had one or more of three risk factors: elevated blood pressure, overweight (BMI ˃ 25), or androgen deprivation therapy (ADT). Cardiopulmonary fitness was measured using SST and cycle ergometry CPET, at two visits three months apart. The validity of SST was assessed by comparing it to CPET. The VO2peak predicted from SST was compared to the VO2peak directly measured with CPET. The reliability of SST was assessed by comparing repeated measures. Bland-Altman analysis was used to derive limits of agreement in validity and reliability analysis. Results Sixty-six men provided data for both SST and CPET. These data were used for validity analysis. 56 men provided SST data on both visits. These data were used for reliability analysis. SST provided valid prediction of the cardiopulmonary fitness in men ˃ 60 years old. The average difference between CPET and SST was 0.64 ml/kg/min with non-significant positive bias towards CPET (P = 0.217). Bland-Altman 95% limits of agreement of SST with CPET were ± 7.62 ml/kg/min. SST was reliable across the whole age range. Predicted VO2peak was on average 0.53 ml/kg/min higher at Visit 2 than at Visit 1 (P = 0.181). Bland-Altman 95% limits of agreement between repeated SST measures were ± 5.84 ml/kg/min. Conclusions SST provides a valid and reliable alternative to CPET for the assessment of cardiopulmonary fitness in older men with prostate cancer. Caution is advised when assessing men 60 years old or younger because the VO2peak predicted with SST was significantly lower than that measured with CPET.

To report patient activation, which is the knowledge, skills, and confidence in self-managing health conditions, and patient-reported outcomes of men after prostate cancer treatment from a community pharmacy lifestyle intervention. The 3-month lifestyle intervention was delivered to 116 men in nine community pharmacies in the UK. Patient Activation Measure (PAM) was assessed at baseline, 3 and 6 months. Prostate cancer-related function and quality of life were assessed using the European Prostate Cancer Index Composite (EPIC-26) and EuroQOL 5-dimension 5-level (EQ5D-5L) questionnaires at baseline and 6 months. Lifestyle assessments included Mediterranean Diet Adherence Screener (MEDAS) at baseline, 3 and 6 months and Godin Leisure Time Exercise Questionnaire (GLTEQ) at baseline and 3 months. PAM score increased from 62 [95% CI 59-65] at baseline to 66 [64-69] after the intervention (p = 0.001) and remained higher at 6 months (p = 0.008). Scores for all the EPIC-26 domains (urinary, bowel and hormonal) were high at both assessments, indicating good function (between 74 [70-78] and 89 [86-91]), except sexual domain, where scores were much lower (21 [17-25] at baseline, increasing to 24 [20-28] at 6 months (p = 0.012)). In EQ5D-5L, 3% of men [1-9] reported self-care problems, while 50% [41-60] reported pain and discomfort, and no significant changes over time. Men who received androgen deprivation therapy, compared with those who did not, reported higher (better) urinary incontinence scores (p 

Saliva is an easy to obtain bodily fluid that is specific to the oral environment. It can be used for metabolomic studies as it is representative of the overall wellbeing of an organism, as well as mouth health and bacterial flora. The metabolomic structure of saliva varies greatly depending on the bacteria present in the mouth as they produce a range of metabolites. In this study we have investigated the metabolomic profiles of human saliva that were obtained using 1H NMR (nuclear magnetic resonance) analysis. 48 samples of saliva were collected from 16 healthy subjects over 3 days. Each sample was split in two and the first half treated with an oral rinse, while the second was left untreated as a control sample. The 96 1H NMR metabolomic profiles obtained in the dataset are affected by three factors, namely 16 subjects, 3 sampling days and 2 treatments. These three factors contribute to the total variation in the dataset. When analysing datasets from saliva using traditional methods such as PCA (principal component analysis), the overall variance is dominated by subjects' contributions, and we cannot see trends that would highlight the effect of specific factors such as oral rinse. In order to identify these trends, we used methods such as MSCA (multilevel simultaneous component analysis) and ASCA (ANOVA simultaneous component analysis), that provide variance splits according to the experimental factors, so that we could look at the particular effect of treatment on saliva. The analysis of the treatment effect was enhanced, as it was isolated from the overall variance and assessed without confounding factors. © 2011 Springer Science+Business Media, LLC.

Healthcare across all sectors, in the UK and globally, was negatively affected by the COVID-19 pandemic. We analysed healthcare services delivered to people with pancreatic cancer from January 2015 to March 2023 to investigate the effect of the COVID-19 pandemic. With the approval of NHS England, and drawing from a nationally representative OpenSAFELY-TPP dataset of 24 million patients (over 40% of the English population), we undertook a cohort study of people diagnosed with pancreatic cancer. We queried electronic healthcare records for information on the provision of healthcare services across the pancreatic cancer pathway. To estimate the effect of the COVID-19 pandemic, we predicted the rates of healthcare services if the pandemic had not happened. We used generalised linear models and the pre-pandemic data from January 2015 to February 2020 to predict rates in March 2020 to March 2023. The 95% confidence intervals of the predicted values were used to estimate the significance of the difference between the predicted and observed rates. The rate of pancreatic cancer and diabetes diagnoses in the cohort was not affected by the pandemic. There were 26,840 people diagnosed with pancreatic cancer from January 2015 to March 2023. The mean age at diagnosis was 72 (±11 SD), 48% of people were female, 95% were of White ethnicity, and 40% were diagnosed with diabetes. We found a reduction in surgical resections by 25-28% during the pandemic. In addition, 20%, 10%, and 4% fewer people received body mass index, glycated haemoglobin, and liver function tests, respectively, before they were diagnosed with pancreatic cancer. There was no impact of the pandemic on the number of people making contact with primary care, but the number of contacts increased on average by 1-2 per person amongst those who made contact. Reporting of jaundice decreased by 28%, but recovered within 12 months into the pandemic. Emergency department visits, hospital admissions, and deaths were not affected. The pandemic affected healthcare in England across the pancreatic cancer pathway. Positive lessons could be learnt from the services that were resilient and those that recovered quickly. The reductions in healthcare experienced by people with cancer have the potential to lead to worse outcomes. Current efforts should focus on addressing the unmet needs of people with cancer. This work was jointly funded by the Wellcome Trust (222097/Z/20/Z); MRC (MR/V015757/1, MC_PC-20059, MR/W016729/1); NIHR (NIHR135559, COV-LT2-0073), and Health Data Research UK (HDRUK2021.000, 2021.0157). This work was funded by Medical Research Council (MRC) grant reference MR/W021390/1 as part of the postdoctoral fellowship awarded to AL and undertaken at the Bennett Institute, University of Oxford. The views expressed are those of the authors and not necessarily those of the NIHR, NHS England, UK Health Security Agency (UKHSA), or the Department of Health and Social Care. Funders had no role in the study design, collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Background: Concerns have been raised that Angiotensin Converting Enzyme-Inhibitors (ACE-I) and Angiotensin Receptor Blockers (ARB) might facilitate transmission of SARS-CoV-2 leading to more severe coronavirus disease (COVID-19) disease and an increased risk of mortality. We aimed to investigate the association between ACE-I/ARB treatment and risk of death amongst people with COVID-19 in the first six months of the pandemic. Methods: We identified a cohort of adults diagnosed with either confirmed or probable COVID-19 (from 1st January – 21st June 2020) using computerised medical records from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care database. This comprised 465 general practices in England, UK with a nationally representative population of 3.7 million people. We constructed mixed-effects logistic regression models to quantify the association between ACE-I/ARBs and all-cause mortality among people with COVID-19, adjusted for sociodemographic factors, co-morbidities, concurrent medication, smoking status, practice clustering and household number. Results: There were 9,586 COVID-19 cases in the sample and 1,463 (15.3%) died during the study period between 01.01.2020 and 21.06.2020. In adjusted analysis ACE-I and ARBs were not associated with all-cause mortality (adjusted OR 1.02, 95% CI 0.85 to 1.21 and 0.84, 95% CI 0.67 to 1.07 respectively). Conclusion: Use of ACE-I/ARB, which are commonly used drugs, did not alter the odds of all-cause mortality amongst people diagnosed with COVID-19. Our findings should inform patient and prescriber decisions concerning continued use of these medications during the pandemic. HDM is an National Institute for Health Research funded Academic Clinical Lecturer and received NIHR SPCR funding for this project (SPCR2014-10043). SJG is supported by an MRC Epidemiology Unit programme: MC_UU_12015/4. The University of Cambridge has received salary support in respect of SJG from the NHS in the East of England through the Clinical Academic Reserve. JHC acknowledges personal support from the British Heart Foundation (FS/14/55/30806) and Cancer Research UK (C5255/A18085) through the Cancer Research UK Oxford Centre

The purpose of this study was to compare fitness parameters and cardiovascular disease risk of older and younger men with prostate cancer (PCa) and explore how men's fitness scores compared to normative age values. 83 men were recruited post-treatment and undertook a cardiopulmonary exercise test (CPET), sit-to-stand, step-and-grip strength tests and provided blood samples for serum lipids and HbA1c. We calculated waist-to-hip ratio, cardiovascular risk (QRISK2), Charlson comorbidity index (CCI) and Godin leisure-time exercise questionnaire [GLTEQ]. Age-group comparisons were made using normative data. Men > 75 years, had lower cardiopulmonary fitness, as measured by VO2 Peak (ml/kg/min) 15.8 + 3.8 p < 0.001, and lower grip strength(28.6+5.2 kg p < 0.001) than younger men. BMI ≥30kg/m2 and higher blood pressure all contributed to a QRisk2 score indicative of 20% chance of cardiovascular risk within 10 years (mean: 36.9–6.1) p < 0.001. Age, BMI and perceived physical activity were significantly associated with lower cardiopulmonary fitness. Men with PCa > 75 years had more cardiovascular risk factors compared to normative standards for men of their age. Although ADT was more frequent in older men, this was not found to be associated with cardiopulmonary fitness, but obesity and low levels of physical activity were. Secondary prevention should be addressed in men with PCa to improve men's overall health.

Patient reported outcome measures (PROMs) are increasingly being used in research to explore experiences of cancer survivors. Techniques to predict symptoms, with the aim of providing triage care, rely on the ability to analyse trends in symptoms or quality of life and at present are limited. The secondary analysis in this study uses a statistical method involving the application of autoregression (AR) to PROMs in order to predict symptom intensity following radiotherapy, and to explore its feasibility as an analytical tool. The technique is demonstrated using an existing dataset of 94 prostate cancer patients who completed a validated battery of PROMs over time. In addition the relationship between symptoms was investigated and symptom clusters were identified to determine their value in assisting predictive modeling. Three symptom clusters, namely urinary, gastrointestinal and emotional were identified. The study indicates that incorporating symptom clustering into predictive modeling helps to identify the most informative predictor variables. The analysis also showed that the degree of rise of symptom intensity during radiotherapy has the ability to predict later radiotherapy-related symptoms. The method was most successful for the prediction of urinary and gastrointestinal symptoms. Quantitative or qualitative prediction was possible on different symptoms. The application of this technique to predict radiotherapy outcomes could lead to increased use of PROMs within clinical practice. This in turn would contribute to improvements in both patient care after radiotherapy and also strategies to prevent side effects. In order to further evaluate the predictive ability of the approach, the analysis of a larger dataset with a longer follow up was identified as the next step.

Background Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse effect of oxaliplatin. CIPN can impair long-term quality of life and limit the dose of chemotherapy. We investigated the association of CIPN over time with age, sex, body mass index, baseline neuropathy, and chemotherapy regimen in people treated with adjuvant oxaliplatin-containing chemotherapy for colorectal cancer. Patients and methods We carried out secondary analysis of data from the SCOT randomised controlled trial. SCOT compared 3 months to 6 months of oxaliplatin-containing adjuvant chemotherapy in 6088 people with colorectal cancer recruited between March 2008 and November 2013. Two different chemotherapy regimens were used: capecitabine with oxaliplatin (CAPOX) or fluorouracil with oxaliplatin (FOLFOX). CIPN was recorded with the Functional Assessment of Cancer Therapy/Gynaecologic Oncology Group-Neurotoxicity 4 tool in 2871 participants from baseline (randomisation) for up to 8 years. Longitudinal trends in CIPN [averages with 95% confidence intervals (CIs)] were plotted stratified by the investigated factors. Analysis of covariance (ANCOVA) was used to analyse the association of factors with CIPN adjusting for the SCOT randomisation arm and oxaliplatin dose. P < 0.01 was adopted as cut-off for statistical significance to account for multiple testing. Results Patients receiving CAPOX had lower CIPN scores than those receiving FOLFOX. Chemotherapy regimen was associated with CIPN from 6 months (P < 0.001) to 2 years (P = 0.001). The adjusted ANCOVA coefficient for CAPOX at 6 months was −1.6 (95% CIs −2.2 to −0.9) and at 2 years it was −1.6 (95% CIs −2.5 to −0.7). People with baseline neuropathy scores ≥1 experienced higher CIPN than people with baseline neuropathy scores of 0 (P < 0.01 for all timepoints apart from 18 months). Age, sex, and body mass index did not link with CIPN. Conclusions A neuropathy assessment before treatment with oxaliplatin can help identify people with an increased risk of CIPN. More research is needed to understand the CIPN-inducing effect of different chemotherapy regimens.

Objective It is well established that exercise and lifestyle behaviours improve men's health outcomes from prostate cancer. With 3.8 million men living with the disease worldwide, the challenge is creating accessible intervention approaches that lead to sustainable lifestyle changes. We carried out a phase II feasibility study of a lifestyle intervention delivered by nine community pharmacies in the United Kingdom to inform a larger efficacy study. Qualitative interviews explored how men experienced the intervention, and these data are presented here. Methods Community pharmacies delivered a multicomponent lifestyle intervention to 116 men with prostate cancer. The intervention included a health, strength, and fitness assessment, immediate feedback, lifestyle prescription with telephone support, and reassessment 12 weeks later. Three months after receiving the intervention, 33 participants took part in semistructured telephone interviews. Results Our framework analysis identified how a teachable moment can be created by a community pharmacy intervention. There was evidence of this when men's self‐perception was challenged and coupled to a positive interaction with a pharmacist. Our findings highlight the social context of behaviour change with men identifying how their lifestyle choices were negotiated within their household. There was a ripple effect as lifestyle behaviours made a positive impact on friends and family. Conclusions The teachable moment is not a serendipitous opportunity but can be created by an intervention. Our study adds insight into how community pharmacists can support cancer survivors to make positive lifestyle behaviour changes and suggests a role for doing rather than just telling.

Background: Patients receiving cancer treatment often have one or more co-morbid conditions that are treated pharmacologically. Co-morbidities are recorded in clinical trials usually only at baseline. However, co-morbidities evolve and new ones emerge during cancer treatment. The interaction between multi-morbidity and cancer recovery is significant but poorly understood. Purpose: To investigate the effect of co-morbidities (e.g. cardiovascular and diabetes) and medications (e.g. statins, antihypertensives, metformin) on radiotherapy-related toxicity and long-term symptoms in order to identify potential risk factors. The possible protective effect of medications such as statins or antihypertensives in reducing radiotherapy-related toxicity will also be explored. Methods: Two datasets will be linked. 1) CHHiP (Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer) randomised control trial. CHHiP contains pelvic symptoms and radiation-related toxicity reported by patients and clinicians. 2) GP (General Practice) data from RCGP RSC (Royal College of General Practitioners Research and Surveillance Centre). The GP records of CHHiP patients will be extracted, including cardiovascular co-morbidities, diabetes and prescription medications. Statistical analysis of the combined dataset will be performed in order to investigate the effect. Conclusions: Linking two sources of healthcare data is an exciting area of big healthcare data research. With limited data in clinical trials (not all clinical trials collect information on co-morbidities or medications) and limited lengths of follow-up, linking different sources of information is increasingly needed to investigate long-term outcomes. With increasing pressures to collect detailed information in clinical trials (e.g. co-morbidities, medications), linkage to routinely collected data offers the potential to support efficient conduct of clinical trials.

Objectives In the UK, guidelines recommend pancreatic enzyme replacement therapy (PERT) to all people with unresectable pancreatic cancer. In 2023, we published a national audit of PERT which showed suboptimal prescribing and wide regional variation in England. The aim of this manuscript was to describe how we used the PERT audit to drive improvements in healthcare. Methods Building on the PERT audit, we deployed an online dashboard which will deliver ongoing updates of the PERT audit. We developed a collaborative intervention with cancer nurse specialists (CNS) to improve care delivered to people with pancreatic cancer. The intervention called Creating a natiOnAL CNS pancrEatic cancer network to Standardise and improve CarE (COALESCE) will use the dashboard to evaluate improvements in prescribing of PERT. Results We demonstrated how large databases of electronic healthcare records (EHRs) can be used to improve cancer care. The PERT audit was implemented into a dashboard for tracking the progress of COALESCE. We will measure improvements in PERT prescribing as the intervention with CNS progresses. Conclusions Improving healthcare is an ongoing and iterative process. By implementing the PERT dashboard, we created a resource-efficient, automated evaluation method enabling COALESCE to deliver a sustainable change. National-scale databases of EHRs enable rapid cycles of audits, providing regular feedback to interventions, working systematically to deliver change. Here, the focus is on pancreatic cancer. However, this methodology is transferable to other areas of healthcare. Implications for Nursing Practice Nurses play a key role in collecting good quality data which are needed in clinical audits to identify shortcomings in healthcare. Nurse-driven interventions can be designed to improve healthcare. In this study, we capitalize on the unique role of CNS coordinating care for every patient with cancer. COALESCE is the first national collaborative study which uses CNS as researchers and change agents.

Objectives To investigate the effect of the COVID-19 pandemic on prostate cancer incidence, prevalence, and mortality in England. Materials and methods With the approval of NHS England, and using the OpenSAFELY-TPP dataset of 24 million patients, we undertook a cohort study of people diagnosed with prostate cancer. We visualised monthly rates in prostate cancer incidence, prevalence and mortality per 100,000 adult men from January 2015 to July 2023. To assess the effect of the pandemic, we used generalised linear models (GLM) and the pre-pandemic data to predict the expected rates from March 2020 as if the pandemic had not occurred. The 95% confidence intervals of the predicted values were used to estimate the significance of the difference between the predicted and observed rates. Results In 2020, there was a drop in recorded incidence by 4,772 (31%) cases (15,550 vs 20,322 [95% CI: 19,241 to 21,403]). In 2021, the incidence started to recover, and the drop was 3,148 cases (18%, 17,950 vs 21,098 [19,740 to 22,456]). By 2022, the incidence returned to the levels that would be expected. During the pandemic, the age at diagnosis shifted towards older men. In 2020, the average age was 71.6 (71.5 to 71.8), in 2021 it was 71.8 (71.7 to 72.0) as compared to 71.3 (71.1 to 71.4) in 2019. Conclusions Given that our dataset represents 40% of the population, we estimate that proportionally the pandemic led to 20,000 missed prostate cancer diagnoses in England alone. The increase in incidence recorded in 2023 was not enough to account for the missed cases. The prevalence of prostate cancer remained lower throughout the pandemic than expected. As the recovery efforts continue, healthcare should focus on finding the men who were affected. The research should focus on investigating the potential harms to men diagnosed at older age.

Purpose: To investigate the role of symptom clusters in the analysis and utilisation of Patient-Reported Outcome Measures (PROMs) for data modelling and clinical practice. To compare symptom clusters with scales, and explore their value in PROMs interpretation and symptom management. Methods: A dataset called RT01 (ISCRTN47772397) of 843 prostate cancer patients was used. PROMs were reported with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI). Symptom clusters were explored with hierarchical cluster analysis (HCA) and average linkage method (correlation >0.6). The reliability of the Urinary Function Scale was evaluated with Cronbach's Alpha. The strength of the relationship between the items was investigated with Spearman's correlation. Predictive accuracy of the clusters was compared to the scales by receiver operating characteristic (ROC) analysis. Presence of urinary symptoms at 3 years measured with the Late Effects on Normal Tissue: Subjective, Objective, Management tool (LENT/SOM) was an endpoint. Results: Two symptom clusters were identified (Urinary Cluster and Sexual Cluster). The grouping of symptom clusters was different than UCLA-PCI Scales. Two items of the Urinary Function Scales (“Number of pads” and “Urinary leak interfering with sex”) were excluded from the Urinary Cluster. The correlation with the other items in the scale ranged from 0.20-0.21 and 0.31-0.39 respectively. Cronbach's Alpha showed low correlation of those items with the Urinary Function Scale (0.14-0.36 and 0.33-0.44 respectively). All Urinary Function Scale items were subject to a ceiling effect. Clusters had better predictive accuracy, AUC = 0.70-0.65, while scales AUC = 0.67-0.61. Conclusion: This study adds to the knowledge on how cluster analysis can be applied for the interpretation and utilisation of PROMs. We conclude that multiple-item scales should be evaluated and that symptom clusters provide an adaptive and study specific approach for modelling and interpretation of PROMs.

Although routine healthcare data are not collected for research, they are increasingly used in epidemiology and are key real-world evidence for improving healthcare. This study presents a method to identify prostate cancer cases from a large English primary care database. 19,619 (1.3%) men had a code for prostate cancer diagnosis. Codes for medium and high Gleason grading enabled identification of additional 94 (0.5%) cases. Many studies do not report codes used to identify patients, and if published, the lists of codes differ from study to study. This can lead to poor research reproducibility and hinder validation. This work demonstrates that carefully developed comprehensive lists of clinical codes can be used to identify prostate cancer; and that approaches that do not solely rely on clinical codes such as ontologies or data linkage should also be considered.

Background The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes.

The effect of the 2020 pandemic, and of the national measures introduced to control it, is not yet fully understood. The aim of this study was to investigate how different types of primary care data can help quantify the effect of the coronavirus disease (COVID-19) crisis on mental health. A retrospective cohort study investigated changes in weekly counts of mental health consultations and prescriptions. The data were extracted from one the UK’s largest primary care databases between January 1 st 2015 and October 31st 2020 (end of follow-up). The 2020 trends were compared to the 2015-19 average with 95% confidence intervals using longitudinal plots and analysis of covariance (ANCOVA). A total number of 504 practices (7,057,447 patients) contributed data. During the period of national restrictions, on average, there were 31% (3957 ± 269, p < 0.001) fewer events and 6% (4878 ± 1108, p < 0.001) more prescriptions per week as compared to the 2015-19 average. The number of events was recovering, increasing by 75 (± 29, p = 0.012) per week. Prescriptions returned to the 2015-19 levels by the end of the study (p = 0.854). The significant reduction in the number of consultations represents part of the crisis. Future service planning and quality improvements are needed to reduce the negative effect on health and healthcare.

Concerns have been raised that angiotensin-converting enzyme-inhibitors (ACE-I) and angiotensin receptor blockers (ARBs) might facilitate transmission of severe acute respiratory syndrome coronavirus 2 leading to more severe coronavirus disease (COVID-19) disease and an increased risk of mortality. We aimed to investigate the association between ACE-I/ARB treatment and risk of death amongst people with COVID-19 in the first 6 months of the pandemic. We identified a cohort of adults diagnosed with either confirmed or probable COVID-19 (from 1 January to 21 June 2020) using computerized medical records from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care database. This comprised 465 general practices in England, United Kingdom with a nationally representative population of 3.7 million people. We constructed mixed-effects logistic regression models to quantify the association between ACE-I/ARBs and all-cause mortality among people with COVID-19, adjusted for sociodemographic factors, comorbidities, concurrent medication, smoking status, practice clustering, and household number. There were 9,586 COVID-19 cases in the sample and 1,463 (15.3%) died during the study period between 1 January 2020 and 21 June 2020. In adjusted analysis ACE-I and ARBs were not associated with all-cause mortality (adjusted odds ratio [OR] 1.02, 95% confidence interval [CI] 0.85-1.21 and OR 0.84, 95% CI 0.67-1.07, respectively). Use of ACE-I/ARB, which are commonly used drugs, did not alter the odds of all-cause mortality amongst people diagnosed with COVID-19. Our findings should inform patient and prescriber decisions concerning continued use of these medications during the pandemic.

Background: Universities in the United Kingdom (UK) are required to incorporate values based recruitment (VBR) into their healthcare student selection processes. This reflects an international drive to strengthen the quality of healthcare service provision. This paper presents novel findings in relation to the reliability and predictive validity of multiple mini interviews (MMIs); one approach to VBR widely being employed by universities. Objectives: To examine the reliability (internal consistency) and predictive validity of MMIs using end of Year One practice outcomes of under-graduate pre-registration adult, child, mental health nursing, midwifery and paramedic practice students. Design: Cross-discipline evaluation study. Setting: One university in the United Kingdom. Participants: Data were collected in two streams: applicants to A) The September 2014 and 2015 Midwifery Studies programmes; B) September 2015 adult; Child and Mental Health Nursing and Paramedic Practice programmes. Fifty-seven midwifery students commenced their programme in 2014 and 69 in 2015; 47 and 54 agreed to participate and completed Year One respectively. 333 healthcare students commenced their programmes in September 2015. Of these, 281 agreed to participate and completed their first year (180 adult, 33 child and 34 mental health nursing and 34 paramedic practice students). Methods: Stream A featured a seven station four-minute model with one interviewer at each station and in Stream B a six station model was employed. Cronbach’s alpha was used to assess MMI station internal consistency and Pearson’s moment correlation co-efficient to explore associations between participants’ admission MMI score and end of Year one clinical practice outcomes (OSCE and mentor grading). Results: Stream A: Significant correlations are reported between midwifery applicant’s MMI scores and end of Year One practice outcomes. A multivariate linear regression model demonstrated that MMI score significantly predicted end of Year One practice outcomes controlling for age and academic entry level: coefficients 0.195 (p = 0.002) and 0.116 (p = 0.002) for OSCE and mentor grading respectively. In Stream B no significant correlations were found between MMI score and practice outcomes measured by mentor grading. Internal consistency for each MMI station was ‘excellent’ with values ranging from 0.966–0.974 across Streams A and B. Conclusion: This novel, cross-discipline study shows that MMIs are reliable VBR tools which have predictive validity when a seven station model is used. These data are important given the current international use of different MMI models in healthcare student selection processes.

To evaluate the effectiveness of the symptom management after radiotherapy (SMaRT) group intervention to improve urinary symptoms in men with prostate cancer. The randomised controlled trial (RCT) recruited men from one radiotherapy centre in the UK after curative radiotherapy or brachytherapy and with moderate to severe urinary symptoms defined as scores ≥ 8 on the International Prostate Symptom Score (IPSS) questionnaire. Sixty-three men were randomised either; to SMaRT, a 10-week symptom-management intervention including group support, education, pelvic floor muscle exercises, or a care-as-usual group. The primary outcome was the IPSS at 6 months from baseline assessment. Secondary outcomes were IPSS at 3 months, and International Continence Society Male Short Form (ICS), European Organisation for Research and Treatment of Cancer Quality of Life prostate scale (EORTC QLQ-PR25), EORTC QLQ-30 and Self-Efficacy for Symptom Control Inventory (SESCI) at 3 and 6 months from baseline. Analysis of covariance (ANCOVA) was used to analyse the effect of the intervention. SMaRT group intervention did not improve urinary symptoms as measured by IPSS at 6-months. The adjusted difference was - 2.5 [95%CI - 5.0 to 0.0], p = 0.054. Significant differences were detected at 3 months in ICS voiding symptoms (- 1.1 [- 2.0 to - 0.2], p = 0.017), ICS urinary incontinence (- 1.0 [- 1.8 to - 0.1], p = 0.029) and SESCI managing symptoms domain (13.5 [2.5 to 24.4], p = 0.017). No differences were observed at 6 months. SMaRT group intervention provided short-term benefit in urinary voiding and continence and helped men manage symptoms but was not effective long term.

Background: Education literature worldwide is replete with studies evaluating the effectiveness of Multiple Mini Interviews (MMIs) in admissions to medicine but

Background Weight loss, hyperglycaemia and diabetes are known features of pancreatic cancer. We quantified the timing and the amount of changes in body mass index (BMI) and glycated haemoglobin (HbA1c), and their association with pancreatic cancer from five years before diagnosis. Methods A matched case-control study was undertaken within 590 primary care practices in England, United Kingdom. 8,777 patients diagnosed with pancreatic cancer (cases) between 1st January 2007 and 31st August 2020 were matched to 34,979 controls by age, gender and diabetes. Longitudinal trends in BMI and HbA1c were visualised. Odds ratios adjusted for demographic and lifestyle factors (aOR) and 95% confidence intervals (CI) were calculated with conditional logistic regression. Subgroup analyses were undertaken according to the diabetes status. Results Changes in BMI and HbA1c observed for cases on longitudinal plots started one and two years (respectively) before diagnosis. In the year before diagnosis, a 1 kg/m2 decrease in BMI between cases and controls was associated with aOR for pancreatic cancer of 1.05 (95% CI 1.05 to 1.06), and a 1 mmol/mol increase in HbA1c was associated with aOR of 1.06 (1.06 to 1.07). ORs remained statistically significant (p < 0.001) for 2 years before pancreatic cancer diagnosis for BMI and 3 years for HbA1c. Subgroup analysis revealed that the decrease in BMI was associated with a higher pancreatic cancer risk for people with diabetes than for people without (aORs 1.08, 1.06 to 1.09 versus 1.04, 1.03 to 1.05), but the increase in HbA1c was associated with a higher risk for people without diabetes than for people with diabetes (aORs 1.09, 1.07 to 1.11 versus 1.04, 1.03 to 1.04). Conclusions The statistically significant changes in weight and glycaemic control started three years before pancreatic cancer diagnosis but varied according to the diabetes status. The information from this study could be used to detect pancreatic cancer earlier than is currently achieved. However, regular BMI and HbA1c measurements are required to facilitate future research and implementation in clinical practice.

Background: The COVID-19 pandemic has resulted in unprecedented impact on the day to day lives of people, with several features potentially adversely affecting mental health. There is growing evidence of the size of the impact of COVID-19 on mental health, but much of this is from ongoing population surveys using validated mental health scores. Objective: This study investigated the impact of the pandemic and control measures on mental health conditions presenting to a spectrum of national healthcare services monitored using real-time syndromic surveillance in England. Methods: We conducted a retrospective observational descriptive study of mental health presentations (those calling the national medical helpline, NHS 111, consulting general practitioners in and out-of-hours, calling ambulance services and attending emergency departments) between 1 January 2019 to 30 September 2020. Estimates for the impact of lockdown measures were provided using an interrupted time series analysis. Results: Mental health presentations showed a marked decrease during the early stages of the pandemic. Post-lockdown, attendances for mental health conditions reached higher than pre-pandemic levels across most systems; a rise of 10% compared to expected for NHS 111 and 21% for GP out-of-hours whilst the number of consultations to in-hours GPs was 13% lower compared to the same time last year. Increases were observed in calls to NHS 111 for sleep problems. Conclusions: These analyses showed marked changes in the healthcare attendances and prescribing for common mental health issues, across a spectrum of healthcare provision, with some of these changes persisting. The reasons for such changes are likely to be complex and multifactorial. The impact of the pandemic on mental health may not be fully understood for some time, and therefore these syndromic indicators should continue to be monitored.

Cancer treatments were variably disrupted during the coronavirus disease 2019 (COVID-19) pandemic. UK guidelines recommend pancreatic enzyme replacement therapy (PERT) to all people with unresectable pancreatic cancer. The aim was to investigate the impact of the COVID-19 pandemic on PERT prescribing to people with unresectable pancreatic cancer and to investigate the national and regional rates from January 2015 to January 2023. With the approval of NHS England, we conducted this study using 24 million electronic health records of people within the OpenSAFELY-TPP research platform. There were 22,860 people diagnosed with pancreatic cancer in the study cohort. We visualized the trends over time and modeled the effect of the COVID-19 pandemic with the interrupted time-series analysis. In contrast to many other treatments, prescribing of PERT was not affected during the pandemic. Overall, since 2015, the rates increased steadily over time by 1% every year. The national rates ranged from 41% in 2015 to 48% in early 2023. There was substantial regional variation, with the highest rates of 50% to 60% in West Midlands. In pancreatic cancer, if PERT is prescribed, it is usually initiated in hospitals by clinical nurse specialists and continued after discharge by primary care practitioners. At just under 50% in early 2023, the rates were still below the recommended 100% standard. More research is needed to understand barriers to prescribing of PERT and geographic variation to improve quality of care. Prior work relied on manual audits. With OpenSAFELY, we developed an automated audit that allows for regular updates (https://doi.org/10.53764/rpt.a0b1b51c7a).