Community antibiotic prescribing in patients with COVID-19 across three pandemic waves: a population-based study in Scotland, UK.

OBJECTIVES: This study aims to examine community antibiotic prescribing across a complete geographical area for people with a positive COVID-19 test across three pandemic waves, and to examine health and demographic factors associated with antibiotic prescribing. DESIGN: A population-based study using administrative data. SETTING: A complete geographical region within Scotland, UK. PARTICIPANTS: Residents of two National Health Service Scotland health boards with SARS-CoV-2 virus test results from 1 February 2020 to 31 March 2022 (n=184 954). Individuals with a positive test result (n=16 025) had data linked to prescription and hospital admission data ±28 days of the test, general practice data for high-risk comorbidities and demographic data. OUTCOME MEASURES: The associations between patient factors and the odds of antibiotic prescription in COVID-19 episodes across three pandemic waves from multivariate binary logistic regression. RESULTS: Data included 768 206 tests for 184 954 individuals, identifying 16 240 COVID-19 episodes involving 16 025 individuals. There were 3263 antibiotic prescriptions ±28 days for 2395 episodes. 35.6% of episodes had a prescription only before the test date, 52.3% of episodes after and 12.1% before and after. Antibiotic prescribing reduced over time: 20.4% of episodes in wave 1, 17.7% in wave 2 and 12.0% in wave 3. In multivariate logistic regression, being female (OR 1.31, 95% CI 1.19 to 1.45), older (OR 3.02, 95% CI 2.50 to 3.68 75+ vs <25 years), having a high-risk comorbidity (OR 1.45, 95% CI 1.31 to 1.61), a hospital admission ±28 days of an episode (OR 1.58, 95% CI 1.42 to 1.77) and health board region (OR 1.14, 95% CI 1.03 to 1.25, board B vs A) increased the odds of receiving an antibiotic. CONCLUSION: Community antibiotic prescriptions in COVID-19 episodes were uncommon in this population and likelihood was associated with patient factors. The reduction over pandemic waves may represent increased knowledge regarding COVID-19 treatment and/or evolving symptomatology.

The implications of competing risks and direct treatment disutility in cardiovascular disease and osteoporotic fracture: risk prediction and cost effectiveness analysis.

Background: Clinical guidelines commonly recommend preventative treatments for people above a risk threshold. Therefore, decision-makers must have faith in risk prediction tools and model-based cost-effectiveness analyses for people at different levels of risk. Two problems that arise are inadequate handling of competing risks of death and failing to account for direct treatment disutility (i.e. the hassle of taking treatments). We explored these issues using two case studies: primary prevention of cardiovascular disease using statins and osteoporotic fracture using bisphosphonates. Objectives: Externally validate three risk prediction tools [QRISK®3, QRISK®-Lifetime, QFracture-2012 (ClinRisk Ltd, Leeds, UK)]; derive and internally validate new risk prediction tools for cardiovascular disease [competing mortality risk model with Charlson Comorbidity Index (CRISK-CCI)] and fracture (CFracture), accounting for competing-cause death; quantify direct treatment disutility for statins and bisphosphonates; and examine the effect of competing risks and direct treatment disutility on the cost-effectiveness of preventative treatments. Design, participants, main outcome measures, data sources: Discrimination and calibration of risk prediction models (Clinical Practice Research Datalink participants: aged 25-84 years for cardiovascular disease and aged 30-99 years for fractures); direct treatment disutility was elicited in online stated-preference surveys (people with/people without experience of statins/bisphosphonates); costs and quality-adjusted life-years were determined from decision-analytic modelling (updated models used in National Institute for Health and Care Excellence decision-making). Results: CRISK-CCI has excellent discrimination, similar to that of QRISK3 (Harrell's c = 0.864 vs. 0.865, respectively, for women; and 0.819 vs. 0.834, respectively, for men). CRISK-CCI has systematically better calibration, although both models overpredict in high-risk subgroups. People recommended for treatment (10-year risk of ≥ 10%) are younger when using QRISK-Lifetime than when using QRISK3, and have fewer observed events in a 10-year follow-up (4.0% vs. 11.9%, respectively, for women; and 4.3% vs. 10.8%, respectively, for men). QFracture-2012 underpredicts fractures, owing to under-ascertainment of events in its derivation. However, there is major overprediction among people aged 85-99 years and/or with multiple long-term conditions. CFracture is better calibrated, although it also overpredicts among older people. In a time trade-off exercise (n = 879), statins exhibited direct treatment disutility of 0.034; for bisphosphonates, it was greater, at 0.067. Inconvenience also influenced preferences in best-worst scaling (n = 631). Updated cost-effectiveness analysis generates more quality-adjusted life-years among people with below-average cardiovascular risk and fewer among people with above-average risk. If people experience disutility when taking statins, the cardiovascular risk threshold at which benefits outweigh harms rises with age (≥ 8% 10-year risk at 40 years of age; ≥ 38% 10-year risk at 80 years of age). Assuming that everyone experiences population-average direct treatment disutility with oral bisphosphonates, treatment is net harmful at all levels of risk. Limitations: Treating data as missing at random is a strong assumption in risk prediction model derivation. Disentangling the effect of statins from secular trends in cardiovascular disease in the previous two decades is challenging. Validating lifetime risk prediction is impossible without using very historical data. Respondents to our stated-preference survey may not be representative of the population. There is no consensus on which direct treatment disutilities should be used for cost-effectiveness analyses. Not all the inputs to the cost-effectiveness models could be updated. Conclusions: Ignoring competing mortality in risk prediction overestimates the risk of cardiovascular events and fracture, especially among older people and those with multimorbidity. Adjustment for competing risk does not meaningfully alter cost-effectiveness of these preventative interventions, but direct treatment disutility is measurable and has the potential to alter the balance of benefits and harms. We argue that this is best addressed in individual-level shared decision-making. Study registration: This study is registered as PROSPERO CRD42021249959. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/12/22) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Before offering a medicine to prevent disease, prescribers must expect it to do more good than harm. This balance depends on how likely it is that the person will develop the disease we want to prevent. But people might first die for other reasons. We call this a 'competing risk'. In most cases, the mathematical tools we use to estimate the chance of developing a disease do not account for competing risks. Another problem is that, when weighing up the benefits and harms of medicines, we ignore the hassle they cause patients, even when they do not cause side effects. We used two examples: statins to prevent heart disease and bisphosphonates to prevent fractures. First, we assessed if existing tools get predictions wrong by not accounting for competing risks. We found that they exaggerate the chance of heart attacks and strokes. However, the exaggeration is greatest among people who would clearly benefit from preventative treatment. So it may not change treatment decisions much. The fracture prediction tool we studied was very inaccurate, exaggerating risk among older people, but underestimating risk among younger people. We made a new fracture risk prediction tool. It gave better predictions, but it was still inaccurate for people aged > 85 years and those with several health problems. Next, we asked people questions designed to put a number on the hassle that statins and bisphosphonates cause. Most people thought that taking either is inconvenient, but the hassle factor for bisphosphonates is bigger. Finally, we updated the mathematical models that the National Institute for Health and Care Excellence used when recommending statins and bisphosphonates. We worked out if competing risks and the hassle of taking medicines make a difference to results. Statins remain a good idea for almost everyone, unless they really hate the idea of taking them. But bisphosphonates would do more harm than good for anyone who agrees with the hassle factor we found.

Activin type I receptor polymorphisms and body composition in older individuals with sarcopenia-Analyses from the LACE randomised controlled trial.

BACKGROUND: Ageing is associated with changes in body composition including an overall reduction in muscle mass and a proportionate increase in fat mass. Sarcopenia is characterised by losses in both muscle mass and strength. Body composition and muscle strength are at least in part genetically determined, consequently polymorphisms in pathways important in muscle biology (e.g., the activin/myostatin signalling pathway) are hypothesised to contribute to the development of sarcopenia. METHODS: We compared regional body composition measured by DXA with genotypes for two polymorphisms (rs10783486, minor allele frequency (MAF) = 0.26 and rs2854464, MAF = 0.26) in the activin 1B receptor (ACVR1B) determined by PCR in a cross-sectional analysis of DNA from 110 older individuals with sarcopenia from the LACE trial. RESULTS: Neither muscle mass nor strength showed any significant associations with either genotype in this cohort. Initial analysis of rs10783486 showed that males with the AA/AG genotype were taller than GG males (174±7cm vs 170±5cm, p = 0.023) and had higher arm fat mass, (median higher by 15%, p = 0.008), and leg fat mass (median higher by 14%, p = 0.042). After correcting for height, arm fat mass remained significantly higher (median higher by 4% padj = 0.024). No associations (adjusted or unadjusted) were seen in females. Similar analysis of the rs2854464 allele showed a similar pattern with the presence of the minor allele (GG/AG) being associated with greater height (GG/AG = 174±7 cm vs AA = 170 ±5cm, p = 0.017) and greater arm fat mass (median higher by 16%, p = 0.023). Again, the difference in arm fat remained after correction for height. No similar associations were seen in females analysed alone. CONCLUSION: These data suggest that polymorphic variation in the ACVR1B locus could be associated with body composition in older males. The activin/myostatin pathway might offer a novel potential target to prevent fat accumulation in older individuals.

Age and cancer type: associations with increased odds of receiving a late diagnosis in people with advanced cancer.

PURPOSE: In order to deliver appropriate and timely care planning and minimise avoidable late diagnoses, clinicians need to be aware of which patients are at higher risk of receiving a late cancer diagnosis. We aimed to determine which demographic and clinical factors are associated with receiving a 'late' cancer diagnosis (within the last 12 weeks of life). METHOD: Retrospective cohort study of 2,443 people who died from cancer ('cancer decedents') in 2013-2015. Demographic and cancer registry datasets linked using patient-identifying Community Health Index numbers. Analysis used binary logistic regression, with univariate and adjusted odds ratios (SPSS v25). RESULTS: One third (n = 831,34.0%) received a late diagnosis. Age and cancer type were significantly associated with late cancer diagnosis (p < 0.001). Other demographic factors were not associated with receiving a late diagnosis. Cancer decedents with lung cancer (Odds Ratios presented in abstract are the inverse of those presented in the main text, where lung cancer is the reference category. Presented as 1/(OR multivariate)) were more likely to have late diagnosis than those with bowel (95% Confidence Interval [95%CI] Odds Ratio (OR)1.52 (OR1.12 to 2.04)), breast or ovarian (95%CI OR3.33 (OR2.27 to 5.0) or prostate (95%CI OR9.09 (OR4.0 to 20.0)) cancers. Cancer decedents aged > 85 years had higher odds of late diagnosis (95%CI OR3.45 (OR2.63 to 4.55)), compared to those aged < 65 years. CONCLUSIONS: Cancer decedents who were older and those with lung cancer were significantly more likely to receive late cancer diagnoses than those who were younger or who had other cancer types.

ACE I/D genotype associates with strength in sarcopenic men but not with response to ACE inhibitor therapy in older adults with sarcopenia: Results from the LACE trial.

BACKGROUND: Angiotensin II (AII), has been suggested to promote muscle loss. Reducing AII synthesis, by inhibiting angiotensin converting enzyme (ACE) activity has been proposed as a method to inhibit muscle loss. The LACE clinical trial was designed to determine whether ACE inhibition would reduce further muscle loss in individuals with sarcopenia but suffered from low recruitment and returned a negative result. Polymorphic variation in the ACE promoter (I/D alleles) has been associated with differences in ACE activity and muscle physiology in a range of clinical conditions. This aim of this analysis was to determine whether I/D polymorphic variation is associated with muscle mass, strength, in sarcopenia or contributed to the lack of response to treatment in the LACE study. METHODS: Sarcopenic individuals were recruited into a 2x2 factorial multicentre double-blind study of the effects of perindopril and/or leucine versus placebo on physical performance and muscle mass. DNA extracted from blood samples (n = 130 72 women and 58 men) was genotyped by PCR for the ACE I/D polymorphism. Genotypes were then compared with body composition measured by DXA, hand grip and quadriceps strength before and after 12 months' treatment with leucine and/or perindopril in a cross-sectional analysis of the influence of genotype on these variables. RESULTS: Allele frequencies for the normal UK population were extracted from 13 previous studies (I = 0.473, D = 0.527). In the LACE cohort the D allele was over-represented (I = 0.412, D = 0.588, p = 0.046). This over-representation was present in men (I = 0.353, D = 0.647, p = 0.010) but not women (I = 0.458, D = 0.532, p = 0.708). In men but not women, individuals with the I allele had greater leg strength (II/ID = 18.00 kg (14.50, 21.60) vs DD = 13.20 kg (10.50, 15.90), p = 0.028). Over the 12 months individuals with the DD genotype increased in quadriceps strength but those with the II or ID genotype did not. Perindopril did not increase muscle strength or mass in any polymorphism group relative to placebo. CONCLUSION: Our results suggest that although ACE genotype was not associated with response to ACE inhibitor therapy in the LACE trial population, sarcopenic men with the ACE DD genotype may be weaker than those with the ACE I/D or II genotype.

Quantifying the impact of taking medicines for primary prevention: a time-trade off study to elicit direct treatment disutility in the UK.

BACKGROUND: Direct treatment disutility (DTD) represents an individual's disutility associated with the inconvenience of taking medicine over a long period of time. OBJECTIVES: The main aim of this study was to elicit DTD values for taking a statin or a bisphosphonate for primary prevention. A secondary aim was to understand factors which influence DTD values. METHODS: Design: We used a cross-sectional study consisting of time-trade off exercises embedded within online surveys. Respondents were asked to compare a one-off pill ('Medicine A') assumed to have no inconvenience and a daily pill ('Medicine B') over 10 years (statins) or 5 years (bisphosphonates).Setting: Individuals from National Health Service (NHS) primary care and the general population were surveyed using an online panel company.Participants: Two types of participants were recruited. First, a purposive sample of patients with experience of taking a statin (n=260) or bisphosphonate (n=100) were recruited from an NHS sampling frame. Patients needed to be aged over 30, have experience of taking the medicine of interest and have no diagnosis of dementia or of using dementia drugs. Second, a demographically balanced sample of members of the public were recruited for statins (n=376) and bisphosphonates (n=359).Primary and secondary outcome measures: Primary outcome was mean DTD. Regression analysis explored factors which could influence DTD values. RESULTS: A total of 879 respondents were included for analysis (514 for statins and 365 for bisphosphonates). The majority of respondents reported a disutility associated with medicine use. Mean DTD for statins was 0.034 and for bisphosphonates 0.067, respectively. Respondent characteristics including age and sex did not influence DTD. Experience of bisphosphonate-use reduced reported disutilities. CONCLUSIONS: Statins and bisphosphonates have a quantifiable DTD. The size of estimated disutilities suggest they are likely to be important for cost-effectiveness, particularly in individuals at low-risk when treated for primary prevention.

Multicenter Randomized Trial Assessing MRI and Image-guided Biopsy for Suspected Prostate Cancer: The MULTIPROS Study.

Background The optimal diagnostic pathway for prostate cancer (PCa) is evolving, requiring further evaluation in a randomized controlled trial. Purpose To assess the diagnostic accuracy of prebiopsy multiparametric MRI in the identification of clinically significant PCa (csPCa) using radical prostatectomy (RP) specimens as the reference standard, and to test the diagnostic accuracy of combined US and MRI fusion-targeted biopsy with systematic biopsies. Materials and Methods In a prospective randomized controlled trial including university hospitals, men with suspected PCa were recruited between January 2015 and August 2020 to assess the diagnostic accuracy of multiparametric MRI before biopsy in detection of csPCa at biopsy and RP histopathologic structure (primary outcome). Men with lesions suspicious for cancer (Prostate Imaging and Reporting Data System [PI-RADS] ≥3) at multiparametric MRI were first randomized to either systematic random prostate biopsies alone (control group) or US and MRI fusion-targeted biopsies with systematic random prostate biopsies (intervention group) at a one-to-one ratio to compare the diagnostic accuracy of systematic random versus combined fusion with systematic random biopsies (secondary outcome). A subset of recruited participants (n = 89) underwent RP and histologic sectioning. Results There were 582 participants who were eligible to undergo multiparametric MRI (mean age, 65 years ± 6 [SD]). In total, 413 had a PI-RADS score of at least 3 and were randomized into either the intervention group (207 of 413; 50.1%) or control group (206 of 413; 49.9%). The csPCa detection rate in the intervention group was higher, with an adjusted odds ratio of 1.79 (95% CI: 1.14, 2.79; P = .01). A subgroup of 89 men underwent RP (21.5%; 89 of 413). Multiparametric MRI helped correctly identify 131 of 182 csPCa foci in 89 men (sensitivity, 72%; 95% CI: 65, 78). The specificity, positive predictive value, and negative predictive value were 71% (91 of 128), 78% (131 of 168), and 64% (91 of 142), respectively. Conclusion Prebiopsy multiparametric MRI was accurate in the depiction of clinically significant PCa. Combining US and MRI fusion-targeted biopsies with systematic biopsies helped detect more clinically significant lesions than did systematic biopsies alone. Clinical trial registration no. NCT02745496 © RSNA, 2023 Supplemental material is available for this article.

External validation of the QLifetime cardiovascular risk prediction tool: population cohort study.

BACKGROUND: Prediction of lifetime cardiovascular disease (CVD) risk is recommended in many clinical guidelines, but lifetime risk models are rarely externally validated. The aim of this study was to externally validate the QRiskLifetime incident CVD risk prediction tool. METHODS: Independent external validation of QRiskLifetime using Clinical Practice Research Datalink data, examining discrimination and calibration in the whole population and stratified by age, and reclassification compared to QRISK3. Since lifetime CVD risk is unobservable, performance was evaluated at 10-years' follow-up, and lifetime performance inferred in terms of performance for in the different age-groups from which lifetime predictions are derived. RESULTS: One million, two hundreds sixty thousand and three hundreds twenty nine women and 1,223,265 men were included in the analysis. Discrimination was excellent in the whole population (Harrell's-C = 0.844 in women, 0.808 in men), but moderate to poor stratified by age-group (Harrell's C in people aged 30-44 0.714 for both men and women, in people aged 75-84 0.578 in women and 0.556 in men). Ten-year CVD risk was under-predicted in the whole population, and in all age-groups except women aged 45-64, with worse under-prediction in older age-groups. Compared to those at highest QRISK3 estimated 10-year risk, those with highest lifetime risk were younger (mean age: women 50.5 vs. 71.3 years; men 46.3 vs. 63.8 years) and had lower systolic blood pressure and prevalence of treated hypertension, but had more family history of premature CVD, and were more commonly minority ethnic. Over 10-years, the estimated number needed to treat (NNT) with a statin to prevent one CVD event in people with QRISK3 ≥ 10% was 34 in women and 37 in men, compared to 99 and 100 for those at highest lifetime risk. CONCLUSIONS: QRiskLifetime underpredicts 10-year CVD risk in nearly all age-groups, so is likely to also underpredict lifetime risk. Treatment based on lifetime risk has considerably lower medium-term benefit than treatment based on 10-year risk.

Derivation and validation of the CFracture competing risk fracture prediction tool compared with QFracture in older people and people with comorbidity: a population cohort study.

BACKGROUND: UK guidelines recommend the QFracture tool to predict the risk of major osteoporotic fracture and hip fracture, but QFracture calibration is poor, partly because it does not account for competing mortality risk. The aim of this study was to derive and validate a competing risk model to predict major osteoporotic fracture and hip fracture (CFracture) and compare its performance with that of QFracture in UK primary care. METHODS: We used UK linked primary care data from the Clinical Practice Research Datalink GOLD database to identify people aged 30-99 years, split into derivation and validation cohorts. In the derivation cohort, we derived models (CFracture) using the same covariates as QFracture with Fine-Gray competing risk modelling, and included the Charlson Comorbidity Index score as an additional predictor of non-fracture death. In a separate validation cohort, we examined discrimination (using Harrell's C-statistic) and calibration of CFracture compared with QFracture. Reclassification analysis examined differences in the characteristics of patients reclassified as higher risk by CFracture but not by QFracture. FINDINGS: The derivation cohort included 1 831 606 women and 1 789 820 men, and the validation cohort included 915 803 women and 894 910 men. Overall discrimination of CFracture was excellent (C-statistic=0·813 [95% CI 0·810-0·816] for major osteoporotic fracture and 0·914 [0·908-0·919] for hip fracture in women; 0·734 [0·729-0·740] for major osteoporotic fracture and 0·886 [0·877-0·895] for hip fracture in men) and was similar to QFracture. CFracture calibration overall and in people younger than 75 years was generally excellent. CFracture overpredicted major osteoporotic fracture and hip fracture in older people and people with comorbidity, but was better calibrated than QFracture. Patients classified as high-risk by CFracture but not by QFracture had a higher prevalence of current smoking and previous fracture, but lower prevalence of dementia, cancer, cardiovascular disease, renal disease, and diabetes. INTERPRETATION: CFracture has similar discrimination to QFracture but is better calibrated overall and in younger people. Both models performed poorly in adults aged 85 years and older. Competing risk models should be recommended for fracture risk prediction to guide treatment recommendations. FUNDING: National Institute for Health and Care Research, Wellcome Trust, Health Data Research UK.

Free-text analysis of general practice out-of-hours (GPOOH) use by people with advanced cancer: an analysis of coded and uncoded free-text data.

BACKGROUND: People with advanced cancer frequently use the GP out-of-hours (GPOOH) service. Considerable amounts of routine GPOOH data are uncoded. Therefore, these data are omitted from existing healthcare datasets. AIM: To conduct a free-text analysis of a GPOOH dataset, to identify reasons for attendance and care delivered through GPOOH to people with advanced cancer. DESIGN AND SETTING: An analysis of a GPOOH healthcare dataset was undertaken. It contained all coded and free- text information for 5749 attendances from a cohort of 2443 people who died from cancer in Tayside, Scotland, from 2013-2015. METHOD: Random sampling methods selected 575 consultations for free-text analysis. Each consultation was analysed by two independent reviewers to determine the following: assigned presenting complaints; key and additional palliative care symptoms recorded in free text; evidence of anticipatory care planning; and free-text recording of dispensed medications. Inter-rater reliability concordance was established through Kappa testing. RESULTS: More than half of all coded reasons for attendance (n = 293; 51.0%) were 'other' or 'missing'. Free-text analysis demonstrated that nearly half (n = 284; 49.4%) of GPOOH attendances by people with advanced cancer were for pain or palliative care. More than half of GPOOH attendances (n = 325; 56.5%) recorded at least one key or additional palliative care symptom in free text, with the commonest being breathlessness, vomiting, cough, and nausea. Anticipatory care planning was poorly recorded in both coded and uncoded records. Uncoded medications were dispensed in more than one- quarter of GPOOH consultations. CONCLUSION: GPOOH delivers a substantial amount of pain management and palliative care, much of which is uncoded. Therefore, it is unrecognised and under-reported in existing large healthcare data analyses.

Community prescribing trends and prevalence in the last year of life, for people who die from cancer.

BACKGROUND: People who die from cancer ('cancer decedents') may latterly experience unpleasant and distressing symptoms. Prescribing medication for pain and symptom control is essential for good-quality palliative care; however, such provision is variable, difficult to quantify and poorly characterised in current literature. This study aims to characterise trends in prescribing analgesia, non-analgesic palliative care medication and non-palliative medications, to cancer decedents, in their last year of life, and to assess any associations with demographic or clinical factors. METHODS: This descriptive study, analysed all 181,247 prescriptions issued to a study population of 2443 cancer decedents in Tayside, Scotland (2013-2015), in the last year of life, linking prescribing data to demographic, and cancer registry datasets using the unique patient-identifying Community Health Index (CHI) number. Anonymised linked data were analysed in Safe Haven using chi-squared test for trend, binary logistic regression and Poisson regression in SPSSv25. RESULTS: In their last year of life, three in four cancer decedents were prescribed strong opioids. Two-thirds of those prescribed opioids were also prescribed laxatives and/or anti-emetics. Only four in ten cancer decedents were prescribed all medications in the 'Just in Case' medication categories and only one in ten was prescribed breakthrough analgesia in the last year of life. The number of prescriptions for analgesia and palliative care drugs increased in the last 12 weeks of life. The number of prescriptions for non-palliative care medications, including anti-hypertensives, statins and bone protection, decreased over the last year, but was still substantial. Cancer decedents who were female, younger, or had lung cancer were more likely to be prescribed strong opioids; however, male cancer decedents had higher odds of being prescribed breakthrough analgesia. Cancer decedents who had late diagnoses had lower odds of being prescribed strong opioids. CONCLUSIONS: A substantial proportion of cancer decedents were not prescribed strong opioids, breakthrough medication, or medication to alleviate common palliative care symptoms (including 'Just in Case' medication). Many patients continued to be prescribed non-palliative care medications in their last days and weeks of life. Age, gender, cancer type and timing of diagnosis affected patients' odds of being prescribed analgesic and non-analgesic palliative care medication.

Patient outcomes following AKI and AKD: a population-based cohort study.

BACKGROUND: Acute kidney injury (AKI) is common and associated with adverse outcomes as well as important healthcare costs. However, evidence examining the epidemiology of acute kidney disease (AKD)-recently defined as AKI persisting between 7 and 90 days-remains limited. The aims of this study were to establish the rates of early AKI recovery, progression to AKD and non-recovery; examine risk factors associated with non-recovery and investigate the association between recovery timing and adverse outcomes, in a population-based cohort. METHODS: All adult residents of Tayside & Fife, Scotland, UK, with at least one episode of community or hospital-managed AKI using KDIGO creatinine-based definition during the period 1 January 2010 to 31 December 2018 were identified. Logistic regression was used to examine factors associated with non-recovery, and Cox modelling was used to establish associations between AKI recovery timing and risks of mortality and development of de novo CKD. RESULTS: Over 9 years, 56,906 patients with at least one AKI episode were identified with 18,773 (33%) of these progressing to AKD. Of those progressing to AKD, 5059 (27%) had still not recovered at day 90 post AKI diagnosis. Risk factors for AKD included: increasing AKI severity, pre-existing cancer or chronic heart failure and recent use of loop diuretics. Compared with early AKI recovery, progression to AKD was associated with increased hazard of 1-year mortality and de novo CKD (HR = 1.20, 95% CI 1.13 to 1.26 and HR = 2.21, 95% CI 1.91 to 2.57 respectively). CONCLUSIONS: These findings highlight the importance of early AKI recognition and management to avoid progression to AKD and long-term adverse outcomes.

Predictive performance of a competing risk cardiovascular prediction tool CRISK compared to QRISK3 in older people and those with comorbidity: population cohort study.

BACKGROUND: Recommended cardiovascular disease (CVD) prediction tools do not account for competing mortality risk and over-predict incident CVD in older and multimorbid people. The aim of this study was to derive and validate a competing risk model (CRISK) to predict incident CVD and compare its performance to that of QRISK3 in UK primary care. METHODS: We used UK linked primary care data from the Clinical Practice Research Datalink (CPRD) GOLD to identify people aged 25-84 years with no previous CVD or statin treatment split into derivation and validation cohorts. In the derivation cohort, we derived models using the same covariates as QRISK3 with Fine-Gray competing risk modelling alone (CRISK) and with Charlson Comorbidity score (CRISK-CCI) as an additional predictor of non-CVD death. In a separate validation cohort, we examined discrimination and calibration compared to QRISK3. Reclassification analysis examined the number of patients recommended for treatment and the estimated number needed to treat (NNT) to prevent a new CVD event. RESULTS: The derivation and validation cohorts included 989,732 and 494,865 women and 946,784 and 473,392 men respectively. Overall discrimination of CRISK and CRISK-CCI were excellent and similar to QRISK3 (for women, C-statistic = 0.863/0.864/0.863 respectively; for men 0.833/0.819/0.832 respectively). CRISK and CRISK-CCI calibration overall and in younger people was excellent. CRISK over-predicted in older and multimorbid people although performed better than QRISK3, whilst CRISK-CCI performed the best. The proportion of people reclassified by CRISK-CCI varied by QRISK3 risk score category, with 0.7-9.7% of women and 2.8-25.2% of men reclassified as higher risk and 21.0-69.1% of women and 27.1-57.4% of men reclassified as lower risk. Overall, CRISK-CCI recommended fewer people for treatment and had a lower estimated NNT at 10% risk threshold. Patients reclassified as higher risk were younger, had lower SBP and higher BMI, and were more likely to smoke. CONCLUSIONS: CRISK and CRISK-CCI performed better than QRISK3. CRISK-CCI recommends fewer people for treatment and has a lower NNT to prevent a new CVD event compared to QRISK3. Competing risk models should be recommended for CVD primary prevention treatment recommendations.

Death from cancer: frequent unscheduled care.

OBJECTIVE: To examine the demographic, clinical, and temporal factors associated with cancer decedents being a frequent or very frequent unscheduled care (GP-general practice Out-Of-Hours (GPOOH) and Accident & Emergency (A&E)) attender, in their last year of life. METHODS: Retrospective cohort study, of all 2443 cancer decedents in Tayside, Scotland, over 30- months period up to 06/2015, comparing frequent attenders (5-9 attendances/year) and very frequent attenders (≥10 attendances/year) to infrequent attenders (1-4 attendances/year) and non-attenders. Clinical and demographic datasets were linked to routinely-collected clinical data using the Community Health Index number. Anonymised linked data were analysed in SafeHaven, using binary/multinomial logistic regression, and Generalised Estimating Equations analysis. RESULTS: Frequent attenders were more likely to be older, and have upper gastrointestinal (GI), haematological, breast and ovarian malignancies, and less likely to live in accessible areas or have a late cancer diagnosis. They were more likely to use GPOOH than A&E, less likely to have face-to-face unscheduled care attendances, and less likely to be admitted to hospital following unscheduled care attendance. CONCLUSIONS: Age, cancer type, accessibility and timing of diagnosis relative to death were associated with increased likelihood of being a frequent or very frequent attender at unscheduled care.

Effect of perindopril or leucine on physical performance in older people with sarcopenia: the LACE randomized controlled trial.

BACKGROUND: This trial aimed to determine the efficacy of leucine and/or perindopril in improving physical function in older people with sarcopenia. METHODS: Placebo-controlled, parallel group, double-blind, randomized two-by-two factorial trial. We recruited adults aged ≥ 70 years with sarcopenia, defined as low gait speed (<0.8 m/s on 4 m walk) and/or low handgrip strength (women < 20 kg, men < 30 kg) plus low muscle mass (using sex and body mass index category-specific thresholds derived from normative UK BioBank data) from 14 UK centres. Eligible participants were randomized to perindopril 4 mg or placebo, and to oral leucine powder 2.5 g or placebo thrice daily. The primary outcome was the between-group difference in the short physical performance battery (SPPB) score over 12-month follow-up by repeated-measures mixed models. Results were combined with existing systematic reviews using random-effects meta-analysis to derive summary estimates of treatment efficacy. RESULTS: We screened 320 people and randomized 145 participants compared with an original target of 440 participants. For perindopril [n = 73, mean age 79 (SD 6), female sex 39 (53%), mean SPPB 7.1 (SD 2.3)] versus no perindopril [n = 72, mean age 79 (SD 6), female sex 39 (54%), mean SPPB 6.9 (SD 2.4)], median adherence to perindopril was lower (76% vs. 96%; P < 0.001). Perindopril did not improve the primary outcome [adjusted treatment effect -0.1 points (95%CI -1.2 to 1.0), P = 0.89]. No significant treatment benefit was seen for any secondary outcome including muscle mass [adjusted treatment effect -0.4 kg (95%CI -1.1 to 0.3), P = 0.27]. More adverse events occurred in the perindopril group (218 vs. 165), but falls rates were similar. For leucine [n = 72, mean age 78 (SD 6), female sex 38 (53%), mean SPPB 7.0 (SD 2.1)] versus no leucine [n = 72, mean age 79 (SD 6), female sex 40 (55%), mean SPPB 7.0 (SD 2.5)], median adherence was the same in both groups (76% vs. 76%; P = 0.99). Leucine did not improve the primary outcome [adjusted treatment effect 0.1 point (95%CI -1.0 to 1.1), P = 0.90]. No significant treatment benefit was seen for any secondary outcome including muscle mass [adjusted treatment effect -0.3 kg (95%CI -1.0 to 0.4), P = 0.47]. Meta-analysis of angiotensin converting enzyme inhibitor/angiotensin receptor blocker trials showed no clinically important treatment effect for the SPPB [between-group difference -0.1 points (95%CI -0.4 to 0.2)]. CONCLUSIONS: Neither perindopril nor leucine improved physical performance or muscle mass in this trial; meta-analysis did not find evidence of efficacy of either ACE inhibitors or leucine as treatments to improve physical performance.

Effect of competing mortality risks on predictive performance of the QFracture risk prediction tool for major osteoporotic fracture and hip fracture: external validation cohort study in a UK primary care population.

Objective: To externally evaluate the QFracture risk prediction tool for predicting the risk of major osteoporotic fracture and hip fracture. Design: External validation cohort study. Setting: UK primary care population. Linked general practice (Clinical Practice Research Datalink (CPRD) Gold), mortality registration (Office of National Statistics), and hospital inpatient (Hospital Episode Statistics) data, from 1 January 2004 to 31 March 2016. Participants: 2 747 409 women and 2 684 730 men, aged 30-99 years, with up-to-standard linked data that had passed CPRD checks for at least one year. Main outcome measures: Two outcomes were modelled based on the QFracture: major osteoporotic fracture and hip fracture. Major osteoporotic fracture was defined as any hip, distal forearm, proximal humerus, or vertebral crush fracture, from general practice, hospital discharge, and mortality data. The QFracture 10 year predicted risk of major osteoporotic fracture and hip fracture was calculated, and performance evaluated versus observed 10 year risk of fracture in the whole population, and in subgroups based on age and comorbidity. QFracture calibration was examined accounting for, and not accounting for, competing risk of mortality from causes other than the major osteoporotic fracture. Results: 2 747 409 women with 95 598 major osteoporotic fractures and 36 400 hip fractures, and 2 684 730 men with 34 321 major osteoporotic fractures and 13 379 hip fractures were included in the analysis. The incidence of all fractures was higher than in the QFracture internal derivation. Competing risk of mortality was more common than fracture from middle age onwards. QFracture discrimination in the whole population was excellent or good for major osteoporotic fracture and hip fracture (Harrell's C statistic in women 0.813 and 0.918, and 0.738 and 0.888 in men, respectively), but was poor to moderate in age subgroups (eg, Harrell's C statistic in women and men aged 85-99 years was 0.576 and 0.624 for major osteoporotic fractures, and 0.601 and 0.637 for hip fractures, respectively). Without accounting for competing risks, QFracture systematically under-predicted the risk of fracture in all models, and more so for major osteoporotic fracture than for hip fracture, and more so in older people. Accounting for competing risks, QFracture still under-predicted the risk of fracture in the whole population, but over-prediction was considerable in older age groups and in people with high comorbidities at high risk of fracture. Conclusions: The QFracture risk prediction tool systematically under-predicted the risk of fracture (because of incomplete determination of fracture rates) and over-predicted the risk in older people and in those with more comorbidities (because of competing mortality). The use of QFracture in its current form needs to be reviewed, particularly in people at high risk of death from other causes.

A pre-operative prognostic model predicting all cause and cause specific mortality for women presenting with invasive breast cancer.

PURPOSE: The aim of this study is to develop a pre-operative prognostic model based on known pre-operative factors. METHODS: A database of ultrasound (US) lesions undergoing biopsy documented US lesion size, stiffness, and patient source prospectively. Women with invasive cancer presenting between 2010 and 2015 were the study group. Breast and axillary core results and ER, PR and HER receptor status were collected prospectively. Assessment of US skin thickening, US distal enhancement and presence of chronic kidney disease (CKD) was performed retrospectively. Patient survival and cause of death were ascertained from computer records. Predictive models for (i) all-cause mortality (ACM) and (ii) breast cancer death (BCD) were built and then validated using bootstrap k-fold cross-validation. A comparison of predictive performance was made between a full cause-specific Cox model, a sub cause-specific Cox model, and a full Fine-Gray sub-distribution hazard model. RESULTS: 1136 patients were included in the study. The median follow-up time was 6.2 years. 125 (11%) women died from breast cancer and 155 (14%) died from other causes. For the prediction of BCD, the cause-specific Cox sub-model performed the best. The time dependent AUC begins above 0.91 in year one to 3 reducing to 0.83 in year 6. The factors included in the Cox sub model were tumour size, skin thickening, source of detection, tumour grade, ER status, pre-operative nodal metastasis and CKD. CONCLUSION: We have shown that a model based on preoperative factors can predict BCD. Such prediction if externally validated and incorporating treatment data could be useful for treatment planning and patient counselling.

Cue-based versus scheduled feeding for preterm infants transitioning from tube to oral feeding: the Cubs mixed-methods feasibility study.

BACKGROUND: There is a lack of evidence of the effect of cue-based feeding compared with scheduled feeding on important outcomes for preterm infants. OBJECTIVES: The objectives were as follows: (1) to describe the characteristics, components, theoretical basis and outcomes of approaches to feeding preterm infants transitioning from tube to oral feeding; (2) to identify operational policies, barriers and facilitators, and staff and parents' educational needs in neonatal units implementing cue-based feeding; (3) to co-produce an intervention for feeding preterm infants in response to feeding cues; (4) to appraise the willingness of parents and staff to implement and sustain the intervention; (5) to assess associated costs of implementing cue-based feeding; (6) to determine the feasibility and acceptability of a future trial; (7) to scope existing data-recording systems and potential outcome measures; and (8) to determine stakeholders' views of whether or not a randomised controlled trial of this approach is feasible. DESIGN: This was a mixed-methods intervention development and feasibility study comprising (1) a systematic review, case studies, qualitative research and stakeholder consensus; (2) the co-production of the intervention; (3) a mixed-methods feasibility study; and (4) an assessment of stakeholder preferences for a future evaluation. SETTING: Three neonatal units in the UK (two level 3 units and one level 2 unit). PARTICIPANTS: Developmentally normal, clinically stable preterm infants receiving enteral feeds (n = 50), parents (n = 15 pre intervention development; n = 14 in the feasibility study) and health-care practitioners (n = 54 pre intervention development; n = 16 in the feasibility study). INTERVENTION: An evidence-informed multicomponent intervention comprising training, a feeding protocol, feeding assessment tools, supplementary training materials [including posters, a film and a narrated PowerPoint (Microsoft Corporation, Redmond, WA, USA) presentation] and the 'Our Feeding Journey' document. MAIN OUTCOME MEASURES: The main outcome measures were recruitment and screening rates, infant weight gain, duration of the intervention, feeding outcomes, implementation outcomes (contextual facilitators and barriers, acceptability, adoption, appropriateness and fidelity) and stakeholder preferences for a future evaluation. RESULTS: The systematic review of 25 studies concluded that evidence in favour of cue-based feeding should be treated cautiously. The case studies and qualitative research highlighted contextual barriers to and facilitators of the implementation of cue-based feeding. The telephone survey found that many neonatal units are considering implementing cue-based feeding. We recruited 37% of eligible infants, and there was good retention in the study until discharge but a high loss to follow-up at 2 weeks post discharge. The mean number of days from intervention to transition to full oral feeding was 10.8, and the mean daily change in weight gain was 25 g. The intervention was acceptable to parents and staff, although there was dissatisfaction with the study documentation. Intervention training did not reach all staff. A cluster-randomised design with a composite outcome was suggested by stakeholders for a future study. LIMITATIONS: The intervention was available only in English. Intervention training did not reach all staff. There was low recruitment to qualitative interviews and observations. Only a small number of medical staff engaged in either the training or the interviews. CONCLUSIONS: It is feasible to implement a cue-based feeding intervention with improved training and documentation. Further work is needed to assess the feasibility of a future trial, noting evidence of existing lack of equipoise. FUTURE WORK: The next steps are to digitalise the intervention and conduct a survey of all neonatal units in the UK. STUDY REGISTRATION: This study is registered as PROSPERO CRD42018097317 and ISRCTN13414304. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 74. See the NIHR Journals Library website for further project information.

Preterm babies who are ready to progress from tube feeding to oral feeding are usually fed according to a fixed schedule. Scheduled feeding protocols set a minimum corrected gestational age at which oral feeding may commence, and specify the rate of change from tube to oral feeding. Scheduled feeding also sets the volume and timing of each feed. A few small studies show that feeding babies according to their cues might have benefits for them and their parents; for example, babies may be discharged from hospital sooner. Cue-based feeding may help parents to understand the needs of their baby and be more involved in their care. Examples of hunger cues are mouthing movements, bringing hands to mouth and sucking. Examples of stop cues are falling asleep and stopping sucking. We developed a cue-based feeding intervention and tested it in three neonatal units to see if a large trial could be done and if parents and staff liked the intervention. We reviewed previous research, visited three hospitals that use cue-based feeding and interviewed parents and staff about their experiences of feeding preterm babies. We developed the intervention with parents and staff. The intervention included a feeding protocol, training for parents and staff, and a feeding record. Parents and staff liked most parts of the intervention. The training did not reach all staff, and staff and parents found it time-consuming to record every feed. Many parents and staff thought that cue-based feeding was better for babies, and parents thought that neonatal units should change to cue-based feeding. We discussed our findings with parents, staff and research experts. Based on their ideas, we recommend that the intervention is developed into an app (application) and that all neonatal units in the UK are surveyed to find out if they use cue-based feeding and if they would agree to be part of a large trial.

Real time remote symptom monitoring during chemotherapy for cancer: European multicentre randomised controlled trial (eSMART).

OBJECTIVE: To evaluate effects of remote monitoring of adjuvant chemotherapy related side effects via the Advanced Symptom Management System (ASyMS) on symptom burden, quality of life, supportive care needs, anxiety, self-efficacy, and work limitations. DESIGN: Multicentre, repeated measures, parallel group, evaluator masked, stratified randomised controlled trial. SETTING: Twelve cancer centres in Austria, Greece, Norway, Republic of Ireland, and UK. PARTICIPANTS: 829 patients with non-metastatic breast cancer, colorectal cancer, Hodgkin's disease, or non-Hodgkin's lymphoma receiving first line adjuvant chemotherapy or chemotherapy for the first time in five years. INTERVENTION: Patients were randomised to ASyMS (intervention; n=415) or standard care (control; n=414) over six cycles of chemotherapy. MAIN OUTCOME MEASURES: The primary outcome was symptom burden (Memorial Symptom Assessment Scale; MSAS). Secondary outcomes were health related quality of life (Functional Assessment of Cancer Therapy-General; FACT-G), Supportive Care Needs Survey Short-Form (SCNS-SF34), State-Trait Anxiety Inventory-Revised (STAI-R), Communication and Attitudinal Self-Efficacy scale for cancer (CASE-Cancer), and work limitations questionnaire (WLQ). RESULTS: For the intervention group, symptom burden remained at pre-chemotherapy treatment levels, whereas controls reported an increase from cycle 1 onwards (least squares absolute mean difference -0.15, 95% confidence interval -0.19 to -0.12; P<0.001; Cohen's D effect size=0.5). Analysis of MSAS sub-domains indicated significant reductions in favour of ASyMS for global distress index (-0.21, -0.27 to -0.16; P<0.001), psychological symptoms (-0.16, -0.23 to -0.10; P<0.001), and physical symptoms (-0.21, -0.26 to -0.17; P<0.001). FACT-G scores were higher in the intervention group across all cycles (mean difference 4.06, 95% confidence interval 2.65 to 5.46; P<0.001), whereas mean scores for STAI-R trait (-1.15, -1.90 to -0.41; P=0.003) and STAI-R state anxiety (-1.13, -2.06 to -0.20; P=0.02) were lower. CASE-Cancer scores were higher in the intervention group (mean difference 0.81, 0.19 to 1.43; P=0.01), and most SCNS-SF34 domains were lower, including sexuality needs (-1.56, -3.11 to -0.01; P<0.05), patient care and support needs (-1.74, -3.31 to -0.16; P=0.03), and physical and daily living needs (-2.8, -5.0 to -0.6; P=0.01). Other SCNS-SF34 domains and WLQ were not significantly different. Safety of ASyMS was satisfactory. Neutropenic events were higher in the intervention group. CONCLUSIONS: Significant reduction in symptom burden supports the use of ASyMS for remote symptom monitoring in cancer care. A "medium" Cohen's effect size of 0.5 showed a sizable, positive clinical effect of ASyMS on patients' symptom experiences. Remote monitoring systems will be vital for future services, particularly with blended models of care delivery arising from the covid-19 pandemic. TRIAL REGISTRATION: Clinicaltrials.gov NCT02356081.