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Abstract 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 85 years had higher odds of late diagnosis (95%CI OR3.45 (OR2.63 to 4.55)), compared to those aged

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. Plain language summary 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. Scientific summary Background Clinical guidelines help define and disseminate best practice. Guidelines increasingly use risk prediction tools to help target primary preventative treatments at people at highest risk. In National Institute for Health and Care Excellence (NICE) guidelines, the choice of risk threshold is commonly informed by model-based cost-effectiveness analyses (CEAs) for different levels of baseline risk. Risk prediction modelling and model-based CEA are therefore increasingly important for developing guidelines that recommend long-term preventative medicines, including primary prevention of cardiovascular disease (CVD) using statins and prevention of osteoporotic fracture using bisphosphonates. Risk prediction and competing mortality risk Most risk prediction models do not account for competing mortality risk, which is when someone dies of another condition (e.g. lung cancer) before experiencing the event being predicted (e.g. CVD or fracture). This can lead to overprediction of event rates among older people and those with multimorbidity. Model-based cost-effectiveness analysis Competing mortality risk is accounted for in model-based CEA, but whole-population estimates of competing mortality will not be correct at all levels of risk of CVD and fracture. Existing models also do not account for all harms, notably direct treatment disutility (DTD), which is the disutility arising from the hassles of taking treatments. Even small levels of DTD can be enough to outweigh relatively small lifetime benefits of primary prevention medication, but, to our knowledge, DTD impact has not been systematically estimated previously. Aim and objectives The overall aim was to improve the evidence generated from risk prediction models and model-based CEAs to inform decision-making for selecting primary prevention treatments for CVD and osteoporotic fracture. The prespecified objectives were to: externally validate the recommended risk prediction tools for primary prevention of CVD [QRISK®3 (ClinRisk Ltd, Leeds, UK)] and for osteoporotic fracture [QFracture-2012 (ClinRisk Ltd)] derive and internally validate new CVD and osteoporotic fracture risk prediction models accounting for competing risks of death externally validate the QRISK-Lifetime CVD risk prediction tool quantify the magnitude, variation and distribution of DTD in the general population and among people treated with statins or bisphosphonates examine the effect of accounting for competing risks and DTD on cost-effectiveness in the context of statins and bisphosphonates for the primary prevention of CVD and osteoporotic fracture, respectively. The prediction modelling protocol was approved by the Clinical Practice Research Datalink (CPRD) Independent Scientific Advisory Committee (reference number 16_248). The Health Research Authority approved the DTD elicitation study (Integrated Research Application System: 220,492) and granted ethics approval (Research Ethics Committee: 17/NW/0124). A systematic review for CEA model parameters was registered with PROSPERO (CRD42021249959). Methods Objective 1 methods For CVD modelling, CPRD GOLD data were used to define a cohort aged 25–84 years without CVD or prior statin prescription. The outcome was incident CVD. Multiple imputation was used to account for missing data. The performance of the published QRISK3–2017 model was evaluated in terms of discrimination (the ability of a tool to distinguish between those with and those without an event) and calibration (whether or not predicted risk is the same as observed risk) in the whole population, stratified by age and Charlson Comorbidity Index (CCI), and in subgroups with type 1 diabetes, type 2 diabetes and chronic kidney disease (CKD). Observed risk was estimated with and without accounting for competing risk (using Aalen–Johansen and Kaplan–Meier estimators, respectively). For fracture modelling, the cohort was aged 30–99 years (prior fracture or bisphosphonate treatment were allowed) with follow-up to specified fracture, death from non-fracture causes, deregistration or end of study. Two outcomes were defined: major osteoporotic fracture (MOF) and hip fracture. QFracture-2012 performance was evaluated as for QRISK3. For both cohorts, the earliest study entry date was 1 January 2004 and the end of the study was 31 March 2016. Objective 2 methods Using the same data set as objective 1, participants were randomly allocated to derivation and test data sets in a 2 : 1 ratio. For CVD, two Fine–Gray models were derived in the derivation data set and internally validated in the test data set, alongside QRISK3. The competing mortality risk model (CRISK) accounted for competing mortality only, whereas the competing mortality risk model with Charlson Comorbidity Index (CRISK-CCI) also included the modified CCI as a predictor. Model performance was examined using discrimination and calibration. For fracture, separate Fine–Gray models (CFracture) were estimated for MOF and hip fracture. Objective 3 methods The same data were used as for objective 1, but with the age range restricted to 30–84 years to match QRISK®-Lifetime (ClinRisk Ltd). As lifetime risk is not observed in this data set, model performance was evaluated at 10 years, and reclassification examined the characteristics of those recommended for treatment on the basis of a QRISK3 10-year risk of > 10%, a QRISK-Lifetime 10-year risk of > 10% and the QRISK-Lifetime highest risk, with thresholds chosen to recommend the same number of people for treatment as with QRISK3 > 10%. Objective 4 methods Two groups of participants were recruited to studies to elicit DTD of preventative statins and bisphosphonates: people with direct experience of taking one of the medicines and a sample of the general population. We described the process of taking each medicine (one tablet per day for statins, one tablet per week taken on an empty stomach with a requirement to stay upright for at least 30 minutes for bisphosphonates). Elicitation used time trade-off (TTO) (primary analysis) and best–worst scaling (BWS) (exploratory analysis) surveys iteratively developed using think-aloud interviews with 19 patients, and online pilot studies. Objective 5 methods For statins for the primary prevention of CVD, we modified the cohort-level decision-analytic model used in NICE’s lipid modification guideline [NICE. Lipid Modification: Cardiovascular Risk Assessment and the Modification of Blood Lipids for the Primary and Secondary Prevention of Cardiovascular Disease. Clinical Guideline (CG181). Methods, Evidence and Recommendations. July 2014. URL: https://web.archive.org/web/20220201050407/https://www.nice.org.uk/guidance/cg181/evidence/lipid-modification-update-full-guideline-pdf-243786637 (accessed 12 October 2022)]. General updates included rapid reviews to identify utility values and costs associated with CVD events, new regressions to predict baseline quality of life for people without CVD (based on Health Survey for England data) and type of first CVD event (based on data from objective 1), and inputs (costs, life expectancy) were updated to present-day values. For bisphosphonates for the prevention of fracture, we used the discrete-event simulation developed for NICE’s Technology Appraisal 464 [NICE. Bisphosphonates for Treating Osteoporosis. Technology Appraisal Guidance (TA464). London: NICE; 2017]. For both models, we explored competing risk by parameterising probability of non-cause-specific death using relative survival models adjusting for predicted risk (QRISK3 or QFracture-2012). We incorporated DTD as elicited in objective 4 under three assumptions (lifelong, time limited, diminishing over time). We explored how these factors alone or in combination affect the estimated value of the preventative medicines in terms of cost per quality-adjusted life-year (QALY). Results Objectives 1 and 2: predicting cardiovascular disease Discrimination of QRISK3 in the whole external validation cohort was excellent (Harrell’s c = 0.865 for women, 0.834 for men), and comparable to the previous internal validation. However, discrimination was worse among people with more comorbidity, and was poor to moderate among older people (e.g. c = 0.611 for women and 0.585 for men aged 75–84 years). Calibration in the whole population, ignoring competing risks, was very good, with minor overprediction. There was larger overprediction among older people, which was considerable after accounting for competing risks. Among people with type 1 diabetes, discrimination was excellent (c = 0.830 for women, 0.853 for men). There was evidence of overprediction at higher levels of predicted risk, which was larger after accounting for competing risks, although most overprediction happened well above the NICE 10% threshold for offering treatment. Discrimination among people with CKD was only moderate (women, c = 0.705; men, c = 0.671), but calibration was reasonable at recommended treatment thresholds. The new competing risk model (CRISK-CCI) had similar discrimination to QRISK3 in the whole population (women, c = 0.864; men, c = 0819), with the same pattern of worse discrimination among older people and those with more comorbidity. Calibration was systematically better than QRISK3, although, as with QRISK3, there was overprediction in some subgroups with high predicted risk. Objectives 1 and 2: predicting fracture Observed age-stratified incidences of both MOF and hip fracture were considerably higher in this study than in a previous external validation, which was partly explained by the use of hospital data in this study to ascertain fractures. Discrimination of QFracture-2012 in external validation was excellent among women (MOF, c = 0.813; hip fracture, c = 0.918) and good to excellent among men (MOF, c = 0.738; hip fracture, c = 0.888), similar to QFracture-2012 internal validation, but had poor to moderate discrimination among older people. Ignoring competing risks, QFracture-2012 showed serious underprediction in the whole population and in all subgroups of age and comorbidity, which was worse for hip fracture than for MOF. Accounting for competing risks reduced observed underprediction in the whole population, but there was very major overprediction among older people and at higher levels of predicted risk among people with more comorbidity. The new competing risk model (CFracture) had similar discrimination to QFracture-2012 in the internal validation cohort (women: c = 0.813 for MOF, c = 0.914 for hip fracture; men: c = 0.734 for MOF, c = 0.883 for hip fracture). CFracture was better calibrated than QFracture-2012 but showed overprediction at higher levels of predicted risk for MOF (both sexes) and for hip fracture (among men). CFracture calibration was poor among people aged 85–99 years for both outcomes. Objective 3: predicting lifetime cardiovascular disease risk Evaluated at 10 years’ follow-up, QRISK-Lifetime had excellent discrimination (women, c = 0.844; men, c = 0.808) in the whole population, with the same pattern as QRISK3 and CRISK-CCI of worse discrimination among older people and those with high comorbidity. QRISK-Lifetime underpredicted 10-year risk among people at higher predicted risk, particularly older people, implying that estimated lifetime risk will be underpredicted. A total of 5.3% of participants were recommended for treatment by both QRISK3 and QRISK-Lifetime, and 27.4% by one or the other, but not both. Participants recommended for treatment by QRISK-Lifetime were younger than those recommended by QRISK3 (mean age: women, 50.5 vs. 71.3 years, respectively; men, 46.3 vs. 63.8 years, respectively), were much more likely to have a strong family history of CVD (women: 36.3% vs. 6.3%, respectively; men: 20.0% vs. 7.2%, respectively) and had many fewer observed events during the 10-year follow-up (women with a CVD event: 4.0% vs. 11.9%, respectively; men with a CVD event: 4.3% vs. 10.8%, respectively). Objective 4: direct treatment disutility elicitation When measured by TTO, long-term statin use was associated with mean DTD of 0.034 among people willing to take statins; the equivalent number for bisphosphonates was significantly greater, at 0.067. The findings from the BWS experiment had face validity in that inconvenience influenced preferences. However, the estimated values for DTD are implausibly large. Consistent with previous studies, these findings suggest three distinct preference phenotypes: some people would avoid taking the medicines at all costs, some people see no problem with them and some people are willing to trade length of life to avoid treatment. The first group are unlikely to initiate treatment and the second group do not anticipate DTD; in the third group, depending on the individual’s strength of preference to avoid treatment and the magnitude of expected QALY gains from prevention, DTD may imply that a preventative medicine’s negative characteristics outweigh its benefits. Objective 5: model-based cost-effectiveness analysis General updates to the CVD model made high-intensity statins more cost-effective for primary prevention. Introducing accurate adjustment for competing risk of non-CVD death had the expected effect: more QALYs among people with below-average CVD risk for their sex and age (who experience lower rates of other-cause mortality) and fewer QALYs among people with above-average risk (whose non-CVD life expectancy is attenuated). However, the impact on incremental cost-effectiveness is minor, and statins remain almost universally cost-effective. Incorporating DTD has a more obvious effect, especially when we assume that it applies undiminished for as long as people take statins for primary prevention. Under that circumstance, the threshold at which expected long-term benefits outweigh DTD-related harm rises with age: for a 40-year-old, a 10-year risk of ≥ 8% would be enough to make treatment net beneficial whereas, for an 80-year-old, that figure rises to 38%. The model assessing bisphosphonates for the primary prevention of osteoporotic fragility fracture shows that we overestimate value for money among people at the highest risk if we do not adjust for competing risk of non-fracture death. However, this generally affects only the magnitude of expected net benefit among people for whom some degree of benefit is expected. Even among people at highest risk of fracture, average QALY gains associated with bisphosphonates are small and swamped by DTD of any duration. Consequently, it is impossible to identify any group of people for whom oral bisphosphonates represent an effective use of NHS resources, if we assume population-level average DTD for everyone to whom the decision applies. Conclusions Implications for healthcare Ignoring competing mortality in risk prediction overestimates the risk of CVD and fracture among older people and those with multimorbidity, which will lead to overestimation of the benefits of treatment. This affects fracture risk prediction more than CVD because CVD is a more substantial proportion of total mortality. The QFracture-2012 prediction tool simultaneously underestimates fracture risk among people without high competing mortality risk, partly because it did not include fractures recorded only in hospital data in its derivation. CVD and fracture risk prediction are improved by accounting for competing mortality risks, and transparency of the tools would be improved by fully publishing the codes used to define events and predictors. We have demonstrated an effective method of making accurate adjustment for competing risk of non-cause-specific death in decision-analytic CEAs. Although it made relatively little difference to the estimated cost-effectiveness of preventative interventions in the examples we explored, we have shown that it could potentially be important. Therefore, we recommend that modellers consider this issue when designing analyses of preventative treatments. Although we have demonstrated that DTD exists and has the potential to alter the balance of benefits and harms for preventative treatments, we do not recommend that population-level average DTD is incorporated in base-case CEAs. Rather, we recommend that decision-makers review scenarios with and scenarios without DTD and highlight its possible impact, enabling prescribers to engage in shared decision-making that gives appropriate weight to individual preferences. Research recommendations The excellent discrimination of QRISK3 and QFracture-2012 arises from including a very broad range of ages, but discrimination and calibration in subgroups are less good. Comparing models created in smaller age groups with whole-population models would be useful. Mortality is only one competing risk, and older people and those with multimorbidity are at risk of many different events. It is important to develop models that better account for multiple important events. Cost-effectiveness analysis of statins for the primary prevention of CVD could usefully be further modified to (1) enable stratification according to specific coexisting long-term conditions, (2) account for likely adherence to statins in practice and (3) update secondary transitions reflecting the subsequent natural history of CVD among people experiencing events. Future CEAs of bisphosphonates for the primary prevention of osteoporotic fragility fracture should explore different fracture risk prediction models, and use those based on demonstrable good ascertainment of fractures and accounting for competing mortality risk. 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.

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.

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.

Objective To externally evaluate the QFracture-2012 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 those predicted by 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-2012 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-2012 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-2012 internal derivation. Competing risk of mortality was more common than fracture from middle age onwards. QFracture-2012 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-2012 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-2012 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-2012 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 current version of QFracture-2016 that is used by the UK's health service needs to be externally validated, particularly in people at high risk of death from other causes.

Abstract Background There is growing evidence suggesting that multiparametric magnetic resonance imaging (mpMRI) is a marker for prostate cancer (PCa) aggressiveness and could be used to plan treatment. Improving early detection of clinically significant PCa with pre-biopsy mpMRI would very likely have advantages including optimising the diagnosis and treatment of diseases and diminishing patient anxiety. Methods and materials This is a prospective multicentre study of pre-biopsy mpMRI diagnostic test accuracy with subgroup randomisation at a 1:1 ratio with respect to transrectal ultrasound (TRUS) and MRI/US fusion-guided biopsy or TRUS-only biopsy. It is designed as a single-gate study with a single set of inclusion criteria. The total duration of the recruitment phase was 48 months; however, this has now been extended to 66 months. A sample size of 600 participants is required. Discussion The primary objective is to determine whether mpMRI can improve PCa detection and characterisation. The key secondary objective is to determine whether MRI/US fusion-guided biopsy can reduce the number of false-negative biopsies. Ethical approval was obtained from the East of Scotland Research Ethics Committee 1 (14/ES/1070) on 20 November 2014. The results of this study will be used for publication and presentation in national and international journals and at scientific conferences. Trial registration ClinicalTrials.gov, NCT02745496. Retrospectively registered on 20 April 2016.

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.

Background: Cognitive impairment is common in older people admitted to hospital, but previous research has focused on single conditions. Objective: This project sits in phase 0/1 of the Medical Research Council Framework for the Development and Evaluation of Complex Interventions. It aims to develop an understanding of current health-care outcomes. This will be used in the future development of a multidomain intervention for people with confusion (dementia and cognitive impairment) in general hospitals. The research was conducted from January 2015 to June 2018 and used data from people admitted between 2012 and 2013. Design: For the review of outcomes, the systematic review identified peer-reviewed quantitative epidemiology measuring prevalence and associations with outcomes. Screening for duplication and relevance was followed by full-text review, quality assessment and a narrative review (141 papers). A survey sought opinion on the key outcomes for people with dementia and/or confusion and their carers in the acute hospital (n = 78). For the analysis of outcomes including cost, the prospective cohort study was in a medical admissions unit in an acute hospital in one Scottish health board covering 10% of the Scottish population. The participants (n = 6724) were older people (aged ≥ 65 years) with or without a cognitive spectrum disorder who were admitted as medical emergencies between January 2012 and December 2013 and who underwent a structured nurse assessment. ‘Cognitive spectrum disorder’ was defined as any combination of delirium, known dementia or an Abbreviated Mental Test score of

Introduction Hepatitis C virus (HCV) is a global public health threat, and novel models of care are required to treat those currently or previously at highest risk of infection, particularly persons who inject drugs (PWID; ever injected), as conventional healthcare models do not have the reach to deliver cure of HCV to disadvantaged, disproportionately affected communities. In Western Europe and Australasia, it is estimated that HCV affects between 0.4% and 1.0% of the regions’ populations, accordingly, it affects between 0.4% and 0.7% of the populations of countries in this study (Scotland, Wales and Australia). Reaching mEthadone users Attending Community pHarmacies with HCV (REACH HCV) will evaluate community pharmacy-based diagnostic outreach and HCV treatment against conventional HCV testing and treatment pathways for clients receiving opioid substitution therapy (OST) in community pharmacies.Methods and analysis REACH HCV is an international multicentre cluster randomised controlled trial with sites in Scotland, Wales and Australia. The sites are community pharmacies which are randomised equally to one of two pathways: the pharmacy intervention pathway or the education-only (control) pathway. Participants are recruited from OST clients in these pharmacies.In the pharmacy intervention pathway, participants receive a rapid point-of-care HCV PCR test in their pharmacy by a study outreach nurse. If positive, direct-acting antivirals (DAAs) are delivered to participants via their pharmacist in line with their OST schedule.In the education-only pathway, pharmacists counsel OST clients on HCV and refer them to the nearest nurse-led clinic or general practitioner offering HCV testing according to standard care protocols. If positive, DAAs are delivered as in the intervention pathway.The primary endpoint for both pathways is sustained viral response at 12 weeks post-treatment . Secondary outcomes are: cost-efficacy by pathway; participants tested by pathway; adherence to therapy by pathway and impact of blood test results on treatment decisions.A statistical analysis plan will be finalised prior to data lock. Analysis will be by intention to treat (ITT) to show superiority. Modified ITT analysis will also be undertaken to explore the steps in the pathways.Ethics and dissemination The trial received ethical favourable opinion from the East of Scotland Research Ethics Committee 2 (19/ES/0025) for UK sites and approval from the Alfred Hospital Ethics Committee (148/19) for Australian sites and complies with principles of Good Clinical Practice. Final results will be presented in peer-reviewed journals and at relevant conferences.Trial registration number ClinicalTrials.gov Registry NCT03935906.Protocol version V.4.0—19 March 2020.

Abstract Background Multiple sclerosis (MS) is a life-long condition primarily affecting younger adults. Neurogenic bowel dysfunction (NBD) occurs in 50–80% of these patients and is the term used to describe constipation and faecal incontinence, which often co-exist. Data from a pilot study suggested feasibility of using abdominal massage for the relief of constipation, but the effectiveness remains uncertain. Methods/design This is a multi-centred patient randomised superiority trial comparing an experimental strategy of once daily abdominal massage for 6 weeks against a control strategy of no massage in people with MS who have stated that their constipation is bothersome. The primary outcome is the Neurogenic Bowel Dysfunction Score at 24 weeks. Both groups will receive optimised advice plus the MS Society booklet on bowel management in MS, and will continue to receive usual care. Participants and their clinicians will not be blinded to the allocated intervention. Outcome measures are primarily self-reported and submitted anonymously. Central trial staff who will manage and analyse the trial data will be unaware of participant allocations. Analysis will follow intention-to-treat principles. Discussion This pragmatic randomised controlled trial will demonstrate if abdominal massage is an effective, cost-effective and viable addition to the treatment of NBD in people with MS. Trial registration ClinicalTrials.gov, ISRCTN85007023 . Registered on 10 June 2014.

Background: Between 50% and 80% of people with multiple sclerosis (PwMS) experience neurogenic bowel dysfunction (NBD) (i.e. constipation and faecal incontinence) that affects quality of life and can lead to hospitalisation. Objectives: To determine the clinical effectiveness and cost-effectiveness of abdominal massage plus advice on bowel symptoms on PwMS compared with advice only. A process evaluation investigated the factors that affected the clinical effectiveness and possible implementation of the different treatments. Design: A randomised controlled trial with process evaluation and health economic components. Outcome analysis was undertaken blind. Setting: The trial took place in 12 UK hospitals. Participants: PwMS who had ‘bothersome’ NBD. Intervention: Following individualised training, abdominal massage was undertaken daily for 6 weeks (intervention group). Advice on good bowel management as per the Multiple Sclerosis Society advice booklet was provided to both groups. All participants received weekly telephone calls from the research nurse. Main outcome measures: The primary outcome was the difference between the intervention and control groups in change in the NBD score from baseline to week 24. Secondary outcomes were measured via a bowel diary, adherence diary, the Constipation Scoring System, patient resource questionnaire and the EuroQol-5 Dimensions, five-level version (EQ-5D-5L). Results: A total of 191 participants were finalised, 189 of whom were randomised (two participants were finalised in error) (control group, n = 99; intervention group, n = 90) and an intention-to-treat analysis was performed. The mean age was 52 years (standard deviation 10.83 years), 81% (n = 154) were female and 11% (n = 21) were wheelchair dependent. Fifteen participants from the intervention group and five from the control group were lost to follow-up. The change in NBD score by week 24 demonstrated no significant difference between groups [mean difference total score –1.64, 95% confidence interval (CI) –3.32 to 0.04; p = 0.0558]; there was a significant difference between groups in the change in the frequency of stool evacuation per week (mean difference 0.62, 95% CI 0.03 to 1.21; p = 0.039) and in the number of times per week that participants felt that they emptied their bowels completely (mean difference 1.08, 95% CI 0.41 to 1.76; p = 0.002), in favour of the intervention group. Of participant interviewees, 75% reported benefits, for example less difficulty passing stool, more complete evacuations, less bloated, improved appetite, and 85% continued with the massage. A cost–utility analysis conducted from a NHS and patient cost perspective found in the imputed sample with bootstrapping a mean incremental outcome effect of the intervention relative to usual care of –0.002 quality-adjusted life-years (QALYs) (95% CI –0.029 to 0.027 QALYs). In the same imputed sample with bootstrapping, the mean incremental cost effect of the intervention relative to usual care was £56.50 (95% CI –£372.62 to £415.68). No adverse events were reported. Limitations include unequal randomisation, dropout and the possibility of ineffective massage technique. Conclusion: The increment in the primary outcome favoured the intervention group, but it was small and not statistically significant. The economic analysis identified that the intervention was dominated by the control group. Given the small improvement in the primary outcome, but not in terms of QALYs, a low-cost version of the intervention might be considered worthwhile by some patients. Future work: Research is required to establish possible mechanisms of action and modes of massage delivery. Trial registration: Current Controlled Trials ISRCTN85007023 and NCT03166007. Funding: This project was funded by the National Institute for Health Research Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 58. See the NIHR Journals Library website for further project information.

ABSTRACT Objectives We looked for an approach to analyze/visualize a set of repeated measures of renal laboratory data (eGFR [estimated Glomerular Filtration Rate] from an observational population-based data set) as safety parameters in a longitudinal design and calculate annual changes in different sub-cohorts. Previous meta-analyses had struggled to address this problem (due to poor data quality and strong heterogeneity in underlying historical studies) and previous large population-based observational studies had only looked into binary outcomes. Particular challenges lay (1) in the complexity of the data set with irregularly spaced observation points, (2) in the observational character of the data with associated bias and confounding by indication and co-medication and (3) in the change of lab method during the observation period. Results Out of a population base of 400.000 we analysed linked longitudinal data of more than 1000 eligible patients with over 1000.000 prescription records of index drug or co-prescription drugs. Data were provided by the Dundee University Health Informatics Centre (HIC). We addressed the differences in covariates (which typically can lead to biased estimates of treatment effects in observational studies) via individual propensity scores (to reduce this bias by balancing the covariates in the two groups) and a hierarchical modelling approach. A Random Coefficient Model (via proc mixed in SAS 9.3) proved a much more powerful statistical tool than analysis of covariance of the summary measure during follow-up, particularly as the latter approach is less efficient when applied to longitudinal data with missing data points and irregularly spaced repeated measures. Visualization was achieved with the SAS 9.3 GPLOT procedure combined with a spline function. The historical change in lab method was addressed via a conversion of lab results to an internationally recognized standard (IDMS aligned method). We were able to achieve plausible and more precise estimates of the annual decline in eGFR in the patient group of interest than previous attempts from other research publications. This led to a publication in a high profile journal. Conclusion Our approach of combining a Propensity Score and Random Coefficient Modelling was successful to answer a question in drug safety using repeated measurement data from a longitudinal observational population based data set. This approach may be useful for other research questions in Drug Safety or in Comparative Clinical Effectiveness Research for continuous outcome measures.

Objectives General practitioners are increasingly required to practice in a paperless environment and to collect clinical data electronically on electronic patient record (EPR) systems. A principal step in meeting general practice information needs continues to be the establishment of disease registers and consequently the identification of patient populations within primary care databases is a prerequisite. This study aims to identify and validate the optimal search strategy for coronary heart disease (CHD). Methods A multiple logistic regression model for the identification of CHD patients was developed in one site using electronic data, the receiver operating characteristic (ROC) curve and Bayesian statistics. The model was tested on two trial sites. Results Young male CHD patients are more easily identified by generic searches than older females. The optimal search strategy for CHD was found to be the diagnostic code for CHD, nitrate and digoxin but this was dependent on the disease description, age and sex of the study population and the coding system used within the database. Diagnostic code for CHD identified 80.6% (95% confidence interval (CI) 77-83%), 90.0% (CI 88-92%) and 95.9% (CI 94-97%) of local, national and international definitions respectively, with 100% positive predictive values (PPVs) for all definitions. Conclusion Generic queries may inadvertently perpetuate inequalities in health care. Queries should be bespoke and mindful of the conceptualisation of disease by the clinicians recording these data.

Introduction Recent evaluations of IT innovations in primary care have highlighted variations between centres and practices in uptake and use. We evaluated whether structural characteristics of a general practice were associated with variations in use of a web-based clinical information system underpinning a Managed Clinical Network in diabetes, between the years 2001 and 2003. Methods Using a computerised audit trail, we calculated the numbers of web-based operations that occurred in each practice, stratified by staff type and year, and adjusted for the numbers of registered diabetic patients. In regression analyses, we determined whether total use was associated with structural characteristics of the practice (total list size, training status, numbers of GPs (general practitioners), mean age of the GPs, numbers of female GPs, level of deprivation of the population and whether staff had received advanced training in diabetes care). Results Initially there were a few practices which made very frequent use of the information system, with relatively high numbers of practices using the facility infrequently. However, overall use gradually became more evenly spread. This effect was particularly evident among nurse users. Frequent use by GPs was evident in only a smallnumber of practices, with meanGPuse decreasing over the three years. In linear regression analyses, none of the general practice variableswere associatedwithonlineuse, either overall or stratified by staff type, except for the numbers of diabetes-educated staff. This was consistently associated with increased use by nurses and GPs. Conclusions The analyses show that structural characteristics of a practice are not associated with uptake of a new IT facility, but that its use may be influenced by post-graduate education in the relevant clinical condition. For this diabetes system at least, practice nurse use was critical in spreading uptake beyond initial GP enthusiasts and for sustained and rising use in subsequent years.

Objectives To determine the uptake of multiple eHealth facilities enabled by the NHS Scotland Electronic Clinical Communications Implementation Programme (ECCI) and to ascertain primary and secondary care users' perceptions. Design Prospective monthly measurement of 37 indicators of roll-out and adoption. Retrospective questionnaire survey of users. Setting Scottish health board regions. Quantitative implementation indicators were gathered in primary and secondary care across all 16 regions. Questionnaire data were obtained from recorded users in five representative regions (112 general practices, 92 secondary care units). Outcome measures Change in uptake levels of ECCI facilities over a 15-month period. Users' perceptions of benefits, facilitators and barriers. Results All health boards participated in the monthly data set collection. The response rate to the survey was 62% in primary care and 37% in secondary care. Across Scotland as a whole, the process of implementation was gradual. While there were marked gains inthe availability of ECCI facilities over the observation period, rates of adoption lagged behind and varied across alternative facilities. Electronic results were widely used, with most laboratories offering them and around half of general practices receiving them. More modest rates of adoption were observed for e-discharge letters, e-referrals, e-clinic letters and clinical email. E-booking was used very little. Among engaged users responding to the survey, electronic access to test results was the most frequently utilised facility and electronic outpatient booking the least. Perceived benefits of ECCI facilities included convenience, ease of use, time-saving and provision of an audit trail. Perceived barriers included the need to duplicate data entry where new systems were not universally implemented, technological difficulties, time, training and resources. Conclusions Significant progress was observed in the implementation of ECCI facilities across Scotland. Users reported that these improved communication and were beneficial, but system reliability, incompatibility and duplication of data hindered more widespread uptake. Data were collected at a transitional phase of the programme. Whilst, among users of ECCI facilities, perceptions of the programme and its potential benefits were generally positive, its full impact will not become evident until the new electronic tools are implemented nationally and have been more fully integrated into normal work routines.