Stereotactic radiotherapy for neovascular age-related macular degeneration (STAR): a pivotal, randomised, double-masked, sham-controlled device trial.

BACKGROUND: Neovascular age-related macular degeneration (nAMD) is a leading cause of blindness. The first-line therapy is anti-vascular endothelial growth factor (anti-VEGF) agents delivered by intravitreal injection. Ionising radiation mitigates key pathogenic processes underlying nAMD, and therefore has therapeutic potential. STAR aimed to assess whether stereotactic radiotherapy (SRT) reduces the number of anti-VEGF injections required, without sacrificing visual acuity. METHODS: This pivotal, randomised, double-masked, sham-controlled trial enrolled participants with pretreated chronic active nAMD from 30 UK hospitals. Participants were randomly allocated in a 2:1 ratio to 16-Gray (Gy) SRT delivered using a robotically controlled device or sham SRT, stratified by treatment centre. Eligible participants were aged 50 years or older and had chronic active nAMD, with at least three previous anti-VEGF injections, including at least one in the last 4 months. Participants and all trial and image reading centre staff were masked to treatment allocation, except one unmasked statistician. The primary outcome was the number of intravitreal ranibizumab injections required over 2 years, tested for superiority (fewer injections). The main secondary outcome was Early Treatment Diabetic Retinopathy Study visual acuity at two years, tested for non-inferiority (five-letter margin). The primary analysis used the intention-to-treat principle, and safety was analysed per-protocol on participants with available data. The study is registered with ClinicalTrials.gov (NCT02243878) and is closed for recruitment. FINDINGS: 411 participants enrolled between Jan 1, 2015, and Dec 27, 2019, and 274 were randomly allocated to the 16-Gy SRT group and 137 to the sham SRT group. 240 (58%) of all participants were female, and 171 (42%) of all participants were male. 241 participants in the 16-Gy SRT group and 118 participants in the sham group were included in the final analysis, and 409 patients were treated and formed the safety population, of whom two patients allocated to sham treatment erroneously received 16-Gy SRT. The SRT group received a mean of 10·7 injections (SD 6·3) over 2 years versus 13·3 injections (5·8) with sham, a reduction of 2·9 injections after adjusting for treatment centre (95% CI -4·2 to -1·6, p<0·0001). The SRT group best-corrected visual acuity change was non-inferior to sham (adjusted mean letter loss difference between groups, -1·7 letters [95% CI -4·2 to 0·8]). Adverse event rates were similar across groups, but reading centre-detected microvascular abnormalities occurred in 77 SRT-treated eyes (35%) and 13 (12%) sham-treated eyes. Overall, eyes with microvascular abnormalities tended to have better best-corrected visual acuity than those without. Fewer ranibizumab injections offset the cost of SRT, saving a mean of £565 per participant (95% CI -332 to 1483). INTERPRETATION: SRT can reduce ranibizumab treatment burden without compromising vision. FUNDING: Medical Research Council and National Institute for Health and Care Research Efficacy and Mechanism Evaluation Programme.

100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report.

BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.).

Clinical utility of whole-genome sequencing in precision oncology.

Precision diagnostics is one of the two pillars of precision medicine. Sequencing efforts in the past decade have firmly established cancer as a primarily genetically driven disease. This concept is supported by therapeutic successes aimed at particular pathways that are perturbed by specific driver mutations in protein-coding domains and reflected in three recent FDA tissue agnostic cancer drug approvals. In addition, there is increasing evidence from studies that interrogate the entire genome by whole-genome sequencing that acquired global and complex genomic aberrations including those in non-coding regions of the genome might also reflect clinical outcome. After addressing technical, logistical, financial and ethical challenges, national initiatives now aim to introduce clinical whole-genome sequencing into real-world diagnostics as a rational and potentially cost-effective tool for response prediction in cancer and to identify patients who would benefit most from 'expensive' targeted therapies and recruitment into clinical trials. However, so far, this has not been accompanied by a systematic and prospective evaluation of the clinical utility of whole-genome sequencing within clinical trials of uniformly treated patients of defined clinical outcome. This approach would also greatly facilitate novel predictive biomarker discovery and validation, ultimately reducing size and duration of clinical trials and cost of drug development. This manuscript is the third in a series of three to review and critically appraise the potential and challenges of clinical whole-genome sequencing in solid tumors and hematological malignancies.

Long-term cost-effectiveness of a melanoma prevention program using genomic risk information compared with standard prevention advice in Australia.

PURPOSE: Evidence indicates that a melanoma prevention program using personalized genomic risk provision and genetic counseling can affect prevention behaviors, including reducing sunburns in adults with no melanoma history. This analysis evaluated its longer-term cost-effectiveness from an Australian health system perspective. METHODS: The primary outcome was incremental cost effectiveness ratio (ICER) of genomic risk provision (intervention) compared with standard prevention advice. A decision-analytic Markov model was developed using randomized trial data to simulate lifetime cost-effectiveness. All costs were presented in 2018/19 Australian dollars (AUD). The intervention effect on reduced sunburns was stratified by sex and traditional risk, which was calculated through a validated prediction model. Deterministic and probabilistic sensitivity analyses were undertaken for robustness checks. RESULTS: The per participant cost of intervention was AUD$189. Genomic risk provision targeting high-traditional risk individuals produced an ICER of AUD$35,254 (per quality-adjusted life year gained); sensitivity analyses indicated the intervention would be cost-effective in more than 50% of scenarios. When the intervention was extended to low-traditional risk groups, the ICER was AUD$43,746 with a 45% probability of being cost-effective. CONCLUSION: Genomic risk provision targeted to high-traditional melanoma risk individuals is likely a cost-effective strategy for reducing sunburns and will likely prevent future melanomas and keratinocyte carcinomas.

Cost-Effectiveness Analysis of Treating Patients With NTRK-Positive Cancer With the Histology-Independent Therapy Entrectinib.

OBJECTIVES: This study tackles several challenges of evaluating histology-independent treatments using entrectinib as an example. Histology-independent treatments are provided based on genetic marker(s) of tumors, regardless of the tumor type. We evaluated the lifetime cost-effectiveness of testing all patients for NTRK fusions and treating the positive cases with entrectinib compared with no testing and standard of care (SoC) for all patients. METHODS: The health economic model consisted of a decision tree reflecting the NTRK testing phase followed by a microsimulation model reflecting treatment with either entrectinib or SoC. Efficacy of entrectinib was based on data from basket trials, whereas historical data from NTRK-negative patients were corrected for the prognostic value of NTRK fusions to model SoC. RESULTS: "Testing" (testing for NTRK fusions, with subsequent entrectinib treatment in NTRK-positive patients and SoC in NTRK-negative patients) had higher per-patient quality-adjusted life-years (QALYs) and costs than "No testing" (SoC for all patients), with a difference of 0.0043 and €732, respectively. This corresponded to an incremental cost-effectiveness ratio (ICER) of €169 957/QALY and, using a cost-effectiveness threshold of €80 000/QALY, an incremental net monetary benefit of -€388. When excluding the costs of genetic testing for NTRK fusions, the ICER was reduced to €36 290/QALY and the incremental net monetary benefit increased to €188. CONCLUSIONS: When treatment requires the identification of a genetic marker, the associated costs and effects need to be accounted for. Because of the low prevalence of NTRK fusions, the number needed-to-test to identify patients eligible for entrectinib is large. Excluding the testing phase reduces the ICER substantially.

Can polygenic risk scores contribute to cost-effective cancer screening? A systematic review.

PURPOSE: Polygenic risk influences susceptibility to cancer. We assessed whether polygenic risk scores could be used in conjunction with other predictors of future disease status in cost-effective risk-stratified screening for cancer. METHODS: We undertook a systematic review of papers that evaluated the cost-effectiveness of screening interventions informed by polygenic risk scores compared with more conventional screening modalities. We included papers reporting cost-effectiveness outcomes with no restriction on type of cancer or form of polygenic risk modeled. We evaluated studies using the Quality of Health Economic Studies checklist. RESULTS: A total of 10 studies were included in the review, which investigated 3 cancers: prostate (n = 5), colorectal (n = 3), and breast (n = 2). Of the 10 papers, 9 scored highly (score >75 on a 0-100 scale) when assessed using the quality checklist. Of the 10 studies, 8 concluded that polygenic risk-informed cancer screening was likely to be more cost-effective than alternatives. CONCLUSION: Despite the positive conclusions of the included studies, it is unclear if polygenic risk stratification will contribute to cost-effective cancer screening given the absence of robust evidence on the costs of polygenic risk stratification, the effects of differential ancestry, potential downstream economic sequalae, and how large volumes of polygenic risk data would be collected and used.

Can upfront DPYD extended variant testing reduce toxicity and associated hospital costs of fluoropyrimidine chemotherapy? A propensity score matched analysis of 2022 UK patients.

AIM: To independently assess the impact of mandatory testing using an extended DPYD variant panel (ToxNav®) and consequent dose adjustment of Capecitabine/5-FU on recorded quantitative toxicity, symptoms of depression, and hospital costs. METHODS: We used propensity score matching (PSM) to match 466 patients tested with ToxNav® with 1556 patients from a historical cohort, and performed regression analysis to estimate the impact of ToxNav®on toxicity, depression, and hospital costs. RESULTS: ToxNav® appeared to reduce the likelihood of experiencing moderate (OR: 0.59; 95%CI: 0.45-0.77) and severe anaemia (OR: 0.55; 95%CI: 0.33-0.90), and experience of pain for more than 4 days a week (OR: 0.50; 95%CI: 0.30-0.83), while it increased the likelihood of mild neutropenia (OR: 1.73; 95%CI: 1.27-2.35). It also reduced the cost of chemotherapy by 12% (95%CI: 3-31) or £9765, the cost of non-elective hospitalisation by 23% (95%CI: 8-36) or £2331, and the cost of critical care by 21% (95%CI: 2-36) or £1219 per patient. For the DPYD variant associated with critical risk of toxicity (rs3918290), the improved non-elective hospital costs were > £20,000, whereas variants associated with hand-foot syndrome toxicity had no detectable cost improvement. CONCLUSION: Upfront testing of DPYD variants appears to reduce the toxicity burden of Capecitabine and 5-FU in cancer patients and can lead to substantial hospital cost savings, only if the dose management of the drugs in response to variants detected is standardised and regulated.

The Net Benefit of Personalized Medicine: A Systematic Literature Review and Regression Analysis.

OBJECTIVES: Amidst conflicting expectations about the benefits of personalized medicine (PM) and the potentially high implementation costs, we reviewed the available evidence on the cost-effectiveness of PM relative to non-PM. METHODS: We conducted a systematic literature review of economic evaluations of PM and extracted data, including incremental quality-adjusted life-years (ΔQALYs) and incremental costs (Δcosts). ΔQALYs and Δcosts were combined with estimates of national cost-effectiveness thresholds to calculate incremental net monetary benefit (ΔNMB). Regression analyses were performed with these variables as dependent variables and PM intervention characteristics as independent variables. Random intercepts were used to cluster studies according to country. RESULTS: Of 4774 studies reviewed, 128 were selected, providing cost-effectiveness data for 279 PM interventions. Most studies were set in the United States (48%) and the United Kingdom (16%) and adopted a healthcare perspective (82%). Cancer treatments (60%) and pharmaceutical interventions (72%) occurred frequently. Prognostic tests (19%) and tests to identify (non)responders (37%) were least and most common, respectively. Industry sponsorship occurred in 32%. Median ΔQALYs, Δcosts, and ΔNMB per individual were 0.03, Int$575, and Int$18, respectively. We found large heterogeneity in cost-effectiveness. Regression analysis showed that gene therapies were associated with higher ΔQALYs than other interventions. PM interventions for neoplasms brought higher ΔNMB than PM interventions for other conditions. Nonetheless, average ΔNMB in the 'neoplasm' group was found to be negative. CONCLUSIONS: PM brings improvements in health but often at a high cost, resulting in 0 to negative ΔNMB on average. Pricing policies may be needed to reduce the costs of interventions with negative ΔNMB.

Defining a Core Data Set for the Economic Evaluation of Precision Oncology.

OBJECTIVES: Precision oncology is generating vast amounts of multiomic data to improve human health and accelerate research. Existing clinical study designs and attendant data are unable to provide comparative evidence for economic evaluations. This lack of evidence can cause inconsistent and inappropriate reimbursement. Our study defines a core data set to facilitate economic evaluations of precision oncology. METHODS: We conducted a literature review of economic evaluations of next-generation sequencing technologies, a common application of precision oncology, published between 2005 and 2018 and indexed in PubMed (MEDLINE). Based on this review, we developed a preliminary core data set for informal expert feedback. We then used a modified-Delphi approach with individuals involved in implementation and evaluation of precision medicine, including 2 survey rounds followed by a final voting conference to refine the data set. RESULTS: Two authors determined that variation in published data elements was reached after abstraction of 20 economic evaluations. Expert consultation refined the data set to 83 unique data elements, and a multidisciplinary sample of 46 experts participated in the modified-Delphi process. A total of 68 elements (81%) were selected as required, spanning demographics and clinical characteristics, genomic data, cancer treatment, health and quality of life outcomes, and resource use. CONCLUSIONS: Cost-effectiveness analyses will fail to reflect the real-world impacts of precision oncology without data to accurately characterize patient care trajectories and outcomes. Data collection in accordance with the proposed core data set will promote standardization and enable the generation of decision-grade evidence to inform reimbursement.

Utility maximization versus regret minimization in health choice behavior: Evidence from four datasets.

Choice models in health are almost exclusively based on the neoclassical economic paradigm of utility maximization. Recently developed choice models have captured and shown empirical support for regret minimization as an alternative decision rule. In health economics, recent applications of RRM models indicate that individuals making health-based choices may exhibit regret minimization-type behavior. In this paper, we build on this research using a more flexible model that allows for heterogeneous decision rules, separately from preference heterogeneity, and comparing it to models that assume single decision rules. We use four datasets from diverse settings in which individuals make health choices: tobacco markets, genomic testing, and HIV prevention. We found that, if a one-size-fits-all rule is applied, then utility maximization was preferable to regret minimization for these datasets. However, we also find that individuals apply varying decision rules in similar proportions in these health settings, suggesting that models for heterogeneous decision rules were needed to capture these behaviors in these settings.

Eliciting risk preferences that predict risky health behavior: A comparison of two approaches.

Information on attitudes to risk could increase understanding of and explain risky health behaviors. We investigate two approaches to eliciting risk preferences in the health domain, a novel "indirect" lottery elicitation approach with health states as outcomes and a "direct" approach where respondents are asked directly about their willingness to take risks. We compare the ability of the two approaches to predict health-related risky behaviors in a general adult population. We also investigate a potential framing effect in the indirect lottery elicitation approach. We find that risk preferences elicited using the direct approach can better predict health-related risky behavior than those elicited using the indirect approach. Moreover, a seemingly innocuous change to the framing of the lottery question results in significantly different risk preference estimates, and conflicting conclusions about the ability of the indicators to predict risky health behaviors.

Public preferences for delayed or immediate antibiotic prescriptions in UK primary care: A choice experiment.

BACKGROUND: Delayed (or "backup") antibiotic prescription, where the patient is given a prescription but advised to delay initiating antibiotics, has been shown to be effective in reducing antibiotic use in primary care. However, this strategy is not widely used in the United Kingdom. This study aimed to identify factors influencing preferences among the UK public for delayed prescription, and understand their relative importance, to help increase appropriate use of this prescribing option. METHODS AND FINDINGS: We conducted an online choice experiment in 2 UK general population samples: adults and parents of children under 18 years. Respondents were presented with 12 scenarios in which they, or their child, might need antibiotics for a respiratory tract infection (RTI) and asked to choose either an immediate or a delayed prescription. Scenarios were described by 7 attributes. Data were collected between November 2018 and February 2019. Respondent preferences were modelled using mixed-effects logistic regression. The survey was completed by 802 adults and 801 parents (75% of those who opened the survey). The samples reflected the UK population in age, sex, ethnicity, and country of residence. The most important determinant of respondent choice was symptom severity, especially for cough-related symptoms. In the adult sample, the probability of choosing delayed prescription was 0.53 (95% confidence interval (CI) 0.50 to 0.56, p < 0.001) for a chesty cough and runny nose compared to 0.30 (0.28 to 0.33, p < 0.001) for a chesty cough with fever, 0.47 (0.44 to 0.50, p < 0.001) for sore throat with swollen glands, and 0.37 (0.34 to 0.39, p < 0.001) for sore throat, swollen glands, and fever. Respondents were less likely to choose delayed prescription with increasing duration of illness (odds ratio (OR) 0.94 (0.92 to 0.96, p < 0.001)). Probabilities of choosing delayed prescription were similar for parents considering treatment for a child (44% of choices versus 42% for adults, p = 0.04). However, parents differed from the adult sample in showing a more marked reduction in choice of the delayed prescription with increasing duration of illness (OR 0.83 (0.80 to 0.87) versus 0.94 (0.92 to 0.96) for adults, p for heterogeneity p < 0.001) and a smaller effect of disruption of usual activities (OR 0.96 (0.95 to 0.97) versus 0.93 (0.92 to 0.94) for adults, p for heterogeneity p < 0.001). Females were more likely to choose a delayed prescription than males for minor symptoms, particularly minor cough (probability 0.62 (0.58 to 0.66, p < 0.001) for females and 0.45 (0.41 to 0.48, p < 0.001) for males). Older people, those with a good understanding of antibiotics, and those who had not used antibiotics recently showed similar patterns of preferences. Study limitations include its hypothetical nature, which may not reflect real-life behaviour; the absence of a "no prescription" option; and the possibility that study respondents may not represent the views of population groups who are typically underrepresented in online surveys. CONCLUSIONS: This study found that delayed prescription appears to be an acceptable approach to reducing antibiotic consumption. Certain groups appear to be more amenable to delayed prescription, suggesting particular opportunities for increased use of this strategy. Prescribing choices for sore throat may need additional explanation to ensure patient acceptance, and parents in particular may benefit from reassurance about the usual duration of these illnesses.

Does bariatric surgery reduce future hospital costs? A propensity score-matched analysis using UK Biobank Study data.

OBJECTIVES: To estimate the hospital costs among persons with obesity undergoing bariatric surgery compared with those without bariatric surgery. METHODS: We analysed the UK Biobank Cohort study linked to Hospital Episode Statistics, for all adults with obesity undergoing bariatric surgery at National Health Service hospitals in England, Scotland, or Wales from 2006 to 2017. Surgery patients were matched with controls who did not have bariatric surgery using propensity scores approach with a ratio of up to 1-to-5 by year. Inverse probability of censoring weighting was used to correct for potential informative censoring. Annual and cumulative hospital costs were assessed for the surgery and control groups. RESULTS: We identified 348 surgical patients (198 gastric bypass, 73 sleeve gastrectomy, 77 gastric banding) during the study period. In total, 324 surgical patients and 1506 matched control participants were included after propensity score matching. Mean 5-year cumulative hospital costs were €11,659 for 348 surgical patients. Compared with controls, surgical patients (n = 324) had significantly higher inpatient expenditures in the surgery year (€7289 vs. €2635, P < 0.001), but lower costs in the subsequent 4 years. The 5-year cumulative costs were €11,176 for surgical patients and €8759 for controls (P = 0.001). CONCLUSIONS: Bariatric surgery significantly increased the inpatient costs in the surgery year, but was associated with decreased costs in the subsequent 4 years. However, any cost savings made up to 4 years were not enough to compensate for the initial surgical expenditure.

Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: a randomized controlled trial.

PURPOSE: We evaluated the impact of personal melanoma genomic risk information on sun-related behaviors and psychological outcomes. METHODS: In this parallel group, open, randomized controlled trial, 1,025 Australians of European ancestry without melanoma and aged 18-69 years were recruited via the Medicare database (3% consent). Participants were randomized to the intervention (n = 513; saliva sample for genetic testing, personalized melanoma risk booklet based on a 40-variant polygenic risk score, telephone-based genetic counseling, educational booklet) or control (n = 512; educational booklet). Wrist-worn ultraviolet (UV) radiation dosimeters (10-day wear) and questionnaires were administered at baseline, 1 month postintervention, and 12 months postbaseline. RESULTS: At 12 months, 948 (92%) participants completed dosimetry and 973 (95%) the questionnaire. For the primary outcome, there was no effect of the genomic risk intervention on objectively measured UV exposure at 12 months, irrespective of traditional risk factors. For secondary outcomes at 12 months, the intervention reduced sunburns (risk ratio: 0.72, 95% confidence interval: 0.54-0.96), and increased skin examinations among women. Melanoma-related worry was reduced. There was no overall impact on general psychological distress. CONCLUSION: Personalized genomic risk information did not influence sun exposure patterns but did improve some skin cancer prevention and early detection behaviors, suggesting it may be useful for precision prevention. There was no evidence of psychological harm.

Content of Health Economics Analysis Plans (HEAPs) for Trial-Based Economic Evaluations: Expert Delphi Consensus Survey.

OBJECTIVES: Health economics analysis plans (HEAPs) currently lack consistency, with uncertainty surrounding appropriate content. We aimed to develop a list of essential items that should be included in HEAPs for economic evaluations conducted alongside randomized trials. METHODS: A list of potential items for inclusion was developed by examining existing HEAPs. An electronic Delphi survey was conducted among professional health economists. Respondents were asked to rate potential items from 1 (least important) to 9 (most important), suggest additional items, and comment on proposed items (round 1). A second survey (round 2) was emailed to participants, including the participant's own scores from round 1 along with summary results from the whole panel; participants were asked to rerate each item. Consensus criteria for inclusion in the final list were predefined as >70% of participants rating an item 7-9 and <15% rating it 1-3 after round 2. A final item selection meeting was held to scrutinize the results and adjudicate on items lacking consensus. RESULTS: 62 participants completed round 1 of the survey. The initial list included 72 potential items; all 72 were carried forward to round 2, and no new items were added. 48 round 1 respondents (77.4%) completed round 2 and reached consensus on 53 items. At the final meeting, the expert panel (n = 9) agreed that 58 items should be included in the essential list, moved 9 items to an optional list, and dropped 5 items. CONCLUSIONS: Via expert consensus opinion, this study identified 58 items that are considered essential in a HEAP.

Estimating the Effect of Healthcare-Associated Infections on Excess Length of Hospital Stay Using Inverse Probability-Weighted Survival Curves.

BACKGROUND: Studies estimating excess length of stay (LOS) attributable to nosocomial infections have failed to address time-varying confounding, likely leading to overestimation of their impact. We present a methodology based on inverse probability-weighted survival curves to address this limitation. METHODS: A case study focusing on intensive care unit-acquired bacteremia using data from 2 general intensive care units (ICUs) from 2 London teaching hospitals were used to illustrate the methodology. The area under the curve of a conventional Kaplan-Meier curve applied to the observed data was compared with that of an inverse probability-weighted Kaplan-Meier curve applied after treating bacteremia as censoring events. Weights were based on the daily probability of acquiring bacteremia. The difference between the observed average LOS and the average LOS that would be observed if all bacteremia cases could be prevented was multiplied by the number of admitted patients to obtain the total excess LOS. RESULTS: The estimated total number of extra ICU days caused by 666 bacteremia cases was estimated at 2453 (95% confidence interval [CI], 1803-3103) days. The excess number of days was overestimated when ignoring time-varying confounding (2845 [95% CI, 2276-3415]) or when completely ignoring confounding (2838 [95% CI, 2101-3575]). CONCLUSIONS: ICU-acquired bacteremia was associated with a substantial excess LOS. Wider adoption of inverse probability-weighted survival curves or alternative techniques that address time-varying confounding could lead to better informed decision making around nosocomial infections and other time-dependent exposures.

Why do hospital prescribers continue antibiotics when it is safe to stop? Results of a choice experiment survey.

BACKGROUND: Deciding whether to discontinue antibiotics at early review is a cornerstone of hospital antimicrobial stewardship practice worldwide. In England, this approach is described in government guidance ('Start Smart then Focus'). However, < 10% of hospital antibiotic prescriptions are discontinued at review, despite evidence that 20-30% could be discontinued safely. We aimed to quantify the relative importance of factors influencing prescriber decision-making at review. METHODS: We conducted an online choice experiment, a survey method to elicit preferences. Acute/general hospital prescribers in England were asked if they would continue or discontinue antibiotic treatment in 15 hypothetical scenarios. Scenarios were described according to six attributes, including patients' presenting symptoms and whether discontinuation would conflict with local prescribing guidelines. Respondents' choices were analysed using conditional logistic regression. RESULTS: One hundred respondents completed the survey. Respondents were more likely to continue antibiotics when discontinuation would 'strongly conflict' with local guidelines (average marginal effect (AME) on the probability of continuing + 0.194 (p < 0.001)), when presenting symptoms more clearly indicated antibiotics (AME of urinary tract infection symptoms + 0.173 (p < 0.001) versus unclear symptoms) and when patients had severe frailty/comorbidities (AME = + 0.101 (p < 0.001)). Respondents were less likely to continue antibiotics when under no external pressure to continue (AME = - 0.101 (p < 0.001)). Decisions were also influenced by the risks to patient health of continuing/discontinuing antibiotic treatment. CONCLUSIONS: Guidelines that conflict with antibiotic discontinuation (e.g. pre-specify fixed durations) may discourage safe discontinuation at review. In contrast, guidelines conditional on patient factors/treatment response could help hospital prescribers discontinue antibiotics if diagnostic information suggesting they are no longer needed is available.

Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear-based messages about antimicrobial resistance.

BACKGROUND: To reduce inappropriate antibiotic use, public health campaigns often provide fear-based information about antimicrobial resistance (AMR). Meta-analyses have found that fear-based campaigns in other contexts are likely to be ineffective unless respondents feel confident they can carry out the recommended behaviour ('self-efficacy'). This study aimed to test the likely impact of fear-based messages, with and without empowering self-efficacy elements, on patient consultations/antibiotic requests for influenza-like illnesses, using a randomised design. METHODS: We hypothesised that fear-based messages containing empowering information about self-management without antibiotics would be more effective than fear alone, particularly in a pre-specified subgroup with low AMR awareness. Four thousand respondents from an online panel, representative of UK adults, were randomised to receive three different messages about antibiotic use and AMR, designed to induce fear about AMR to varying degrees. Two messages (one 'strong-fear', one 'mild-fear') also contained empowering information regarding influenza-like symptoms being easily self-managed without antibiotics. The main outcome measures were self-reported effect of information on likelihood of visiting a doctor and requesting antibiotics, for influenza-like illness, analysed separately according to whether or not the AMR information was 'very/somewhat new' to respondents, pre-specified based on a previous (non-randomised) survey. RESULTS: The 'fear-only' message was 'very/somewhat new' to 285/1000 (28.5%) respondents, 'mild-fear-plus-empowerment' to 336/1500 (22.4%), and 'strong-fear-plus-empowerment' to 388/1500 (25.9%) (p = 0.002). Of those for whom the respective information was 'very/somewhat new', only those given the 'strong-fear-plus-empowerment' message said they would be less likely to request antibiotics if they visited a doctor for an influenza-like illness (p < 0.0001; 182/388 (46.9%) 'much less likely'/'less likely', versus 116/336 (34.5%) with 'mild-fear-plus-empowerment' versus 85/285 (29.8%) with 'fear-alone'). Those for whom the respective information was not 'very/somewhat new' said they would be less likely to request antibiotics for influenza-like illness (p < 0.0001) across all messages (interaction p < 0.0001 versus 'very/somewhat new' subgroup). The three messages had analogous self-reported effects on likelihood of visiting a doctor and in subgroups defined by believing antibiotics would 'definitely/probably' help an influenza-like illness. Results were reproduced in an independent randomised survey (additional 4000 adults). CONCLUSIONS: Fear could be effective in public campaigns to reduce inappropriate antibiotic use, but should be combined with messages empowering patients to self-manage symptoms effectively without antibiotics.

The complete costs of genome sequencing: a microcosting study in cancer and rare diseases from a single center in the United Kingdom.

PURPOSE: The translation of genome sequencing into routine health care has been slow, partly because of concerns about affordability. The aspirational cost of sequencing a genome is $1000, but there is little evidence to support this estimate. We estimate the cost of using genome sequencing in routine clinical care in patients with cancer or rare diseases. METHODS: We performed a microcosting study of Illumina-based genome sequencing in a UK National Health Service laboratory processing 399 samples/year. Cost data were collected for all steps in the sequencing pathway, including bioinformatics analysis and reporting of results. Sensitivity analysis identified key cost drivers. RESULTS: Genome sequencing costs £6841 per cancer case (comprising matched tumor and germline samples) and £7050 per rare disease case (three samples). The consumables used during sequencing are the most expensive component of testing (68-72% of the total cost). Equipment costs are higher for rare disease cases, whereas consumable and staff costs are slightly higher for cancer cases. CONCLUSION: The cost of genome sequencing is underestimated if only sequencing costs are considered, and likely surpasses $1000/genome in a single laboratory. This aspirational sequencing cost will likely only be achieved if consumable costs are considerably reduced and sequencing is performed at scale.