A note on obtaining correct marginal predictions from a random intercepts model for binary outcomes.

BACKGROUND: Clustered data with binary outcomes are often analysed using random intercepts models or generalised estimating equations (GEE) resulting in cluster-specific or 'population-average' inference, respectively. METHODS: When a random effects model is fitted to clustered data, predictions may be produced for a member of an existing cluster by using estimates of the fixed effects (regression coefficients) and the random effect for the cluster (conditional risk calculation), or for a member of a new cluster (marginal risk calculation). We focus on the second. Marginal risk calculation from a random effects model is obtained by integrating over the distribution of random effects. However, in practice marginal risks are often obtained, incorrectly, using only estimates of the fixed effects (i.e. by effectively setting the random effects to zero). We compare these two approaches to marginal risk calculation in terms of model calibration. RESULTS: In simulation studies, it has been seen that use of the incorrect marginal risk calculation from random effects models results in poorly calibrated overall marginal predictions (calibration slope <1 and calibration in the large ≠ 0) with mis-calibration becoming worse with higher degrees of clustering. We clarify that this was due to the incorrect calculation of marginal predictions from a random intercepts model and explain intuitively why this approach is incorrect. We show via simulation that the correct calculation of marginal risks from a random intercepts model results in predictions with excellent calibration. CONCLUSION: The logistic random intercepts model can be used to obtain valid marginal predictions by integrating over the distribution of random effects

Sample size calculation for a stepped wedge trial.

BACKGROUND: Stepped wedge trials (SWTs) can be considered as a variant of a clustered randomised trial, although in many ways they embed additional complications from the point of view of statistical design and analysis. While the literature is rich for standard parallel or clustered randomised clinical trials (CRTs), it is much less so for SWTs. The specific features of SWTs need to be addressed properly in the sample size calculations to ensure valid estimates of the intervention effect. METHODS: We critically review the available literature on analytical methods to perform sample size and power calculations in a SWT. In particular, we highlight the specific assumptions underlying currently used methods and comment on their validity and potential for extensions. Finally, we propose the use of simulation-based methods to overcome some of the limitations of analytical formulae. We performed a simulation exercise in which we compared simulation-based sample size computations with analytical methods and assessed the impact of varying the basic parameters to the resulting sample size/power, in the case of continuous and binary outcomes and assuming both cross-sectional data and the closed cohort design. RESULTS: We compared the sample size requirements for a SWT in comparison to CRTs based on comparable number of measurements in each cluster. In line with the existing literature, we found that when the level of correlation within the clusters is relatively high (for example, greater than 0.1), the SWT requires a smaller number of clusters. For low values of the intracluster correlation, the two designs produce more similar requirements in terms of total number of clusters. We validated our simulation-based approach and compared the results of sample size calculations to analytical methods; the simulation-based procedures perform well, producing results that are extremely similar to the analytical methods. We found that usually the SWT is relatively insensitive to variations in the intracluster correlation, and that failure to account for a potential time effect will artificially and grossly overestimate the power of a study. CONCLUSIONS: We provide a framework for handling the sample size and power calculations of a SWT and suggest that simulation-based procedures may be more effective, especially in dealing with the specific features of the study at hand. In selected situations and depending on the level of intracluster correlation and the cluster size, SWTs may be more efficient than comparable CRTs. However, the decision about the design to be implemented will be based on a wide range of considerations, including the cost associated with the number of clusters, number of measurements and the trial duration

Future COVID-19 Booster Vaccine Refusal in Healthcare Workers after a Massive Breakthrough Infection Wave, a Nationwide Survey-Based Study

Background: An unprecedented coronavirus disease 2019 (COVID-19) wave occurred in China between December 2022 and January 2023, challenging the efficacy of the primary series of COVID-19 vaccines. The attitudes toward future COVID-19 booster vaccines (CBV) after the massive breakthrough infection among healthcare workers remain unknown. This study aimed to explore the prevalence and determinants of future CBV refusal after the unprecedented COVID-19 wave among healthcare workers. Methods: Between 9 and 19 February 2023, a cross-sectional nationwide online survey was conducted using a self-administered questionnaire vaccine among healthcare workers in China. Sociodemographics, profession, presence of chronic medical conditions, previous COVID-19 infection, attitudes towards future CBV, and reasons for future CBV refusal were collected. We estimated odds ratio [OR] with 95% confidence interval [CI] using a multivariable logistic regression model to explore the factors associated with future CBV refusal. Results: Among the 1618 participants who completed the survey, 1511 respondents with two or more doses of COVID-19 vaccines were analyzed. A total of 648 (41.8%) of respondents were unwilling to receive a future CBV. Multivariable logistic regression analysis revealed the association of CBV refusal with profession (vs. other staff, physician-adjusted OR 1.17, 95%CI 0.79–1.72, nurse-adjusted OR 1.88, 95%CI 1.24−2.85, p = 0.008), history of allergy (adjusted OR 1.72, 95%CI 1.05–2.83, p = 0.032), a lower self-perceived risk of future COVID-19 infection (p < 0.001), and a lower belief in CBV effectiveness (p = 0.014), safety (p < 0.001), and necessities for healthcare workers and the public (p < 0.001, respectively). Conclusions: Our findings highlight that a considerable proportion of healthcare workers were against a future booster dose after an unprecedented COVID-19 wave. Self-perception of future COVID-19 risk, and potential harm or doubtful efficacy of vaccines are the main determinants. Our findings may help public health authorities to establish future COVID-19 vaccination programs

A comparison of low- versus standard-dose bridging alteplase in acute ischemic stroke mechanical thrombectomy using indirect methods

Background: Whether low-dose alteplase is similar to standard-dose bridging alteplase prior to endovascular mechanical thrombectomy in patients with acute ischemic stroke (AIS) remains uncertain. Aims: The aim of this study was to compare the efficacy and safety outcomes of low- versus standard-dose bridging alteplase therapy (BT) in patients with acute ischemic stroke (AIS) who are eligible for intravenous thrombolysis (IVT) within 4.5 h after onset. Methods: We conducted an indirect comparison of low- versus standard-dose bridging alteplase before mechanical thrombectomy in AIS of current available clinical randomized controlled trials (RCTs) that compared direct mechanical thrombectomy treatment (dMT) to BT. Primary efficacy outcomes were functional independence and excellent recovery defined as a dichotomized modified Rankin Scale (mRS) 0–2 and 0–1 at 90 days. Safety outcomes included symptomatic intracranial hemorrhage (sICH) and any intracranial hemorrhage (ICH). Results: We included six RCTs of 2334 AIS patients in this analysis, including one trial using low-dose bridging alteplase (n = 103) and five trials using standard-dose bridging alteplase (n = 1067) against a common comparator (dMT). Indirect comparisons of low- to standard-dose bridging alteplase yielded an odds ratio (OR) of 0.84 (95% CI 0.47–1.50) for 90-day mRS 0–2, 1.18 (95% CI 0.65–2.12) for 90-day mRS 0–1, 1.21 (95% CI 0.44–3.36) for mortality, and 1.11 (95% CI 0.39–3.14) for successful recanalization. There were no significant differences in the odds for sICH (OR 1.05, 95% CI 0.32–3.41) or any ICH (OR 1.71, 95% CI 0.94–3.10) between low- and standard-dose bridging alteplase. Conclusion: Indirect evidence shows that the effects of low- and standard-dose bridging alteplase are similar for key efficacy and safety outcomes. Due to the wide confidence intervals, larger randomized trials comparing low- and standard-dose alteplase bridging therapy are required

The effects of cancer therapies on physical fitness before oesophagogastric cancer surgery: a prospective, blinded, multi-centre, observational, cohort study [version 1; peer review: 2 approved]

Background: Neoadjuvant cancer treatment is associated with improved survival following major oesophagogastric cancer surgery. The impact of neoadjuvant chemo/chemoradiotherapy on physical fitness and operative outcomes is however unclear. This study aims to investigate the impact of neoadjuvant chemo/chemoradiotherapy on fitness and post-operative mortality. / Methods: Patients with oesophagogastric cancer scheduled for chemo/chemoradiotherapy and surgery were recruited to a prospective, blinded, multi-centre, observational cohort study. Primary outcomes were changes in fitness with chemo/chemoradiotherapy, measured using cardiopulmonary exercise testing and its association with mortality one-year after surgery. Patients were followed up for re-admission at 30-days, in-hospital morbidity and quality of life (exploratory outcomes). / Results: In total, 384 patients were screened, 217 met the inclusion criteria, 160 consented and 159 were included (72% male, mean age 65 years). A total of 132 patients (83%) underwent chemo/chemoradiotherapy, 109 (71%) underwent chemo/chemoradiotherapy and two exercise tests, 100 (63%) completed surgery and follow-up. A significant decline in oxygen uptake at anaerobic threshold and oxygen uptake peak was observed following chemo/chemoradiotherapy: -1.25ml.kg-1.min-1 (-1.80 to -0.69) and -3.02ml.kg-1.min-1 (-3.85 to -2.20); p<0.0001). Baseline chemo/chemoradiotherapy anaerobic threshold and peak were associated with one-year mortality (HR=0.72, 95%CI 0.59 to 0.88; p=0.001 and HR=0.85, 0.76 to 0.95; p=0.005). The change in physical fitness was not associated with one-year mortality. / Conclusion: Chemo/chemoradiotherapy prior to oesophagogastric cancer surgery reduced physical fitness. Lower baseline fitness was associated with reduced overall survival at one-year. Careful consideration of fitness prior to chemo/chemoradiotherapy and surgery is urgently needed

Quality research in healthcare: are researchers getting enough statistical support?

BACKGROUND: Reviews of peer-reviewed health studies have highlighted problems with their methodological quality. As published health studies form the basis of many clinical decisions including evaluation and provisions of health services, this has scientific and ethical implications. The lack of involvement of methodologists (defined as statisticians or quantitative epidemiologists) has been suggested as one key reason for this problem and this has been linked to the lack of access to methodologists. This issue was highlighted several years ago and it was suggested that more investments were needed from health care organisations and Universities to alleviate this problem. METHODS: To assess the current level of methodological support available for health researchers in England, we surveyed the 25 National Health Services Trusts in England, that are the major recipients of the Department of Health's research and development (R&D) support funding. RESULTS AND DISCUSSION: The survey shows that the earmarking of resources to provide appropriate methodological support to health researchers in these organisations is not widespread. Neither the level of R&D support funding received nor the volume of research undertaken by these organisations showed any association with the amount they spent in providing a central resource for methodological support for their researchers. CONCLUSION: The promotion and delivery of high quality health research requires that organisations hosting health research and their academic partners put in place funding and systems to provide appropriate methodological support to ensure valid research findings. If resources are limited, health researchers may have to rely on short courses and/or a limited number of advisory sessions which may not always produce satisfactory results

Epidermal Notch1 recruits RORγ+ group 3 innate lymphoid cells to orchestrate normal skin repair

Notch has a well-defined role in controlling cell fate decisions in the embryo and the adult epidermis and immune systems, yet emerging evidence suggests Notch also directs non-cell-autonomous signalling in adult tissues. Here, we show that Notch1 works as a damage response signal. Epidermal Notch induces recruitment of immune cell subsets including RORγ + ILC3s into wounded dermis; RORγ + ILC3s are potent sources of IL17F in wounds and control immunological and epidermal cell responses. Mice deficient for RORγ + ILC3s heal wounds poorly resulting from delayed epidermal proliferation and macrophage recruitment in a CCL3-dependent process. Notch1 upregulates TNFα and the ILC3 recruitment chemokines CCL20 and CXCL13. TNFα, as a Notch1 effector, directs ILC3 localization and rates of wound healing. Altogether these findings suggest that Notch is a key stress/injury signal in skin epithelium driving innate immune cell recruitment and normal skin tissue repair

Estimation of required sample size for external validation of risk models for binary outcomes

Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is choosing an adequate sample size. In this paper, we investigate the sample size requirements for validation studies with binary outcomes to estimate measures of predictive performance (C-statistic for discrimination and calibration slope and calibration in the large). We aim for sufficient precision in the estimated measures. In addition, we investigate the sample size to achieve sufficient power to detect a difference from a target value. Under normality assumptions on the distribution of the linear predictor, we obtain simple estimators for sample size calculations based on the measures above. Simulation studies show that the estimators perform well for common values of the C-statistic and outcome prevalence when the linear predictor is marginally Normal. Their performance deteriorates only slightly when the normality assumptions are violated. We also propose estimators which do not require normality assumptions but require specification of the marginal distribution of the linear predictor and require the use of numerical integration. These estimators were also seen to perform very well under marginal normality. Our sample size equations require a specified standard error (SE) and the anticipated C-statistic and outcome prevalence. The sample size requirement varies according to the prognostic strength of the model, outcome prevalence, choice of the performance measure and study objective. For example, to achieve an SE < 0.025 for the C-statistic, 60–170 events are required if the true C-statistic and outcome prevalence are between 0.64–0.85 and 0.05–0.3, respectively. For the calibration slope and calibration in the large, achieving SE < 0.15 would require 40–280 and 50–100 events, respectively. Our estimators may also be used for survival outcomes when the proportion of censored observations is high

Spectroscopic and Mechanistic Studies of Heterodimetallic Forms of Metallo-β-lactamase NDM-1

In an effort to characterize the roles of each metal ion in metallo-β-lactamase NDM-1, heterodimetallic analogues (CoCo-, ZnCo-, and CoCd-) of the enzyme were generated and characterized. UV–vis, 1H NMR, EPR, and EXAFS spectroscopies were used to confirm the fidelity of the metal substitutions, including the presence of a homogeneous, heterodimetallic cluster, with a single-atom bridge. This marks the first preparation of a metallo-β-lactamase selectively substituted with a paramagnetic metal ion, Co(II), either in the Zn1 (CoCd-NDM-1) or in the Zn2 site (ZnCo-NDM-1), as well as both (CoCo-NDM-1). We then used these metal-substituted forms of the enzyme to probe the reaction mechanism, using steady-state and stopped-flow kinetics, stopped-flow fluorescence, and rapid-freeze-quench EPR. Both metal sites show significant effects on the kinetic constants, and both paramagnetic variants (CoCd- and ZnCo-NDM-1) showed significant structural changes on reaction with substrate. These changes are discussed in terms of a minimal kinetic mechanism that incorporates all of the data