Distributive randomization: a pragmatic fractional factorial design to screen or evaluate multiple simultaneous interventions in a clinical trial.

BACKGROUND: In some medical indications, numerous interventions have a weak presumption of efficacy, but a good track record or presumption of safety. This makes it feasible to evaluate them simultaneously. This study evaluates a pragmatic fractional factorial trial design that randomly allocates a pre-specified number of interventions to each participant, and statistically tests main intervention effects. We compare it to factorial trials, parallel-arm trials and multiple head-to-head trials, and derive some good practices for its design and analysis. METHODS: We simulated various scenarios involving 4 to 20 candidate interventions among which 2 to 8 could be simultaneously allocated. A binary outcome was assumed. One or two interventions were assumed effective, with various interactions (positive, negative, none). Efficient combinatorics algorithms were created. Sample sizes and power were obtained by simulations in which the statistical test was either difference of proportions or multivariate logistic regression Wald test with or without interaction terms for adjustment, with Bonferroni multiplicity-adjusted alpha risk for both. Native R code is provided without need for compiling or packages. RESULTS: Distributive trials reduce sample sizes 2- to sevenfold compared to parallel arm trials, and increase them 1- to twofold compared to factorial trials, mostly when fewer allocations than for the factorial design are possible. An unexpectedly effective intervention causes small decreases in power (< 10%) if its effect is additive, but large decreases (possibly down to 0) if not, as for factorial designs. These large decreases are prevented by using interaction terms to adjust the analysis, but these additional estimands have a sample size cost and are better pre-specified. The issue can also be managed by adding a true control arm without any intervention. CONCLUSION: Distributive randomization is a viable design for mass parallel evaluation of interventions in constrained trial populations. It should be introduced first in clinical settings where many undercharacterized interventions are potentially available, such as disease prevention strategies, digital behavioral interventions, dietary supplements for chronic conditions, or emerging diseases. Pre-trial simulations are recommended, for which tools are provided.

Measuring and correcting staff variability in large-scale OSCEs.

CONTEXT: Objective Structured Clinical Examinations (OSCEs) are an increasingly popular evaluation modality for medical students. While the face-to-face interaction allows for more in-depth assessment, it may cause standardization problems. Methods to quantify, limit or adjust for examiner effects are needed. METHODS: Data originated from 3 OSCEs undergone by 900-student classes of 5th- and 6th-year medical students at Université Paris Cité in the 2022-2023 academic year. Sessions had five stations each, and one of the three sessions was scored by consensus by two raters (rather than one). We report OSCEs' longitudinal consistency for one of the classes and staff-related and student variability by session. We also propose a statistical method to adjust for inter-rater variability by deriving a statistical random student effect that accounts for staff-related and station random effects. RESULTS: From the four sessions, a total of 16,910 station scores were collected from 2615 student sessions, with two of the sessions undergone by the same students, and 36, 36, 35 and 20 distinct staff teams in each station for each session. Scores had staff-related heterogeneity (p<10-15), with staff-level standard errors approximately doubled compared to chance. With mixed models, staff-related heterogeneity explained respectively 11.4%, 11.6%, and 4.7% of station score variance (95% confidence intervals, 9.5-13.8, 9.7-14.1, and 3.9-5.8, respectively) with 1, 1 and 2 raters, suggesting a moderating effect of consensus grading. Student random effects explained a small proportion of variance, respectively 8.8%, 11.3%, and 9.6% (8.0-9.7, 10.3-12.4, and 8.7-10.5), and this low amount of signal resulted in student rankings being no more consistent over time with this metric, rather than with average scores (p=0.45). CONCLUSION: Staff variability impacts OSCE scores as much as student variability, and the former can be reduced with dual assessment or adjusted for with mixed models. Both are small compared to unmeasured sources of variability, making them difficult to capture consistently.

Outbreak of Achromobacter xylosoxidans and Ochrobactrum anthropi Infections after Prostate Biopsies, France, 2014.

We report an outbreak of healthcare-associated prostatitis involving rare environmental pathogens in immunocompetent patients undergoing transrectal prostate biopsies at Hôpital Édouard Herriot (Lyon, France) during August 13-October 10, 2014. Despite a fluoroquinolone-based prophylaxis, 5 patients were infected with Achromobacter xylosoxidans and 3 with Ochrobactrum anthropi, which has not been reported as pathogenic in nonimmunocompromised persons. All patients recovered fully. Analysis of the outbreak included case investigation, case-control study, biopsy procedure review, microbiologic testing of environmental and clinical samples, and retrospective review of hospital records for 4 years before the outbreak. The cases resulted from asepsis errors during preparation of materials for the biopsies. A low-level outbreak involving environmental bacteria was likely present for years, masked by antimicrobial drug prophylaxis and a low number of cases. Healthcare personnel should promptly report unusual pathogens in immunocompetent patients to infection control units, and guidelines should explicitly mention asepsis during materials preparation.

Targeting VEGFR1 on endothelial progenitors modulates their differentiation potential.

OBJECTIVES: We studied whether plasma levels of angiogenic factors VEGF and placental growth factor (PlGF) in coronary artery disease patients or undergoing cardiac surgery are modified, and whether those factors modulate endothelial progenitor's angiogenic potential. METHODS AND RESULTS: A total of 143 patients' plasmas from two different studies were analyzed (30 coronary artery disease patients, 30 patients with stable angina, coupled with 30 age and sex-matched controls; 53 patients underwent cardiac surgery). Among factors screened, only PlGF was found significantly increased in these pathological populations. PlGF-1 and PlGF-2 were then tested on human endothelial-colony-forming cells (ECFCs). We found that PlGF-1 and PlGF-2 induce VEGFR1 phosphorylation and potentiate ECFCs tubulogenesis in vitro. ECFCs VEGFR1 was further inhibited using a specific small interfering RNA (siRNA) and the chemical compound 4321. We then observed that the VEGFR1-siRNA and the compound 4321 decrease ECFCs tubulogenesis potential in vitro. Finally, we tested the compound 4321 in the preclinical Matrigel(®)-plug model with C57Bl/6J mice as well as in the murine hindlimb ischemia model. We found that 4321 inhibited the plug vascularization, attested by the hemoglobin content and the VE-Cadherin expression level and that 4321 inhibited the post-ischemic revascularization. CONCLUSION: PlGF plasma levels were found increased in cardiovascular patients. Disrupting PlGF/VEGFR1 pathway could modulate ECFC-induced tubulogenesis, the cell type responsible for newly formed vessels in vivo.

Sex differences and outcomes in surgical infective endocarditis.

BACKGROUND: Cardiac surgery for infective endocarditis (IE) is associated with significant hospital mortality, and female sex may be associated with worse outcomes. However, the impact of sex on the presenting characteristics, management, and outcomes of patients operated on for acute infective endocarditis (IE) has not been adequately studied. OBJECTIVES: The goal of our study was to analyse differences in management and outcome of IE between women and men who undergo surgery. METHODS: Clinical data of 717 patients undergoing cardiac surgery for IE between December 2005 and December 2019 were prospectively collected. Sex-related postoperative outcomes including in-hospital mortality were recorded. Univariable and multivariable analyses were performed to identify potential sex-related determinant of in-hospital mortality. RESULTS: In all, 532 male patients (74.2%) and 185 female patients (25.8%) underwent surgery for IE. At baseline, women had more frequent mitral regurgitation with 63 patients (34.1%) than men with 135 patients (25.4%) (P = 0.002). Female sex was associated with higher in-hospital mortality (23.2% versus 17.3%, P = 0.049). However, multivariable analysis revealed age (P < 0.01), antibiotics < 7 days before surgery (P = 0.01) and staphylococcal IE (P < 0.01) but not female sex (P = 0.99) as independent determinants of hospital mortality. CONCLUSIONS: In this study of patients operated-on for IE, female sex was associated with more severe manifestations of IE and significantly higher in-hospital mortality. However, after multivariable analysis, initial presentation, but not sex, seemed to determine clinical outcomes.

Thrombin receptor PAR1 silencing in endothelial colony-forming cells modifies stemness and vasculogenic properties.

BACKGROUND: The involvement of thrombin receptor PAR1 in blood vessel development has been largely demonstrated in knockout mice; however, its implication in adult mouse angiogenesis seems very moderate. OBJECTIVES: We aimed to explore the potential relationships between PAR1, stemness, and angiogenic properties of human endothelial colony-forming cells (ECFCs). METHODS AND RESULTS: PAR1 activation on ECFCs using the selective PAR1-activating peptide induced a significant decrease in CD133 expression (RTQ-PCR analysis). In line, silencing of PAR1 gene expression with siRNA increased CD133 mRNA as well as intracellular CD133 protein expression. To confirm the link between CD133 and PAR1, we explored the association between PAR1 and CD133 levels in fast and slow fibroblasts prone to reprogramming. An imbalance between PAR1 and CD133 levels was evidenced, with a decreased expression of PAR1 in fast reprogramming fibroblasts expressing a high CD133 level. Regarding in vitro ECFC angiogenic properties, PAR1 silencing with specific siRNA induced cell proliferation evidenced by the overexpression of Ki67. However, it did not impact migration properties nor ECFC adhesion on smooth muscle cells or human arterial endothelial cells. In a mouse model of hind-limb ischemia, PAR1 silencing in ECFCs significantly increased postischemic revascularization compared to siCtrl-ECFCs along with a significant increase in cutaneous blood flows (P < .0001), microvessel density (P = .02), myofiber regeneration (P < .0001), and human endothelial cell incorporation in muscle (P < .0001). CONCLUSION: In conclusion, our work describes for the first time a link between PAR1, stemness, and vasculogenesis in human ECFCs.

Effect of data validation audit on hospital mortality ranking and pay for performance.

BACKGROUND: Quality improvement and epidemiology studies often rely on database codes to measure performance or impact of adjusted risk factors, but how validity issues can bias those estimates is seldom quantified. OBJECTIVES: To evaluate whether and how much interhospital administrative coding variations influence a typical performance measure (adjusted mortality) and potential incentives based on it. DESIGN: National cross-sectional study comparing hospital mortality ranking and simulated pay-for-performance incentives before/after recoding discharge abstracts using medical records. SETTING: Twenty-four public and private hospitals located in France PARTICIPANTS: All inpatient stays from the 78 deadliest diagnosis-related groups over 1 year. INTERVENTIONS: Elixhauser and Charlson comorbidities were derived, and mortality ratios were computed for each hospital. Thirty random stays per hospital were then recoded by two central reviewers and used in a Bayesian hierarchical model to estimate hospital-specific and comorbidity-specific predictive values. Simulations then estimated shifts in adjusted mortality and proportion of incentives that would be unfairly distributed by a typical pay-for-performance programme in this situation. MAIN OUTCOME MEASURES: Positive and negative predictive values of routine coding of comorbidities in hospital databases, variations in hospitals' mortality league table and proportion of unfair incentives. RESULTS: A total of 70 402 hospital discharge abstracts were analysed, of which 715 were recoded from full medical records. Hospital comorbidity-level positive predictive values ranged from 64.4% to 96.4% and negative ones from 88.0% to 99.9%. Using Elixhauser comorbidities for adjustment, 70.3% of hospitals changed position in the mortality league table after correction, which added up to a mean 6.5% (SD 3.6) of a total pay-for-performance budget being allocated to the wrong hospitals. Using Charlson, 61.5% of hospitals changed position, with 7.3% (SD 4.0) budget misallocation. CONCLUSIONS: Variations in administrative data coding can bias mortality comparisons and budget allocation across hospitals. Such heterogeneity in data validity may be corrected using a centralised coding strategy from a random sample of observations.

In Silico Evaluation of Pharmacokinetic Optimization for Antimitogram-Based Clinical Trials.

Antimitograms are prototype in vitro tests for evaluating chemotherapeutic efficacy using patient-derived primary cancer cells. These tests might help optimize treatment from a pharmacodynamic standpoint by guiding treatment selection. However, they are technically challenging and require refinements and trials to demonstrate benefit to be widely used. In this study, we performed simulations aimed at exploring how to validate antimitograms and how to complement them by pharmacokinetic optimization. A generic model of advanced cancer, including pharmacokinetic-pharmacodynamic monitoring, was used to link dosing schedules with progression-free survival (PFS), as built from previously validated modules. This model was used to explore different possible situations in terms of pharmacokinetic variability, pharmacodynamic variability, and antimitogram performance. The model recapitulated tumor dynamics and standalone therapeutic drug monitoring efficacy consistent with published clinical results. Simulations showed that combining pharmacokinetic and pharmacodynamic optimization should increase PFS in a synergistic fashion. Simulated data were then used to compute required clinical trial sizes, which were 30% to 90% smaller when pharmacokinetic optimization was added to pharmacodynamic optimization. This improvement was observed even when pharmacokinetic optimization alone exhibited only modest benefit. Overall, our work illustrates the synergy derived from combining antimitograms with therapeutic drug monitoring, permitting a disproportionate reduction of the trial size required to prove a benefit on PFS. Accordingly, we suggest that strategies with benefits too small for standalone clinical trials could be validated in combination in a similar manner.Significance: This work offers a method to reduce the number of patients needed for a clinical trial to prove the hypothesized benefit of a drug to progression-free survival, possibly easing opportunities to evaluate combinations. Cancer Res; 78(7); 1873-82. ©2018 AACR.

Vaccination of healthcare workers: A review.

Vaccine-preventable diseases are a significant cause of morbidity and mortality. As new vaccines are proving to be effective and as the incidence of some infections decreases, vaccination practices are changing. Healthcare workers (HCWs) are particularly exposed to and play a role in nosocomial transmission, which makes them an important target group for vaccination. Most vaccine-preventable diseases still carry a significant risk of resurgence and have caused outbreaks in recent years. While many professional societies favor vaccination of HCWs as well as the general population, recommendations differ from country to country. In turn, vaccination coverage varies widely for each microorganism and for each country, making hospitals and clinics vulnerable to outbreaks. Vaccine mandates and non-mandatory strategies are the subject of ongoing research and controversies. Optimal approaches to increase coverage and turn the healthcare workforce into an efficient barrier against infectious diseases are still being debated.