Serum cytokine panels in pediatric clinical practice.

BACKGROUND: Cytokines are soluble signaling proteins that regulate inflammation and coordinate immune responses. Serum cytokine panels are increasingly used in medical practice, yet our understanding of cytokines as biomarkers for disease remains limited. OBJECTIVE: We sought to analyze real-world single-center use of a multiplexed cytokine panel, correlate its results with diagnosis and severity, and explore its use in pediatric practice. METHODS: A multiplexed cytokine panel, able to return same-day results, was implemented in April 2020 at the Children's Hospital of Philadelphia (Philadelphia, Pa) and its performance was validated for clinical use. Coded patient data were collected using the REDCap database, and correlations between cytokine levels and outcomes of interest were analyzed retrospectively. RESULTS: Cytokine levels correlate with acuity of care, with patients admitted to the pediatric intensive care unit having the highest cytokine values. Patients with familial hemophagocytic lymphohistiocytosis (fHLH) showed prominent peaks in IFN-γ, IL-10, and TNF, whereas patients with sepsis exhibited high IL-6 and IL-8 with relatively modest IFN-γ. Cytokine release syndrome (CRS) after chimeric antigen receptor T-cell therapy often demonstrated pan-panel positivity at peak levels, with a similar pattern as that of fHLH. A ratio of [IFN-γ] + [IL-10]/[IL-6] + [IL-8] levels was able to distinguish fHLH and CRS from severe sepsis. CONCLUSIONS: Cytokine levels correlate with severity of illness and can help differentiate between syndromes that present similarly, including fHLH and CRS compared with sepsis. Cytokine panels can be used as biomarkers to inform diagnosis and management decisions, but significant work remains to dissect complex clinical patterns of disease.

Amyloid-DNA Composites of Bacterial Biofilms Stimulate Autoimmunity.

Research on the human microbiome has established that commensal and pathogenic bacteria can influence obesity, cancer, and autoimmunity through mechanisms mostly unknown. We found that a component of bacterial biofilms, the amyloid protein curli, irreversibly formed fibers with bacterial DNA during biofilm formation. This interaction accelerated amyloid polymerization and created potent immunogenic complexes that activated immune cells, including dendritic cells, to produce cytokines such as type I interferons, which are pathogenic in systemic lupus erythematosus (SLE). When given systemically, curli-DNA composites triggered immune activation and production of autoantibodies in lupus-prone and wild-type mice. We also found that the infection of lupus-prone mice with curli-producing bacteria triggered higher autoantibody titers compared to curli-deficient bacteria. These data provide a mechanism by which the microbiome and biofilm-producing enteric infections may contribute to the progression of SLE and point to a potential molecular target for treatment of autoimmunity.

Medical Malpractice Claims Related to Performance of Transesophageal Echocardiography by Anesthesiologists.

More than 300,000 adults have cardiac surgery in the United States annually, and most undergo intraoperative transesophageal echocardiography (TEE). This patient population is often older with multiple comorbidities, increasing their risk for complications for even routine procedures. Major morbidity or mortality caused by TEE is rare, and it is unknown how often such complications lead to malpractice lawsuits. The authors identified 13 cases out of 2,564 in a closed claims database that involved TEE and reviewed their etiology. Esophageal injury accounted for most of the suits, and only 2 were related to diagnosis. Most expert reviews deemed the care provided by the anesthesiologist to be appropriate.

Variation in Hospitalization Costs, Charges, and Lengths of Hospital Stay for Coronavirus Disease 2019 Patients Treated With Venovenous Extracorporeal Membrane Oxygenation in the United States: A Cohort Study.

OBJECTIVES: The aim was to characterize hospitalization costs, charges, and lengths of hospital stay for COVID-19 patients treated with venovenous (VV) extracorporeal membrane oxygenation (ECMO) in the United States during 2020. Secondarily, differences in hospitalization costs, charges, and lengths of hospital stay were explored based on hospital-level factors. DESIGN: Retrospective cohort study. SETTING: Multiple hospitals in the United States. PARTICIPANTS: Adult patients with COVID-19 who were on VV ECMO in 2020 and had data in the national inpatient sample. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Demographics and baseline comorbidities were recorded for patients. Primary study outcomes were hospitalization costs, charges, and lengths of hospital stay. Study outcomes were compared after stratification by hospital region, bed size, and for-profit status. The median hospitalization cost for the 3,315-patient weighted cohort was $200,300 ($99,623, $338,062). Median hospitalization charges were $870,513 ($438,228, $1,553,157), and the median length of hospital stay was 30 days (17, 46). Survival to discharge was 54.4% for all patients in the cohort. Median hospitalization cost differed by region (p = 0.01), bed size (p < 0.001), and for-profit status (p = 0.02). Median hospitalization charges also differed by region (p = 0.04), bed size (p = 0.002), and for-profit status (p < 0.001). Length of hospital stay differed by region (p = 0.03) and bed size (p < 0.001), but not for-profit status (p = 0.40). Hospitalization costs were the lowest, and charges were highest in private-for-profit hospitals. Large hospitals also had higher costs, charges, and hospital stay lengths than small hospitals. CONCLUSIONS: In this retrospective cohort study, hospitalization costs and charges for patients with COVID-19 on VV ECMO were found to be substantial but similar to what has been reported previously for patients without COVID-19 on VV ECMO. Significant variation was observed in costs, charges, and lengths of hospital stay based on hospital-level factors.

Presenting Risks and Benefits: Helping the Data Monitoring Committee Do Its Job.

Data monitoring committees (DMCs), or data and safety monitoring boards, protect clinical trial participants by conducting benefit-risk assessments during the course of a clinical trial. These evaluations may be improved by broader access to data and more effective analyses and presentation. Data monitoring committees should have access to all data, including efficacy data, at each interim review. The DMC reports should include graphical presentations that summarize benefits and harms in efficient ways. Benefit-risk assessments should include summaries that are consistent with the intention-to-treat principle and have a pragmatic focus. This article provides examples of graphical summaries that integrate benefits and harms, and proposes that such summaries become standard in DMC reports.

An additive boundary for group sequential designs with connection to conditional error.

Group sequential designs allow stopping a clinical trial for meeting its efficacy objectives based on interim evaluation of the accumulating data. Various methods to determine group sequential boundaries that control the probability of crossing the boundary at an interim or the final analysis have been proposed. To monitor trials with uncertainty in group sizes at each analysis, error spending functions are often used to derive stopping boundaries. Although flexible, most spending functions are generic increasing functions with parameters that are difficult to interpret. They are often selected arbitrarily, sometimes using trial and error, so that the corresponding boundaries approximate the desired behavior numerically. Lan and DeMets proposed a spending function that approximates in a natural way the O'Brien-Fleming boundary based on the Brownian motion process. We extend this approach to a general family that has an additive boundary for the Brownian motion process. The spending function and the group sequential boundary share a common parameter that regulates how fast the error is spent. Three subfamilies are considered with different additive terms. In the first subfamily, the parameter has an interpretation as the conditional error rate, which is the conditional probability to reject the null hypothesis at the final analysis. This parameter also provides a connection between group sequential and adaptive design methodology. More choices of designs are allowed in the other two subfamilies. Numerical results are provided to illustrate flexibility and interpretability of the proposed procedures. A clinical trial is described to illustrate the utility of conditional error in boundary determination.

The changing landscape of data monitoring committees-Perspectives from regulators, members, and sponsors.

Data Monitoring Committees (DMCs) are an integral part of clinical drug development. Their use has evolved along with changing study designs and regulatory expectations, which has associated statistical and ethical implications. Although there is guidance from the different regulatory agencies, there are opportunities to bring more consistency to address practical issues of establishing and operating a DMC. Challenging issues include defining the scope of DMC decisions, the regulatory requirements and expectations, the perceived independence of DMCs, the specific focus primarily on safety, etc. Wider use of adaptive clinical trial designs in recent years introduce additional challenges in terms of trial governance and the complexity of DMC activities. A panel comprised of clinical and statistical experts from across academia, industry, and regulatory agencies shared their experience and thoughts on the importance of these aspects and offered perspectives on the future of the DMCs. This paper documents the thinking from the panel session at the CEN-ISBS conference held in Vienna, Austria, 2017.

Adaptive designs: The Swiss Army knife among clinical trial designs?

There has been considerable progress in the development and implementation of adaptive designs over the past 30 years. A major driver for this class of novel designs is the possibility to increase the information value of clinical trial data to enable better decisions, leading to more efficient drug development processes and improved late-stage success rates. In the first part of this article, we review the development of adaptive designs from different perspectives. We trace back key historical papers, report on landmark adaptive design clinical trials, review major cross-industry collaborations, and highlight key regulatory guidance documents. In the second, more technical part of this article, we address the question of whether it is possible to define factors which guide the choice between a fixed or an adaptive design for a given trial. We show that in non-linear regression models with a moderate variance of the responses, the first-stage sample size of an adaptive design should be chosen sufficiently large in order to address variability in the interim parameter estimate. In conclusion, the choice between an adaptive and a fixed design depends in a sensitive manner on the specific statistical problem under investigation.

Simultaneous inference on treatment effects in survival studies with factorial designs.

A clinical trial with a 2×2 factorial design involves randomization of subjects to treatment A or A‾ and, within each group, further randomization to treatment B or B‾. Under this design, one can assess the effects of treatments A and B on a clinical endpoint using all patients. One may additionally compare treatment A, treatment B, or combination therapy AB to A‾B‾. With multiple comparisons, however, it may be desirable to control the overall type I error, especially for regulatory purposes. Because the subjects overlap in the comparisons, the test statistics are generally correlated. By accounting for the correlations, one can achieve higher statistical power compared to the conventional Bonferroni correction. Herein, we derive the correlation between any two (stratified or unstratified) log-rank statistics for a 2×2 factorial design with a survival time endpoint, such that the overall type I error for multiple treatment comparisons can be properly controlled. In addition, we allow for adjustment of prognostic factors in the treatment comparisons and conduct simultaneous inference on the effect sizes. We use simulation studies to show that the proposed methods perform well in realistic situations. We then provide an application to a recently completed randomized controlled clinical trial on alcohol dependence. Finally, we discuss extensions of our approach to other factorial designs and multiple endpoints.

Detecting type 2 diabetes and prediabetes among asymptomatic adults in the United States: modeling American Diabetes Association versus US Preventive Services Task Force diabetes screening guidelines.

BACKGROUND: Screening to detect prediabetes and diabetes enables early prevention and intervention. This study describes the number and characteristics of asymptomatic, undiagnosed adults in the United States who could be detected with prediabetes and type 2 diabetes using the American Diabetes Association (ADA) guidelines compared to the United States Preventive Services Task Force (USPSTF) guidelines. METHODS: We developed predictive models for undiagnosed diabetes and prediabetes using polytomous logistic regression from data on risk factors in the 2003-2010 National Health and Nutrition Examination Survey (n = 19,056). We applied these predictive models to the 2010 Medical Expenditure Panel Survey, which contains health care use data, to generate probabilities of undiagnosed diabetes and undetected prediabetes for each adult. We summed individual probabilities to estimate the number of adults who would be detected with prediabetes and/or type 2 diabetes if screened under ADA or USPSTF guidelines. We analyzed health care use patterns of people at high risk for diabetes. RESULTS: In 2010, 59.1 million adults met the USPSTF screening criteria including 24.4 million people with undetected prediabetes and 3.7 million people with undiagnosed diabetes. In comparison, among the 86.3 million people who met the ADA screening criteria, there were 33.9 million with undetected prediabetes and 4.6 million with undiagnosed type 2 diabetes. The ADA guidelines detected 38.9% more cases of prediabetes and 24.3% more cases of type 2 diabetes compared to the USPSTF guidelines. Subgroup analysis showed that ADA guidelines would detect 78% more cases of diabetes among the age 54 and younger population, in 40% more blacks, and in more than twice as many Hispanics than USPSTF guidelines. Only 58% of adults meeting ADA guidelines and 70% meeting USPSTF guidelines had ≥ 1 primary care office visit in 2010. CONCLUSIONS: Compared to USPSTF guidelines, ADA guidelines would screen more people and detect more cases of both prediabetes and type 2 diabetes, though a substantial percentage of patients with undetected cases had no contact with a primary care provider in 2010. Addressing the problem of large numbers of undetected prediabetes and type 2 diabetes cases will require new strategies for screening.

Alternative views on setting clinical trial futility criteria.

A feature increasingly utilized in clinical trial practice is to allow a study to stop early when it seems unlikely to achieve its primary efficacy objectives. This is commonly referred to as stopping for futility, and can be motivated by ethical and financial considerations. A number of methods for addressing futility have been described in the literature, including rules based upon conditional power, predictive probability, beta spending functions, and others. We consider futility stopping from the point of view of quantifying and providing an objective sensible balance between risks of incorrect decisions (e.g., stopping trials which should continue, and continuing trials which should stop), and discuss how specific considerations within a trial can lead to choice of a sensible scheme. This approach is not specific to any particular scales in the literature such as those just mentioned, and we describe interrelationships among criteria expressed on different scales. As futility may be evaluated multiple times in a long-term trial and the amount of information available at scheduled interim analyses may be difficult to predict in advance, we present a specific optimality criterion and discuss which of the familiar scales tend to produce schemes simple to describe and implement, and with better behavior across different timepoints at which futility might be evaluated.

EGFR-ErbB2 dual kinase inhibitor lapatinib decreases autoantibody levels and worsens renal disease in Interferon α-accelerated murine lupus.

Glomerulonephritis remains a major cause of morbidity and mortality in systemic lupus erythematosus (SLE). We have reported that expression of HER2/ErbB2, a member of the EGFR family, is increased in kidneys of patients and mice with lupus nephritis. We therefore asked if EGFR-family inhibition could ameliorate murine lupus nephritis. We used lapatinib, an EGFR-ErbB2 dual kinase inhibitor in female lupus-prone NZBxW/F1 mice, in which lupus onset was accelerated by injecting an IFN-α-expressing adenovirus. Mice received lapatinib (75 mg/Kg) or vehicle from the beginning of the acceleration or after the mice developed severe proteinuria (>300 mg/dL). Autoantibodies, kidney disease and markers of fibrosis and wound healing were analyzed. Exposure to IFNα induced ErbB2 expression in the kidney of lupus prone mice. Lapatinib, administered before but not after renal disease onset, lowered autoantibody titers and lessened immune complex deposition in the kidney. However, lapatinib increased proteinuria, kidney fibrosis and mouse mortality. Lapatinib also inhibited an in vitro wound healing assay testing renal cells. Our results suggest that EGFR-ErbB2 dual kinase inhibitor lapatinib decreases autoimmunity but worsens renal disease in IFNα-accelerated lupus, by increasing fibrosis and inhibiting wound healing. Type I Interferons are highlighted as important regulators of HER2/ErbB2 expression in the kidney. Further studies are required to parse the beneficial aspects of EGFR inhibition on autoimmunity from its negative effects on wound healing in lupus nephritis.

The Protective Role of Transcription Factor Nrf2 in Murine Macrophage Activation Syndrome.

OBJECTIVE: Macrophage activation syndrome (MAS) is characterized by multi-lineage cytopenias, hypercytokinemia, and tissue hemophagocytosis. Transcription factor Nrf2 is a master regulator of redox homeostasis. In this work we aim to investigate the role of Nrf2 in murine hyperinflammation and the mechanisms by which Nrf2 activation by red blood cell products regulates pro-inflammatory cytokine production. METHODS: We induce murine MAS in wildtype and Nrf2 knockout (Nrf2 -/-) mice by repeat administration of TLR9-agonist CpG. Clinical and biochemical markers of disease were measured including complete blood counts, liver and spleen pathology, serum free heme, ferritin, and cytokine profiles. In vitro bone marrow derived macrophages and dendritic cells were used to investigate regulation of CpG-induced cytokine expression by oxidized red blood cells and hemin. RESULTS: Patients with hyperinflammatory disease have higher levels of Nrf2 gene expression. Mice with CpG-induced hyperinflammation have elevated systemic lipid peroxidation which is exacerbated in Nrf2 -/- mice. Compared to wildtype controls, Nrf2 -/- mice develop significantly worse organomegaly, organ pathology, and reticulocytosis. Nrf2 -/- mice have exacerbated hypercytokinemia in cytokines central MAS physiology: IL-12, IFNg, and IL-10. In vitro we found that oxidized red blood cell lysates and hemin are able to suppress IL-12 transcription and protein production from bone marrow derived dendritic cells in a Nrf2-dependent manner. CONCLUSION: Together our findings show that transcription factor Nrf2 is highly expressed in patients with hyperinflammatory disease and demonstrate a protective role for Nrf2 in a murine model of MAS in part due to Nrf2-mediated suppression of proinflammatory cytokine production.

Modeling the indirect economic implications of musculoskeletal disorders and treatment.

BACKGROUND: Musculoskeletal disorders impose a substantial economic burden on American society, but few studies have examined the economic benefits associated with treating such disorders. The purpose of this research is to estimate the indirect economic implications of activity limitations associated with musculoskeletal disorders and to quantifying the potential economic gains from elective surgery to treat arthritis of the knee and hip. METHODS: Using regression analysis with the National Health Interview Survey (2004-2010 data, n=185,829 adults) we quantify the relationship between severity of activity limitations (walking, sitting, standing, etc.) and employment, household income, missed work days, and receipt of supplemental security income for disability. Activity limitations are combined to create an index similar to the Functional Ability Index from the Short Form 36 Health Questionnaire (SF-36) often used in clinical trials to measure patient functional mobility. This index is included in the regression analyses. We use data from published, prospective clinical trials to establish the improvement in patient functional ability following surgery to treat arthritis of the knee and hip. RESULTS: Improved physical function is associated with higher likelihood of employment, higher household income and fewer missed work days for those who are employed, and reduced likelihood of receiving supplemental security income for disability. The magnitude of the impact and statistical significance vary by activity limitation and severity. Each percentage point increase in the index value is associated with a 2-percentage-point increase in the odds of being employed, a 3-percentage-point-day decline in work days missed and an additional $180 in annual household income if employed, and a 2-percentage-point decline in the odds of receiving supplemental security income for disability. All estimates are statistically significant at the 0.05 level. CONCLUSIONS: Using a large, representative sample of non-institutionalized adults in the U.S., we find that physical activity limitations are associated with worse economic outcomes across multiple economic metrics. Combined with estimates of improved functional ability following knee and hip surgery, we quantify some of the economic benefits of surgery for arthritis of the knee and hip. This information helps improve understanding of the societal benefits of medical treatment for musculoskeletal conditions.

Graphical assessment of consistency in treatment effect among countries in multi-regional clinical trials.

BACKGROUND: One key objective of a multi-regional clinical trial (MRCT) is to use the trial results to 'bridge' from the global level to local region in support of local registrations. However, data from each individual country are typically limited and the large number of countries will increase the chance of false positive findings. PURPOSE: Graphical tools to facilitate identification of potential outlying countries could be useful for country-level assessment. Existing methods such as funnel plot and expected range of treatment effect can substantially increase the false positive rate. The expected range approach can also have a very low power when there are a large number of small countries, which is typical in a MRCT. METHODS: In this article, we apply normal probability plots, commonly used as a diagnostic tool in linear regression analysis, to assess the differences among countries. Evidence of possible inconsistency, which incorporates both the estimated treatment effect and sample size, is plotted against its expected order statistic. RESULTS: A simulation study is conducted to assess the impact of the negative correlation among residuals due to unequal sample sizes among countries and the performance of the proposed methods compared to existing approaches. The proposed methods tend to have a balanced consideration with substantially smaller false positive rate and reasonable probability to identify outlying countries in realistic scenarios. LIMITATIONS: While much lower than that of commonly used methods, the false positive rates of the proposed methods are not strictly controlled. This may be acceptable for these graphical tools with intention to flag potential outliers for investigation. CONCLUSIONS: We recommend routine use of normal probability plots in MRCTs as a tool to identify potential outliers. If the normal probability plot is approximately linear but has heavy tails with a few outlying countries, these potential outliers should be examined carefully to understand the possible reasons.

Challenges in Implementing Futility Schemes, with Reference to Aducanumab.

Stopping an ongoing clinical trial based on an interim analysis that shows poor outcomes, often referred to as a judgment of "futility", is a familiar feature in current clinical trials practice. Interim data can be misleading, and the implications of prematurely terminating a trial that should not stop are severe. It is thus critical that designs allowing futility stopping be planned and implemented carefully and cautiously. A recent Phase III development program for aducanumab in Alzheimer's disease was halted based on a pre-defined futility guideline, yet based upon updated data and closer examination, the terminated studies became the basis for a regulatory submission. Not surprisingly, this situation generated much controversy and discussion. It provides a good basis for illustrating important principles governing the planning and implementation of futility schemes.

An adaptive strategy for assessing regional consistency in multiregional clinical trials.

BACKGROUND: Unexpected regional difference in treatment effect has been reported in recent multiregional clinical trials (MRCTs). This may cause difficulty in interpreting results and can have regulatory implications such as marketing approvals and/or product labels in various markets. Careful consideration of consistency across regions and appropriate plans to address potential regional difference are necessary at the design stage. However, assessment of consistency in treatment effect is generally not the primary objective, and therefore, when there is no strong a priori reason to expect a regional difference, a MRCT is not usually designed to address the regional consistency. Unexpected regional finding may arise and increase the risk of ambiguous or controversial results at the end of the study. PURPOSE: To mitigate this risk, we propose an adaptive strategy for regional assessment based upon accumulated blinded data. METHODS: If review of accumulated blinded data shows unexpectedly severe imbalance in an intrinsic or extrinsic factor, and further assessment indicates that this factor could be a potential effect modifier as supported by biological plausibility or blinded correlation analysis, a stratified regional analysis controlled for this factor may be specified and documented before database lock. RESULTS: The proposed adaptive strategy can help with the interpretation of unexpected regional finding. A recent trial is used to illustrate the approach. LIMITATIONS: Even if the imbalanced factor may appear to explain away the regional difference, establishment of causal effect is usually difficult and requires more involved effort. CONCLUSIONS: This approach, by prespecifying the stratified analysis, can reduce the risk of post hoc exaggerated emphases across many possible exploratory analyses and provide greater confidence in the validity of the conclusions. If a causal effect can be established that the apparent regional difference is likely caused by this intrinsic or extrinsic factor, this prespecified analysis can also help guide clinical practice.

Viewpoints on the FDA draft adaptive designs guidance from the PhRMA working group.

The US Food and Drug Administration has recently released a draft guidance document on adaptive clinical trials. We comment on the document from the particular perspective of the authors as members of a PhRMA working group on this topic, which has interacted with FDA personnel on adaptive trial issue during recent years. We describe the activities and prior work of our working group, and use this as a basis to discuss the content of the guidance document as it relates to several issues of current relevance, such as data monitoring processes, adaptive dose finding, so-called seamless trial designs, and sample size reestimation.

Challenges in Assessing the Impact of the COVID-19 Pandemic on the Integrity and Interpretability of Clinical Trials.

Abstract-The COVID-19 pandemic has a global impact on the conduct of clinical trials of medical products. This article discusses implications of the COVID-19 pandemic on clinical research methodology aspects and provides points to consider to assess and mitigate the risk of seriously compromising the integrity and interpretability of clinical trials. The information in this article will support discussions that need to occur cross-functionally on an ongoing basis to "integrate all available knowledge from the ethical, the medical, and the methodological perspective into decision making." This article aims at facilitating: (i) risk assessments of the impact of the pandemic on trial integrity and interpretability; (ii) identification of the relevant data and information related to the impact of the pandemic on the trial that needs to be collected; (iii) short-term decision making impacting ongoing trial operations; (iv) ongoing monitoring of the trial conduct until completion, including the possible involvement of data monitoring committees, and adequately documenting all measures taken to secure trial integrity throughout and after the pandemic, and (v) proper analysis and interpretation of the eventual interim or final trial data.