PCOM Library / Archive for "Hot Topics in Research"

Category: Hot Topics in Research

Hot Topics: Antimalarial Drug Decreases Covid-19 Patient Survival

Jackie Werner Hot Topics in Research, Infectious Disease, Pharmaceutical Sciences

Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis

Mehra MR, Desai SS, Ruschitzka F, Patel AN. Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: A multinational registry analysis. The Lancet. https://doi.org/10.1016/S0140-6736(20)31180-6.

Background

Hydroxychloroquine or chloroquine, often in combination with a second-generation macrolide, are being widely used for treatment of COVID-19, despite no conclusive evidence of their benefit. Although generally safe when used for approved indications such as autoimmune disease or malaria, the safety and benefit of these treatment regimens are poorly evaluated in COVID-19.

Methods

We did a multinational registry analysis of the use of hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19. The registry comprised data from 671 hospitals in six continents. We included patients hospitalised between Dec 20, 2019, and April 14, 2020, with a positive laboratory finding for SARS-CoV-2. Patients who received one of the treatments of interest within 48 h of diagnosis were included in one of four treatment groups (chloroquine alone, chloroquine with a macrolide, hydroxychloroquine alone, or hydroxychloroquine with a macrolide), and patients who received none of these treatments formed the control group. Patients for whom one of the treatments of interest was initiated more than 48 h after diagnosis or while they were on mechanical ventilation, as well as patients who received remdesivir, were excluded. The main outcomes of interest were in-hospital mortality and the occurrence of de-novo ventricular arrhythmias (non-sustained or sustained ventricular tachycardia or ventricular fibrillation).

Findings

96 032 patients (mean age 53·8 years, 46·3% women) with COVID-19 were hospitalised during the study period and met the inclusion criteria. Of these, 14 888 patients were in the treatment groups (1868 received chloroquine, 3783 received chloroquine with a macrolide, 3016 received hydroxychloroquine, and 6221 received hydroxychloroquine with a macrolide) and 81 144 patients were in the control group. 10 698 (11·1%) patients died in hospital. After controlling for multiple confounding factors (age, sex, race or ethnicity, body-mass index, underlying cardiovascular disease and its risk factors, diabetes, underlying lung disease, smoking, immunosuppressed condition, and baseline disease severity), when compared with mortality in the control group (9·3%), hydroxychloroquine (18·0%; hazard ratio 1·335, 95% CI 1·223–1·457), hydroxychloroquine with a macrolide (23·8%; 1·447, 1·368–1·531), chloroquine (16·4%; 1·365, 1·218–1·531), and chloroquine with a macrolide (22·2%; 1·368, 1·273–1·469) were each independently associated with an increased risk of in-hospital mortality. Compared with the control group (0·3%), hydroxychloroquine (6·1%; 2·369, 1·935–2·900), hydroxychloroquine with a macrolide (8·1%; 5·106, 4·106–5·983), chloroquine (4·3%; 3·561, 2·760–4·596), and chloroquine with a macrolide (6·5%; 4·011, 3·344–4·812) were independently associated with an increased risk of de-novo ventricular arrhythmia during hospitalisation.

Interpretation

We were unable to confirm a benefit of hydroxychloroquine or chloroquine, when used alone or with a macrolide, on in-hospital outcomes for COVID-19. Each of these drug regimens was associated with decreased in-hospital survival and an increased frequency of ventricular arrhythmias when used for treatment of COVID-19.

Hot Topics: Computer Models Could Predict Suicide Risk

Jackie Werner Hot Topics in Research, Psychology and Psychiatry

Validation of an Electronic Health Record–Based Suicide Risk Prediction Modeling Approach Across Multiple Health Care Systems

Barak-Corren Y, Castro VM, Nock MK, et al. Validation of an electronic health Record–Based suicide risk prediction modeling approach across multiple health care systems. JAMA Netw Open. 2020;3(3):e201262. https://doi.org/10.1001/jamanetworkopen.2020.1262.

Importance  Suicide is a leading cause of mortality, with suicide-related deaths increasing in recent years. Automated methods for individualized risk prediction have great potential to address this growing public health threat. To facilitate their adoption, they must first be validated across diverse health care settings.

Objective  To evaluate the generalizability and cross-site performance of a risk prediction method using readily available structured data from electronic health records in predicting incident suicide attempts across multiple, independent, US health care systems.

Design, Setting, and Participants  For this prognostic study, data were extracted from longitudinal electronic health record data comprising International Classification of Diseases, Ninth Revision diagnoses, laboratory test results, procedures codes, and medications for more than 3.7 million patients from 5 independent health care systems participating in the Accessible Research Commons for Health network. Across sites, 6 to 17 years’ worth of data were available, up to 2018. Outcomes were defined by International Classification of Diseases, Ninth Revision codes reflecting incident suicide attempts (with positive predictive value >0.70 according to expert clinician medical record review). Models were trained using naive Bayes classifiers in each of the 5 systems. Models were cross-validated in independent data sets at each site, and performance metrics were calculated. Data analysis was performed from November 2017 to August 2019.

Main Outcomes and Measures  The primary outcome was suicide attempt as defined by a previously validated case definition using International Classification of Diseases, Ninth Revision codes. The accuracy and timeliness of the prediction were measured at each site.

Results  Across the 5 health care systems, of the 3 714 105 patients (2 130 454 female [57.2%]) included in the analysis, 39 162 cases (1.1%) were identified. Predictive features varied by site but, as expected, the most common predictors reflected mental health conditions (eg, borderline personality disorder, with odds ratios of 8.1-12.9, and bipolar disorder, with odds ratios of 0.9-9.1) and substance use disorders (eg, drug withdrawal syndrome, with odds ratios of 7.0-12.9). Despite variation in geographical location, demographic characteristics, and population health characteristics, model performance was similar across sites, with areas under the curve ranging from 0.71 (95% CI, 0.70-0.72) to 0.76 (95% CI, 0.75-0.77). Across sites, at a specificity of 90%, the models detected a mean of 38% of cases a mean of 2.1 years in advance.

Conclusions and Relevance  Across 5 diverse health care systems, a computationally efficient approach leveraging the full spectrum of structured electronic health record data was able to detect the risk of suicidal behavior in unselected patients. This approach could facilitate the development of clinical decision support tools that inform risk reduction interventions.

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Hot Topics: Reports of Drug Side Effects Inconsistent

Jackie Werner Hot Topics in Research, Lung, Oncology, Pharmaceutical Sciences

Variation in toxicity reporting methods for early phase lung cancer treatment trials at oncology conferences

Simons EA, Smith DE, Gao D, Camidge DR. Variation in toxicity reporting methods for early phase lung cancer treatment trials at oncology conferences. Journal of Thoracic Oncology. https://doi.org/10.1016/j.jtho.2020.04.020.

Introduction

Phase I and II trials provide the initial human safety and tolerability data for new drugs. However, the methods for presenting toxicity data are not standardized. Clinicians often first encounter these data at professional conferences. We sought to characterize how the burden of adverse events (AE) is reported at the largest professional conference in clinical oncology.

Methods

We collected toxicity data from all lung cancer-associated phase I and II trial presentations and posters at the American Society for Clinical Oncology annual meetings 2017-2019. We captured AE features including the minimum incidence utilized for reporting; whether AEs shown were treatment-emergent or treatment-related, grouped by organ system or separated by individual descriptors; whether combined or separated across dose levels when a dose escalation component was included; and whether dose-limiting toxicities, serious AE, dose reduction rules and denominators for laboratory tests were described.

Results

209 trials were analyzed. There was wide variability in toxicity reporting practices. Six different thresholds for reporting AE of any grade were used. Treatment-related AEs were reported twice as frequently as treatment-emergent AEs. Toxicities were as likely to be reported across dose level as by dose level. Terms such as dose-limiting toxicity and serious AE were rarely defined. Dose reduction rules and denominators for laboratory tests were never defined.

Conclusion

Standardization of methods for reporting toxicities could improve the quality and ease of comparability of data on adverse effects in early phase therapeutic trials. A minimal AE data disclosure template is proposed.

Hot Topics: Loss of Smell May Mean Less Severe COVID-19

Jackie Werner Hot Topics in Research, Infectious Disease

Self‐reported olfactory loss associates with outpatient clinical course in Covid‐19

Yan CH, Faraji F, Prajapati DP, Ostrander BT, DeConde AS. Self-reported olfactory loss associates with outpatient clinical course in covid-19. Int Forum Allergy Rhinol. 2020. https://doi.org/10.1002/alr.22592.

Background

Rapid spread of the SARS‐CoV‐2 virus has left many health systems around the world overwhelmed, forcing triaging of scarce medical resources. Identifying indicators of hospital admission for Covid‐19 patients early in the disease course could aid the efficient allocation of medical interventions. Self‐reported olfactory impairment has recently been recognized as a hallmark of Covid‐19 and may be an important predictor of clinical outcome.

Methods

A retrospective review of all patients presenting to a San Diego Hospital system with laboratory‐confirmed positive Covid‐19 infection was conducted with evaluation of olfactory and gustatory function and clinical disease course. Univariable and multivariable logistic regression were performed to identify risk factors for hospital admission and anosmia.

Results

A total of 169 patients tested positive for Covid‐19 disease between March 3 and April 8, 2020. Olfactory and gustatory data were obtained for 128/169 (75.7%) subjects of which 26/128 (20.1%) required hospitalization. Admission for Covid‐19 was associated with intact sense of smell and taste, increased age, diabetes, as well as subjective and objective parameters associated with respiratory failure. On adjusted analysis, anosmia was strongly and independently associated with outpatient care (aOR 0.09 95% CI: 0.01‐0.74) while positive findings of pulmonary infiltrates and/or pleural effusion on chest radiograph (aOR 8.01 95% CI: 1.12‐57.49) was strongly and independently associated with admission.

Conclusions

Normosmia is an independent predictor of admission in Covid‐19 cases. Smell loss in Covid‐19 may associate with a milder clinical course.

Hot Topics: AI Could Assist Radiology Interpretation

Jackie Werner Hot Topics in Research, Radiology

Comparison of Artificial Intelligence–Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing

Fischer AM, Varga-Szemes A, van Assen M, et al. Comparison of artificial Intelligence–Based fully automatic chest CT emphysema quantification to pulmonary function testing. Am J Roentgenol. 2020;214(5):1065-1071. https://doi.org/10.2214/AJR.19.21572.

OBJECTIVE. The purpose of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for fully automated quantification of emphysema on chest CT compared with pulmonary function testing (spirometry).

MATERIALS AND METHODS. A total of 141 patients (72 women, mean age ± SD of 66.46 ± 9.7 years [range, 23–86 years]; 69 men, mean age of 66.72 ± 11.4 years [range, 27–91 years]) who underwent both chest CT acquisition and spirometry within 6 months were retrospectively included. The spirometry-based Tiffeneau index (TI; calculated as the ratio of forced expiratory volume in the first second to forced vital capacity) was used to measure emphysema severity; a value less than 0.7 was considered to indicate airway obstruction. Segmentation of the lung based on two different reconstruction methods was carried out by using a deep convolution image-to-image network. This multilayer convolutional neural network was combined with multilevel feature chaining and depth monitoring. To discriminate the output of the network from ground truth, an adversarial network was used during training. Emphysema was quantified using spatial filtering and attenuation-based thresholds. Emphysema quantification and TI were compared using the Spearman correlation coefficient.

RESULTS. The mean TI for all patients was 0.57 ± 0.13. The mean percentages of emphysema using reconstruction methods 1 and 2 were 9.96% ± 11.87% and 8.04% ± 10.32%, respectively. AI-based emphysema quantification showed very strong correlation with TI (reconstruction method 1, ρ = −0.86; reconstruction method 2, ρ = −0.85; both p < 0.0001), indicating that AI-based emphysema quantification meaningfully reflects clinical pulmonary physiology.

CONCLUSION. AI-based, fully automated emphysema quantification shows good correlation with TI, potentially contributing to an image-based diagnosis and quantification of emphysema severity.

Hot Topics: Race and Class Affect COVID-19 Risk

Jackie Werner Hot Topics in Research, Infectious Disease, Public Health

Disparities in the Population at Risk of Severe Illness From COVID-19 by Race/Ethnicity and Income

Raifman M, Raifman J. Disparities in the population at risk of severe illness from COVID-19 by race/ethnicity and income. American Journal of Preventive Medicine. 2020. https://doi.org/10.1016/j.amepre.2020.04.003.

Identifying those at heightened risk of severe illness from novel coronavirus disease 2019 (COVID-19) is essential for modeling disease, designing return-to-work criteria, allocating economic assistance, advancing health equity, and limiting morbidity and mortality. The U.S. Centers for Disease Control and Prevention has identified criteria associated with risk of severe complications from COVID-19 infection. Structural inequities have shaped racial, ethnic, and income disparities for many of these criteria. To date, there has been limited analysis of the proportion of the population at risk in the U.S. based on these criteria, or risk factors by race/ethnicity or income. Preliminary national data on cases by race/ethnicity suggest that disparities in hospitalization are already developing. Quantifying disparities in risk is important for allocating resources to prevent, identify, and treat COVID-19-related severe illness and limit diverging outcomes for already vulnerable subgroups.

Hot Topics: Soda Tax Did Not Affect Soda Consumption

Jackie Werner Hot Topics in Research, Public Health

Sugar-Sweetened and Diet Beverage Consumption in Philadelphia One Year after the Beverage Tax

Zhong Y, Auchincloss AH, Lee BK, McKenna RM, Langellier BA. Sugar-Sweetened and Diet Beverage Consumption in Philadelphia One Year after the Beverage Tax. International Journal of Environmental Research and Public Health. 2020; 17(4):1336. https://doi.org/10.3390/ijerph17041336

In January 2017, Philadelphia (Pennsylvania) implemented an excise tax ($ 0.015/ounce) on sugar-sweetened and diet beverages. This study is a general population-based study to report on the longer-term impacts of the tax on within-person changes in consumption 12 months after implementation. A quasi-experimental difference-in-difference design was used to contrast Philadelphia vs. nearby comparison cities (Trenton, New Jersey; Camden, New Jersey; and Wilmington, Delaware) at baseline (December 2016–January 2017) vs. 12-month follow-up (December 2017–February 2018). A random-digit-dialing phone survey was administered to a population-based cohort. Analyses assessed changes in 30-day consumption frequency and ounces of sugar-sweetened and diet beverages (and a substitution beverage, bottled water) in the analytic sample (N = 515). After 12 months, relative to the comparison group, Philadelphians were slightly more likely to decrease their frequency of sugar-sweetened beverage consumption (39.2% vs. 33.5%), and slightly less likely to increase their frequency of sugar-sweetened beverage consumption (38.9% vs. 43.0%). The effects of the tax estimated in the adjusted difference-in-difference analysis were very small (for example, changes in monthly sugar-sweetened beverage consumption in Philadelphia relative to comparison cities was −3.03 times or −51.65 ounces) and confidence intervals were very wide. Results suggested that, one year after implementation, there was no major overall impact of the tax on general population-level consumption of sugar-sweetened or diet beverages, or bottled water. Future studies should test whether the tax’s effect differs in vulnerable sub-populations.

Hot Topics: New Bile Acid Discovered

Jackie Werner Biomedical Sciences, Hot Topics in Research

Global chemical effects of the microbiome include new bile-acid conjugations

Quinn RA, Melnik AV, Vrbanac A, et al. Global chemical effects of the microbiome include new bile-acid conjugations. Nature. 2020. https://doi.org/10.1038/s41586-020-2047-9.

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families that are known to be produced by the microbiome have a marked effect on the balance between health and disease. Considering the diversity of the human microbiome (which numbers over 40,000 operational taxonomic units), the effect of the microbiome on the chemistry of an entire animal remains underexplored. Here we use mass spectrometry informatics and data visualization approaches to provide an assessment of the effects of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free and specific-pathogen-free mice. We found that the microbiota affects the chemistry of all organs. This included the amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic acid, which have not previously been characterized despite extensive research on bile-acid chemistry. These bile-acid conjugates were also found in humans, and were enriched in patients with inflammatory bowel disease or cystic fibrosis. These compounds agonized the farnesoid X receptor in vitro, and mice gavaged with the compounds showed reduced expression of bile-acid synthesis genes in vivo. Further studies are required to confirm whether these compounds have a physiological role in the host, and whether they contribute to gut diseases that are associated with microbiome dysbiosis.

Hot Topics: Hearing Aids Could Delay Cognitive Decline

Jackie Werner Hot Topics in Research, Neurology, Otolaryngology

The Effect of Hearing Aid Use on Cognition in Older Adults: Can We Delay Decline or Even Improve Cognitive Function?

Sarant J, Harris D, Busby P, et al. The effect of hearing aid use on cognition in older adults: Can we delay decline or even improve cognitive function? J Clin Med. 2020;9(1). https://doi.org/10.3390/jcm9010254

Hearing loss is a modifiable risk factor for dementia in older adults. Whether hearing aid use can delay the onset of cognitive decline is unknown. Participants in this study (aged 62-82 years) were assessed before and 18 months after hearing aid fitting on hearing, cognitive function, speech perception, quality of life, physical activity, loneliness, isolation, mood, and medical health. At baseline, multiple linear regression showed hearing loss and age predicted significantly poorer executive function performance, while tertiary education predicted significantly higher executive function and visual learning performance. At 18 months after hearing aid fitting, speech perception in quiet, self-reported listening disability and quality of life had significantly improved. Group mean scores across the cognitive test battery showed no significant decline, and executive function significantly improved. Reliable Change Index scores also showed either clinically significant improvement or stability in executive function for 97.3% of participants, and for females for working memory, visual attention and visual learning. Relative stability and clinically and statistically significant improvement in cognition were seen in this participant group after 18 months of hearing aid use, suggesting that treatment of hearing loss with hearing aids may delay cognitive decline. Given the small sample size, further follow up is required.

Hot Topics: Existing Drugs May Fight Coronavirus

Jackie Werner Hot Topics in Research, Infectious Disease

Discovery and development of safe-in-man broad-spectrum antiviral agents

Andersen PI, Ianevski A, Lysvand H, et al. Discovery and development of safe-in-man broad-spectrum antiviral agents. Int J Infect Dis. 2020. https://doi.org/10.1016/j.ijid.2020.02.018

Viral diseases are one of the leading causes of morbidity and mortality in the world. Virus-specific vaccines and antiviral drugs are the most powerful tools to combat viral diseases. However, broad-spectrum antiviral agents (BSAAs, i.e. compounds targeting viruses belonging to two or more viral families) could provide additional protection of general population from emerging and re-emerging viral diseases reinforcing the arsenal of available antiviral options. Here, we reviewed discovery and development of BSAAs and summarized the information on 119 safe-in-man agents in freely accessible database (https://drugvirus.info/). Future and ongoing pre-clinical and clinical studies will increase the number of BSAAs, expand spectrum of their indications, and identify drug combinations for treatment of emerging and re-emerging viral infections as well as co-infections.