Determining the cutoff based on a continuous variable to define two populations with application to vaccines

Prevalence and factors associated with suicidal ideation, cannabis, and alcohol use during the COVID-19 pandemic in Saskatchewan: findings from a joint-effect modeling

BACKGROUND

Generally, pandemics such as COVID-19 take an enormous toll on people's lives. As the pandemic now turns to an endemic state, growing attention has been paid to the multiple adverse mental health and behavioral issues, such as suicidal ideation and substance use. However, the interplay of suicidality and substance misuse during the pandemic has been limited. We aimed to investigate the prevalence of co-occurrence of suicide ideation, alcohol and cannabis misuse, and the factors that are associated with these co-occurrences in the province of Saskatchewan during the COVID-19 pandemic.

METHODS

We performed a multivariable trivariate probit regression on a sample of 666 Saskatchewan adolescents and adults (16 years or older), drawn from the cycle 10 data collection (March 2022) of the Mental Health Commission of Canada, and Canadian Centre on Substance Use and Addiction (MHCC-CCSA) dataset.

RESULTS

The prevalence of suicidal ideation was higher among respondents who reported both problematic cannabis and alcohol use (25.8%) than single users of alcohol (23.2%) and cannabis (18.7%). Younger respondents (16-34 years) and those who reported recent changes in other substance use were independent factors that were associated with the common experience of suicide ideation, problematic cannabis, and alcohol use. Having a diagnosis of mental health disorders either before or during the pandemic, and the perceived inability to bounce back after the pandemic (low resilience) are strong correlates of suicidal ideation. Those who lived alone, between 35 and 55 years of age were more likely to report problematic alcohol use. Those who reported changes in alternative activities, who reported pandemic stress, and declared a LGBTQIA2S + identity had higher probability of problematic cannabis use.

CONCLUSIONS

As the pandemic persists, improving access to suicide and substance use interventions for the vulnerable groups identified in this study may be impactful.

Clinicopathological and prognostic significance of long non-coding RNA EWSAT1 in human cancers: A review and meta analysis

Background

Ewing sarcoma-associated transcript 1 (lncRNA EWSAT1) is reported to have a close relationship with the overall survival in many cancers. However, the role of its prognosis and correlations with the clinicopathological features in different cancers haven’t been explored yet. Herein, we intend to assess the prognostic value and correlations with the clinicopathological features in several cancers.

Methods

PubMed, Embase, Web of Science, and The Cochrane Library were searched for literature review from inception to October 25, 2021. Valid data was extracted to make forest and sensitivity analysis plots using Review Manager 5.4 and Stata software. Hazard ratio (HR) or odds ratio (OR) with 95% confidence interval (CI) was used to evaluate the relationship between different expression of EWSAT1 and patients’ prognosis and clinicopathological features.

Results

7 studies were screened for this review, including 550 samples. Meta-analysis showed that high expression of lncRNA EWSAT1 was associated with poor overall survival (OS) (HR = 2.10, 95% CI, 1.60–2.75, p < 0.0001) in cancers reported. In addition, patients in high expression group of EWAST1 tended to have more metastasis (OR = 2.20, 95% CI 1.47–3.31, p = 0.0001), and higher TNM stage (I+II vs. III: OR = 0.34, 95% CI 0.21–0.56, p < 0.0001), but in the same time with higher differentiation (well + moderate vs. Poor: OR = 2.21, 95% CI 1.02–4.76, p = 0.04). Age (OR = 1.47, 95% CI 0.94–2.30, p = 0.09) was not significantly different in patients with aberrant expression of EWSAT1.

Conclusions

Our study shows that high expression of EWSAT1 may indicate poor overall survival and associated with several clinicopathological features, which can be used as a potential prognosis biomarker for multiple cancers.

SPPB as a predictor of functional loss of hospitalized older adults

Abstract Introduction: Immobility is associated with adverse outcomes such as loss of functional capacity and longer hospitalization. Objective: To assess intra-hospital mobility at admission as a predictor of loss of functional capacity during older adults´ hospitalization. Methods: A prospective cohort study was conducted, and personal and hospital related risk factors were assessed at admission and discharge. To determine whether Short Physical Performance Battery (SPPB) on admission could predict loss of functional capacity during hospitalization, a ROC curve was performed and area under the curve (AUC) was calculated. Binary logistic regression models were used to identify predictors of loss of functional capacity. Model 1 contained only SPPB. Model 2 SPPB was matched with age, sex, instrumental activity of daily living (IADL), cognition, depression and surgery. Data were entered into SPSS version 18.0. Results: 1,191 patients were included with a mean age of 70.02 (± 7.34). SPPB cutoff point of 6.5 (sensitivity 62%, specificity 54%) identified 593 (49.8%) patients at risk for functional loss. In logistic regression, SPPB alone showed prediction of functional loss (p < 0.001, OR 1.8, 95% CI = 1.5-2.5) between admission and discharge. Model 1 explained between 22 to 32% of the variation in functional capacity. In Model 2, three variables contributed to the loss. SPPB 6.5 increased 1.8 times (95% CI = 1.3-2.4), being a woman increased 1.4 times (95% CI = 1.0-1.8) and not having surgery increased 2 times (95% CI = 1.4-2.8) the chance of having functional loss during hospitalization. Conclusion: SPPB is a good instrument to predict loss of functional capacity in hospitalized older adults.

A method to estimate probability of disease and vaccine efficacy from clinical trial immunogenicity data

Vaccine efficacy is often assessed by counting disease cases in a clinical trial. A new quantitative framework proposed here ("PoDBAY," Probability of Disease Bayesian Analysis), estimates vaccine efficacy (and confidence interval) using immune response biomarker data collected shortly after vaccination. Given a biomarker associated with protection, PoDBAY describes the relationship between biomarker and probability of disease as a sigmoid probability of disease ("PoD") curve. The PoDBAY framework is illustrated using clinical trial simulations and with data for influenza, zoster, and dengue virus vaccines. The simulations demonstrate that PoDBAY efficacy estimation (which integrates the PoD and biomarker data), can be accurate and more precise than the standard (case-count) estimation, contributing to more sensitive and specific decisions than threshold-based correlate of protection or case-count-based methods. For all three vaccine examples, the PoD fit indicates a substantial association between the biomarkers and protection, and efficacy estimated by PoDBAY from relatively little immunogenicity data is predictive of the standard estimate of efficacy, demonstrating how PoDBAY can provide early assessments of vaccine efficacy. Methods like PoDBAY can help accelerate and economize vaccine development using an immunological predictor of protection. For example, in the current effort against the COVID-19 pandemic it might provide information to help prioritize (rank) candidates both earlier in a trial and earlier in development.

Some extensions in continuous models for immunological correlates of protection

BACKGROUND

A scaled logit model has previously been proposed to quantify the relationship between an immunological assay and protection from disease, and has been applied in a number of settings. The probability of disease was modelled as a function of the probability of exposure, which was assumed to be fixed, and of protection, which was assumed to increase smoothly with the value of the assay.

METHODS

Some extensions are here investigated. Alternative functions to represent the protection curve are explored, applications to case-cohort designs are evaluated, and approaches to variance estimation compared. The steepness of the protection curve must sometimes be bounded to achieve convergence and methods for doing so are outlined. Criteria for evaluating the fit of models are proposed and approaches to assessing the utility of results suggested. Models are evaluated by application to sixteen datasets from vaccine clinical trials.

RESULTS

Alternative protection curve functions improved model evaluation criteria for every dataset. Standard errors based on the observed information were found to be unreliable; bootstrap estimates of precision were to be preferred. In most instances, case-cohort designs resulted in little loss of precision. Some results achieved suggested measures for utility.

CONCLUSIONS

The original scaled logit model can be improved upon. Evaluation criteria permit well-fitting models and useful results to be identified. The proposed methods provide a comprehensive set of tools for quantifying the relationship between immunological assays and protection from disease.

Hemagglutination Inhibition Antibody Titers as a Correlate of Protection Against Seasonal A/H3N2 Influenza Disease

Background. To investigate the relationship between hemagglutinin-inhibition (HI) antibody levels to the risk of influenza disease, we conducted a correlate of protection analysis using pooled data from previously published randomized trials.

Methods. Data on the occurrence of laboratory-confirmed influenza and HI levels pre- and postvaccination were analyzed from 4 datasets: 3 datasets included subjects aged <65 years who received inactivated trivalent influenza vaccine (TIV) or placebo, and 1 dataset included subjects aged ≥65 years who received AS03-adjuvanted TIV (AS03-TIV) or TIV. A logistic model was used to evaluate the relationship between the postvaccination titer of A/H3N2 HI antibodies and occurrence of A/H3N2 disease. We then built a receiver-operating characteristic curve to identify a potential cutoff titer between protection and no protection.

Results. The baseline odds ratio of A/H3N2 disease was higher for subjects aged ≥65 years than <65 years and higher in seasons of strong epidemic intensity than moderate or low intensity. Including age and epidemic intensity as covariates, a 4-fold increase in titer was associated with a 2-fold decrease in the risk of A/H3N2 disease.

Conclusions. The modeling exercise confirmed a relationship between A/H3N2 disease and HI responses, but it did not allow an evaluation of the predictive power of the HI response.