Vaccine efficacy at a point in time.

Vaccine trials are generally designed to assess efficacy on clinical disease. The vaccine effect on infection, while important both as a proxy for transmission and to describe a vaccine's entire effects, requires frequent (e.g., twice a week) longitudinal sampling to capture all infections. Such sampling may not always be feasible. A logistically easy approach is to collect a sample to test for infection at a regularly scheduled visit. Such point or cross-sectional sampling does not permit estimation of classic vaccine efficacy on infection, as long duration infections are sampled with higher probability. Building on work by Rinta-Kokko and others (2009) and Lipsitch and Kahn (2021), we evaluate proxies of the vaccine effect on transmission at a point in time; the vaccine efficacy on prevalent infection and on prevalent viral load, VE$_{\rm PI}$ and VE$_{\rm PVL}$, respectively. Longer infections with higher viral loads should have more transmission potential and prevalent vaccine efficacy naturally captures this aspect. We demonstrate how these parameters obtain from an underlying proportional hazards model for infection and allow for waning efficacy on infection, duration, and viral load. We estimate these parameters based on regression models with either repeated cross-sectional sampling or frequent longitudinal sampling. We evaluate the methods by simulation and analyze a phase III vaccine trial with polymerase chain reaction (PCR) cross-sectional sampling for subclinical infection.

Clarifying the causal contrast: An empirical example applying the prevalent new user study design.

PURPOSE: The prevalent new user design extends the active comparator new user design to include patients switching to a treatment of interest from a comparator. We examined the impact of adding "switchers" to incident new users on the estimated hazard ratio (HR) of hospitalized heart failure. METHODS: Using MarketScan claims data (2000-2014), we estimated HRs of hospitalized heart failure between patients initiating GLP-1 receptor agonists (GLP-1 RA) and sulfonylureas (SU). We considered three estimands: (1) the effect of incident new use; (2) the effect of switching; and (3) the effect of incident new use or switching, combining the two population. We used time-conditional propensity scores (TCPS) and time-stratified standardized morbidity ratio (SMR) weighting to adjust for confounding. RESULTS: We identified 76 179 GLP-1 RA new users, of which 12% were direct switchers (within 30 days) from SU. Among incident new users, GLP-1 RA was protective against heart failure (adjHRSMR = 0.74 [0.69, 0.80]). Among switchers, GLP-1 RA was not protective (adjHRSMR = 0.99 [0.83, 1.18]). Results in the combined population were largely driven by the incident new users, with GLP-1 RA having a protective effect (adjHRSMR = 0.77 [0.72, 0.83]). Results using TCPS were consistent with those estimated using SMR weighting. CONCLUSIONS: When analyses were conducted only among incident new users, GLP-1 RA had a protective effect. However, among switchers from SU to GLP-1 RA, the effect estimates substantially shifted toward the null. Combining patients with varying treatment histories can result in poor confounding control and camouflage important heterogeneity.

Impact of social, familial and personal factors on depressive symptoms in middle-aged and older adults from the national CHARLS cohort.

BACKGROUND: This study aimed to evaluate whether social, familial and personal factors can predict incident and prevalent depressive symptoms in Chinese adults aged ≥ 45 years using data from the China Health and Retirement Longitudinal Study (CHARLS). METHODS: Study subjects without depressive symptoms from CHARLS at baseline were enrolled. Depressive symptoms were defined by the 10-item Center for Epidemiologic Studies Depression Scale. Statistical adjustment, subgroup exploration and unmeasured confounding assessment were undertaken to derive reliable estimates. RESULTS: 1681 (27.04%) of 6215 subjects who had no depressive symptoms in 2011, suffered one or more depressive symptoms in 2018. Multivariate analyses showed that number of grandchildren (odds ratio [95% confidence interval]: 1.06 [1.02, 1.10]), social activity score (0.95 [0.91, 0.98]), instrumental activities of daily living (IADL) (1.35 [1.11, 1.65]) and number of comorbidities (1.16 [1.10, 1.22]) were independently and significantly associated with the presence of incident depressive symptoms. Further categorization revealed significance for social activity score (odds ratio [95% confidence interval]: 0.78 [0.69, 0.89] and 0.71 [0.53, 0.95] for 1-5 and > 5 vs. 0), IADL (1.35 [1.11, 1.65] for yes vs. no) and number of comorbidities (1.38 [1.20, 1.58], 1.44 [1.16, 1.81] and 2.42 [1.54, 3.80] for 1-2, 3-4 and > 4 vs. 0) associated with incident depressive symptoms. Restricting analysis to wave IV data in 2018 observed significant association of number of grandchildren, social activity score, IADL and number of comorbidities with prevalent depressive symptoms. CONCLUSIONS: The present study findings support the marked contribution of social activity score, IADL and number of comorbidities to incident and prevalent depressive symptoms in Chinese middle-aged and older adults.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Non-parametric estimation of the age-at-onset distribution from a cross-sectional sample.

We propose and study a simple and innovative non-parametric approach to estimate the age-of-onset distribution for a disease from a cross-sectional sample of the population that includes individuals with prevalent disease. First, we estimate the joint distribution of two event times, the age of disease onset and the survival time after disease onset. We accommodate that individuals had to be alive at the time of the study by conditioning on their survival until the age at sampling. We propose a computationally efficient expectation-maximization (EM) algorithm and derive the asymptotic properties of the resulting estimates. From these joint probabilities we then obtain non-parametric estimates of the age-at-onset distribution by marginalizing over the survival time after disease onset to death. The method accommodates categorical covariates and can be used to obtain unbiased estimates of the covariate distribution in the source population. We show in simulations that our method performs well in finite samples even under large amounts of truncation for prevalent cases. We apply the proposed method to data from female participants in the Washington Ashkenazi Study to estimate the age-at-onset distribution of breast cancer associated with carrying BRCA1 or BRCA2 mutations.

Change in prevalence of vertebral fractures over two decades: a Japanese medical examination-based study.

INTRODUCTION: Although remarkable progress has been made in osteoporosis treatment over the last two decades, no study has reported the change in the prevalence of vertebral fractures (VFs) during this time. This study aimed to compare the prevalence and pattern of VFs at three time points from 1997 to 2019 in a Japanese medical examination-based study. MATERIALS AND METHODS: The participants of this study were inhabitants of a typical Japanese mountain village who participated in these surveys at three time points: 1997 (group A), 2009 or 2011 (group B), and 2019 (group C). The age- and sex-adjusted groups were defined as groups A', B', and C', respectively (39 men and 85 women; mean age 73.6-74.0 years old). The type and extent of deformities of the prevalent fractures from T4 to L4 on the lateral thoracic and lumbar spine radiographs were semiquantitatively evaluated. RESULTS: The prevalence of VFs has significantly decreased over the past two decades. In group A, the percentages of thoracic level, biconcave type, and severe deformity of VFs were significantly higher than expected. The bone mineral density of the participants increased significantly over time. The treatment rate for osteoporosis in participants with osteoporosis has improved over the past two decades. CONCLUSION: This study demonstrated that the prevalence of VFs has decreased, and the pattern of VFs has changed over the last two decades in a typical Japanese mountain village due to multifactorial improvements in skeletal fragility, including improvement in osteoporosis treatment rate.

Prevalent new user designs: A literature review of current implementation practice.

PURPOSE: Prevalent new user (PNU) designs extend the active comparator new user design by allowing for the inclusion of initiators of the study drug who were previously on a comparator treatment. We performed a literature review summarising current practice. METHODS: PubMed was searched for studies applying the PNU design since its proposal in 2017. The review focused on three components. First, we extracted information on the overall study design, including the database used. We summarised information on implementation of the PNU design, including key decisions relating to exposure set definition and estimation of time-conditional propensity scores. Finally, we reviewed the analysis strategy of the matched cohort. RESULTS: Nineteen studies met the criteria for inclusion. Most studies (73%) implemented the PNU design in electronic health record or registry databases, with the remaining using insurance claims databases. Of 15 studies including a class of prevalent users, 40% deviated from the original exposure set definition proposals in favour of a more complex definition. Four studies did not include prevalent new users but used other aspects of the PNU framework. Several studies lacked details on exposure set definition (n = 2), time-conditional propensity score model (n = 2) or integration of complex analytical techniques, such as the high-dimensional propensity score algorithm (n = 3). CONCLUSION: PNU designs have been applied in a range of therapeutic and disease areas. However, to encourage more widespread use of this design and help shape best practice, there is a need for improved accessibility, specifically through the provision of analytical code alongside guidance to support implementation and transparent reporting.

Core concepts in pharmacoepidemiology: Key biases arising in pharmacoepidemiologic studies.

Pharmacoepidemiology has an increasingly important role in informing and improving clinical practice, drug regulation, and health policy. Therefore, unrecognized biases in pharmacoepidemiologic studies can have major implications when study findings are translated to the real world. We propose a simple taxonomy for researchers to use as a starting point when thinking through some of the most pervasive biases in pharmacoepidemiology. We organize this discussion according to biases best assessed with respect to the study population (including confounding by indication, channeling bias, healthy user bias, and protopathic bias), the study design (including prevalent user bias and immortal time bias), and the data source (including misclassification bias and missing data/loss to follow up). This tutorial defines, provides a curated list of recommended references, and illustrates through relevant case examples these key biases to consider when planning, conducting, or evaluating pharmacoepidemiologic studies.

Survival Modelling For Data From Combined Cohorts: Opening the Door to Meta Survival Analyses and Survival Analysis using Electronic Health Records.

Non-parametric estimation of the survival function using observed failure time data depends on the underlying data generating mechanism, including the ways in which the data may be censored and/or truncated. For data arising from a single source or collected from a single cohort, a wide range of estimators have been proposed and compared in the literature. Often, however, it may be possible, and indeed advantageous, to combine and then analyze survival data that have been collected under different study designs. We review non-parametric survival analysis for data obtained by combining the most common types of cohort. We have two main goals: (i) To clarify the differences in the model assumptions, and (ii) to provide a single lens through which some of the proposed estimators may be viewed. Our discussion is relevant to the meta analysis of survival data obtained from different types of study, and to the modern era of electronic health records.

The Structural Abnormalities Are Deeply Involved in the Cause of RPGRIP1-Related Retinal Dystrophy in Japanese Patients.

Leber congenital amaurosis (LCA) is the most severe form of inherited retinal dystrophy. RPGRIP1-related LCA accounts for 5-6% of LCA. We performed whole-exome sequencing and whole-genome sequencing (WGS) on 29 patients with clinically suspected LCA and examined ophthalmic findings in patients with biallelic pathogenic variants of RPGRIP1. In addition to five previously reported cases, we identified five cases from four families with compound heterozygous RPGRIP1 variants using WGS. Five patients had null variants comprising frameshift variants, an Alu insertion, and microdeletions. A previously reported 1339 bp deletion involving exon 18 was found in four cases, and the deletion was relatively prevalent in the Japanese population (allele frequency: 0.002). Microdeletions involving exon 1 were detected in four cases. In patients with RPGRIP1 variants, visual acuity remained low, ranging from light perception to 0.2, and showed no correlation with age. In optical coherence tomography images, the ellipsoid zone (EZ) length decreased with age in all but one case of unimpaired EZ. The retinal structure was relatively preserved in all cases; however, there were cases with great differences in visual function compared to their siblings and a 56-year-old patient who still had a faint EZ line. Structural abnormalities may be important genetic causes of RPGRIP1-related retinal dystrophy in Japanese patients, and WGS was useful for detecting them.

Evaluation of the natural history of disease by combining incident and prevalent cohorts: application to the Nun Study.

The Nun study is a well-known longitudinal epidemiology study of aging and dementia that recruited elderly nuns who were not yet diagnosed with dementia (i.e., incident cohort) and who had dementia prior to entry (i.e., prevalent cohort). In such a natural history of disease study, multistate modeling of the combined data from both incident and prevalent cohorts is desirable to improve the efficiency of inference. While important, the multistate modeling approaches for the combined data have been scarcely used in practice because prevalent samples do not provide the exact date of disease onset and do not represent the target population due to left-truncation. In this paper, we demonstrate how to adequately combine both incident and prevalent cohorts to examine risk factors for every possible transition in studying the natural history of dementia. We adapt a four-state nonhomogeneous Markov model to characterize all transitions between different clinical stages, including plausible reversible transitions. The estimating procedure using the combined data leads to efficiency gains for every transition compared to those from the incident cohort data only.

Alternative analytic and matching approaches for the prevalent new-user design: A simulation study.

PURPOSE: To describe the creation of prevalent new user (PNU) cohorts and compare the relative bias and computational efficiency of several alternative analytic and matching approaches in PNU studies. METHODS: In a simulated cohort, we estimated the effect of a treatment of interest vs a comparator among those who switched to the treatment of interest using the originally proposed time-conditional propensity score (TCPS) matching, standardized morbidity ratio weighting (SMRW), disease risk scores (DRS), and several alternative propensity score matching approaches. For each analytic method, we compared the average RR (across 2000 replicates) to the known risk ratio (RR) of 1.00. RESULTS: SMRW and DRS yielded unbiased results (RR = 0.998 and 0.997, respectively). TCPS matching with replacement was also unbiased (RR = 0.999). TCPS matching without replacement was unbiased when matches were identified starting with patients with the shortest treatment history as initially proposed (RR = 0.999), but it resulted in very slight bias (RR = 0.983) when starting with patients with the longest treatment history. Similarly, creating a match pool without replacement starting with patients with the shortest treatment history yielded an unbiased estimate (RR = 0.997), but matching with the longest treatment history first resulted in substantial bias (RR = 0.903). The most biased strategy was matching after selecting one random comparator observation per individual that continued on the comparator (RR = 0.802). CONCLUSIONS: Multiple analytic methods can estimate treatment effects without bias in a PNU cohort. Still, researchers should be wary of introducing bias when selecting controls for complex matching strategies beyond the initially proposed TCPS.

Glucosamine and lower mortality and cancer incidence: Selection bias in the observational studies.

BACKGROUND: Glucosamine is a widely used supplement to treat joint pain and osteoarthritis despite inconclusive randomized trial results on its effectiveness. In contrast, observational studies associate glucosamine with significant reductions in mortality and cancer incidence. We evaluated the extent of bias, particularly selection bias, to explain these surprising beneficial effects. METHODS: We searched the literature to identify all observational studies reporting on the effect of glucosamine use on major outcomes. RESULTS: We identified 11 observational studies, reporting a mean 16% reduction in all-cause mortality (hazard ratio [HR] 0.84, 95% CI: 0.81-0.87) with glucosamine use, as well as significant reductions in cancer incidence and other major diseases including cardiovascular, respiratory and diabetes. We show that these significant effects can result from selection bias due to collider stratification, as all studies used "prevalent" cohorts, where glucosamine use started before cohort entry, and where subjects agreed to join the cohorts. Our illustration of the bias using the UK Biobank publication involving a half-million subjects shows how a true rate ratio of mortality of 1.0 in the population can result in a biased rate ratio of 0.82 in the prevalent cohort. CONCLUSIONS: The observational studies reporting significant reductions in mortality, cancer incidence and other outcomes with glucosamine were affected by selection bias from collider stratification. In the absence of properly conducted observational studies that circumvent this bias by considering "new users", the studies to date cannot support the prescription of this supplement as a preventive measure for mortality, cancer, and other chronic diseases.

Undernutrition - thirty years of the Regional Basic Diet: the legacy of Naíde Teodósio in different fields of knowledge.

Undernutrition is characterized by an imbalance of essential nutrients with an insufficient nutritional intake, a disorder in which the clinical manifestations in most cases are the result of the economic and social context in which the individual lives. In 1990, the study by the medical and humanitarian Naíde Teodósio (1915-2005) and coworkers, which formulated the Regional Basic Diet (RBD) model for inducing undernutrition, was published. This diet model took its origin from the observation of the dietary habits of families that inhabited impoverished areas from the Pernambuco State. RBD mimics an undernutrition framework that extends not only to the Brazilian population, but to populations in different regions worldwide. The studies based on RBD-induced deficiencies provide a better understanding of the impact of undernutrition on the pathophysiological mechanisms underlying the most diverse prevalent diseases. Indexed papers that are analyzed in this review focus on the importance of using RBD in different areas of knowledge. These papers reflect a new paradigm in translational medicine: they show how the study of pathology using the RBD model in animals over the past 30 years has and still can help scientists today, shedding light on the mechanisms of prevalent diseases that affect impoverished populations.

In a Stationary Population, the Average Lifespan of the Living Is a Length-Biased Life Expectancy.

What is the average lifespan in a stationary population viewed at a single moment in time? Even though periods and cohorts are identical in a stationary population, we show that the answer to this question is not life expectancy but a length-biased version of life expectancy. That is, the distribution of lifespans of the people alive at a single moment is a self-weighted distribution of cohort lifespans, such that longer lifespans have proportionally greater representation. One implication is that if death rates are unchanging, the average lifespan of the current population always exceeds period life expectancy. This result connects stationary population lifespan measures to a well-developed body of statistical results; provides new intuition for established demographic results; generates new insights into the relationship between periods, cohorts, and prevalent cohorts; and offers a framework for thinking about mortality selection more broadly than the concept of demographic frailty.

Sagittal Band Injuries: A Review and Modification of the Classification System.

Sagittal band injuries, although relatively uncommon, can be difficult to treat. This review provides a contemporary perspective on this pathology, as well as a modification to the classification system. This modification aims to incorporate the spectrum of disease seen, guide treatment, and allow standardization when documenting and describing injuries.

Contact sensitization in pediatric patients with atopic dermatitis: a purpose for a new patch testing serie for the Portuguese population.

Summary: Atopic dermatitis is a common illness in pediatric age. Children with atopic dermatitis are prone to develop cutaneous sensitization due to skin barrier dysfunction and immune dysregulation. Recent studies have shown a higher prevalence of certain allergens, which identification may be clinically relevant and have implications for atopic dermatitis management. Considering the most prevalent and relevant allergens based on a retrospective analysis of 145 pediatric patients, 44.1% (n = 63) with atopic dermatitis, and comparing the positive results, we propose the application of an adapted baseline series with the most relevant 20 allergens for the Portuguese pediatric population with atopic dermatitis with recommendation for an evaluation of allergic contact dermatitis.

The Spectrum of Tuberculosis Disease in an Urban Ugandan Community and Its Health Facilities.

BACKGROUND: New, sensitive diagnostic tests facilitate identification and investigation of milder forms of tuberculosis (TB) disease. We used community-based TB testing with the Xpert MTB/RIF Ultra assay ("Ultra") to characterize individuals with previously undiagnosed TB and compare them to those from the same community who were diagnosed with TB through routine care. METHODS: We offered community-based sputum Ultra testing to adult residents of a well-defined area (population 34 000 adults) in Kampala, Uganda, via door-to-door screening and venue-based testing, then used detailed interview and laboratory testing to characterize TB-positive individuals. We compared these individuals to residents diagnosed with pulmonary TB at local health facilities and a representative sample of residents without TB (controls). RESULTS: Of 12 032 residents with interpretable Ultra results, 113 (940 [95% confidence interval {CI}, 780-1130] per 100 000) tested positive, including 71 (63%) positive at the lowest (trace) level. A spectrum of TB disease was observed in terms of chronic cough (93% among health facility-diagnosed cases, 77% among residents with positive community-based Ultra results at levels above trace, 33% among trace-positive community participants, and 18% among TB-negative controls), TB symptom prevalence (99%, 87%, 60%, and 38%, respectively), and C-reactive protein (75th percentile: 101 mg/L, 28 mg/L, 6 mg/L, and 4 mg/L, respectively). Community-diagnosed cases were less likely than health facility-diagnosed cases to have human immunodeficiency virus coinfection or previous TB. The specificity of Ultra was 99.4% (95% CI, 99.2%-99.5%) relative to a single spot sputum culture. CONCLUSIONS: People with undiagnosed prevalent TB in the community have different characteristics than those diagnosed with pulmonary TB in health facilities. Newer diagnostic tests may identify a group of people with early or very mild disease.

Initiator Types and the Causal Question of the Prevalent New-User Design: A Simulation Study.

New-user designs restricting to treatment initiators have become the preferred design for studying drug comparative safety and effectiveness using nonexperimental data. This design reduces confounding by indication and healthy-adherer bias at the cost of smaller study sizes and reduced external validity, particularly when assessing a newly approved treatment compared with standard treatment. The prevalent new-user design includes adopters of a new treatment who switched from or previously used standard treatment (i.e., the comparator), expanding study sample size and potentially broadening the study population for inference. Previous work has suggested the use of time-conditional propensity-score matching to mitigate prevalent user bias. In this study, we describe 3 "types" of initiators of a treatment: new users, direct switchers, and delayed switchers. Using these initiator types, we articulate the causal questions answered by the prevalent new-user design and compare them with those answered by the new-user design. We then show, using simulation, how conditioning on time since initiating the comparator (rather than full treatment history) can still result in a biased estimate of the treatment effect. When implemented properly, the prevalent new-user design estimates new and important causal effects distinct from the new-user design.

Invited Commentary: The Prevalent New-User Design in Pharmacoepidemiology-Challenges and Opportunities.

The prevalent new-user design includes a broader study population than the traditional new-user approach that is frequently used in pharmacoepidemiologic research. In an article appearing in this issue (Am J Epidemiol. 2021;190(7):1341-1348), Webster-Clark et al. describe the treatment initiator types included in the prevalent new-user design and contrast the causal questions assessed using a prevalent new-user design versus a new-user design. They further applied a series of simulation studies showing the importance of accounting for treatment history in addition to time since initiation of the comparator in the prevalent new-user design. In this commentary, we put their findings in the broader context with a discussion of the strengths and limitations of the prevalent new-user design and settings where it would be most useful. The prevalent new-user design and new-user design both address unique questions of clinical and public health importance. Real-world evidence generated by pharmacoepidemiologic research is increasingly being used by regulators and other knowledge users to inform their decision-making. Understanding the causal questions addressed by different designs is crucial in this process; the study by Webster-Clark et al. represents an important step in addressing this issue.