Differential recall bias in estimating treatment effects in observational studies.

Observational studies are frequently used to estimate the effect of an exposure or treatment on an outcome. To obtain an unbiased estimate of the treatment effect, it is crucial to measure the exposure accurately. A common type of exposure misclassification is recall bias, which occurs in retrospective cohort studies when study subjects may inaccurately recall their past exposure. Particularly challenging is differential recall bias in the context of self-reported binary exposures, where the bias may be directional rather than random and its extent varies according to the outcomes experienced. This paper makes several contributions: (1) it establishes bounds for the average treatment effect even when a validation study is not available; (2) it proposes multiple estimation methods across various strategies predicated on different assumptions; and (3) it suggests a sensitivity analysis technique to assess the robustness of the causal conclusion, incorporating insights from prior research. The effectiveness of these methods is demonstrated through simulation studies that explore various model misspecification scenarios. These approaches are then applied to investigate the effect of childhood physical abuse on mental health in adulthood.

Integrating randomized and observational studies to estimate optimal dynamic treatment regimes.

Sequential multiple assignment randomized trials (SMARTs) are the gold standard for estimating optimal dynamic treatment regimes (DTRs), but are costly and require a large sample size. We introduce the multi-stage augmented Q-learning estimator (MAQE) to improve efficiency of estimation of optimal DTRs by augmenting SMART data with observational data. Our motivating example comes from the Back Pain Consortium, where one of the overarching aims is to learn how to tailor treatments for chronic low back pain to individual patient phenotypes, knowledge which is lacking clinically. The Consortium-wide collaborative SMART and observational studies within the Consortium collect data on the same participant phenotypes, treatments, and outcomes at multiple time points, which can easily be integrated. Previously published single-stage augmentation methods for integration of trial and observational study (OS) data were adapted to estimate optimal DTRs from SMARTs using Q-learning. Simulation studies show the MAQE, which integrates phenotype, treatment, and outcome information from multiple studies over multiple time points, more accurately estimates the optimal DTR, and has a higher average value than a comparable Q-learning estimator without augmentation. We demonstrate this improvement is robust to a wide range of trial and OS sample sizes, addition of noise variables, and effect sizes.

A fast bootstrap algorithm for causal inference with large data.

Estimating causal effects from large experimental and observational data has become increasingly prevalent in both industry and research. The bootstrap is an intuitive and powerful technique used to construct standard errors and confidence intervals of estimators. Its application however can be prohibitively demanding in settings involving large data. In addition, modern causal inference estimators based on machine learning and optimization techniques exacerbate the computational burden of the bootstrap. The bag of little bootstraps has been proposed in non-causal settings for large data but has not yet been applied to evaluate the properties of estimators of causal effects. In this article, we introduce a new bootstrap algorithm called causal bag of little bootstraps for causal inference with large data. The new algorithm significantly improves the computational efficiency of the traditional bootstrap while providing consistent estimates and desirable confidence interval coverage. We describe its properties, provide practical considerations, and evaluate the performance of the proposed algorithm in terms of bias, coverage of the true 95% confidence intervals, and computational time in a simulation study. We apply it in the evaluation of the effect of hormone therapy on the average time to coronary heart disease using a large observational data set from the Women's Health Initiative.

Propensity score matching for estimating a marginal hazard ratio.

Propensity score matching is commonly used to draw causal inference from observational survival data. However, its asymptotic properties have yet to be established, and variance estimation is still open to debate. We derive the statistical properties of the propensity score matching estimator of the marginal causal hazard ratio based on matching with replacement and a fixed number of matches. We also propose a double-resampling technique for variance estimation that takes into account the uncertainty due to propensity score estimation prior to matching.

Dynamics of T-Lymphocyte Activation Related to Paradoxical Tuberculosis-Associated Immune Reconstitution Inflammatory Syndrome in Persons With Advanced HIV.

Most persons living with HIV (PLWH) experience a significant restoration of their immunity associated with successful inhibition of viral replication after antiretroviral therapy (ART) initiation. Nevertheless, with the robust quantitative and qualitative restoration of CD4+ T-lymphocytes, a fraction of patients co-infected with tuberculosis develop immune reconstitution inflammatory syndrome (TB-IRIS), a dysregulated inflammatory response that can be associated with significant tissue damage. Several studies underscored the role of adaptive immune cells in IRIS pathogenesis, but to what degree T lymphocyte activation contributes to TB-IRIS development remains largely elusive. Here, we sought to dissect the phenotypic landscape of T lymphocyte activation in PLWH coinfected with TB inititating ART, focusing on characterization of the profiles linked to development of TB-IRIS. We confirmed previous observations demonstrating that TB-IRIS individuals display pronounced CD4+ lymphopenia prior to ART initiation. Additionally, we found an ART-induced increase in T lymphocyte activation, proliferation and cytotoxicity among TB-IRIS patients. Importantly, we demonstrate that TB-IRIS subjects display higher frequencies of cytotoxic CD8+ T lymphocytes which is not affected by ART. Moreover, These patients exhibit higher levels of activated (HLA-DR+) and profilerative (Ki-67+) CD4+ T cells after ART commencenment than their Non-IRIS counterparts. Our network analysis reveal significant negative correlations between Total CD4+ T cells counts and the frequencies of Cytotoxic CD8+ T cells in our study population which could suggest the existance of compensatory mechanisms for Mtb-infected cells elimination in the face of severe CD4+ T cell lymphopenia. We also investigated the correlation between T lymphocyte activation profiles and the abundance of several inflammatory molecules in plasma. We applied unsupervised machine learning techniques to predict and diagnose TB-IRIS before and during ART. Our analyses suggest that CD4+ T cell activation markers are good TB-IRIS predictors, whereas the combination of CD4+ and CD8+ T cells markers are better at diagnosing TB-IRIS patients during IRIS events Overall, our findings contribute to a more refined understanding of immunological mechanisms in TB-IRIS pathogenesis that may assist in new diagnostic tools and more targeted patient management.

Leveraging vibration of effects analysis for robust discovery in observational biomedical data science.

Hypothesis generation in observational, biomedical data science often starts with computing an association or identifying the statistical relationship between a dependent and an independent variable. However, the outcome of this process depends fundamentally on modeling strategy, with differing strategies generating what can be called "vibration of effects" (VoE). VoE is defined by variation in associations that often lead to contradictory results. Here, we present a computational tool capable of modeling VoE in biomedical data by fitting millions of different models and comparing their output. We execute a VoE analysis on a series of widely reported associations (e.g., carrot intake associated with eyesight) with an extended additional focus on lifestyle exposures (e.g., physical activity) and components of the Framingham Risk Score for cardiovascular health (e.g., blood pressure). We leveraged our tool for potential confounder identification, investigating what adjusting variables are responsible for conflicting models. We propose modeling VoE as a critical step in navigating discovery in observational data, discerning robust associations, and cataloging adjusting variables that impact model output.

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Does Exist a Differential Impact of Degarelix Versus LHRH Agonists on Cardiovascular Safety? Evidences From Randomized and Real-World Studies.

The main systemic therapy for the management of hormone-sensitive prostate cancer (PC) is androgen deprivation therapy (ADT), with the use of long-acting luteinizing hormone releasing-hormone (LHRH) agonists considered the main form of ADT used in clinical practice to obtain castration in PC. The concomitant administration of antiandrogens for the first weeks could reduce the incidence of clinical effects related to the testosterone flare-up in the first injection of LHRH. On the contrary, Gonadotropin Rh (GnRH) antagonists produce a rapid decrease of testosterone levels without the initial flare-up, with degarelix commonly used in clinical practice to induce castration in PC patients. Even if no long-term data are reported in terms of survival to define a superiority of GnRH or LHRH, for oncological efficacy and PC control, data from randomized clinical trials and from real-life experiences, suggest a difference in cardiovascular risk of patients starting ADT. The age-related decline in testosterone levels may represent a factor connected to the increase of cardiovascular disease risk, however, the role of ADT in increasing CV events remains controversial. For these reasons, the aim of the paper is to synthesize the difference in cardiovascular risk between LHRH and degarelix in patients undergoing ADT. A difference in cardiovascular risk could be indeed an important parameter in the evaluation of these two forms of castration therapy. The Randomized trials analyzed in this paper sustain a possible protective role for degarelix versus LHRH agonists in reducing the rate of new CV events and interventions in the short-term period. On the contrary, real-word data are contradictory in different national experiences and are strongly conditioned by huge differences between the LHRH agonists group and the degarelix group.

Global epidemiology of acromegaly: a systematic review and meta-analysis.

OBJECTIVE: To date, no systematic reviews and meta-analysis on the global epidemiology of acromegaly are available in the literature. The aims of this study are to provide a systematic review and a meta-analysis of the global epidemiology of acromegaly and to evaluate the quality of study reporting for the identified studies. METHODS: MEDLINE, EMBASE and The Cochrane Library databases were searched for studies assessing the epidemiology of acromegaly from inception until 31 January 2020. We included original observational studies written in English, reporting acromegaly prevalence and/or incidence for a well-defined geographic area. Two reviewers independently extracted data and performed quality assessments. Prevalence and incidence pooled estimates were derived by performing a random-effects meta-analysis. RESULTS: A total of 32 studies were included in the systematic review, and 22 of them were included in the meta-analysis. The pooled prevalence of acromegaly was 5.9 (95% CI: 4.4-7.9) per 100 000 persons, while the incidence rate (IR) was 0.38 (95% CI: 0.32-0.44) cases per 100 000 person-years. For both prevalence and IR, considerable between-study heterogeneity was found (I2 = 99.3 and 86.0%, respectively). The quality of study reporting was rated as the medium for 20 studies and low for 12 studies. CONCLUSIONS: Although the largest amount of heterogeneity was due to the high precision of the studies' estimates, data source and geographic area could represent relevant study-level factors which could explain about 50% of the total between-study variability. Large-scale high-quality studies on the epidemiology of acromegaly are warranted to help the public health system in making decisions.

General Health Checks in Adult Primary Care: A Review.

Importance: General health checks, also known as general medical examinations, periodic health evaluations, checkups, routine visits, or wellness visits, are commonly performed in adult primary care to identify and prevent disease. Although general health checks are often expected and advocated by patients, clinicians, insurers, and health systems, others question their value. Observations: Randomized trials and observational studies with control groups reported in prior systematic reviews and an updated literature review through March 2021 were included. Among 19 randomized trials (906 to 59 616 participants; follow-up, 1 to 30 years), 5 evaluated a single general health check, 7 evaluated annual health checks, 1 evaluated biannual checks, and 6 evaluated health checks delivered at other frequencies. Twelve of 13 observational studies (240 to 471 415 participants; follow-up, cross-sectional to 5 years) evaluated a single general health check. General health checks were generally not associated with decreased mortality, cardiovascular events, or cardiovascular disease incidence. For example, in the South-East London Screening Study (n = 7229), adults aged 40 to 64 years who were invited to 2 health checks over 2 years, compared with adults not invited to screening, experienced no 8-year mortality benefit (6% vs 5%). General health checks were associated with increased detection of chronic diseases, such as depression and hypertension; moderate improvements in controlling risk factors, such as blood pressure and cholesterol; increased clinical preventive service uptake, such as colorectal and cervical cancer screening; and improvements in patient-reported outcomes, such as quality of life and self-rated health. In the Danish Check-In Study (n = 1104), more patients randomized to receive to a single health check, compared with those randomized to receive usual care, received a new antidepressant prescription over 1 year (5% vs 2%; P = .007). In a propensity score-matched analysis (n = 8917), a higher percentage of patients who attended a Medicare Annual Wellness Visit, compared with those who did not, underwent colorectal cancer screening (69% vs 60%; P < .01). General health checks were sometimes associated with modest improvements in health behaviors such as physical activity and diet. In the OXCHECK trial (n = 4121), fewer patients randomized to receive annual health checks, compared with those not randomized to receive health checks, exercised less than once per month (68% vs 71%; difference, 3.3% [95% CI, 0.5%-6.1%]). Potential adverse effects in individual studies included an increased risk of stroke and increased mortality attributed to increased completion of advance directives. Conclusions and Relevance: General health checks were not associated with reduced mortality or cardiovascular events, but were associated with increased chronic disease recognition and treatment, risk factor control, preventive service uptake, and improved patient-reported outcomes. Primary care teams may reasonably offer general health checks, especially for groups at high risk of overdue preventive services, uncontrolled risk factors, low self-rated health, or poor connection or inadequate access to primary care.

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Población veg(etari)ana argentina: Una aproximación a sus características sociodemográficas, estado nutricional y alimentación habitual / Argentinian veg(etari)ans: an approach to its socio-demographic characteristics, nutritional status and regular diet

Fundamentos: Las prácticas alimentarias veg(etari)anas son cada vez más frecuentes a nivel global y estimaciones recientes indican que 9% de la población de Argentina adhiere a las mismas. En esta investigación nos propusimos analizar características sociodemográficas, estado nutricional antropométrico y alimentación habitual de población ovo-lacto-vegetariana(OLV) y vegana (VGN) residente en los tres principales centros urbanos del país. Métodos: Para este estudio observacional, exploratorio y de corte transversal, se diseñó un cuestionario de encuesta que fue completado online por 282 personas. Para el análisis de datos se utilizó el programa estadístico STATA 14.0. Resultados: Los participantes presentan un peso dentro de los parámetros recomendados y llevan una dieta saludable, con mayor presencia de verduras, frutas, cereales integrales y pseudocereales, semillas y frutos secos entre la población VGN. No obstante, menos de un tercio cubre los requerimientos en cuanto al consumo diario de agua y, entre la población OLV, se observó un bajo uso de suplementos de vitamina B12. Conclusiones: Estos hallazgos coinciden con los de investigaciones desarrolladas previamente, a la vez que indican la necesidad de difundir las recomendaciones para este grupopoblacional que se encuentra en franco crecimiento tanto a nivel nacional como global. (AU)

Background: Veg(etari)an eating practices are increasingly frequent globally, and recent estimates indicate that9% of the Argentinian population adheres to such diets. In this research, we aimed to analyze sociodemographic characteristics, anthropometric nutritional status, and usual diet of ovo-lacto-vegetarian (OLV) and vegan (VGN) population of the three main urban centers of the country. Methods: For this observational, exploratory, cross-sectional study, a survey questionnaire was designed and completed online by 282 respondents. The statistical program STATA 14.0 was used for the analysis of data. Results: Participants present a weight within the recommended parameters and have a healthy diet, with a greater presence of vegetables, fruits, whole grains and pseudocereals, seeds and nuts among the VGN population. However, less than a third covers the requirements of daily water consumption, and a low use of vitamin B12 supplements was observed among the OLV population. Conclusions: These findings are in line with previous research and indicate the need to disseminate recommendationsfor this population group, which is growing rapidly both nationally and globally. (AU)

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