Advances in Epidemiological and Statistical Methods for Medical Research

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Epidemiology & Public Health".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 9010

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Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue entitled “Advances in Epidemiological and Statistical Methods for Medical Research". In additional to original methodologic research, we are particularly interested in topic overviews, tutorials, and seminal work of current interest in the field.

We hope this Special Issue will be of interest to you. Collaboration with students and research fellows in your group also is encouraged. Following submission, manuscripts will receive prompt attention and undergo fair but thorough review by experts in the field. 

Your questions are welcome, as are pre-submission queries regarding the suitability of and interest in your manuscript.

Prof. Dr. Jimmy T. Efird
Guest Editor

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Keywords

  • epidemiologic methods
  • causal inference
  • clinical trial methodology
  • mendelian randomization
  • imputation techniques
  • log-linear models
  • genetic biomarker analysis
  • statistical genetics modeling
  • bayesian methods
  • advanced methods for risk assessment
  • survival analysis and longitudinal data methods
  • epidemiological measures
  • pharmacoepidemiological analytics
  • spatial analysis
  • medical research methodology
  • multivariate modelling
  • big data approaches and machine learning

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Published Papers (5 papers)

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Research

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8 pages, 1014 KiB  
Article
The Preparation of Future Statistically Oriented Physicians: A Single-Center Experience in Saudi Arabia
by Anwar A. Sayed
Medicina 2024, 60(10), 1694; https://doi.org/10.3390/medicina60101694 - 15 Oct 2024
Viewed by 725
Abstract
Background and Objectives: Statistics are of paramount significance to physicians as they allow them to critically interpret the medical literature and to contribute to it. However, teaching statistics to medical students and physicians, as well as learning statistics, is nothing short of [...] Read more.
Background and Objectives: Statistics are of paramount significance to physicians as they allow them to critically interpret the medical literature and to contribute to it. However, teaching statistics to medical students and physicians, as well as learning statistics, is nothing short of difficult and anxiety-inducing to a great extent. Materials and Methods: In this study, an example of a novel approach to teaching statistics to medical students is introduced at a single college of medicine in Saudi Arabia. In this retrospective report, a new approach that has been developed and delivered to students is described. Results: The approach, referred to as the personal experience pathway, is part of a major curriculum change to the MBBS program. The track presents statistics to students as a tool, rather than a subject, that students will need to interpret results, either present in the literature or those of the research projects they are conducting. The outcome of this process has been assessed through measuring students’ scholarly output through student self-reporting and has been followed up over four student cohorts graduating between the years 2019 and 2022. The approach has successfully equipped students with a solid foundation of statistical understanding that has allowed them to publish in peer-reviewed journals. Such scholarly output has increased significantly over the last two years. Conclusions: The current study presents a framework through which the detailed curriculum plan could be applied to other medical schools, nationally and internationally, which will better prepare future statistically oriented physicians. Full article
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10 pages, 329 KiB  
Article
Assessing Additive Interactions between Protective Factors Using Relative Risk Reduction Due to Interaction
by Andrea Nova, Teresa Fazia and Luisa Bernardinelli
Medicina 2024, 60(7), 1053; https://doi.org/10.3390/medicina60071053 - 26 Jun 2024
Viewed by 1606
Abstract
Background and Objectives: In the context of disease prevention, interaction on an additive scale is commonly assessed to determine synergistic effects between exposures. While the “Relative Excess Risk due to Interaction” represents the main measure of additive interaction between risk factors, in [...] Read more.
Background and Objectives: In the context of disease prevention, interaction on an additive scale is commonly assessed to determine synergistic effects between exposures. While the “Relative Excess Risk due to Interaction” represents the main measure of additive interaction between risk factors, in this study we aimed to extend this approach to assess additive interaction between factors known to prevent the event’s occurrence, such as medical interventions and drugs. Materials and Methods: We introduced and described the “Relative Risk Reduction due to Interaction” (RRRI) as a key measure to assess additive interactions between preventive factors, such as therapeutic interventions and drug combinations. For RRRI values closer to 1, the combination of exposures has a greater impact on reducing the event risk due to their interaction. As a purely illustrative example, we re-evaluated a previous investigation of the synergistic effect between statins and blood pressure-lowering drugs in preventing major adverse cardiovascular events (MACE). Moreover, simulation studies were used to empirically evaluate the performance of a robust Poisson regression model to estimate RRRI across different scenarios. Results: In our example, the drug combination revealed a positive additive interaction in further reducing MACE risk (RRRI > 0), even if not statistically significant. This result is more straightforward to interpret as compared to the original one based on the RERI. Additionally, our simulations highlighted the importance of large sample sizes for detecting significant interaction effects. Conclusion: We recommend RRRI as the main measure to be considered when exploring additive interaction effects between protective exposures, such as the investigation of synergistic effects between drug combinations or preventive treatments. Full article
11 pages, 2292 KiB  
Article
Leukemia Types and Subtypes Analysis: Epidemiological Age-Standardized Exploration in the Mexican Bajio Region
by Pablo Romero-Morelos, Ana Lilia González-Yebra, Luis Jonathan Bueno-Rosario and Beatriz González-Yebra
Medicina 2024, 60(5), 731; https://doi.org/10.3390/medicina60050731 - 28 Apr 2024
Cited by 2 | Viewed by 1871
Abstract
Background and Objectives: Leukemia, characterized by abnormal leukocyte production, exhibits clonal origin from somatic mutations. Globally, it ranked 15th in cancer incidence in 2020, with higher prevalence in developing countries. In Mexico, it was the ninth most frequent cancer. Regional registries are [...] Read more.
Background and Objectives: Leukemia, characterized by abnormal leukocyte production, exhibits clonal origin from somatic mutations. Globally, it ranked 15th in cancer incidence in 2020, with higher prevalence in developing countries. In Mexico, it was the ninth most frequent cancer. Regional registries are vital for understanding its epidemiology. This study aims to analyze the prevalence and age-standardized incidence rates of leukemias in a tertiary care hospital in the Mexican Bajio region. Materials and Methods: Leukemia cases from 2008–2018 were analyzed, and 535 medical records were included in this study. The prevalence, distribution, and age-specific incidence rate of different types and subtypes of leukemia were determined according to sex and age groups. Results: Overall, 65.79% consisted of lymphocytic leukemia, 33.64% of myeloid leukemia, and 0.56% of monocytic leukemia. No significant sex-based differences were found, but age-specific patterns were observed. Leukemia distribution by age revealed significant associations. Lymphocytic leukemia dominated in the pediatric population, particularly acute lymphocytic leukemia, while myeloid leukemia shifted towards adulthood. Age-specific incidence patterns showed, first, that lymphocytic leukemia is the most common leukemia in pediatric ages, and second, there is a shift from acute lymphocytic leukemia dominance in pediatric ages to myeloid leukemia incidence in late adulthood, emphasizing nuanced epidemiological dynamics. Conclusions: Acute leukemia cases occurred with high prevalence in our study population, with a high incidence in pediatric and adulthood populations, especially for acute lymphocytic leukemia, showing a (<18 years) 153.8 age-standardized incidence rate in the pediatric group, while in the adult population, the age-standardized rate was 59.84. In the age-specific analysis, we found that the childhood group (5–9 years) were the most affected by acute lymphocytic leukemia in the pediatric population, while in the adult population, the early-adulthood group (15–29 years) were the most affected age group. In contrast, chronic myeloid leukemia affected both adults and the pediatric populations, while chronic lymphocytic leukemia and monocytic leukemia were exclusive to adults. The study underscores the need for tailored diagnostic, treatment, and preventive strategies based on age, contributing valuable insights into the leukemia epidemiology of the Bajio region. Full article
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21 pages, 1579 KiB  
Article
Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm
by Aquilino García-Perea, Edwin Fernández-Cruz, Victor de la O-Pascual, Eduardo Gonzalez-Zorzano, María J. Moreno-Aliaga, Josep A. Tur and J. Alfredo Martinez
Medicina 2024, 60(4), 610; https://doi.org/10.3390/medicina60040610 - 8 Apr 2024
Cited by 1 | Viewed by 2071
Abstract
Background and Objectives: Modern classification and categorization of individuals’ health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers’ health [...] Read more.
Background and Objectives: Modern classification and categorization of individuals’ health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers’ health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies. Full article
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Review

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14 pages, 514 KiB  
Review
Unveiling the Value of Meta-Analysis in Disease Prevention and Control: A Comprehensive Review
by Christos Ntais and Michael A. Talias
Medicina 2024, 60(10), 1629; https://doi.org/10.3390/medicina60101629 - 5 Oct 2024
Viewed by 1655
Abstract
Given the plethora of studies today that focus on the same topic, clinicians and other healthcare professionals increasingly rely on meta-analysis to aid in their evidence-based decision-making. This research method, which combines data from multiple studies to produce a single, more precise estimate [...] Read more.
Given the plethora of studies today that focus on the same topic, clinicians and other healthcare professionals increasingly rely on meta-analysis to aid in their evidence-based decision-making. This research method, which combines data from multiple studies to produce a single, more precise estimate of effect size, is invaluable for synthesizing evidence, resolving inconsistencies and guiding clinical practice and public health policies. Especially in disease prevention and control, meta-analysis has emerged as a critical tool. Meta-analysis is particularly valuable in assessing the effectiveness of preventive interventions such as vaccines, lifestyle modifications and screening programs. It provides robust evidence that supports the implementation of effective preventive measures and the discontinuation of ineffective or harmful ones. Furthermore, meta-analysis provides evidence to develop clinical practice guidelines, ensuring patients receive evidence-based treatments. In addition, public health policies aimed at disease prevention and control often rely on evidence from meta-analyses, which provide the data needed to justify and design large-scale public health initiatives. This comprehensive review delves into the role of meta-analysis in disease prevention and control, exploring its advantages, applications, challenges and overall impact on guiding clinical practice and public health policies. Through case studies and an examination of future directions, this paper underscores the pivotal role of meta-analysis in disease prevention and control. Full article
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