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New Advances in Clinical Epidemiological Research Methods

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Research Methods".

Deadline for manuscript submissions: 20 March 2026 | Viewed by 635

Special Issue Editors

Department of Translational Immunology and Experimental Intensive Care, Centre of Postgraduate Medical Education, Warsaw, Poland
Interests: research methodology; reproductive health; clinical epidemiological research methods

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Guest Editor
Department of Obstetrics, Perinatology and Neonatology, Centre of Postgraduate Medical Education, Warsaw, Poland
Interests: obstetric delivery; prenatal diagnosis; fetal development; fetal medicine; fetal diseases

Special Issue Information

Dear Colleagues,

Clinical epidemiology stands at the intersection of methodological rigor and practical application in patient-centered research. Recent years have brought about remarkable developments in study designs, analytical approaches, and data integration techniques, including real-world data, artificial intelligence, and causal inference frameworks. These innovations are transforming how we investigate disease etiology, assess interventions, and inform clinical decision-making.

This Special Issue aims to highlight cutting-edge methodological advances that enhance the validity, transparency, and relevance of clinical epidemiological research. We welcome submissions focusing on the following areas:

  • Novel study designs in observational and interventional research;
  • Real-world data in epidemiological research;
  • Advanced statistical and computational methods;
  • Approaches to bias control and confounding adjustment;
  • Integration of multi-source data (e.g., electronic health records, registries, and omics);
  • Applications of machine learning in clinical research;
  • Reproducibility and reporting standards;
  • Ethical and regulatory challenges in modern epidemiological practice.

By showcasing methodological innovation across diverse clinical areas, we hope to stimulate interdisciplinary dialogue and promote best practices in clinical epidemiology.

We look forward to your contributions to this Special Issue.

Dr. Dorota Sys
Dr. Anna Scholz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • clinical epidemiology
  • research methodology
  • observational studies
  • causal inference
  • real-world data
  • machine learning
  • bias control

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Published Papers (1 paper)

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Research

14 pages, 1011 KB  
Article
Measuring What Matters in Trial Operations: Development and Validation of the Clinical Trial Site Performance Measure
by Mattia Bozzetti, Alessio Lo Cascio, Daniele Napolitano, Nicoletta Orgiana, Vincenzina Mora, Stefania Fiorini, Giorgia Petrucci, Francesca Resente, Irene Baroni, Rosario Caruso and Monica Guberti
J. Clin. Med. 2025, 14(19), 6839; https://doi.org/10.3390/jcm14196839 - 26 Sep 2025
Viewed by 475
Abstract
Background/Objectives: The execution of clinical trials is increasingly constrained by operational complexity, regulatory requirements, and variability in site performance. These challenges have direct implications for the reliability of trial outcomes. However, standardized methods to evaluate site-level performance remain underdeveloped. This study introduces the [...] Read more.
Background/Objectives: The execution of clinical trials is increasingly constrained by operational complexity, regulatory requirements, and variability in site performance. These challenges have direct implications for the reliability of trial outcomes. However, standardized methods to evaluate site-level performance remain underdeveloped. This study introduces the Clinical Trial Site Performance Measure (CT-SPM), a novel framework designed to systematically capture site-level operational quality and to provide a scalable short form for routine monitoring. Methods: We conducted a multicenter study across six Italian academic hospitals (January–June 2025). Candidate performance indicators were identified through a systematic review and expert consultation, followed by validation and reduction using advanced statistical approaches, including factor modeling, ROC curve analysis, and nonparametric scaling methods. The CT-SPM was assessed for structural validity, discriminative capacity, and feasibility for use in real-world settings. Results: From 126 potential indicators, 18 were retained and organized into four domains: Participant Retention and Consent, Data Completeness and Timeliness, Adverse Event Reporting, and Protocol Compliance. A bifactor model revealed two higher-order dimensions (participant-facing and data-facing performance), highlighting the multidimensional nature of site operations. A short form comprising four items demonstrated good scalability and sufficient accuracy to identify underperforming sites. Conclusions: The CT-SPM represents an innovative, evidence-based instrument for monitoring trial execution at the site level. By linking methodological rigor with real-world applicability, it offers a practical solution for benchmarking, resource allocation, and regulatory compliance. This approach contributes to advancing clinical research by providing a standardized, data-driven method to evaluate and improve performance across networks. Full article
(This article belongs to the Special Issue New Advances in Clinical Epidemiological Research Methods)
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