Current Trends and Future Directions of Statistical Methods in Medical Research: A Scientometric Analysis

IF 2.1 4区医学 Q3 HEALTH CARE SCIENCES & SERVICES

Journal of evaluation in clinical practice Pub Date : 2025-09-08 DOI:10.1111/jep.70257

Fatma Yardibi, Chaomei Chen, Cagdas Hakan Aladag, Ozkan Kose

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引用次数: 0

Abstract

Aims and Objective

The field of medical statistics has experienced significant advancements driven by integrating innovative statistical methodologies. This study aims to conduct a comprehensive analysis to explore current trends, influential research areas, and future directions in medical statistics.

Methods

This paper maps the evolution of statistical methods used in medical research based on 4,919 relevant publications retrieved from the Web of Science. High-frequency keywords and citation metrics were analyzed to identify research hotspots. A dual-map overlay and document co-citation analysis were performed using CiteSpace to uncover thematic clusters and track knowledge flow between disciplines. Additionally, network metrics, such as betweenness centrality and sigma, were employed to quantify the influence and novelty of publications.

Results

Results identified a strong interdisciplinary exchange between medical statistics and fields such as health, nursing, molecular biology, and computer science, with clinical trials, survival analysis, and predictive modeling emerging as central themes. The influence of artificial intelligence (AI), machine learning (ML), and deep learning (DL) is growing substantially, particularly in areas such as diagnostic imaging, epidemiology, and treatment prediction, highlighting a shift towards more complex, data-driven methodologies. While traditional statistical techniques, such as survival analysis and regression, remain vital, emerging technologies are reshaping research approaches, fostering collaboration, and advancing the field's capabilities.

Conclusion

Future research will likely focus on overcoming challenges related to data privacy, ethical considerations, and the need for continued biostatistics education in healthcare. This study offers a roadmap for ongoing research and highlights opportunities for future interdisciplinary collaborations to address the complexities of modern medical data analysis. This scientometrics study reveals the evolution of statistical methods used in medical research over time, evaluates frequently cited models and thematic changes, and provides implications that can enhance evidence-based decision-making processes regarding methodological choices that guide contemporary clinical practice.

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医学研究中统计方法的当前趋势和未来方向：科学计量分析

医学统计领域在整合创新统计方法的推动下取得了重大进展。本研究旨在对医学统计学的发展趋势、影响研究领域和未来发展方向进行综合分析。方法基于Web of Science检索到的4919篇相关文献，对医学研究中统计方法的演变进行梳理。分析高频关键词和被引指标，确定研究热点。利用CiteSpace进行双图叠加和文献共被引分析，揭示主题集群并跟踪学科间的知识流动。此外，网络指标，如中间性中心性和西格玛，被用来量化出版物的影响力和新颖性。结果表明，医学统计学与健康、护理、分子生物学和计算机科学等领域之间存在着强有力的跨学科交流，临床试验、生存分析和预测建模成为中心主题。人工智能（AI）、机器学习（ML）和深度学习（DL）的影响正在大幅增长，特别是在诊断成像、流行病学和治疗预测等领域，突显出向更复杂、数据驱动的方法的转变。虽然传统的统计技术，如生存分析和回归仍然至关重要，但新兴技术正在重塑研究方法，促进合作，并推进该领域的能力。未来的研究可能会集中在克服与数据隐私、伦理考虑以及医疗保健中持续生物统计学教育的需求相关的挑战。这项研究为正在进行的研究提供了路线图，并强调了未来跨学科合作的机会，以解决现代医学数据分析的复杂性。这项科学计量学研究揭示了医学研究中使用的统计方法随时间的演变，评估了经常被引用的模型和主题变化，并提供了一些启示，可以加强关于指导当代临床实践的方法选择的循证决策过程。

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来源期刊

Journal of evaluation in clinical practice 医学-卫生保健

CiteScore

4.80

自引率

4.20%

发文量

143

审稿时长

3-8 weeks

期刊介绍： The Journal of Evaluation in Clinical Practice aims to promote the evaluation and development of clinical practice across medicine, nursing and the allied health professions. All aspects of health services research and public health policy analysis and debate are of interest to the Journal whether studied from a population-based or individual patient-centred perspective. Of particular interest to the Journal are submissions on all aspects of clinical effectiveness and efficiency including evidence-based medicine, clinical practice guidelines, clinical decision making, clinical services organisation, implementation and delivery, health economic evaluation, health process and outcome measurement and new or improved methods (conceptual and statistical) for systematic inquiry into clinical practice. Papers may take a classical quantitative or qualitative approach to investigation (or may utilise both techniques) or may take the form of learned essays, structured/systematic reviews and critiques.