{"title":"Statistical analysis and significance tests for clinical trial data","authors":"Gregory L Ginn, Clare Campbell-Cooper","doi":"10.1016/j.mpmed.2025.04.005","DOIUrl":"10.1016/j.mpmed.2025.04.005","url":null,"abstract":"<div><div>The analysis of clinical trial data is vital for determining the true effects of treatments and differentiating these effects from random variation. Two key statistical methodologies are discussed: descriptive and inferential. Descriptive statistics provide insights by summarizing participant characteristics, treatment outcomes, and variable distributions using measures such as the mean, median, standard deviation and interquartile range. These summaries set the stage for hypothesis testing and assumption validation. Inferential statistics extend this foundation by enabling generalizations about a broader population, employing methods such as hypothesis testing, confidence intervals and regression models. Hypothesis testing evaluates the evidence for treatment effects, often using statistical tests such as <em>t</em>-tests, analysis of variance or chi-squared tests, while confidence intervals quantify the precision of these effects. Survival analysis, such as Kaplan–Meier curves and Cox models, is employed for time-to-event data. Adjusting for covariates is crucial for controlling confounding factors and is often paired with methods to manage multiple comparisons, such as Bonferroni corrections and false discovery rate (FDR) procedures. Proper power calculations ensure adequate sample sizes to detect meaningful effects, minimizing type I and type II errors. This comprehensive approach strengthens the reliability of clinical trial conclusions, supporting evidence-based decision-making in medical research.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 376-379"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Clinical trial design and conduct","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.04.001","DOIUrl":"10.1016/j.mpmed.2025.04.001","url":null,"abstract":"<div><div>This article provides an overview of the clinical and scientific challenges that must be considered in developing a clinical trial. Here, the clinical, scientific and regulatory setting of clinical trials are considered. In particular, the article discusses the issues surrounding the identification of the target population, definition of the treatment, choice of clinical outcomes and choice of comparators. It includes a discussion of the choice of randomization strategies, blinding, conduct and monitoring of the study, and plans for reporting the results. The importance of a well-defined study protocol is emphasized.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 355-357"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cognitive bias and human factors in statistics and data in healthcare","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.03.008","DOIUrl":"10.1016/j.mpmed.2025.03.008","url":null,"abstract":"<div><div>Bias and human factors play a major role in the way in which data are interpreted and the resultant decisions. Six common sources of bias and the link that they have to human factors are presented. An understanding of bias and human factors is essential if information and data are to be correctly used. Testing strategies and cultural factors play a major role in preventing the misinterpretation of data.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 399-401"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Choosing statistical methods for clinical trials","authors":"Gregory L Ginn, Clare Campbell-Cooper","doi":"10.1016/j.mpmed.2025.04.007","DOIUrl":"10.1016/j.mpmed.2025.04.007","url":null,"abstract":"<div><div>Choosing the appropriate statistical methods is vital for ensuring the integrity, validity and efficiency of clinical trials. The selection of the methods to be used depends on trial-specific factors, including the nature of the data collected, hypothesis to be tested, sample size, duration, complexity and nature of the intervention. Once the overall methods are established, power analysis (balancing type I and II error risks, typically targeting 80–90% power to detect true treatment effects) needs to be considered. Variability, allocation ratio, study design and potential attrition also influence the methods selected. Incorporating these methodologies into clinical trial design ensures statistical rigour, resource efficiency and ethical integrity, enabling researchers to generate reliable, impactful evidence to guide clinical practice and advance medical knowledge.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 380-384"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mendelian randomization and studies","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.03.009","DOIUrl":"10.1016/j.mpmed.2025.03.009","url":null,"abstract":"<div><div>Mendelian randomization is an analytical method that uses genetic variants to overcome the confounding factors of observational studies. For Mendelian randomization analysis to be valid, several assumptions must be true: that genetic variants are associated with exposure; that there is no confounding relationship between the variant and the outcome; and that there are no effects of the variant independent of the outcome. Assuming these assumption are met, Mendelian randomization is a valuable tool in determining causality.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 361-363"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Greg L Ginn, Clare Campbell-Cooper, Anthony Lockett
{"title":"The growing role of Bayesian methods in clinical trial design and analysis","authors":"Greg L Ginn, Clare Campbell-Cooper, Anthony Lockett","doi":"10.1016/j.mpmed.2025.04.006","DOIUrl":"10.1016/j.mpmed.2025.04.006","url":null,"abstract":"<div><div>Bayesian methods are increasingly used in clinical trials because of their flexibility and ability to incorporate prior knowledge into data analysis. Unlike frequentist approaches, which rely solely on current trial data, Bayesian methods combine prior information – such as data from earlier studies or expert opinion – with observed data to update the probability of a hypothesis. This dynamic updating process, based on Bayes’ theorem, provides a more intuitive framework for decision-making, particularly in adaptive trials or when sample sizes are small. Bayesian methods excel in handling complex problems such as multiple endpoints or subgroup analyses and allow continuous updates as new data become available. Key advantages include the incorporation of prior information, direct probability-based interpretations of results and greater adaptability compared with frequentist approaches. Applications in clinical trials include: adaptive designs, where trial parameters may be modified based on interim data; efficient use of prior information to reduce sample sizes; probabilistic decision-making to guide trial progress; and enhanced reliability in rare diseases or small trials. By offering a robust, intuitive framework for analysing trial data, Bayesian methods address the complexities of modern clinical research, improving efficiency, adaptability and resource utilization while supporting more informed regulatory and development decisions.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 388-391"},"PeriodicalIF":0.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Self-assessment/CPD answers","authors":"","doi":"10.1016/j.mpmed.2025.04.009","DOIUrl":"10.1016/j.mpmed.2025.04.009","url":null,"abstract":"","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 411-415"},"PeriodicalIF":0.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Iron, vitamin B12 and folate","authors":"Gayatri Saxena, Bethany Singh, Annelies Billen","doi":"10.1016/j.mpmed.2025.01.004","DOIUrl":"10.1016/j.mpmed.2025.01.004","url":null,"abstract":"<div><div>Iron, vitamin B<sub>12</sub>, and folate are essential for the body’s metabolic reactions. Deficiency of these in isolation or in combination can lead to anaemia and systemic symptoms. Sometimes the systemic symptoms and deficiency can precede the anaemia. Deficiency states are commonly seen in everyday practice so it is vital to be able to recognize and treat them appropriately. Differentiating and diagnosing the cause of anaemia allows clinicians to understand the steps in clinical presentation and the specific investigations. Every effort should be made to determine the cause of the nutritional deficiency and treat it if possible. Transfusion is rarely required and many of these presentations can be successfully treated with a period of supplementation. Patient compliance with treatment is key to successful treatment.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 4","pages":"Pages 181-185"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Inherited bleeding disorders","authors":"Gavin Ling, Pu-Lin Luo","doi":"10.1016/j.mpmed.2025.01.007","DOIUrl":"10.1016/j.mpmed.2025.01.007","url":null,"abstract":"<div><div>Inherited bleeding disorders (IBDs) encompass a large number of different but rare conditions that can lead to increased risk of bleeding. The most common IBDs are von Willebrand disease, haemophilia A and haemophilia B. The diagnosis of IBDs requires a detailed history of the bleeding and specialized coagulation testing. The management of bleeding episodes in patients with IBDs can include the use of coagulation factor concentrate, desmopressin and antifibrinolytics such as tranexamic acid. This brief review focuses on the more common IBDs.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 4","pages":"Pages 225-228"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Management of patients who refuse blood transfusion","authors":"Kelly Feane, James Uprichard","doi":"10.1016/j.mpmed.2025.01.011","DOIUrl":"10.1016/j.mpmed.2025.01.011","url":null,"abstract":"<div><div>The management of patients who refuse blood transfusion presents a unique combination of ethical, legal and medical challenges. Refusal can stem from religious beliefs, such as those held by Jehovah's Witnesses, or other personal reasons, such as fear of transfusion-transmitted infections or being given blood from vaccinated donors. This article presents the principles of respecting patient autonomy while ensuring safe and effective medical care, particularly when life-sustaining treatments are declined. Informed by the UK Mental Capacity Act 2005, which upholds a patient's right to refuse treatment, the article outlines a multidisciplinary approach to patient care that involves identification of the blood refuser, preoperative optimization, intraoperative blood conservation techniques and legal considerations. It also addresses some of the issues in the management of paediatric patients when parents refuse transfusions on behalf of their children. Alternative strategies such as erythropoietin, intravenous iron and cell salvage are discussed. The importance of individualized care plans, early identification, thorough documentation and continuing communication between the multidisciplinary team and the patient or family is emphasized to achieve the best possible outcomes.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 4","pages":"Pages 253-256"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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