{"title":"Chronic myeloid leukaemia","authors":"Samantha Drummond, Mhairi Copland","doi":"10.1016/j.mpmed.2025.03.001","DOIUrl":"10.1016/j.mpmed.2025.03.001","url":null,"abstract":"<div><div>Chronic myeloid leukaemia (CML) is a clonal myeloproliferative disorder resulting from a reciprocal translocation between the long arms of chromosomes 9 and 22. This is termed the Philadelphia chromosome, and leads to production of the fusion oncoprotein BCR::ABL1, a 210 kDa constitutively active tyrosine kinase. CML has two distinct phases: chronic and blast. Most patients (95%) present in the chronic phase, which is associated with leucocytosis and splenomegaly. Blast phase is associated with bone marrow failure and carries a poor prognosis. The introduction of tyrosine kinase inhibitors (TKIs; imatinib, dasatinib, nilotinib, bosutinib, ponatinib) and a STAMP (specifically targeting the ABL myristoyl pocket) inhibitor (asciminib) have altered the clinical course of CML for most patients, turning it from a fatal leukaemia to a chronic disorder managed with oral medication. Patients with chronic phase CML have excellent responses to TKIs, and individuals with an optimal response can expect a normal lifespan; some successfully discontinue TKI therapy. However, resistance to TKIs is seen, particularly in blast phase CML. In these patients, allogeneic stem cell transplantation is an important treatment option. With increasing experience in TKI use, different adverse effect profiles are emerging and require consideration when choosing the most suitable TKI for an individual patient.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 5","pages":"Pages 304-307"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924653","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}
Austin G Kulasekararaj, Shreyans Gandhi, Roochi Trikha
{"title":"Bone marrow failure: causes and complications","authors":"Austin G Kulasekararaj, Shreyans Gandhi, Roochi Trikha","doi":"10.1016/j.mpmed.2025.02.009","DOIUrl":"10.1016/j.mpmed.2025.02.009","url":null,"abstract":"<div><div>Aplastic anaemia (AA), a rare but serious form of bone marrow failure (BMF), is characterized by pancytopenia with hypocellular bone marrow. The pathophysiology of acquired AA is predominantly immunologically mediated, with damage to haemopoietic stem cells by autoreactive T lymphocytes. The aberrant immune response can be triggered by environmental triggers, such as drugs, toxins, chemicals and viral infections, especially after seronegative hepatitis. A careful medical and family history, physical examination and investigations are required to rule out rarer inherited causes of BMFs, as well as other acquired diseases, such as hypoplastic myelodysplastic syndrome, with a similar phenotype. The clinical spectrum of acquired AA varies: some patients with mild cytopenia do not require therapy; others have life-threatening complications resulting from severe pancytopenia. The autoimmune basis provides the rationale for treatment, with either combined immunosuppressive therapy using horse antithymocyte globulin and ciclosporin with eltrombopag, or allogeneic haemopoietic stem cell transplantation (HSCT). Long-term survival of 70–80% can be expected from these standard therapeutic modalities. Recurrence of pancytopenia, secondary to relapse, clonal evolution to myelodysplastic syndrome and paroxysmal nocturnal haemoglobinuria are late sequelae after immunosuppressive therapy. By contrast, HSCT provides the chance of long-term cure.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 5","pages":"Pages 273-277"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924748","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":"Observational and real-world studies","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.03.010","DOIUrl":"10.1016/j.mpmed.2025.03.010","url":null,"abstract":"<div><div>While randomized studies provide the best evidence, they are not practical in some circumstances, for example rare diseases. Observational and real-world studies cannot replace randomized trials but they provide evidence of causality to be interpreted with other data. Observational studies are of two types – descriptive and analytical. Observational and real-world studies suffer from several biases, mainly selection bias. This is hard to overcome, but can be mitigated by the use of propensity analysis and sensitivity analysis.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 358-360"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147590","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":"Systematic review and meta-analysis in clinical trials","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.04.004","DOIUrl":"10.1016/j.mpmed.2025.04.004","url":null,"abstract":"<div><div>A systematic review aims to evaluate the effectiveness of interventions by comprehensively analysing published studies. The basis is a thorough search across multiple databases to identify studies meeting predefined inclusion criteria, with data extracted on study design, participant characteristics and key outcomes. Results are often pooled using meta-analysis where appropriate, revealing the key findings. Systematic reviews and meta-analyses are cornerstone methodologies in evidence-based research, providing a structured and comprehensive approach to synthesizing existing evidence on a specific topic. Although they are related, they are distinct concepts. A systematic review is a type of literature search that uses repeatable steps to find evaluate and synthesize evidence to answer a research question. Meta-analyses use statistical techniques to pool data from multiple studies, providing a quantitative summary of the evidence. These methods are widely used across disciplines including medicine, public health, psychology, education and social sciences, to inform policy, practice and further research. While they are separate methods, systematic review and meta-analysis share common features and the need for common standards.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 364-367"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147592","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":"Statistics and data in health economics","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.03.007","DOIUrl":"10.1016/j.mpmed.2025.03.007","url":null,"abstract":"<div><div>Health economics is the study of value for money to guide decision-making. The conduct of heath economic analysis involves a wide variety of data types, collected from both publicly available sources and by specific data collection. Specialist and non-specialist methods of analysis are used to conduct the different types of analysis. These include cost evaluation, cost minimization, cost-effectiveness and cost–benefit analysis.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 396-398"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147816","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":"Summarizing and presenting data from clinical trials","authors":"Gregory L Ginn, Clare Campbell-Cooper","doi":"10.1016/j.mpmed.2025.04.008","DOIUrl":"10.1016/j.mpmed.2025.04.008","url":null,"abstract":"<div><div>Clinical trials rely on rigorous data preparation and analysis to ensure robust, reliable outcomes. Key components include defining analysis populations, handling missing data and evaluating primary and secondary endpoints. Analysis populations, such as intent-to-treat and per-protocol, play a pivotal role in interpreting treatment efficacy under both real-world and ideal conditions. Handling of missing data, a critical challenge, employs techniques such as multiple imputation and maximum likelihood estimation to minimize bias and preserve validity. Efficacy data analysis revolves around predefined endpoints, with primary endpoints driving trial success and regulatory approval, and secondary endpoints providing broader insights into treatment effects. Subgroup and longitudinal analyses offer nuanced understandings of differential treatment effects and time-based outcomes, leveraging statistical tools such as mixed-effects models and Kaplan–Meier curves. Safety analyses, including adverse event reporting and time-to-event models, are essential for assessing treatment risks. Comparative safety analysis evaluates adverse events, serious adverse events and risk–benefit balances between treatments using methods such as logistic regression and Cox proportional hazards models. By integrating these methodologies, clinical trials provide comprehensive evaluations of treatments, guiding regulatory decisions and advancing medical knowledge. This systematic approach ensures that findings are both scientifically rigorous and clinically relevant.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 368-375"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147491","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":"Interpreting clinical guidelines","authors":"Shams Al-Ani, Anthony Lockett","doi":"10.1016/j.mpmed.2025.04.003","DOIUrl":"10.1016/j.mpmed.2025.04.003","url":null,"abstract":"<div><div>Clinical guidelines are an essential part of clinical and patient decision-making. To be relevant clinical guidelines must incorporate evidence and the opinion of clinicians and patients. Guidelines should be developed to quality standards and regularly updated if they are to be of value. Guidelines should be departed from if there is new evidence or depending on individual circumstances.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 392-395"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147815","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 measurement in clinical trials","authors":"Anthony Lockett","doi":"10.1016/j.mpmed.2025.03.012","DOIUrl":"10.1016/j.mpmed.2025.03.012","url":null,"abstract":"<div><div>Clinical measurement is a cornerstone of healthcare, enabling accurate diagnosis, monitoring and treatment evaluation. It encompasses a wide range of tools and techniques, from vital sign assessments to advanced imaging and biomarker analysis. Key challenges include ensuring accuracy, precision and reliability while minimizing the variability caused by human error, device limitations or patient factors. The standardization and calibration of instruments are critical to maintaining data integrity. Innovations such as wearable devices and point-of-care testing are transforming clinical measurement, offering real-time, patient-centred data. Addressing these challenges and leveraging technological advancements are essential for improving patient outcomes and advancing evidence-based medical practices.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 385-387"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147494","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":"The effect of web-based clinical misinformation on patient interactions","authors":"David Wandless","doi":"10.1016/j.mpmed.2025.03.011","DOIUrl":"10.1016/j.mpmed.2025.03.011","url":null,"abstract":"<div><div>The proliferation of online misinformation has reshaped patient–provider interactions, posing risks to trust, adherence and effective healthcare delivery. With the accessibility of Web 2.0 platforms, patients increasingly turn to online sources for health information, often encountering unverified and misleading content. This article examines the impact of web-based clinical misinformation on patient interactions, highlighting how false claims influence trust, decision-making and adherence to treatment. Key contributing factors, such as social media dynamics, cognitive biases and spread of misinformation, are explored, alongside the role of healthcare professionals in mitigating the effects of misinformation. Strategies to address misinformation, including digital literacy education, collaborative efforts with technology platforms and improved patient guidance, are discussed. This article underscores the need for a unified approach to combating misinformation, fostering a healthcare environment that supports informed, evidence-based patient engagement.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 407-410"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147496","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":"Audit and quality improvement in statistics and data in healthcare","authors":"Anthony Lockett, Elizabeth Lockett","doi":"10.1016/j.mpmed.2025.04.002","DOIUrl":"10.1016/j.mpmed.2025.04.002","url":null,"abstract":"<div><div>Audit and quality improvement are central to the governance of healthcare and research. They are cyclical in nature, with audit having shorter cycles than quality improvement. The type of audit and improvement depends on the objectives and the data available. However, both use the ‘model for improvement’ system to achieve objectives.</div></div>","PeriodicalId":74157,"journal":{"name":"Medicine (Abingdon, England : UK ed.)","volume":"53 6","pages":"Pages 402-406"},"PeriodicalIF":0.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147127","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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