Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 3 appraisals
Medicine
Survival benefit of concurrent beta-blocker use in cancer patients treated with radiotherapy: A systematic review and meta-analysis
BACKGROUND: Both preclinical and retrospective studies have implicated β-adrenergic signaling in cancer progression, leading to interest in β-blockers (BBs) as adjunctive anticancer agents. There is evidence that they may enhance the sensitivity of cancer cells to radiotherapy and other conventional therapies. We conducted a systematic review and meta-analysis to explore the radiosensitizing effects of BBs. METHODS: PubMed, the Cochrane Library, Embase, Web of Science, the China National Knowledge Infrastructure, the China biology medicine database, Wan fang Data, and the VIP database were searched for articles in both English and Chinese from the establishment of the databases to September 8, 2025, to identify studies comparing outcomes according to beta-blocker use (yes vs no) in patients with solid tumors treated with radiotherapy. The primary endpoint was overall Survival (OS), Secondary objectives included 1, 2, 5-Year Survival, disease-free survival, distant metastasis-free survival, locoregional progression-free survival and progression-free survival (PFS). RESULTS: 8 studies (3165 patients), including 7 retrospective cohort studies and 1 randomized controlled trial, were analyzed. The most common cancer was non-small cell lung cancer (n = 5). BB use was associated with significantly improved OS (hazard ratio [HR] 0.73, 95% confidence interval: 0.64-0.83). Benefits were also observed for disease-free survival (HR 0.69) and Distant Metastasis-Free Survival (HR 0.62), indicating reduced recurrence and metastasis. CONCLUSION: In this meta-analysis, the use of BBs during or around radiotherapy may be associated with longer OS in cancer patients, suggesting that it may enhance the efficacy of radiotherapy and provide a survival benefit. Alternatively, the effect of β-blockers on survival may shift from a nonspecific effect to an intriguing cancer-specific effect over time. Beta-blockers are an intriguing option to explore in prospective studies of patients with solid tumors undergoing radiotherapy.
26 July 2026
Read appraisal →Journal of the American Heart Association
Social Determinants of Health and Cardiovascular Disease-Related Outcome Disparities Among Breast Cancer Survivors: A Systematic Review
BACKGROUND: Breast cancer is the most commonly diagnosed malignancy worldwide. Breast cancer survivors face an increased risk of cardiovascular disease (CVD), a leading cause of death in this group. Social determinants of health (SDoHs), operationalized as economic, environmental, and psychosocial factors, play an important role in CVD disparities. However, few studies have examined how SDoHs are associated with CVD disparities in this population, and no systematic review has addressed their multilevel influences. METHODS: This systematic review summarizes the current evidence on the relationships between SDoHs at different levels and CVD disparities among breast cancer survivors. Using the 2024 American College of Cardiology/American Heart Association framework, SDoHs were categorized at the individual, interpersonal, or community levels. Studies published in peer-reviewed journals between January 1, 2010, and November 30, 2025, were identified through searching electronic databases (PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, Web of Science, PsycINFO) and citations. RESULTS: Of 6550 unique records, 37 articles that addressed the impact of SDoHs on CVD outcomes were selected. Most (n=31) were conducted in the United States and used retrospective designs (n=29). Most (n=30) focused on individual-level SDoHs such as race, income, or education; 2 on interpersonal-level SDoHs (ie, psychosocial stress); and 13 on community-level SDoHs, including neighborhood socioeconomic status and residential area. Black race, lower neighborhood socioeconomic status, and rural residence were associated with a higher incidence of CVD and increased cardiovascular death. CONCLUSIONS: This review highlights the urgent need to address SDoHs and emphasizes the importance of multilevel interventions to reduce CVD disparities among breast cancer survivors.
9 July 2026
Read appraisal →Biomedical physics & engineering express
Parameter-efficient adaptation of foundational models for automated myocardial strain analysis
Purpose. Automated myocardial strain analysis requires accurate segmentation and motion tracking, but deep learning methods trained on one dataset often fail when applied to images from different scanners or institutions. We investigate how general-purpose foundational models can be efficiently adapted for cardiac strain estimation, establishing the minimal data requirements for robust cross-domain deployment.Methods. We propose CardiacSAM, a lightweight adaptation of the Segment Anything Model (SAM) fine-tuned with Low-Rank Adaptation, for cardiac structure segmentation, paired with uniGradICON for myocardial motion estimation. We compute global strain in cardiac coordinates for both short-axis (SAX) and long-axis (LAX) views.Results. Validated on four public and one private dataset comprising over 900 subjects, CardiacSAM achieved mean left ventricle (LV) Dice scores of0.90±0.02using only 10 training studies per domain for SAX (50 for LAX). Motion estimation achieved median average endpoint error (AEPE) of 3.08 mm on 15 volunteers without known cardiac disease with expert landmark annotations. Strain measurements discriminated significantly between reference and disease groups across all datasets. Comparing SAX and LAX strain in 360 subjects showed moderate correlation for radial strain (r=0.64) but weak correlation for longitudinal strain (r=0.17), suggesting SAX and LAX capture complementary information about cardiac function.Conclusion. Parameter-efficient adaptation of foundational models enables automated cardiac strain assessment with high data efficiency and robust cross-dataset generalization.
23 June 2026
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