Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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Cancer medicine
Applications of Artificial Intelligence in Cancer Diagnosis and Treatment
Driven by changes in lifestyle and environmental factors, the global incidence of cancer is steadily increasing, which has established it as a leading cause of mortality worldwide. The current paradigm for cancer diagnosis and treatment relies on conventional methods, such as imaging, endoscopy, and tissue biopsy, which present significant limitations regarding sensitivity in early screening, diagnostic specificity, and personalized treatment. Consequently, the development of more efficient and accurate technologies remains a major objective in modern oncology research, and artificial intelligence (AI) has emerged as a particularly promising solution. Through machine learning and deep learning algorithms, AI is reshaping cancer care by enabling automated detection of minute lesions during screening and quantitative analysis of pathological features for diagnosis. It may also advance tumor theranostics through multimodal data integration for treatment stratification, response prediction, and image-guided or targeted therapeutic decision-making, whereas providing data-driven recommendations for personalized treatment. Despite these prospects, medical AI development faces several key issues, including data bias, model explainability, clinical reliability and generalizability, emerging limitations of foundation models and generative AI, and regulatory and ethical issues that need to be addressed. By reviewing recent advances in AI across screening, diagnosis, theranostics, and treatment, we aim to clarify where these methods are already useful, where evidence remains limited, and why closer collaboration among clinicians, engineers, and data scientists is needed for clinical translation. We hope this review serves as a practical reference for researchers and clinicians evaluating how AI may be integrated into oncology in a more standardized, clinically responsible way.
1 Aug 2026
Read appraisal →Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Patient experiences of tissue donation and digital consent support in primary craniospinal tumour research.
PURPOSE: Requests for tissue donation for research are often made at times of heightened vulnerability, particularly around diagnosis and surgery. This study explored patient experiences of tissue donation discussions, perspectives on consent, and the acceptability of digital decision support in primary craniospinal tumour research. METHODS: A UK national online cross-sectional survey was conducted with 50 adults with a primary brain tumour or spinal sarcoma. The survey was developed with patient and public involvement; six patient contributors reviewed the initial questionnaire before launch. Descriptive statistics summarised closed responses, and open-text comments were grouped descriptively to contextualise quantitative findings. Reporting was informed by STROBE guidance. RESULTS: Just over half of participants reported being invited to donate tissue for research (26/50, 52%). Respondents strongly preferred tissue donation to be discussed at or after a clinic appointment, and none selected the day of surgery as the preferred time. Among invited respondents, most reported that information was easy to understand (22/26, 85%), that they had an opportunity to ask questions (23/25, 92%), and that they had sufficient time to consider the decision (23/26, 88%). Sixteen of 26 invited respondents (62%) discussed the decision with family or friends; among invited respondents who had not done so, 7/10 (70%) would have liked the opportunity. Interest in a secure digital adjunct was high (46/49, 94%). CONCLUSION: Overall experience was generally positive, but the data identify specific, practical opportunities to strengthen consent support in rare craniospinal tumour pathways, including appropriate timing, clear and revisitable information, opportunities for question-asking, and resources that support family-inclusive decision-making.
19 July 2026
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