Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 3 appraisals
Clinical and experimental dermatology
The role of dermoscopy in optimizing surgical margins for keratinocyte cancers: updated evidence from a systematic review and meta-analysis
BACKGROUND: Keratinocyte cancer (KC) is the most common malignancy worldwide. Surgical excision is the primary treatment, with clear margin delineation critical for oncological and cosmetic outcomes. Dermoscopy, well established for diagnosis, has recently been included in updated British guidelines as an alternative method for surgical margin planning and may offer improved border visualization. OBJECTIVES: To update the existing evidence on dermoscopy-guided excision of KC, focusing on margin control and recurrence risk and incorporating newly published studies and re-evaluating its use considering evolving guideline recommendations. METHODS: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. PubMed, EMBASE and CENTRAL were searched to October 2024. Eligible studies compared dermoscopy-guided with conventional surgical excision of histologically confirmed KC. The primary outcome was the incomplete excision rate. Risk of bias was assessed using ROBINS-I, and meta-analysis was conducted using a DerSimonian-Laird random-effects model. RESULTS: Ten studies (1151 patients; 1186 lesions) were included; 4 contributed to meta-analysis. Most focused on basal cell carcinoma; squamous cell carcinoma data were limited. Dermoscopy was associated with improved surgical precision and reduced incomplete excision (pooled odds ratio 0.30, 95% confidence intervals 0.27-0.34, P < 0.001; I² = 0%, P > 0.99), although all studies were observational and at moderate to serious risk of bias. Narrower margins were often achieved without compromising recurrence outcomes. CONCLUSIONS: Dermoscopy may enhance preoperative planning in KC excision, but evidence remains limited by methodological constraints. These findings support further high-quality trials to confirm clinical utility and define its role in future surgical guidelines.
27 May 2026
Read appraisal →Journal of clinical pathology
Clinicopathological and molecular characterisation of superficial CD34-positive fibroblastic tumour: A systematic review
AIM: This systematic review aims to comprehensively evaluate the clinicopathological and molecular features of superficial CD34-positive fibroblastic tumour (SCD34FT), a recently described intermediate-grade soft-tissue neoplasm recognised in the 5th edition of the WHO classification of soft tissue tumours. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we systematically searched for English-language studies in PubMed, Scopus, Google Scholar and Web of Science. Retrospective or original case series with ≥3 histologically confirmed cases were selected for review, whereas review articles, single case reports and conference abstracts were excluded. Risk of bias was assessed using the Joanna Briggs Institute checklist. RESULTS: A total of 190 patients across 14 selected studies met the inclusion criteria. SCD34FT mainly affected middle-aged adults, with the most common site being the lower extremity. Diffuse CD34 expression was universal across all studies. A high number of cases displayed SynCAM/CADM3 positivity, while WT1 and Pan-CK (focal) were frequent. PRDM10 fusion was detected in 73% of cases, and the most common fusions were PRDM10::MED12 (66%) and PRDM10::CITED2 (28%). Only 9/169 (5.3%) had local recurrences, whereas 4/190 (2.1%) cases had lymph node metastasis, with no distant metastasis or disease-related death. CONCLUSION: SCD34FT is a novel entity with consistent CD34 expression and recurrent PRDM10 rearrangements and shows indolent behaviour. A high index of suspicion for SCD34FT should be warranted in a superficially located tumour with striking nuclear pleomorphism but an unexpectedly low mitotic index. Molecular studies demonstrating PRDM10 rearrangement may be helpful in atypical cases.
19 May 2026
Read appraisal →Histochemistry and cell biology
Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.
Small tissue biopsies, including renal core biopsies, bone marrow trephines, gastrointestinal endoscopic samples, prostate needle cores, liver biopsies, and skin punch or shave specimens, are fundamental to contemporary diagnostic pathology. Their limited volume, focal sampling, and susceptibility to technical artifacts impose distinct interpretive challenges, often requiring semi-quantitative assessment within a restricted architectural context. Although artificial intelligence (AI) has rapidly expanded in digital pathology, most models have been developed using large surgical resection specimens, with comparatively limited attention to small biopsy material. This minireview examines current and emerging applications of AI in small biopsy diagnostics across renal, hepatic, gastrointestinal, hematopathological, dermatopathological, and urological pathology. Reported applications include glomerular segmentation and fibrosis quantification in renal biopsies; automated cellularity, blast detection, and fibrosis grading in bone marrow trephines; dysplasia and microorganism detection in gastrointestinal biopsies; quantitative steatosis and fibrosis assessment in liver samples; tumor detection and grading in prostate cores; and neoplastic pattern recognition in skin specimens. Despite encouraging performance in research settings, substantial barriers to routine clinical implementation remain, including limited dataset size, class imbalance, pre-analytical variability, inter-institutional heterogeneity, and insufficient external validation. We discuss methodological considerations relevant to diagnostic practice, including multi-institutional validation, stain normalization, multimodal integration with histochemistry and ancillary testing, explainability, and regulatory oversight. In the context of small biopsies, AI should be regarded as a quantitative adjunct to morphological interpretation rather than an autonomous diagnostic system. Careful integration within established histopathological workflows is essential to ensure reproducibility, safety, and clinical accountability.
15 May 2026
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