Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 5 appraisals
Journal of pediatric surgery
Artificial intelligence in rare pediatric solid tumor research and clinical care: A scoping review
BACKGROUND: Clinical and research advances for children with solid tumors are limited by their rare nature. Artificial intelligence (AI) and machine learning (ML) hold potential for advancing diagnosis, risk stratification, and treatment in rare diseases where individual patients contribute high-dimensional data. This review characterizes current AI/ML applications in rare pediatric solid tumors. METHODS: PubMed, Embase, and Web-of-Science Core Collection databases were queried for relevant articles published before February 10, 2025. Eligible studies applied AI/ML methods to study rare tumors in pediatric populations (≤19 years). Articles were evaluated for tumor diagnosis, AI/ML methods, clinical applications, comparators, effectiveness, and interpretability. RESULTS: Twenty-three studies (2009-2025) were included. Hepatoblastoma (12/23) and pediatric thyroid cancers (4/23) were most frequently studied. Supervised learning predominated (20/23), followed by unsupervised (9/23), deep learning (4/23), and hybrid/ensemble models (6/23). Applications included diagnosis (12/23), prognosis (10/23), and risk stratification (9/23). Twenty studies reported effectiveness measures, with many models achieving AUCs >0.85. In comparative analysis (17/23), AI/ML often equaled or exceeded expert consensus, traditional models, or alternative algorithms. Eight studies reported external validation. CONCLUSIONS: Current AI/ML research in rare pediatric extra-cranial solid tumors focuses on diagnosis, risk stratification, and prognosis, often outperforming traditional methods. Future work should prioritize external validation and clinical applicability.
1 July 2026
Read appraisal →Journal of robotic surgery
Perioperative outcomes of transoral endoscopic vs. robotic thyroidectomy: a systematic review and meta-analysis
BACKGROUND: Transoral endoscopic thyroidectomy vestibular approach (TOETVA) and transoral robotic thyroidectomy (TORT) have emerged as scarless alternatives to conventional open thyroidectomy, offering excellent cosmetic outcomes. However, the comparative perioperative outcomes between these two minimally invasive techniques remain to be systematically evaluated. This meta-analysis aimed to compare the perioperative outcomes of TOETVA and TORT in patients undergoing thyroid surgery. METHODS: A systematic search was performed in PubMed, Embase, the Cochrane Library, and Web of Science from inception to March 1, 2026, for studies comparing TOETVA and TORT. The primary outcomes included recurrent laryngeal nerve injury, hypoparathyroidism, mental nerve injury, seroma, surgical site infection, and postoperative hemorrhage. The secondary outcome included operation time, length of hospital stay, number of lymph nodes dissected, and postoperative pain score. Pooled weighted mean differences (MD) or odds ratios (OR) with 95% confidence intervals (CI) were calculated using a random-effects model. Study quality was assessed using the ROBINS-I tool. RESULTS: A total of 5 studies involving 1,080 patients were included (639 in the TOETVA group and 441 in the TORT group). Compared with TOETVA, TORT was associated with significantly longer operation time (MD = -56.74 min, 95% CI [-73.41, -40.07], p < 0.05) but shorter hospital stay (MD = 0.26 days, 95% CI [0.03, 0.49], p < 0.05). The incidence of transient recurrent laryngeal nerve injury was significantly higher in the TOETVA group than in the TORT group (OR = 3.56, 95% CI [1.14, 11.06], p = 0.03). There were no significant differences between the two groups in the number of lymph nodes dissected, the number of metastatic central compartment lymph nodes, the incidence of permanent recurrent laryngeal nerve injury, mental nerve injury, transient or permanent hypoparathyroidism, seroma, surgical site infection, or postoperative hemorrhage. CONCLUSION: Although TORT is associated with longer operative time, it demonstrates potential advantages in terms of length of hospital stay and neuroprotection.The two procedures are comparable in terms of radicality of lymph node dissection, postoperative pain, and low complication rates. TORT is a safe and effective minimally invasive surgical option with better neural protection, especially suitable for patients prioritizing cosmetic outcomes. Long-term oncological safety still needs to be verified in future multicenter studies with larger samples and longer follow-up durations.
18 May 2026
Read appraisal →Journal of robotic surgery
Longitudinal health-related quality of life after remote-access versus open thyroidectomy for thyroid cancer: a systematic review and meta-analysis
As remote-access thyroidectomy (RAT) becomes more widely used, evidence on patient- reported outcomes, particularly health-related quality of life (HRQoL), remains scarce and inconsistent. This meta-analysis compared postoperative HRQoL between thyroid cancer (TC) patients undergoing RAT and open thyroidectomy (OT) and assessed changes over time. A comprehensive search of five major databases was conducted from inception to August 2025. Studies reporting HRQoL after RAT or OT were included. Outcomes were grouped by postoperative timepoints. Outcomes were stratified across distinct postoperative timepoints to calculate pooled standardized mean difference (SMD) or mean difference (MD). Heterogeneity was explored through rigorous subgroup analyses encompassing surgical modalities, countries, and assessment instruments. Forty-one studies met the inclusion criteria, and 29 records were included in the quantitative synthesis. RAT demonstrated early advantages in comprehensive quality of life at 1 month and 3 months, and these advantages dissipated long term. Pain trajectories exhibited a biphasic pattern: RAT was associated with lower pain scores on postoperative day 1 but paradoxically higher scores during the 1-2 week period, with subsequent convergence. Cosmetic satisfaction and swallowing function consistently favored RAT from 1-2 weeks through 6 months, while voice outcomes showed no discernible differences. RAT appears to confer selected short- to medium-term patient-reported advantages over OT, particularly in cosmetic satisfaction and swallowing function. But these benefits are heterogeneous and not consistently maintained across all domains or timepoints. Future studies should standardize cross-culturally validated PRO instruments and adopt harmonized follow-up intervals and reporting guidelines to clarify the patient-centered value of RAT.
15 May 2026
Read appraisal →Endocrine pathology
Impact of Molecular Testing on Surgical Decision-Making in Indeterminate Thyroid Nodules: A Global Meta-Analysis Across Test Generations
Thyroid nodules with indeterminate cytology represent a clinical challenge owing to uncertain malignancy risk, often leading to diagnostic surgery. Molecular testing has emerged as a promising adjunct to improve risk stratification and guide surgical decision-making. However, the clinical utility and impact of different molecular platforms remain debated. The present study evaluates the impact of molecular testing on surgical decision-making in indeterminate thyroid nodules and compares outcomes between first- and second-generation molecular platforms. A PRISMA-guided systematic review and meta-analysis identified 132 studies including 66,448 thyroid nodules, of which 30,292 (45.6%) were indeterminate (Bethesda III/IV). Pooled analyses included studies directly comparing conventional management with molecular testing or different molecular platforms. Primary outcomes were surgical resection rates and risk of malignancy (ROM), stratified by diagnostic approach and test generation. Conventional management demonstrated significantly higher surgical rates than molecular testing group (OR = 2.258, 95% CI: 1.548-3.293, p < 0.001). ROM among resected nodules was lower in the conventional management compared with the molecular testing group (OR = 0.594, 95% CI: 0.388-0.911, p = 0.017). First-generation molecular tests showed higher surgical rates and lower ROM than second-generation assays (OR = 1.709, 95% CI: 1.122-2.601, p = 0.013; OR = 0.665, 95% CI: 0.515-0.858, p = 0.002, respectively). Exclusion of non-invasive follicular thyroid neoplasm with papillary-like nuclear features attenuated differences in malignancy rates. Molecular testing significantly reduces surgical interventions in indeterminate thyroid nodules without evidence of reduced detection of clinically significant malignancy, particularly with second-generation platforms supporting more individualized and evidence-based management strategies.
14 May 2026
Read appraisal →PloS one
Utilizing the transformer mechanism to predict cervical lymph node metastasis in patients with papillary thyroid carcinoma
RATIONALE AND OBJECTIVE: The status of cervical lymph node metastasis(LNM) in Papillary thyroid carcinoma(PTC) can affect the patient's treatment plan and prognosis. This study aims to develop and validate the application value of Vision transformer (ViT) model in preoperatively predicting cervical LNM in PTC. MATERIALS AND METHODS: A total of 540 PTC patients were retrospectively reviewed from two hospitals from April 20,2022 to August 20,2023.The ViT model is built based on the two-dimensional rectangular ultrasound image of the primary thyroid tumor, and at the same time, to compare its performance, a deep learning model of the traditional Convolutional neural network (CNN) framework, a ultrasound radiomics combined model(Clinical-Rad model), and clinical model are built. RESULTS: The ViT model demonstrated an AUC of 0.807 (95% CI: 0.709-0.905) in the internal validation cohort and 0.809 (95% CI: 0.720-0.900) in the external validation cohort. The ViT model's AUC ranged from 0.807-0.814 across all cohorts, significantly exceeding the clinical model (AUC: 0.595-0.669, P<0.001). While the AUC of the ViT model in the training cohort was slightly lower than that of the combined ultrasound radiomics model (0.814 vs 0.828, P=0.491), it showed significantly higher AUC values in the internal (0.807 vs 0.718, P=0.049) and external validation cohorts (0.809 vs 0.691, P<0.001). Compared to the clinical and combined radiomics models, the ViT model exhibited stable and superior predictive performance for PTC cervical lymph node metastasis.In the internal validation cohort, Doctor C's net reclassification improvement (NRI) with the ViT model was 0.106 (P=0.022), and the integrated discrimination improvement (IDI) was 0.106 (P=0.023). Doctor D showed NRI and IDI values of 0.113 (P=0.022) and 0.106 (P=0.024), respectively. In the external validation cohort, Doctor C's NRI and IDI were 0.090 (P=0.024) and 0.106 (P=0.024), while Doctor D had values of 0.011 (P=0.013) and 0.106 (P=0.013). The ViT model enhanced the diagnostic capabilities of both Doctor C, with less clinical experience, and Doctor D, with extensive experience. CONCLUSION: The deep learning model based on the Transformer mechanism shows good performance in predicting LNM in PTC patients, which is superior to the clinical model, Clinical-Rad model, and traditional CNN model.
5 Apr 2026
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