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find Author "XUE Xinyu" 3 results
  • Survival Outcomes of segmentectomy versus lobectomy for T1c non-small cell lung cancer: A systematic review and meta-analysis

    Objective To evaluate the survival outcomes of segmentectomy versus lobectomy for T1c non-small cell lung cancer (NSCLC). Methods We searched PubMed, EMbase, Cochrane Central Register of Controlled Trials (CENTRAL), CNKI (China National Knowledge Infrastructure), and Wanfang Data, with the search time limit set from the inception of the databases to February 2024. Three researchers independently screened the literature, extracted relevant information, and evaluated the risk of bias of the included literature according to the Newcastle-Ottawa Scale (NOS). Meta-analysis was conducted using STATA 15.1. Hazard ratios (HRs) and their 95% confidence interval were pooled using an inverse variance-weighted approach, and heterogeneity was assessed using I-square (I2) statistic and Cochran’s Q test. Results A total of 8 retrospective cohort studies were included, involving 7,433 patients. The NOS scores of the included studies were all higher than 7 points. Among the 7 433 patients enrolled in eight eligible studies published from 2004 to 2022. The pooled adjusted HR found that patients who underwent lobectomy had significantly higher five-year OS compared to those who underwent lobectomy (adjusted HR=1.11, 95%CI 0.99-1.24, P=0.042). Compared with lobectomy, segmentectomy shows no significant difference in adjusted three-year OS and adjusted five-year LCSS of patients with T1c NSCLC (three-year OS: adjusted HR=0.88, 95%CI 0.62-1.24, P=0.468; five-year LCSS: adjusted HR=1.10, 95%CI 0.80-1.51, P=0.556). Moreover, there were no differences in the five-year adjusted RFS, and adverse events after the segmentectomy group were significantly less than those in the lobectomy group (five-year RFS: adjusted HR=1.23, 95%CI 0.82 to 1.85, P=0.319; complications: OR=0.57, 95%CI0.37 to 0.90, P=0.015). Subgroup analysis based on whether patients received neoadjuvant therapy showed that among studies that excluded patients who received neoadjuvant therapy, no significant difference in 5-year adjusted OS was observed between segmentectomy and lobectomy (adjusted HR=1.02, 95%CI 0.81 to 1.28, P=0.870). Conclusion Segmentectomy and lobectomy showed no significant difference in long-term survival in stage T1c NSCLC patients, with segmentectomy associated with fewer postoperative complications. Further high-quality research is needed to confirm the comparative efficacy and safety of lobectomy and segmentectomy for T1c NSCLC patients.

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  • Interpretation of the DECIDE-AI guideline: a reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence

    Artificial intelligence has been extensively applied in healthcare services recently, and clinical decision support systems driven by artificial intelligence are one of the applications. Early-stage clinical evaluation of artificial intelligence (AI)-based clinical decision support systems lies between preclinical development (in silico), offline validation, and large-scale trials, but few AI-related clinical studies have addressed human factors evaluations and reported the implementation environment, user characteristics, selection process and algorithm identification of AI systems. In order to bridge the development-to-implementation gap in clinical artificial intelligence and to promote the transparent and standardized reporting of early-stage clinical studies of AI-based decision support systems. A reporting guideline for the developmental and exploratory clinical investigations of decision support systems driven by artificial intelligence (DECIDE-AI) was published in 2022. This paper aimed to interpret the background, development process and key items of the DECIDE-AI guideline and promote its understanding as well as dissemination in China.

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  • The methodological framework of surgical innovation: The empirical evidence of IDEAL framework

    IDEAL framework and recommendations provide a scientific and integrated evaluation pathway for surgical innovations and other complex therapeutic interventions, and underline that the preliminary studies are needed to prepare for a successful randomized controlled trial. IDEAL framework provides a series of recommendations in terms of nature stages of surgical innovation. We have reported the introduction and reporting guidelines of the IDEAL framework and recommendations in our IDEAL series paper. This paper aimed to provide some empirical evidence, focusing specifically on stages 2a and 2b, to help surgeons and researchers to understand how to imply IDEAL framework and recommendations into their clinical practice.

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