Artificial intelligence in genitourinary oncology: publication trends and systematic review

IF 4.1 2区医学 Q1 UROLOGY & NEPHROLOGY

BJU International Pub Date : 2026-09-07 Epub Date: 2026-06-26 DOI:10.1111/bju.70361

Alee Kim, Nicole A. Moore, Tammy Dong, Kelsy Fu, Katie Keyser, Shari Clifton, Adanma Ayanambakkam, Ryan Nipp

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引用次数: 0

Abstract

Objective

To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current state of artificial intelligence (AI) use in genitourinary (GU) oncology, as AI has emerged as a transformative tool in healthcare with potential applications in diagnostics, treatment planning, and prognostication.

Methods

We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE; Ovid), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) Ultimate for studies related to AI and GU oncology, excluding non-English papers, non-human studies, review articles, and articles using AI solely for manuscript writing. Publication trends were analysed from 2013 to 2023 and categorized by study design and cancer type. RCTs were evaluated through systematic review using Covidence (Veritas Health Innovation Ltd, Melbourne, Victoria, Australia) for screening and data extraction. Two reviewers independently assessed all studies, with risk of bias (RoB) evaluated using the Cochrane RoB 2.0 tool.

Results

Of 2409 articles identified, 1220 met inclusion criteria. These included 962 retrospective articles, 175 prospective studies, 79 studies with combined retrospective/prospective methods, and four RCTs. Studies most commonly addressed prostate (n = 923), renal (n = 274), and urothelial (n = 194) cancers. Publications grew from 14 in 2013 to 362 in 2023, with substantial acceleration in 2019. Four RCTs were identified – one in urothelial cancer and three in prostate cancer. Two RCTs evaluated AI-based diagnostics, demonstrating improved performance over conventional methods; the remaining two RCTs evaluated AI in prognostication and treatment planning, showing improved gains in imaging interpretation and operational efficiency. RoB varied across studies, primarily related to randomisation and deviations from intended interventions.

Conclusions

Artificial intelligence research in GU oncology has grown, although high-level evidence from RCTs remains limited. Existing trials underscore AI's promise in diagnostics, prognostication, and treatment planning, and the rapidly evolving nature of this field warrants continued prospective investigation.

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泌尿生殖肿瘤中的人工智能：发表趋势和系统综述

目的分析发表趋势并对随机对照试验（rct）进行系统评价，以表征人工智能（AI）在泌尿生殖系统（GU）肿瘤学中的应用现状，因为人工智能已成为医疗保健领域的变革性工具，在诊断、治疗计划和预后方面具有潜在的应用前景。方法我们检索医学文献分析与检索系统在线（MEDLINE）、医学摘录数据库（EMBASE; Ovid）和护理与相关健康文献累积索引（CINAHL） Ultimate，检索与人工智能和GU肿瘤学相关的研究，排除非英文论文、非人类研究、综述文章和仅使用人工智能撰写论文的文章。对2013年至2023年的出版物趋势进行了分析，并按研究设计和癌症类型进行了分类。采用covience （Veritas Health Innovation Ltd, Melbourne, Victoria, Australia）进行筛选和数据提取，对随机对照试验进行系统评价。两名审稿人独立评估所有研究，使用Cochrane RoB 2.0工具评估偏倚风险（RoB）。结果2409篇文献中，1220篇符合纳入标准。其中包括962篇回顾性研究、175项前瞻性研究、79项回顾性/前瞻性联合研究和4项随机对照试验。研究最常见的是前列腺癌（923例）、肾癌（274例）和尿路上皮癌（194例）。发表的论文从2013年的14篇增加到2023年的362篇，并在2019年大幅加速。四项随机对照试验被确定，一项是尿路上皮癌，三项是前列腺癌。两项随机对照试验评估了基于人工智能的诊断，显示出优于传统方法的性能；其余两项随机对照试验评估了人工智能在预测和治疗计划方面的作用，显示了成像解释和操作效率的改善。RoB在不同的研究中有所不同，主要与随机化和预期干预的偏差有关。结论：尽管来自随机对照试验的高水平证据仍然有限，但人工智能在GU肿瘤学中的研究已经有所发展。现有的试验强调了人工智能在诊断、预测和治疗计划方面的前景，并且该领域的快速发展性质需要继续进行前瞻性研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BJU International 医学-泌尿学与肾脏学

CiteScore

9.10

自引率

4.40%

发文量

262

审稿时长

1 months

期刊介绍： BJUI is one of the most highly respected medical journals in the world, with a truly international range of published papers and appeal. Every issue gives invaluable practical information in the form of original articles, reviews, comments, surgical education articles, and translational science articles in the field of urology. BJUI employs topical sections, and is in full colour, making it easier to browse or search for something specific.