Department of Gastrointestinal Surgery, HPB unit, 60496Stavanger University Hospital, Stavanger, Norway.
Department of Clinical Medicine, University of Bergen, Bergen, Norway.
Cancer Control. 2023 Jan-Dec;30:10732748231154711. doi: 10.1177/10732748231154711.
The overall poor prognosis in pancreatic cancer is related to late clinical detection. Early diagnosis remains a considerable challenge in pancreatic cancer. Unfortunately, the onset of clinical symptoms in patients usually indicate advanced disease or presence of metastasis.
Currently, there are no designated or for pancreatic cancer in clinical use. Thus, identifying risk groups, preclinical risk factors or surveillance strategies to facilitate early detection is a target for ongoing research. Hereditary genetic syndromes are a obvious, but small group at risk, and warrants close surveillance as suggested by society guidelines. Screening for pancreatic cancer in asymptomatic individuals is currently associated with the risk of false positive tests and, thus, risk of harms that outweigh benefits. The promise of cancer biomarkers and use of 'omics' technology (genomic, transcriptomics, metabolomics etc.) has yet to see a clinical breakthrough. Several proposed biomarker studies for early cancer detection lack external validation or, when externally validated, have shown considerably lower accuracy than in the original data. Biopsies or tissues are often taken at the time of diagnosis in research studies, hence invalidating the value of a time-dependent lag of the biomarker to detect a pre-clinical, asymptomatic yet operable cancer. New technologies will be essential for early diagnosis, with emerging data from image-based radiomics approaches, artificial intelligence and machine learning suggesting avenues for improved detection.
Early detection may come from analytics of various body fluids (eg 'liquid biopsies' from blood or urine). In this review we present some the technological platforms that are explored for their ability to detect pancreatic cancer, some of which may eventually change the prospects and outcomes of patients with pancreatic cancer.
胰腺癌总体预后较差与临床检测较晚有关。早期诊断仍然是胰腺癌面临的重大挑战。不幸的是,患者出现临床症状通常表明疾病已进展或存在转移。
目前,临床上尚无专门用于胰腺癌的筛查或诊断方法。因此,确定高危人群、临床前风险因素或监测策略以促进早期发现是当前研究的目标。遗传性遗传综合征是一个明显的但风险较小的群体,需要按照社会指南进行密切监测。对无症状个体进行胰腺癌筛查目前与假阳性测试的风险相关,因此,风险大于收益。癌症生物标志物的应用和“组学”技术(基因组学、转录组学、代谢组学等)的应用前景尚未取得临床突破。几项用于早期癌症检测的拟议生物标志物研究缺乏外部验证,或者在外部验证时,其准确性明显低于原始数据。在研究中,活检或组织通常在诊断时获取,因此,生物标志物检测临床前、无症状但可手术的癌症的时间滞后价值无效。新技术对于早期诊断至关重要,基于影像学的放射组学方法、人工智能和机器学习的新兴数据为提高检测水平提供了途径。
早期检测可能来自各种体液的分析(例如来自血液或尿液的“液体活检”)。在这篇综述中,我们介绍了一些正在探索用于检测胰腺癌的技术平台,其中一些可能最终会改变胰腺癌患者的前景和结局。