Jenkins Cerys, Woods Freya, Chandler Susan, Carter Kym, Jenkins Rhys, Cunningham Andrew, Nelson Kayleigh, Still Rachel, Walters Jenna A, Gwynn Non, Chea Wilson, Harford Rachel, O'Neill Claire, Hepburn Julie, Hill Ian, Wilkes Heather, Fegan Greg, Dunstan Peter, Harris Dean A
Physics Department, College of Science, Centre for NanoHealth, Swansea University, Swansea, UK.
Swansea University Medical School, Swansea University, Swansea, UK.
BJGP Open. 2023 Mar 21;7(1). doi: 10.3399/BJGPO.2022.0077. Print 2023 Mar.
The majority of colorectal cancers (CRCs) are detected after symptomatic presentation to primary care. Given the shared symptoms of CRC and benign disorders, it is challenging to manage the risk of missed diagnosis. Colonoscopy resources cannot keep pace with increasing demand. There is a pressing need for access to simple triage tools in primary care to help prioritise patients for referral.
To evaluate the performance of a novel spectroscopy-based CRC blood test in primary care.
DESIGN & SETTING: Mixed-methods pilot study of test performance and GP focus group discussions in South Wales.
Patients on the urgent suspected cancer (USC) pathway were recruited for the Raman spectroscopy (RS) test coupled to machine learning classification ('Raman-CRC') to identify CRC within the referred population. Qualitative focus group work evaluated the acceptability of the test in primary care by thematic analysis of focus group theorising.
A total of 532 patients aged ≥50 years referred on the USC pathway were recruited from 27 GP practices. Twenty-nine patients (5.0%) were diagnosed with CRC. Raman-CRC identified CRC with sensitivity 95.7%, specificity 69.3% with area under curve (AUC) of 0.80 compared with colonoscopy as the reference test (248 patients). Stage I and II cancers were detected with 78.6% sensitivity. Focus group themes underlined the convenience of a blood test for the patient and the test's value as a risk assessment tool in primary care.
The findings support this novel, non-invasive, blood-based method to prioritise those patients most likely to have CRC. Raman-CRC may accelerate access to diagnosis with potential to improve cancer outcomes.
大多数结直肠癌（CRC）是在出现症状后到初级保健机构就诊时被发现的。鉴于CRC和良性疾病有共同症状，管理漏诊风险具有挑战性。结肠镜检查资源无法满足不断增长的需求。迫切需要在初级保健中使用简单的分诊工具，以帮助确定患者转诊的优先级。
评估一种基于光谱学的新型CRC血液检测在初级保健中的性能。
在南威尔士进行的关于检测性能的混合方法试点研究以及全科医生焦点小组讨论。
招募处于紧急疑似癌症（USC）路径的患者进行拉曼光谱（RS）检测，并结合机器学习分类（“拉曼 - CRC”），以在转诊人群中识别CRC。定性焦点小组工作通过对焦点小组理论化的主题分析，评估该检测在初级保健中的可接受性。
从27家全科医生诊所招募了532名年龄≥50岁且处于USC路径的患者。29名患者（5.0%）被诊断为CRC。与作为参考检测的结肠镜检查（248名患者）相比，拉曼 - CRC识别CRC的灵敏度为95.7%，特异性为69.3%，曲线下面积（AUC）为0.80。I期和II期癌症的检测灵敏度为78.6%。焦点小组的主题强调了血液检测对患者的便利性以及该检测作为初级保健中风险评估工具的价值。
研究结果支持这种新型的、非侵入性的、基于血液的方法，以确定最有可能患有CRC的患者的优先级。拉曼 - CRC可能加快诊断速度，有可能改善癌症治疗结果。
