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基层医疗中对有症状患者进行胸内癌症早期检测的成像技术评估:一项系统综述

Evaluation of imaging techniques for early detection of intrathoracic cancers in symptomatic patients in primary care: a systematic review.

作者信息

Grigore Bogdan, Peters Jaime L, Hamad Wasim, Calanzani Natalia, Asare Lauren, Walter Fiona M, Neal Richard

机构信息

Exeter Test Group, Department of Health and Community Sciences, University of Exeter, Exeter, UK

Exeter Test Group, Department of Health and Community Sciences, University of Exeter, Exeter, UK.

出版信息

BMJ Open. 2025 Aug 16;15(8):e091435. doi: 10.1136/bmjopen-2024-091435.

Abstract

OBJECTIVES

Intrathoracic cancers, such as lung cancer, mesothelioma and thymoma, represent diagnostic challenges in primary care. We aimed to summarise evidence on the performance of imaging techniques that could aid the detection of intrathoracic cancers in low prevalence settings.

DESIGN

Systematic review and quality appraisal using Quality Assessment of Diagnostic Accuracy Studies-2 and Grading of Recommendations Assessment, Development and Evaluation.

DATA SOURCES

MEDLINE, Embase and Web of Science were searched with a predesigned search strategy for articles from January 2000 to January 2024.

ELIGIBILITY CRITERIA

We included studies relevant for primary care, where participants were suspected of having intrathoracic cancer and reported on at least one diagnostic performance measure. We excluded studies where the cancer diagnosis was already established. Data extraction and synthesis screening were conducted independently by two reviewers. Data extraction and quality appraisal were conducted by one reviewer and checked by a second reviewer.

RESULTS

Out of 30 539 records identified by the database searches, 13 studies were included. There was heterogeneity in the types of cancers, populations included and reported diagnosis pathways for suspected cancers. Imaging modalities investigated included chest X-ray (three studies), computer tomography (CT, six studies), magnetic resonance imaging (two studies), positron emission tomography CT (two studies), ultrasound (two studies) and scintigraphy (one study). Chest X-ray sensitivity reported for lung cancer ranged from 33.3% to 75.9%, with specificity ranging from 83.2% to 95.5%. For CT, reported sensitivity varied from 58% for pleural malignancy to 100% for lung cancer. One study investigating an artificial intelligence tool to detect lung cancer found poor detection performance in a real-world patient cohort.

CONCLUSIONS

We found a limited number of studies reporting on the diagnostic performance of usual imaging techniques when used in unselected primary care settings for the diagnosis of intrathoracic cancer in symptomatic patients. There is a need for more studies evaluating such techniques in the general population presenting in primary care, where the prevalence is relatively low. A better understanding of the performance could lead to better detection strategies for intrathoracic cancers in primary care. Intrathoracic cancers, such as lung cancer, mesothelioma and thymoma, represent diagnostic challenges in primary care. We aimed to summarise evidence on the performance of imaging techniques that could aid the detection of intrathoracic cancers in low prevalence settings.

摘要

目的

胸内癌症,如肺癌、间皮瘤和胸腺瘤,在基层医疗中构成诊断挑战。我们旨在总结关于成像技术在低患病率环境中辅助检测胸内癌症的性能证据。

设计

使用诊断准确性研究质量评估 - 2和推荐分级评估、制定与评价进行系统评价和质量评估。

数据来源

使用预先设计的检索策略在MEDLINE、Embase和科学网中检索2000年1月至2024年1月的文章。

纳入标准

我们纳入了与基层医疗相关的研究,这些研究中的参与者疑似患有胸内癌症,并报告了至少一项诊断性能指标。我们排除了癌症诊断已确定的研究。由两名评审员独立进行数据提取和综合筛选。由一名评审员进行数据提取和质量评估,并由另一名评审员进行检查。

结果

在数据库检索识别出的30539条记录中,纳入了13项研究。在癌症类型、纳入人群以及疑似癌症的报告诊断途径方面存在异质性。所研究的成像方式包括胸部X线(3项研究)、计算机断层扫描(CT,6项研究)、磁共振成像(2项研究)、正电子发射断层扫描CT(2项研究)、超声(2项研究)和闪烁扫描(1项研究)。报告的肺癌胸部X线敏感性范围为33.3%至75.9%,特异性范围为83.2%至95.5%。对于CT,报告敏感性从胸膜恶性肿瘤的58%到肺癌的100%不等。一项调查用于检测肺癌的人工智能工具的研究发现,在真实世界患者队列中检测性能较差。

结论

我们发现,在未经过筛选的基层医疗环境中,针对有症状患者诊断胸内癌症时,报告常规成像技术诊断性能的研究数量有限。需要更多研究在基层医疗中就诊的普通人群(患病率相对较低)中评估此类技术。更好地了解其性能可能会为基层医疗中胸内癌症带来更好的检测策略。胸内癌症,如肺癌、间皮瘤和胸腺瘤,在基层医疗中构成诊断挑战。我们旨在总结关于成像技术在低患病率环境中辅助检测胸内癌症的性能证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794d/12359469/da045bd426da/bmjopen-15-8-g001.jpg

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