ArticleBJR open2021
The diagnostic performance of chest radiographs for lung malignancy in symptomatic primary-care populations: A systematic review and meta-analysis.
Article in BJR open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.Health technology assessment (Winchester, England) · 2024Pooled it
- Real-world diagnostic pathways and treatment patterns for suspected lung cancer in Japan: a nationwide claims database analysis.ESMO real world data and digital oncology · 2026Article
- The incidence of lung cancer amongst primary care chest radiograph referrals-an evaluation of national and local datasets within the United Kingdom.The British journal of radiology · 2024Article
- Laterocervical lymph node metastases from suspected thyroidal primary site that turned out to be metastases of lung cancer: A case report.Clinical case reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo synthesise existing evidence for the diagnostic accuracy of chest radiographs to detect lung malignancy in symptomatic patients presenting to primary care.
methodsA systematic review was performed and reported in accordance with the PRISMA framework, using a protocol prospectively registered with the PROSPERO database (CRD42020212450). Nine databases were searched for relevant studies. Data were extracted and chest radiograph sensitivity and specificity calculated where possible. Risk of bias was assessed using a validated tool. Random effects meta-analysis was performed.
resultsTen studies were included. Sensitivity meta-analysis was performed in five studies which were not the high risk of bias, with summary sensitivity of 81% (95% CI: 74-87%). Specificity could be calculated in five studies, with summary specificity of 68% (95% CI: 49-87%).
conclusionsThe sensitivity of chest radiographs for detecting lung malignancy in primary care is relatively low. Physicians and policymakers must consider strategies to attenuate the possibility of false reassurance with a negative chest radiograph for this significant pathology. Options include widening access to cross-sectional imaging in primary care; however, any intervention would need to take into account the medical and financial costs of possible over-investigation. Prospective trials with long-term follow-up are required to further evaluate the risks and benefits of this strategy. ADVANCES IN KNOWLEDGE: The chest radiograph has a sensitivity of 81% and specificity of 68% for lung malignancy in a symptomatic primary-care population. A negative chest radiograph does not exclude lung cancer, and physicians should maintain a low threshold to consider specialist referral or cross-sectional imaging.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.