SynthesisBMJ open2025
Evaluation of imaging techniques for early detection of intrathoracic cancers in symptomatic patients in primary care: a systematic review.
Synthesis in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesIntrathoracic 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.
designSystematic 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.
resultsOut 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.
conclusionsWe 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.
Indexed as
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.