ArticleThoracic cancer2022
Predictors of malignant lymph node involvement in patients with mediastinal lymphadenopathy and previous cancer: A cohort study.
Article in Thoracic cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 9 citations in OpenAlex.
- Mediastinal lymphadenopathy: Causes, symptoms and factors predicting good yield of endoscopic ultrasound-guided biopsy.World journal of clinical cases · 2025Article
- Distinguishing lymphoma from benign lymph node diseases in fever of unknown origin using PET/CT radiomics.EJNMMI research · 2024Article
- Prediction of metastases in confusing mediastinal lymph nodes based on flourine-18 fluorodeoxyglucose (Quantitative imaging in medicine and surgery · 2024Article
- Differential diagnosis of lymphoma withJournal of cancer research and clinical oncology · 2023Observational
- Predictors of malignant lymph node involvement in patients with mediastinal lymphadenopathy and previous cancer: A cohort study.Thoracic cancer · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMediastinal lymphadenopathy is a common finding in follow-up after diagnosis of malignancy, and may represent recurrence of malignancy, or benign processes such as sarcoidosis. CT and PET-CT are commonly used, despite limited ability to discriminate between benign and malignant disease, and although EBUS-guided bronchoscopy is often performed, it is relatively invasive and may not always be safe in high-risk patients. Clinical and radiological predictors for cancer recurrence could therefore be of value.
methodsA retrospective cohort analysis of all patients with mediastinal lymphadenopathy and previous malignancy undergoing mediastinal lymph node sampling via bronchoscopy was undertaken. Demographics, smoking status, details of previous malignancy, time since cancer diagnosis, and imaging data were collected, as well as follow-up in the years following the procedure. We then compared specific characteristics of patients with malignant and benign lymphadenopathy in order to identify predictors of malignant versus benign lymphadenopathy.
resultsA total of 113 patients were analyzed of which 63% had tumor recurrence, while the rest had benign disease including sarcoidosis. Smoking history and previous lung cancer were both correlated with lymph node malignancy, while symmetric hilar enlargement, and the presence of multiple pathological stations were correlated with benign outcome. Size, maximal SUV uptake or time interval since cancer diagnosis were not associated with the final diagnosis.
conclusionsThese findings may help in assessing the pretest probability of tumor recurrence in patients with mediastinal lymphadenopathy, thus aiding in the clinical decision-making in such scenarios.
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.