SynthesisGeneral thoracic and cardiovascular surgery2021
Can we predict mediastinal lymph nodes metastasis in esophagogastric junction cancer? Results of a systematic review and meta-analysis.
Synthesis in General thoracic and cardiovascular surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 5 citations in OpenAlex.
- The development and validation of automated machine learning models for predicting lymph node metastasis in Siewert type II T1 adenocarcinoma of the esophagogastric junction.Frontiers in medicine · 2024Article
- Role of Lower Esophageal Squamous Cell Carcinoma Margin Location on Abdominal Lymph Node Metastasis Risk.Journal of clinical medicine · 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
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this systematic review and meta-analysis was to define clinical indicator that predicts mediastinal lymph nodes metastasis (MLNM) in patients with Esophagogastric junction cancer (EGJC) to select patient population requiring esophagectomy.
methodsA systematic and electronic search of several electronic databases was performed up to August 2020. Studies containing information on risk factors for MLNM in patients diagnosed with EJGC and who underwent curative surgery were included.
resultsTwo predictors, including undifferentiated type (OR = 1.82, 95% CI = 1.07-3.10, p = 0.03) and esophageal invasion length (EIL) (OR = 10.95, 95% CI = 6.37-18.82, p < 0.00001) were identified as significant predictors for the risk of MLNM.
conclusionKnowledge of the associations of these clinicopathological features with MLNM can be useful in determining operative strategy for EGJC.
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.