Evidence map›Paper›PMID 36231143›Full record

ArticleCells2022

Sina Dadafarin, Tomás C Rodríguez, Michelle A Carnazza, Raj K Tiwari, Augustine Moscatello, Jan Geliebter

Open access · goldAbstract read
In one paragraph

Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Sina DadafarinDepartment of Otolaryngology-Head and Neck Surgery, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-7956-0419
Tomás C RodríguezRNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01655, USA.ORCID 0000-0002-8724-5427
Michelle A CarnazzaDepartment of Pathology, Microbiology and Immunology, New York Medical College, Valhalla, NY 10595, USA.
Raj K TiwariDepartment of Pathology, Microbiology and Immunology, New York Medical College, Valhalla, NY 10595, USA.
Augustine MoscatelloDepartment of Otolaryngology, New York Medical College, Valhalla, NY 10595, USA.
Jan GeliebterDepartment of Pathology, Microbiology and Immunology, New York Medical College, Valhalla, NY 10595, USA.
New York Medical College · USUniversity of Massachusetts Chan Medical School · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Papillary thyroid cancer is the most common endocrine malignancy, occurring at an incidence rate of 12.9 per 100,000 in the US adult population. While the overall 10-year survival of PTC nears 95%, the presence of lymph node metastasis (LNM) or capsular invasion indicates the need for extensive neck dissection with possible adjuvant radioactive iodine therapy. While imaging modalities such as ultrasound and CT are currently in use for the detection of suspicious cervical lymph nodes, their sensitivities for tumor-positive nodes are low. Therefore, advancements in preoperative detection of LNM may optimize the surgical and medical management of patients with thyroid cancer. To this end, we analyzed bulk RNA-sequencing datasets to identify candidate markers highly predictive of LNM. We identified

Indexed as

Cancer-Associated FibroblastsCarcinoma, PapillaryThyroid NeoplasmsAdultHumansIodine RadioisotopesLymphatic MetastasisRNA, Long NoncodingThyroid Cancer, PapillaryIodine RadioisotopesMEG3 non-coding RNA, humanRNA, Long Noncodingbiomarkerlong-noncoding RNAthyroid cancer

Identifiers

PMID36231143
PMCPMC9562881
OpenAlexW4304128126

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.