Evidence map›Paper›PMID 29862295›Full record

Trial reportBioMed research international2018

A Predictive Model to Determine the Pattern of Nodal Metastasis in Oral Squamous Cell Carcinoma.

B S M S Siriwardena, I K Rambukewela, T N Pitakotuwage, M N G P K Udagama, P V R Kumarasiri, W M Tilakaratne

Open access · hybridAbstract readClinical Trial
In one paragraph

Trial report in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 22 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 1 institution in 1 country.

B S M S SiriwardenaDepartment of Oral Pathology, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, Sri Lanka.ORCID 0000-0002-5178-5026
I K RambukewelaDepartment of Oral Pathology, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, Sri Lanka.
T N PitakotuwageDepartment of Oral Pathology, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, Sri Lanka.
M N G P K UdagamaDepartment of Oral Pathology, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, Sri Lanka.
P V R KumarasiriDepartment of Community Medicine, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka.
W M TilakaratneDepartment of Oral Pathology, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, Sri Lanka.
University of Peradeniya · LK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeveloping histological prediction models that estimate the probability of developing metastatic deposit will help clinicians to identify individuals who need either radical or prophylactic neck dissection, which leads to better prognosis. Identification of accurate predictive models in oral cancer is important to overcome extensive prophylactic surgical management for neck nodes. Therefore, accurate prediction of metastasis in oral cancer would have an immediate clinical impact, especially to avoid unnecessary radical treatment of patients who are at a low risk of metastasis.

methodsHistologically confirmed OSCC cases with neck dissection were used. Interrelation of demographic, clinical, and histological data was done using univariate and multivariate analysis.

results465 cases were used and presence of metastasis and extracapsular invasion were statistically well correlated with level of differentiation (

conclusionsThe proposed predictive model may provide some guidance for maxillofacial surgeons to decide the appropriate treatment plan for OSCC, especially in developing countries. This model appears to be reliable and simple and may guide surgeons in planning surgical management of neck nodes.

Indexed as

Carcinoma, Squamous CellModels, BiologicalMouth NeoplasmsAdultAgedAged, 80 and overDisease-Free SurvivalFemaleHumansMaleMiddle AgedNeoplasm MetastasisSurvival Rate

Identifiers

PMID29862295
PMCPMC5971289
OpenAlexW2802744186

What OpenQuestion holds

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LicenceCC BY
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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.