Evidence map›Paper›PMID 35265479›Full record

ArticleInternational journal of applied & basic medical research

Diagnostic Accuracy of Calculated Tumor Volumes and Apparent Diffusion Coefficient Values in Predicting Endometrial Cancer Grade.

Chandan Kakkar, Kamini Gupta, Kunal Jain, Vikram Narang, Aminder Singh, Kavita Saggar, Namita Bansal, Dania Cioni, Emanuele Neri

Open access · greenAbstract read
In one paragraph

Article in International journal of applied & basic medical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

4 citing papers in PubMed, 5 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

9 authors at 2 institutions in 2 countries.

Chandan KakkarDepartment of Translational Research, University of Pisa, Pisa, Italy.
Kamini GuptaDepartment of Radiodiagnosis and Imaging, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Kunal JainDepartment of Medical Oncology, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Vikram NarangDepartment of Pathology, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Aminder SinghDepartment of Pathology, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Kavita SaggarDepartment of Radiodiagnosis and Imaging, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Namita BansalDepartment of Biostatistics, Dayanand Medical College and Hospital, Ludhiana, Punjab, India.
Dania CioniDepartment of Translational Research, University of Pisa, Pisa, Italy.
Emanuele NeriDepartment of Translational Research, University of Pisa, Pisa, Italy.
Dayanand Medical College & Hospital · INUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Magnetic resonance imaging (MRI) has been shown to be an accurate imaging technique for the preoperative assessment of local staging of endometrial cancer and for evaluating the depth of myometrial invasion. Materials and Methods: This was a single-center retrospective study performed on patients with histopathologically proven endometrial carcinoma who underwent an MRI examination of the pelvis between October 2017 and May 2020. Results: In the present analysis, mean apparent diffusion coefficient (ADC) values for each histologic grade were 0.72 ± 0.13 × 10 Conclusion: Preoperative noninvasive radiological assessment for tumor volume, TV/ UV or tumor volume/uterine volume is important surrogate markers for preoperative prognostication of endometrial carcinoma.

Indexed as

Endometrial carcinomagrademagnetic resonance imagingtumor volume

Identifiers

PMID35265479
PMCPMC8848552
OpenAlexW4210368266

What OpenQuestion holds

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LicenceCC BY-NC-SA
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.