Evidence map›Paper›PMID 30093800›Full record

ArticleClinical Medicine Insights. Oncology2018

Early Clinical Outcomes, Patterns of Failure, and Acute Haematologic Toxicity of Image-Guided Volumetric Modulated Arc Therapy (IG-VMAT) in the Definitive Treatment of Locally Advanced Carcinoma Cervix.

Irfan Ahmad, Kundan Singh Chufal, Irfan Bashir, Chandi Prasad Bhatt, Ram Bajpai, Lalit Sharma, Sandeep Rathour

Abstract read
In one paragraph

Article in Clinical Medicine Insights. Oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Irfan AhmadDepartment of Radiotherapy, Batra Hospital & Medical Research Centre, New Delhi, India.
Kundan Singh ChufalDepartment of Radiotherapy, Rajiv Gandhi Cancer Institute & Research Centre, Rohini, New Delhi, India.
Irfan BashirDepartment of Radiotherapy, Batra Hospital & Medical Research Centre, New Delhi, India.
Chandi Prasad BhattDepartment of Radiotherapy, Batra Hospital & Medical Research Centre, New Delhi, India.
Ram BajpaiLee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
Lalit SharmaDepartment of Radiotherapy, Batra Hospital & Medical Research Centre, New Delhi, India.
Sandeep RathourDepartment of Radiotherapy, Batra Hospital & Medical Research Centre, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate clinical outcomes and failure patterns in patients with locally advanced cervical cancer (LACC) treated definitively using image-guided volumetric-modulated arc therapy (IG-VMAT). METHODS AND MATERIALS: This retrospective review included 18 consecutively treated patients with LACC. Treatment consisted of IG-VMAT and concurrent chemotherapy followed by intracavitary radiotherapy. The primary end points were overall survival (OS) and disease-free survival (DFS). Acute haematologic toxicity was evaluated using Radiation Therapy Oncology Group (RTOG) criteria.

resultsA total of 16 patients were either stage IIB or IIIB and the median follow-up was 30.5 months (interquartile range: 13-36.25 months). The 2-year DFS was 63.3% (95% confidence interval [CI]: 52.8%-72.4%) and 2-year OS was 72.2% (95% CI: 62.1%-80.5%). There were 7 treatment failures, predominantly in-field. Acute haematologic toxicity was low.

conclusionsIG-VMAT is associated with favourable outcomes for patients with LACC.

Indexed as

cervical carcinomaconcurrent chemoradiationimage guidanceintensity-modulated radiotherapyVolumetric-modulated arc therapy

Identifiers

PMID30093800
PMCPMC6081749

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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.