Evidence map›Paper›PMID 33968725›Full record

ArticleFrontiers in oncology2021

The Clinical Accuracy and Risk Stratification in End of Therapy

Yi Wen Mo, Zi Zheng Xiao, Yuan Wei, Xin Ling Li, Xu Zhang, Wei Fan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. 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
0.8field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Assessing the intracranial metabolic score as a novel prognostic tool in primary CNS lymphoma with end of induction-chemotherapyCancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Article
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.

Yi Wen MoSun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China.
Zi Zheng XiaoSun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China.
Yuan WeiSun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China.
Xin Ling LiSun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China.
Xu ZhangSun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China.
Wei FanSun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeBurkitt lymphoma (BL) is an invasive lymphoma subtype with FDG avid at MATERIALS AND

methodsA total of 189 patients were retrospectively included: 97 underwent baseline PET/CT and all underwent EOT-PET. Survival curves were plotted according to the Kaplan-Meier method. Different DS cutoff values in EOT-PET were evaluated for risk stratification in Burkitt lymphoma.

resultsThe median progression free survival (PFS) and overall survival (OS) were 52 and 53 months, respectively. Applying the conventional DS 4 to 5, there was significant difference in outcome between EOT-PET negative and positive patients. However, the positive predictive value (PPV) (28.3% for PFS and 26.4% for OS) is low despite a high negative predictive value (NPV) (94.1% for OS and 94.9% for OS). When we moved the cutoff point to DS 5, the PPV was improved evidently (88.2% for PFS and 82.3% for OS) with the satisfactory NPV simultaneously (95.3% for PFS and 95.9% for OS).

conclusionsEOT-PET results using DS significantly related with PFS and OS. DS of 5 may be a better cutoff point at the end of treatment to determine whether patients have a significant risk of recurrence or progress.

Indexed as

Burkitt lymphomaDeauville 5-point scaleFDGPET/CTprognosis

Identifiers

PMID33968725
PMCPMC8098980
OpenAlexW3156901894

What OpenQuestion holds

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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.