Evidence map›Paper›PMID 37148293›Full record

ArticleJournal of cancer research and clinical oncology2023

Diagnostic and prognostic value of pretreatment PET/CT in extranodal natural killer/T-cell lymphoma: a retrospective multicenter study.

Mingjie Yu, Zegeng Chen, Zhao Wang, Xiaojie Fang, Xi Li, Haimei Ye, Tongyu Lin, He Huang

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. 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
1.3field-weighted citation impact, top 21% 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

8 authors at 3 institutions in 1 country.

Mingjie Yu *Department of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
Zegeng Chen *Department of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
Zhao WangDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
Xiaojie FangDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
Xi LiDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
Haimei YeDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China.
Tongyu LinDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China. linty@sysucc.org.cn.
He HuangDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, Guangdong, China. huanghe@sysucc.org.cn.
Sun Yat-sen University Cancer Center · CNSun Yat-sen University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe objective of this research was to assess the utility of positron emission tomography combined with computed tomography (PET/CT) to detect bone marrow invasion (BMI) and the predictive value of PET/CT in extranodal natural killer/T-cell lymphoma (ENKTL) patients. PATIENTS AND

methodsThis multicentre study enrolled ENKTL patients who underwent pretherapy PET/CT and bone marrow biopsy (BMB). The specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV) of PET/CT and BMB for BMI were evaluated. Multivariate analysis was used to identify predictive parameters for constructing a nomogram.

resultsSeven hundred and forty-eight patients were identified from four hospitals, with eighty (10.7%) having focal skeletal lesions on PET/CT and fifty (6.7%) having positive BMB. When BMB is considered as the gold standard, the specificity, sensitivity, PPV, and NPV of PET/CT for diagnosing BMI were found to be 93.8%, 74.0%, 46.3%, and 98.1%, respectively. PET/CT-positive individuals showed significantly worse OS than PET/CT-negative patients in the subgroup of BMB-negative cases. The nomogram model created according to the significant risk factors from multivariate analysis performed well in predicting survival probability.

conclusionPET/CT offers a superior degree of precision for determining BMI in ENKTL. A nomogram model including the parameters of PET/CT can predict survival probability and may help in applying appropriate personalized therapy.

Indexed as

Lymphoma, Extranodal NK-T-CellPositron Emission Tomography Computed TomographyBiopsyFluorodeoxyglucose F18HumansKiller Cells, NaturalPositron-Emission TomographyPrognosisRetrospective StudiesFluorodeoxyglucose F18Bone marrow biopsyExtranodal natural killer/T-cell lymphoma (ENKTL)NomogramPET/CTSUVmax

Identifiers

PMID37148293
PMCPMC11797323
OpenAlexW4372358249

What Socratic holds

Textmetadata
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 Socratic graph.