Evidence map›Paper›PMID 33419476›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2021

Nomograms based on SUVmax of

Hongyan Li, Guozhu Shao, Yajing Zhang, Xiaomin Chen, Chengcheng Du, Kun Wang, Zairong Gao

Open access · goldAbstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.3field-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

20 citing papers in PubMed, 22 citations in OpenAlex.

  1. A clinical-radiomic model based on best subset regression for prognostic prediction in natural killer/T-cell lymphoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  2. Prognostic value of interim [European radiology · 2025
    Article
  3. Prognostic value of the pre-treatment SUVmax ofCancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. ElevatedFrontiers in oncology · 2025
    Article
  8. Article
  9. Article
  10. Prognostic Value ofKorean journal of radiology · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. American journal of nuclear medicine and molecular imaging · 2023
    Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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 at 2 institutions in 1 country.

Hongyan LiDepartment of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China.
Guozhu ShaoHubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China.
Yajing ZhangDepartment of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China.
Xiaomin ChenDepartment of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China.
Chengcheng DuDepartment of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China.
Kun WangDepartment of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China.
Zairong GaoDepartment of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, China. gaobonn@163.com.
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing · CNWuhan University · CN

Funding

National Natural Science Foundation of China (CN) 81771866
6 · The paper itself

Abstract

backgroundThe prognostic value of

methodsA total of 171 patients with newly diagnosed ENKTL undergoing

resultsMultivariate analysis demonstrated that pretreatment SUVmax≥9.5, disease stage II and III-IV, elevated lactate dehydrogenase (LDH), and elevated β2-microglobulin (β2-MG) had the strongest association with unfavorable PFS and OS. In addition, hemoglobin (Hb) < 120 g/L had a tendency to be associated with PFS. Both nomogram models incorporated SUVmax, Ann Arbor stage, LDH, and β2-MG. The PFS nomogram also included Hb. The nomograms showed good prediction accuracies, with the C-indexes for PFS and OS were 0.729 and 0.736, respectively. The calibration plots for 3-year and 5-year PFS/OS reported good consistency between predicted and observed probabilities for survival time. The PFS and OS were significantly different according to tertiles of nomogram scores (p < 0.001). The C-index and AUCs of the nomograms were higher than that of IPI and KPI. Moreover, DCA showed that the predictive accuracy of the nomograms for PFS and OS were both higher than that of IPI and KPI.

conclusionsThis study established nomograms that incorporate pretreatment SUVmax and clinical parameters, which could be effective tools for individualized prognostication of both PFS and OS in patients with newly diagnosed ENKTL.

Indexed as

NomogramsAdultAgedData Interpretation, StatisticalDisease-Free SurvivalDisease ProgressionFemaleFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedKaplan-Meier EstimateKiller Cells, NaturalLymphoma, Extranodal NK-T-CellMaleMiddle AgedMultivariate AnalysisFluorodeoxyglucose F18Radiopharmaceuticals18F-FDG PET/CTExtranodal natural killer/T-cell lymphomaNomogramPrognosisSUVmax

Identifiers

PMID33419476
PMCPMC7796613
OpenAlexW3118675362

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.