Evidence map›Paper›PMID 32231439›Full record

ArticleCancer management and research2020

A New Immunological Prognostic Model Based on Immunohistochemistry for Extranodal Natural Killer/T-Cell Lymphoma Patients After Non-Anthracycline-Based Chemotherapy.

Sio Teng Lam, He Huang, Xiaojie Fang, Zhao Wang, Huangming Hong, Quanguang Ren, Ying Tian, Suxia Lin, Tongyu Lin

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 34% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. FoxP3Cancers · 2024
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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 1 institution in 1 country.

Sio Teng Lam *Department of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.
He Huang *Department of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.
Xiaojie FangDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.
Zhao WangDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.ORCID 0000-0002-8969-9932
Huangming HongDepartment of Medical Oncology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China.ORCID 0000-0002-0803-1077
Quanguang RenDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.
Ying TianDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.
Suxia LinDepartment of Pathology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
Tongyu LinDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, and Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeProgrammed death ligand 1 (PD-L1) has been proposed as an important prognostic factor in many types of cancer. However, the role of predicting the prognosis of PD-L1 in extranodal natural killer/T-cell lymphoma (ENKTL) was controversial. Combining other biomarkers might enhance its predictive power. This study aims to evaluate the prognostic value of PD-L1 in conjunction with tumor-infiltrating FoxP3+Tregs for ENKTL after non-anthracycline-based chemotherapy. PATIENTS AND

methodsA total of 81 patients with ENKTL were included in this study. Clinicopathological characteristics were collected, and prognostic significance of PD-L1 in neoplastic cells (nPD-L1) and tumor-infiltrating FoxP3+Tregs were evaluated.

resultsPatients with nPD-L1-positive had significantly inferior overall survival (OS) and progression-free survival (PFS) compared with nPD-L1-negative (3-year OS, 37.2% vs 67.3%, p = 0.014; 3-year PFS, 31.0% vs 61.8%, p =0.010, respectively). Patients who had low FoxP3+Tregs had significantly inferior OS and PFS compared with high FoxP3+Tregs (3-year OS, 36.4% vs 63.0%, p = 0.004; 3-year PFS, 31.7% vs 56.3%, p = 0.020, respectively). The results of multivariate analysis showed that nPD-L1 positivity (HR 6.629, 95% CI 1.966-22.350, p=0.002) and low FoxP3+Tregs (HR 7.317, 95% CI 2.154-24.855, p=0.001) were independent predictors of inferior OS. Using these 2 variables, we constructed a new prognostic model that singled out 3 groups with different risk profiles: group 1, no adverse factors; group 2, 1 adverse factor; and group 3, 2 adverse factors. The 3-year OS rates of group 1, group 2, and group 3 were 93.3%, 46.6% and 20.8%, respectively (p<0.001), and the 3-year PFS rates were 86.7%, 40.8% and 15.0%, respectively (p=0.001).

conclusionThis study is the first to validate the prognostic value of nPD-L1 and tumor-infiltrating FoxP3+Tregs in ENKTL; the new immunological prognostic model might be used to stratify ENKTL patients in clinical trials for new therapeutic strategies.

Indexed as

extranodal natural killer/T-cell lymphomaFoxP3+TregsPD-L1prognosis

Identifiers

PMID32231439
PMCPMC7085340
OpenAlexW3011146332

What OpenQuestion holds

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LicenceCC BY-NC
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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.