Evidence map›Paper›PMID 36439900›Full record

ArticleJournal of oncology2022

Clinical Characteristics, Outcomes, and Risk Factors for Patients with Diffuse Large B-Cell Lymphoma and Development of Nomogram to Identify High-Risk Patients.

Jinrong Zhao, Yan Zhang, Wei Wang, Wei Zhang, Dao-Bin Zhou

Abstract read
In one paragraph

Article in Journal of oncology, 2022. 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. 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

5 authors.

Jinrong ZhaoDepartment of Hematology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0001-7663-9861
Yan ZhangDepartment of Hematology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Wei WangDepartment of Hematology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-1192-4896
Wei ZhangDepartment of Hematology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0001-9489-5965
Dao-Bin ZhouDepartment of Hematology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-1592-1932

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To analyse the clinical features, outcomes, and risk factors of patients with diffuse large B-cell lymphoma (DLBCL) in China, with the aim to establish a new prognostic model based on risk factors. Methods: Clinical features and outcomes of 564 patients newly diagnosed with DLBCL from Jan 2009 to May 2017 were analyzed retrospectively. Variables were screened by LASSO regression and nomogram was constructed. Results: The 5-year overall survival (OS) of the cohort was 75%. The 5-year OS of patients differentiated by International Prognostic Index (IPI) score was 90% (score 0-2), 73% (score 3), and 51% (score 4-5), respectively. Age > 60, Eastern Cooperative Oncology Group (ECOG) > 1, Ann Arbor stage III-IV, bone marrow involvement, low level of albumin (ALB), and lymphatic/monocyte ratio (LMR) were independent predictors of OS. The predictive model was developed based on factors including age, bone marrow involvement, LMR, ALB, and ECOG scores. The predictive ability of the model (AUC, 0.77) was better than that of IPI (AUC, 0.74) and NCCN-IPI (AUC, 0.69). The 5-year OS of patients in the low-, intermediate-, and high-risk groups identified by the new predictive model was 89%, 70%, and 33%, respectively. Conclusions: The new prediction model had better predictive performance and could better identify high-risk patients.

Identifiers

PMID36439900
PMCPMC9691331

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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.