Evidence map›Paper›PMID 33889512›Full record

ArticleTranslational lung cancer research2021

Development of RECLS score to predict survival in lung cancer patients with malignant pleural effusion.

Tianli Zhang, Xi Chen, Bing Wan, Yangyang Xu, Hongbing Liu, Tangfeng Lv, Ping Zhan, Yong Song

Open access · diamondAbstract read
In one paragraph

Article in Translational lung cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

9 citing papers in PubMed, 9 citations in OpenAlex.

  1. Comparison of LENT, PROMISE, and RECLS scores in malignant pleural effusions.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  4. Lymph nodes rather than pleural metabolic activity inTranslational lung cancer research · 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

8 authors at 4 institutions in 1 country.

Tianli ZhangDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Medical School of Southeast University, Nanjing, China.
Xi ChenDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.
Bing WanDepartment of Respiratory and Critical Care Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
Yangyang XuDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Jinling Clinical College of Nanjing Medical University, Nanjing, China.
Hongbing LiuDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Medical School of Southeast University, Nanjing, China.
Tangfeng LvDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Medical School of Southeast University, Nanjing, China.
Ping ZhanDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Medical School of Southeast University, Nanjing, China.
Yong SongDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Medical School of Southeast University, Nanjing, China.
Nanjing Medical University · CNNanjing General Hospital of Nanjing Military Command · CNSoutheast University · CNNanjing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalignant pleural effusion (MPE) is usually caused by lung cancer, and the prognostic factors are poorly understood. We aimed to develop models to predict the survival of lung cancer patients and lung adenocarcinoma patients with MPE.

methodsWe enrolled lung cancer patients with MPE in Nanjing Jinling Hospital from January 2008 to June 2018 into our study. We selected risk factors using multivariable Cox proportional-hazards analysis in the development cohort. The risk models were created according to the risk ratio (RR) value. The participants were categorized into low-risk, moderate-risk, and high-risk groups according to the sum of every risk factor.

resultsA total of 367 lung cancer patients were included in the development cohort. The scoring systems RECLS (relapse or not, ECOG PS, CRP, pleural LDH, and TNM stage) and RECLSAM (relapse or not, ECOG PS, CRP, pleural LDH, TNM stage, albumin-globulin ratio, and activating gene mutation) were created for lung cancer patients with MPE and lung adenocarcinoma patients with MPE. The area under the curve (AUC) values for the RECLS model were 0.911, 0.845, and 0.754, respectively, at 1 month, 6 months, and 12 months.

conclusionsThis study developed prognostic models for lung cancer patients with MPE. The RECLS and RECLSAM scores are practical, clinically applicable models to help guide the selection of optimal treatment strategies.

Indexed as

Lung cancermalignant pleural effusionprognostic model

Identifiers

PMID33889512
PMCPMC8044486
OpenAlexW3139905109

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.