Evidence map›Paper›PMID 34594418›Full record

ArticleOncology letters2021

Construction and validation of nomograms for non-metastatic Ewing sarcoma: A prognostic factor analysis based on the SEER database.

Runzhi Huang, Dong Han, Chengcheng Shi, Penghui Yan, Peng Hu, Xiaolong Zhu, Huabin Yin, Tong Meng, Zongqiang Huang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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 3 institutions in 1 country.

Runzhi HuangDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
Dong HanDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
Chengcheng ShiDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
Penghui YanDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
Peng HuDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
Xiaolong ZhuDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
Huabin YinDepartment of Orthopaedics, Shanghai Bone Tumor Institute, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, P.R. China.
Tong MengDivision of Spine Surgery, Department of Orthopaedics, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, P.R. China.
Zongqiang HuangDepartment of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China.
First Affiliated Hospital of Zhengzhou University · CNShanghai First People's Hospital · CNTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ewing sarcoma is the second most common osseous disease in children and adolescents. It presents with a poor prognosis due to the high degree of malignancy and distant metastasis. In order to predict the disease prognosis and investigate a suitable therapeutic strategy for Ewing sarcoma, the present study aimed to describe the clinical characteristics, and to construct and validate nomograms for patients with non-metastatic Ewing sarcoma. A total of 627 cases of non-metastatic Ewing sarcoma were retrospectively collected from the Surveillance, Epidemiology, and End Results database between 2005 and 2014. Survival analysis and a machine learning model were used to identify independent prognostic variables and establish nomograms to estimate overall survival (OS) and cause-specific survival (CSS). The nomograms were bootstrap internally validated and externally validated using non-metastatic Ewing sarcoma cases from the First Affiliated Hospital of Zhengzhou University. The accuracy was also assessed by comparing with current American Joint Committee on Cancer (AJCC) staging systems. The total series consisted of 627 patients with non-metastatic Ewing sarcoma with a mean age of 20.14 years. Age, tumor extension, sex, International Classification of Diseases for Oncology, 3rd Edition histology, surgery and chemotherapy were identified as independent risk factors for OS and CSS. The aforementioned outcomes were incorporated to construct the nomograms, and the concordance indices (C-indices) for internal validation of OS and CSS prediction were 0.791 and 0.813, which were higher than those for AJCC sixth edition (OS, 0.531; CSS, 0.534) and seventh edition (OS, 0.547; CSS, 0.561), while the C-indices for external validation of OS and CSS prediction were 0.834 and 0.825, respectively. In conclusion, age, sex, tumor extension and surgery were independent prognostic factors for both OS and CSS. In addition, with regard to OS, the Ewing sarcoma subtype was a poor factor and chemotherapy was a favorable one. Nomograms based on reduced Cox models attained a satisfactory accuracy in predicting the survival of patients with non-metastatic Ewing sarcoma and could assist clinicians in evaluating survival more accurately.

Indexed as

external validationnomogramnon-metastatic Ewing sarcomaprognostic factorsurvival analysis

Identifiers

PMID34594418
PMCPMC8456482
OpenAlexW3199055385

What OpenQuestion holds

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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.