Evidence map›Paper›PMID 33785046›Full record

ArticleJournal of orthopaedic surgery and research2021

Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study.

Shouliang Lu, Yanhua Wang, Guangfei Liu, Lu Wang, Pengfei Wu, Yong Li, Cai Cheng

Open access · goldAbstract readValidation Study
In one paragraph

Article in Journal of orthopaedic surgery and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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  10. Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
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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

7 authors at 1 institution in 1 country.

Shouliang Lu *NO.1 Orthopedics Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China. lushouliang0317@163.com.
Yanhua Wang *ECG Examination Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China.
Guangfei LiuNO.1 Orthopedics Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China.
Lu WangNO.1 Orthopedics Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China.
Pengfei WuNO.1 Orthopedics Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China.
Yong LiNO.1 Orthopedics Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China.
Cai ChengNO.1 Orthopedics Department, Cangzhou Central Hospital, Cangzhou, Hebei Province, China.
Cangzhou Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteosarcoma is most common malignant bone tumors. OS patients with metastasis have a poor prognosis. There are few tools to assess metastasis; we want to establish a nomogram to evaluate metastasis of osteosarcoma.

methodsData from the Surveillance, Epidemiology, and End Results (SEER) database of patients with osteosarcoma were retrieved for retrospective analysis. We identify risk factors through univariate logistic regression and multivariate logistic regression analysis. Based on the results of multivariate analysis, we established a nomogram to predict metastasis of patients with osteosarcoma and used the concordance index (C-index) and calibration curves to test models.

resultsOne thousand fifteen cases were obtained from the SEER database. In the univariate and multivariate logistic regression analysis, age, primary site, grade, T stage, and surgery are risk factors. The nomogram for metastasis was constructed based on these factors. The C-index of the training and validation cohort was 0.754 and 0.716. This means that the nomogram predictions of patients with metastasis are correct, and the calibration plots also show the good prediction performance of the nomogram.

conclusionWe successfully develop the nomogram which can reliably predict metastasis in different patients with osteosarcoma and it only required basic information of patients. The nomogram that we developed can help clinicians better predict the metastasis with OS and determine postoperative treatment strategies.

Indexed as

NomogramsAdultBone NeoplasmsFemaleForecastingHumansLogistic ModelsMaleMiddle AgedNeoplasm MetastasisNeoplasm StagingOsteosarcomaPrognosisRetrospective StudiesRisk FactorsSurvival RateLogistic regressionMetastasisNomogramOsteosarcoma

Identifiers

PMID33785046
PMCPMC8008682
OpenAlexW3139694522

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.