Evidence map›Paper›PMID 32787692›Full record

ArticleTechnology in cancer research & treatment

Prognostic Factors in Patients With Osteosarcoma With the Surveillance, Epidemiology, and End Results Database.

Peng Fu, Yu Shi, Gang Chen, Yaohua Fan, Yanhong Gu, Zhenzhen Gao

Abstract read
In one paragraph

Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  10. Lipid Peroxidation-Related Redox Signaling in Osteosarcoma.International journal of molecular sciences · 2024
    Review
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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

6 authors.

Peng FuDepartment of Orthopedic, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.ORCID 0000-0003-2982-6300
Yu ShiDepartment of Radiotherapy, 74567Affiliated Hospital of Nantong University, Nantong, China.
Gang ChenDepartment of Orthopedic, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
Yaohua FanDepartment of Clinical Oncology, 569220The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
Yanhong GuDepartment of Clinical Oncology, 74734The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Zhenzhen GaoDepartment of Clinical Oncology, 569220The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.ORCID 0000-0002-9518-7634

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteosarcoma is a rare type of bone tumor, and this study aimed to assess the clinicopathologic features and prognoses of osteosarcoma patients.

methodsClinicopathologic and survival data of 1025 patients between 2010 and 2016, 230 between 2008 and 2009 were downloaded and analyzed from the SEER database. Patients' survival was analyzed using the Kaplan-Meier analysis; prognostic factors were assessed using the Cox regression hazards model. The 1-, 3-, and 5-year survival rates were estimated with nomogram. Competitive risk models were used to identify prognostic risk factors related to endpoint events of osteosarcoma patients.

resultsOverall, 722 samples were obtained from the extremities, 134 from the axial bones, and 119 from the cranial and mandible in SEER (2010-2016 cohort). After the preliminary diagnosis, the median survival time of patients with osteosarcoma was 39 months, and the 1-, 3-, and 5-year survival rates were 87.3%, 67.2%, and 58.0%, respectively (P < 0.001). The competitive risk model revealed no competitive risks of the endpoint event.

conclusionOur study found out the prognostic factors in patients with Osteosarcoma by Cox regression hazards model, after that, nomogram was established to predict the 1-, 3-, and 5-year survival rates, which may help oncologists to understand the highly malignant tumor.

Indexed as

Bone NeoplasmsDatabases, FactualDisease ManagementFemaleHumansKaplan-Meier EstimateMaleNomogramsOsteosarcomaPrognosisProportional Hazards ModelsPublic Health SurveillanceRisk FactorsSEER ProgramUnited Statescompetitive risk modelscox regression hazards modelnomogramosteosarcomaSEER database

Identifiers

PMID32787692
PMCPMC7427153

What OpenQuestion holds

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LicenceCC BY-NC
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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.