Evidence map›Paper›PMID 36154721›Full record

ArticleGlobal spine journal2024

Clinical Features, Risk Factors, and Prediction Nomogram for Primary Spinal Osteosarcoma: A Large-Cohort Retrospective Study.

Zhangheng Huang, Chao Huang, Yu Wang, Ye Wu, Chuan Guo, Weilong Li, Qingquan Kong

Abstract read
In one paragraph

Article in Global spine journal, 2024. 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

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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

7 authors.

Zhangheng HuangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-6885-098X
Chao HuangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-7140-3304
Yu WangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.
Ye WuDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.
Chuan GuoDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.
Weilong LiDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.
Qingquan KongDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-4732-4948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

designRetrospective cohort study.

objectivesThe goal of this study was to determine the clinical characteristics of patients with primary spinal osteosarcoma and to construct a practical clinical prediction model for patients to achieve an accurate prediction of overall survival.

methodsThis study included 230 patients diagnosed between 2004-2015 from the Surveillance, Epidemiology, and End Results database. Independent risk factors were screened in the training set using Cox regression algorithms, and a prognostic model was developed. Internal and external validation sets were used to test the nomogram model's calibration, discrimination, and clinical utility. A risk classification system based on the nomogram was developed and validated.

resultsFour independent prognostic factors were identified, and based on this a nomogram model was developed for predicting patient prognosis. The C-index of the training set was .737, while that of the validation set was .693. The time-varying area under the curve values was greater than .720 in both cohorts. The calibration curves proved that the prediction model has high prediction accuracy. The decision curve analysis showed that the nomogram is clinically useful. A risk classification system was established, which allows all patients to be divided into two different risk groups.

conclusionsA nomogram and risk classification system was developed for patients with primary spinal osteosarcoma to accurately predict overall patient survival and achieve risk stratification of patient mortality. These tools are expected to play an important role in clinical practice, informing clinicians in making decisions.

Indexed as

nomogramosteosarcomaoverall survivalspinalsurveillance, epidemiology, and end results

Identifiers

PMID36154721
PMCPMC11192120

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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.