Evidence map›Paper›PMID 36867400›Full record

ArticleAnnals of nuclear medicine2023

Prognosis of thyroid carcinoma patients with osseous metastases: an SEER-based study with machine learning.

Wanying Shi, Weiming Wu, Luyang Zhang, Qiang Jia, Jian Tan, Wei Zheng, Ning Li, Ke Xu, Zhaowei Meng

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Article in Annals of nuclear medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Wanying ShiDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Weiming WuDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Luyang ZhangGraduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan.
Qiang JiaDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Jian TanDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Wei ZhengDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Ning LiDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Ke XuTianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China. ke_xu@hotmail.com.
Zhaowei MengDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China. zmeng@tmu.edu.cn.ORCID http://orcid.org/0000-0001-6370-7394

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveOsseous metastasis (OM) is the second most common site of thyroid cancer distant metastasis and presents a poor prognosis. Accurate prognostic estimation for OM has clinical significance. Ascertain the risk factors for survival and develop an effective model to predict the 3-year, 5-year overall survival (OS) and cancer-specific survival (CSS) for thyroid cancer patients with OM.

methodsWe retrieved the information of patients with OMs between 2010 and 2016 from the Surveillance, Epidemiology, and End Result Program. The Chi-square test, and univariate and multivariate Cox regression analyses were performed. Four machine learning (ML) algorithms, which were most commonly used in this field, were applied.

resultA total of 579 patients having OMs were eligible. Advanced age, tumor size ≥ 40 mm, combined with other distant metastasis were associated with worse OS in DTC OMs patients. Radioactive iodine (RAI) significantly improved CSS in both males and females. Among four ML models [logistic regression, support vector machines, extreme gradient boosting, and random forest (RF)], RF had the best performance [area under the receiver-operating characteristic curve: 0.9378 for 3-year CSS, 0.9105 for 5-year CSS, 0.8787 for 3-year OS, 0.8909 for 5-year OS]. The accuracy and specificity of RF were also the best.

conclusionsRF model shall be used to establish an accurate prognostic model for thyroid cancer patients with OM, not only from the SEER cohort but also intended for all thyroid cancer patients in the general population, which may be applicable in clinical practice in the future.

Indexed as

Bone NeoplasmsThyroid NeoplasmsFemaleHumansIodine RadioisotopesMaleNeoplasm StagingPrognosisIodine RadioisotopesMachine learning (ML)Osseous metastases (OMs)Radioactive iodine (RAI)Random forest (RF)SurveillanceSurvivalThyroid carcinoma (TC)

Identifiers

PMID36867400

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