Analysis of Factors Influencing Recurrence in Osteosarcoma Patients and Construction of Nomogram Prediction Model

Guoyu MA; Xin YANG; Weilin SHAO; Chuqi QUAN; Xiaohui YANG; Zuozhang YANG; Zhihong YAO

Article Contents

Article Navigation > Journal of Kunming Medical University > 2025 > Accepted Manuscript

Guoyu MA, Xin YANG, Weilin SHAO, Chuqi QUAN, Xiaohui YANG, Zuozhang YANG, Zhihong YAO. Analysis of Factors Influencing Recurrence in Osteosarcoma Patients and Construction of Nomogram Prediction Model[J]. Journal of Kunming Medical University.

Citation:

PDF( 1360 KB)

Analysis of Factors Influencing Recurrence in Osteosarcoma Patients and Construction of Nomogram Prediction Model

Guoyu MA¹,
Xin YANG²,
Weilin SHAO^{3, 4},
Chuqi QUAN^{3, 4},
Xiaohui YANG^{2, 4},
Zuozhang YANG²,
Zhihong YAO^{3
,
,}

1.
Department of Cancer Prevention and Control，The Third Afflated Hospital of Kunming Medical University，Yunnan Cancer Hospital，Peking University Cancer Hospital Yunnan
2.
Department of Orthopaedics，Bone and Soft Tissue Tumors Research Centre of Yunnan Province
3.
Cancer Research Institute of Yunnan Province，Kunming Yunnan 650118
4.
Clinical Oncology College of Kunming Medical University，Kunming Yunnan 650500，China

Received Date: 2025-07-15

Abstract

Abstract

Objectives To identify key clinical factors influencing recurrence in osteosarcoma patients, to construct and validate a Nomogram-based recurrence risk prediction model, thereby providing a quantitative tool for clinical decision-making and recurrence prevention/control. Methods Clinical data of 469 osteosarcoma patients admitted to Yunnan Cancer Hospital between 2013～2022 were retrospectively collected. Statistical analysis was performed using R software （version 4.3.2）. Potential influencing factors were initially screened via univariate analysis and LASSO regression analysis. Independent predictors of osteosarcoma recurrence were then identified using multivariate logistic regression analysis. Based on the identified independent factors, a Nomogram prediction model for recurrence risk was constructed. The area under the receiver operating characteristic curve （AUC） was used to evaluate the model's discriminative ability. Results Among the entire cohort, 68 patients experienced recurrence, yielding a recurrence rate of 14.50%. Multivariate analysis identified the following as independent predictors of recurrence: Primary Tumor Location: Tibial lesions （P = 0.009） were associated with a significantly lower recurrence risk compared to femoral lesions （OR = 0.297）, while lesions in "Other Bones" （P = 0.008） carried a significantly higher risk （OR = 3.294）. Biopsy Method: Needle biopsy（P = 0.033） was associated with a significantly lower recurrence risk compared to open biopsy （OR = 0.461）. Lung Metastasis Status: Patients with lung metastasis （P < 0.001） had a significantly higher recurrence risk than those without （OR = 11.873）. Lymphocyte Count: A higher lymphocyte count （P = 0.001） was a protective factor, associated with a lower recurrence risk （OR = 0.450）. The constructed Nomogram prediction model demonstrated excellent performance: Validation results showed an AUC=0.842（95%CI: 0.806～0.875）, indicating outstanding discriminative ability. Conclusions This study successfully constructed and validated a Nomogram prediction model for osteosarcoma recurrence risk integrating key clinical factors. The model demonstrates superior discriminative ability and can accurately and quantitatively assess the recurrence risk for individual patients. This tool thus provides critical reference for guiding clinical treatment decisions.
- Osteosarcoma,
- Recurrence risk,
- Influencing factors,
- Nomogram prediction model

FullText(HTML)

References(20)

References

[1]	Yoshida A. Osteosarcoma: Old and new challenges[J]. Surg Pathol Clin, 2021, 14(4): 567-583. doi: 10.1016/j.path.2021.06.003
[2]	Danese M D, Groundland J S. Effect of chemotherapy and surgery timing on mortality in upper and lower extremity osteosarcoma[J]. J Natl Cancer Inst, 2025, 117(4): 611-618. doi: 10.1093/jnci/djae229
[3]	Beird H C, Bielack S S, Flanagan A M, et al. Osteosarcoma[J]. Nat Rev Dis Primers, 2022, 8: 77. doi: 10.1038/s41572-022-00409-y
[4]	Lacinski R A, Dziadowicz S A, Melemai V K, et al. Spatial multiplexed immunofluorescence analysis reveals coordinated cellular networks associated with overall survival in metastatic osteosarcoma[J]. Bone Res, 2024, 12(1): 55. doi: 10.1038/s41413-024-00359-z
[5]	Xie D, Hu C, Zhu Y, et al. Sequential therapy for osteosarcoma and bone regeneration via chemodynamic effect and cuproptosis using a 3D-printed scaffold with TME-responsive hydrogel[J]. Small, 2025, 21(5): e2406639. doi: 10.1002/smll.202406639
[6]	Ding W Z, Liu K, Li Z, et al. A meta-analysis of prognostic factors of osteosarcoma[J]. Eur Rev Med Pharmacol Sci, 2020, 24(8): 4103-4112.
[7]	Balachandran V P, Gonen M, Smith J J, et al. Nomograms in oncology: More than meets the eye[J]. Lancet Oncol, 2015, 16(4): e173-e180. doi: 10.1016/S1470-2045(14)71116-7
[8]	郭卫. 日本骨科协会(JOA)原发恶性骨肿瘤管理临床实践指南重点内容解读[J]. 中国修复重建外科杂志, 2025, 39(7): 814-823.
[9]	马国玉, 黄瑾, 杨鑫, 等. 骨肉瘤患者肺转移影响因素分析及预测模型的构建与验证[J]. 肿瘤学杂志., 2025, 31(3): 231-237.
[10]	李嘉伊, 任庆兰. 晚期骨肉瘤分子靶向治疗研究进展[J]. 现代医药卫生., 2019, 35(19): 2996-2999.
[11]	Yao Z, Tan Z, Yang J, et al. Prognostic nomogram for predicting 5-year overall survival in Chinese patients with high-grade osteosarcoma[J]. Sci Rep, 2021, 11(1): 17728. doi: 10.1038/s41598-021-97090-0
[12]	唐顺, 郭卫, 杨荣利, 等. 40岁以上成年骨肉瘤患者的外科治疗及预后因素[J]. 北京大学学报(医学版)., 2015, 47(1): 165-169.
[13]	吕卫星, 周胜利, 严米云, 等. 甲氨蝶呤联合雷公藤多苷片治疗骨肉瘤的临床效果及对炎症因子、复发率的影响[J]. 世界复合医学, 2024, 10(10): 78-81.
[14]	Andreou D, Bielack S S, Carrle D, et al. The influence of tumor- and treatment-related factors on the development of local recurrence in osteosarcoma after adequate surgery. An analysis of 1355 patients treated on neoadjuvant Cooperative Osteosarcoma Study Group protocols[J]. Ann Oncol, 2011, 22(5): 1228-1235. doi: 10.1093/annonc/mdq589
[15]	Koirala P, Roth M E, Gill J, et al. Immune infiltration and PD-L1 expression in the tumor microenvironment are prognostic in osteosarcoma[J]. Sci Rep, 2016, 6: 30093. doi: 10.1038/srep30093
[16]	Strauss S J, Frezza A M, Abecassis N, et al. Bone sarcomas: ESMO-EURACAN-GENTURIS-ERN PaedCan Clinical Practice Guideline for diagnosis, treatment and follow-up[J]. Ann Oncol, 2021, 32(12): 1520-1536. doi: 10.1016/j.annonc.2021.08.1995
[17]	Abd Elmoneim H M, Huwait H F, Nafady-Hego H, et al. Prognostic implications of pd-l1 expression and loss of pten in patients with rhabdomyosarcoma, Ewing’s sarcoma and osteosarcoma[J]. Exp Oncol, 2024, 45(3): 337-350.
[18]	闫广宁, 喻玲, 赖续文, 等. 骨肉瘤中PD-1和CTLA-4的表达与患者临床病理特征及预后的相关性[J]. 肿瘤防治研究., 2023, 50(1): 63-68.
[19]	褚吉祥, 冯超凡, 何喆, 等. 影像组学-临床特征联合模型预测骨肉瘤术后复发的价值[J]. 现代肿瘤医学, 2025, 6(16): 1-9.
[20]	乔相帅, 郑凯, 徐明, 等. 肿瘤生长方式影像学表现对骨肉瘤预后影响的临床研究[J]. 骨科., 2024, 15(4): 332-338.

Relative Articles(20)

Relative Articles

[1]	Qianrong YANG, Xue CAO, Jiao YANG, Yanqiu ZHAO, Nan SHEN, Yajiao SUN. Status and Influencing Factors of Stigma in Lung Cancer Patients. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20250108
[2]	Jiang ZHANG, Xijuan ZHAO, Jiang WU, Bingkun YANG, Ni YANG, Liping ZHOU. Analysis of Frailty Status and Influencing Factors in Lung Cancer Patients Undergoing Radiotherapy. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20250218
[3]	Qing LI, Wei GENG, Fengxi ZHANG, Dan ZHANG. Clinical Study on Predicting Pregnancy Outcomes through The Imbalance of Vaginal Microbiota and Levels of Inflammatory Factors in Pregnant Women. Journal of Kunming Medical University,
[4]	Junqiang WANG, Ying CHEN, Fengchen GAO, Wenxiu ZHAO, Shuxuan CAO, Yixi LI, Limei HE, Zexing YANG. The Construction of A Predictive Model for Clinical Pregnancy Outcome in Frozen-thawed Embryo Transfer Cycles in Women with Advanced Maternal Age. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20250807
[5]	Yuanzhen WANG, Hongyan WEI, Renhai TIAN, Yongzhen Chen, Danqing XU, Yingyuan ZHANG, Lixian CHANG, Chunyun LIU, Li LIU. Establishment and Evaluation of a Risk Prediction Model for Chronic Liver Failure Complicated by Primary Hepatocellular Carcinoma Before Intervention. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20250321
[6]	Yunhui ZHANG, Xiaorong YANG, Xieqiao HE, Fameng LUO, Haiyan ZHANG. Analysis of Nutritional Risk Factors in Inflammatory Bowel Disease Patients. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20250622
[7]	Binbin MA, Shaoxiong ZHANG, Yongli GAO. Bioinformatics-based Investigation of the Prognostic Value of ESCRT-related Genes in Osteosarcoma Assessment. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20250406
[8]	Yanmei JI, Wenjun LI, Qingyun LI, Ni GUO, Ni MENG, Dan ZHOU, Qiuyu LI, Xingfang JIN. The Analysis of Related Factors of Cognitive Impairment after the Acute Ischemic Stroke and Construction of Nomogram Model. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20240511
[9]	Shumei QIU, Jingrui YANG, Xuecai QIU. The Risk and Influencing Factors of Vascular Dementia in Middle-aged and Elderly People in Kunming. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20240914
[10]	Rui WANG, Cilin HAN, Yuanqing CAO, Xiaoyan YANG. Multi-level Model Analysis of Factors Influencing Physicians' Job Burnout. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20241110
[11]	Juan LI, Jun ZHANG, Qiao-ling ZHENG, Pu-qiong FENG, Jin HE. Analysis of Monitoring Results and Influencing Factors of Vancomycin Blood Concentration in Neurosurgery Department. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20210614
[12]	Xin-tian LONG, Jie CHEN, Yong MAO, Xiu-qing WANG, Shuang-yan LU, Hui-jie PU, Jia ZHOU, Cheng-huan SUN, Song-mei WANG, Ai-fang YE. Detection Rate and Determinants of Hypertension among Seniors in Anning City. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20211210
[13]	Xue-song HU, Li-yue CHEN, Shi-fu LI, Wen-bin DONG, Zi-qian HE, Shao-xin DONG, Shun-xiang LI. Influencing Factors Contributing to Insomnia Among Patients with Chronic Pain. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20210207
[14]	Ling ZHOU, Feng-di HU, Rong LI, Ye-dan LIAO, Zheng-qin GENG, Jia-dai TANG, Xue-qi ZHANG, Lin XIE, Zuo-zhang YANG. A Clinical Scoring System Predicting the Osteosarcoma Chemotherapy Drug Resistance. Journal of Kunming Medical University, doi: 10.12259/j.issn.2095-610X.S20210144
[15]	Li Shan Shan , Quan Yu Hang , Gong Ling Li , Yang Hui , Pu Jing Hong , Wang Zhong Hui . . Journal of Kunming Medical University,
[16]	Zhang Jin Yu , Peng Zhuo Hui . Relationship between Single Nucleotide Polymorphisms of ERCC Gene and Survival of Osteosarcoma. Journal of Kunming Medical University,
[17]	Ma Xiao Yan . The Depression Status and Influencing Factors for the Late Pregnancy Women. Journal of Kunming Medical University,
[18]	Lu Bin . . Journal of Kunming Medical University,
[19]	Luo Wen Dong . . Journal of Kunming Medical University,
[20]	He Li Ping . . Journal of Kunming Medical University,