Background: Bone metastasis (BM) has been proven to be responsible for the poor prognosis of primary malignant bone neoplasms (PMBNs). We aimed to identify the prevalence, risk factors, and prognostic factors for PMBNs patients with BM based on the Surveillance, Epidemiology, and End Results (SEER) database.
Methods: 4,758 patients diagnosed with PMBNs from 2010 to 2018 were selected from the SEER database. All patients were divided into two groups: the BM group or the non-BM group. Pearson's chi-square test and Fisher's exact method were used to assess baseline characteristics, and logistic regression analysis was applied to assess risk factors. In addition, a nomogram was constructed based on the results of Cox regression analysis among 227 patients with BM. The good performance and clinical applicability of the nomogram were tested by the concordance index, operating characteristic curve, area under the curve, calibration curves, and decision curve analysis.
Results: 227 (4.8%) patients had metastasis to bone at diagnosis. Primary site outside the extremities (axial: odds ratio, OR = 1.770; others: OR = 1.951), Ewing sarcoma (OR = 2.845), larger tumor size (5-8 cm: OR = 3.403; >8 cm: OR = 5.562), tumor extension beyond the periosteum (OR = 2.477), and regional lymph node metastasis (OR = 2.900) were associated with a higher risk of BM at the initial diagnosis of PMBNs. Five independent prognostic factors were found in the survival analysis: pathological type (chondrosarcoma vs. osteosarcoma: hazard ratio, HR = 0.342; Ewing sarcoma vs. osteosarcoma: HR = 0.592; and chordoma vs. osteosarcoma: HR = 0.015), marital status (HR = 2.457), pulmonary metastasis (HR = 1.934), surgery at the primary site (HR = 0.164), and chemotherapy (HR = 0.084). A nomogram based on these prognostic factors could be a good predictor of cancer-specific survival.
Conclusions: We identified the prevalence, risk factors, and prognostic factors correlated with BM in PMBNs patients. The related nomogram could be a practical tool for therapeutic decision-making and individual counseling.
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http://dx.doi.org/10.1155/2022/9935439 | DOI Listing |
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School of Nursing, Jinan University, Guangzhou, China.
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Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
This dataset contains demographic, morphological and pathological data, endoscopic images and videos of 191 patients with colorectal polyps. Morphological data is included based on the latest international gastroenterology classification references such as Paris, Pit and JNET classification. Pathological data includes the diagnosis of the polyps including Tubular, Villous, Tubulovillous, Hyperplastic, Serrated, Inflammatory and Adenocarcinoma with Dysplasia Grade & Differentiation.
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