A Novel Nomogram for Predicting Cancer-Specific Survival in Patients With Spinal Chordoma: A Population-Based Analysis

Huang, Zhangheng; Fan, Zhaoqing; Zhao, Chengliang; Sun, He

doi:10.1177/15330338211036533

Cited by 10 publications

(9 citation statements)

References 24 publications

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“…The National Comprehensive Cancer Network for Bone Cancer screening guidelines also clearly state the significant role of neoadjuvant and adjuvant multidrug chemotherapy in improving the prognosis of patients with osteosarcoma and Ewing’s sarcoma ( 16 ). This conclusion is somewhat similar to the study we did previously ( 7 ). However, radiation therapy and chemotherapy were not included as statistically significant variables in our study in the nomogram.…”

Section: Discussionsupporting

confidence: 93%

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Clinical characteristics, prognostic factors, and predictive model for elderly primary spinal tumor patients who are difficult to tolerate surgery or refuse surgery

Huang

Zhao²,

Wang³

et al. 2022

Front. Oncol.

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BackgroundAs a rare tumor, surgery is the best treatment for primary spinal tumors. However, for elderly patients who cannot undergo surgery, the prognosis is often difficult to evaluate. The purpose of this study was to identify the risk factors that may lead to death and predict the prognosis of elderly patients with primary spinal tumors who have not undergone surgical treatment. MethodsIn this study, 426 patients aged 60 years or older diagnosed with a primary spinal tumor between 1975 and 2015 were selected and included from the Surveillance, Epidemiology, and End Results database. A retrospective analysis was performed by using the Cox regression algorithm to identify independent prognostic factors. A nomogram model was developed based on the results. Multiple evaluation methods (calibration curve, receiver operating characteristic curve, and decision curve analyses) were used to evaluate and validate the performance of the nomogram.ResultsA nomogram was developed, with age, histological type, and stage as independent prognostic factors. The results indicated that the prognostic risk tended to increase significantly with age and tumor spread. Osteosarcoma was found to have the most prominent risk prognosis in this patient group, followed by chondrosarcoma and chordoma. The area under the curve and the C-index of the model were both close to or greater than 0.7, which proved the high-differentiation ability of the model. The calibration curve and decision curve analyses showed that the model had high predictive accuracy and application value.ConclusionsWe successfully established a practical nomogram to assess the prognosis of elderly patients with primary spinal tumors who have not undergone surgical treatment, providing a scientific basis for clinical management.

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Section: Discussionsupporting

confidence: 93%

“…A nomogram, a simple visualization of Cox regression results, can help clinicians predict the prognosis with significant advantages and greatly improve predictive accuracy (7). In a previous study, Zhou et al constructed a prognostic nomogram model for patients with all types of primary spinal tumors (8).…”

Section: Introductionmentioning

confidence: 99%

Clinical characteristics, prognostic factors, and predictive model for elderly primary spinal tumor patients who are difficult to tolerate surgery or refuse surgery

Huang

Zhao²,

Wang³

et al. 2022

Front. Oncol.

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“…In addition to age, logistic regression analysis showed that tumor grade, tumor stage, and histological type of tumor are also key factors. Te prognosis of survival in patients with primary tumors of the spine has been welldocumented to correlate with these factors, and many authors have constructed related nomograms [10,[18][19][20][21][22][23][24][25][26]. In our previous studies, we have shown that tumor grade, tumor stage, and histological type of tumor are the key factors infuencing postoperative OS in patients with primary spinal tumors, which is consistent with the results of this study [25].…”

Section: Discussionsupporting

confidence: 90%

A Simple-to-Use Nomogram for Predicting Postoperative Early Death Risk in Elderly Patients with Spinal Tumors: A Population-Based Study

Huang

Zhao

Liu

et al. 2023

Journal of Oncology

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Background. For elderly patients with primary spinal tumors, surgery is the best option for many elderly patients, in addition to palliative care. However, due to the unique physical function of elderly patients, the short-term prognosis is often unpredictable. It is therefore essential to develop a novel nomogram as a clinical aid to predict the risk of early death for elderly patients with primary spinal tumors who undergo surgery. Materials and Methods. In this study, clinical data were obtained from 651 patients through the SEER database, and they were retrospectively analyzed. Logistic regression analyses were used for risk-factor screening. Predictive modeling was performed through the R language. The prediction models were calibrated as well as evaluated for accuracy in the validation cohort. The receiver operating characteristic (ROC) curve and the decision curve analysis (DCA) were used to evaluate the functionality of the nomogram. Results. We identified four separate risk factors for constructing nomograms. The area under the receiver operating characteristic curve (training set 0.815, validation set 0.815) shows that the nomogram has good discrimination ability. The decision curve analysis demonstrates the clinical use of this nomogram. The calibration curve indicates that this nomogram has high accuracy. At the same time, we have also developed a web version of the online nomogram for clinical practitioners to apply. Conclusions. We have successfully developed a nomogram that can accurately predict the risk of early death of elderly patients with primary spinal tumors undergoing surgery, which can provide a reference for clinicians.

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“…Nomograms, the prognostic device capable of combing multiple parameters that can reveal the relationship between chordoma and prognosis with greater accuracy and convenience than every single parameter that reflects only limited associations with a particular aspect of chordoma, and thus are now widely used for individualized prediction of tumor patients [17,18]. In the past, nomograms based on traditional Cox proportional hazard regression models and Kaplan-Meier methods have been employed extensively to predict survival outcomes in chordoma patients [16,[19][20][21]. However, it is a non-negligible drawback that competing risk (in other word, non-cause-specific death), such as non-cancer-specific death (NCSD), is treated as censored data in the traditional Cox and Kaplan-Meier survival analyses [22].…”

Section: Introductionmentioning

confidence: 99%

Competing risk nomogram for predicting prognosis of patients with spinal and pelvic chordoma: A SEER-based retrospective study

Yuan

et al. 2023

Eur Spine J

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Purpose Recently, competing risk nomograms were widely applied to predict prognosis in numerous tumors other than chordoma. Here, we aimed to construct and validate a competing-risk-based prognostic nomogram to predict 3- and 5-year cancer-specific death (CSD) in patients with spinal and pelvic chordoma. Methods All chordoma patient data were abstracted from the Surveillance, Epidemiology, and End Results (SEER) resource, and a total of 485 chordoma patients were eventually included in this study. Multivariate competing risk model and multivariate Cox model were used to determine independent prognostic factors, respectively, and the results of the two models were compared. Nomogram was employed to visualize the competing risk model. The discrimination, calibration, and clinical utility of this model were evaluated by Harrell concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Ten-fold cross-validation was further utilized to validate the prognostic nomogram. Results Significant prognostic factors affecting CSD were age (P = 0.016), localized involvement (P < 0.0001), and radical resection (P < 0.001) in the multivariate competing risk model. C-indexes were 0.799 and 0.76, and AUC were 0.812 and 0.778 for 3- and 5-year CSD. Calibration plots demonstrated the nomogram was well-fitted, and DCA indicated good clinical utility. The nomogram showed good performance in the 10-fold cross-validation. Conclusion We successfully built the first competing-risk-based nomogram to predict clinical outcomes in patients with spinal and pelvic chordoma. This well-established nomogram hopes to help clinicians with precise prognostic assessment and thus improve clinical outcomes.

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A Novel Nomogram for Predicting Cancer-Specific Survival in Patients With Spinal Chordoma: A Population-Based Analysis

Cited by 10 publications

References 24 publications

Clinical characteristics, prognostic factors, and predictive model for elderly primary spinal tumor patients who are difficult to tolerate surgery or refuse surgery

Clinical characteristics, prognostic factors, and predictive model for elderly primary spinal tumor patients who are difficult to tolerate surgery or refuse surgery

A Simple-to-Use Nomogram for Predicting Postoperative Early Death Risk in Elderly Patients with Spinal Tumors: A Population-Based Study

Competing risk nomogram for predicting prognosis of patients with spinal and pelvic chordoma: A SEER-based retrospective study

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