Construction and Validation of New Nomograms to Predict Risk and Prognostic Factors of Breast Cancer Bone Metastasis in Asian Females: A Population-Based Retrospective Study

Deng, Junsen; Zhang, Di; Zhang, Wenming; Li, Junhui

doi:10.2147/ijgm.s335123

Cited by 6 publications

(7 citation statements)

References 35 publications

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“…Many studies have suggested that histological subtype, primary site, and BC subtype are independent predictors of BC patient diagnosis or prognosis (11)(12)(13). In this study, although simple analysis indicated that these variables might affect the diagnosis and prognosis of MBCBM patients, multivariate analysis revealed no significance (P>0.05).…”

Section: Malignant Tumor Cells Interfere With Bone Microenvironment H...contrasting

confidence: 62%

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Risk stratification system and visualized dynamic nomogram constructed for predicting diagnosis and prognosis in rare male breast cancer patients with bone metastases

Gao

et al. 2022

Front. Endocrinol.

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BackgroundBone metastases (BM) from malignant tumors could disrupt the balance between osteoclasts and osteoblasts and affect bone homeostasis. Malignant breast cancer (BC) is rare in male patients, and co-occurrence of BM is even rarer. Given its low incidence, there is limited research evaluating risk and prognosis. Despite the widespread application of nomograms to predict uncommon malignancies, no studies have constructed predictive models focusing on the diagnosis and prognosis of male breast cancer with bone metastases (MBCBM).MethodsThis study selected all male breast cancer patients (MBC) between 2010 and 2019 in the Surveillance, Epidemiology, and End Results (SEER) database. We used simple and multivariate Logistic regression analyses to identify independent risk factors for BM in MBC patients. Then simple and multivariate Cox regression analyses were employed to determine the independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in MBCBM patients. We established and validated three new nomograms based on these independent factors.ResultA total of 4187 MBC patients were included, with 191 (4.56%) having bone metastases at the time of diagnosis. The independent risk factors of BM in MBC patients included age, tumor size, marital status, T stage, and N stage. In MBCBM patients, independent prognostic factors for OS and CSS were both age, T stage, ER status, PR status, and surgery. The concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic curve (ROC), the calibration curve, and the decision curve analysis (DCA) confirmed that these three nomograms could accurately predict the diagnosis and prognosis of MBCBM patients with excellent discrimination and clinical utility superior to the TNM staging system. We then established two prognostic-based risk stratification systems and three visualized dynamic nomograms that could be applied in clinical practice.ConclusionIn conclusion, this study aimed to establish and validate an accurate novel nomogram to objectively predict the diagnosis and prognosis of MBCBM patients. On this basis, prognostic-based risk stratification systems and visualized dynamic nomograms were constructed to facilitate doctors and patients to quantify individual BM risk probability and survival probability to assist in personalized risk assessment and clinical decision-making.

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Section: Malignant Tumor Cells Interfere With Bone Microenvironment H...contrasting

confidence: 62%

“…This has a substantial detrimental impact on patients' quality of life and mental health, as well as increasing social burden and triggering public anxiety. To date, there are many published reports on FBC with BM, but few on the clinical characteristics and prognostic survival of MBC with BM (MBCBM) (11)(12)(13)(14).…”

Section: Introductionmentioning

confidence: 99%

Risk stratification system and visualized dynamic nomogram constructed for predicting diagnosis and prognosis in rare male breast cancer patients with bone metastases

Gao

et al. 2022

Front. Endocrinol.

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“…The nomogram can make the prediction model simple and visualize the results in a graphical formal, which is widely used clinically in a variety of tumorigenesis and prognosis prediction, including breast cancer [ 29 ], gastric cancer [ 30 ], prostate cancer [ 31 ] and so on. However, most of the current nomograms of CLNM prediction in PTMC patients were established on the basis of postoperative pathological characteristics, and few models were proposed to make predictions about the CLNM preoperatively or intraoperatively [ 8 , 32 ].…”

Section: Discussionmentioning

confidence: 99%

Development of a nomogram for prediction of central lymph node metastasis of papillary thyroid microcarcinoma

Qiu,

Guo,

Pan

et al. 2024

BMC Cancer

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Background Papillary thyroid carcinoma (PTC) is the most frequent malignant tumor in thyroid carcinoma. The aim of this study was to explore the risk factors associated with central lymph node metastasis in papillary thyroid microcarcinoma (PTMC) and establish a nomogram model that can assess the probability of central lymph node metastasis (CLNM). Methods The clinicopathological data of 377 patients with cN0 PTMC were collected and analyzed from The Second Affiliated Hospital of Fujian Medical University from July 1st, 2019 to December 30th, 2021. All patients were examined by underwent ultrasound (US), found without metastasis to central lymph nodes, and diagnosed with PTMC through pathologic examination. All patients received thyroid lobectomy or total thyroidectomy with therapeutic or prophylactic central lymph node dissection (CLND). R software (Version 4.1.0) was employed to conduct a series of statistical analyses and establish the nomogram. Results A total of 119 patients with PTMC had central lymph node metastases (31.56%). After that, age (P < 0.05), gender (P < 0.05), tumor size (P < 0.05), tumor multifocality (P < 0.05), and ultrasound imaging-suggested tumor boundaries (P < 0.05) were identified as the risk factors associated with CLNM. Subsequently, multivariate logistic regression analysis indicated that the area under the receiver operating characteristic (ROC) curve (AUC) of the training cohort was 0.703 and that of the validation cohort was 0.656, demonstrating that the prediction ability of this model is relatively good compared to existing models. The calibration curves indicated a good fit for the nomogram model. Finally, the decision curve analysis (DCA) showed that a probability threshold of 0.15–0.50 could benefit patients clinically. The probability threshold used in DCA captures the relative value the patient places on receiving treatment for the disease, if present, compared to the value of avoiding treatment if the disease is not present. Conclusion CLNM is associated with many risk factors, including age, gender, tumor size, tumor multifocality, and ultrasound imaging-suggested tumor boundaries. The nomogram established in our study has moderate predictive ability for CLNM and can be applied to the clinical management of patients with PTMC. Our findings will provide a better preoperative assessment and treatment strategies for patients with PTMC whether to undergo central lymph node dissection.

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“…In addition, tumor-specific prognostic scores do not provide large amounts of patients as more generalized studies do. However, the relative risk of each specific cancer can be an acceptable surrogate and must be taken under consideration [ 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

The Prediction of Survival after Surgical Management of Bone Metastases of the Extremities—A Comparison of Prognostic Models

et al. 2022

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Individualized survival prognostic models for symptomatic patients with appendicular metastatic bone disease are key to guiding clinical decision-making for the orthopedic surgeon. Several prognostic models have been developed in recent years; however, most orthopedic surgeons have not incorporated these models into routine practice. This is possibly due to uncertainty concerning their accuracy and the lack of comparison publications and recommendations. Our aim was to conduct a review and quality assessment of these models. A computerized literature search in MEDLINE, EMBASE and PubMed up to February 2022 was done, using keywords: “Bone metastasis”, “survival”, “extremity” and “prognosis”. We evaluated each model’s performance, assessing the estimated discriminative power and calibration accuracy for the analyzed patients. We included 11 studies out of the 1779 citations initially retrieved. The 11 studies included seven different models for estimating survival. Among externally validated survival prediction scores, PATHFx 3.0, 2013-SPRING and potentially Optimodel were found to be the best models in terms of performance. Currently, it is still a challenge to recommend any of the models as the standard for predicting survival for these patients. However, some models show better performance status and other quality characteristics. We recommend future, large, multicenter, prospective studies to compare between PATHfx 3.0, SPRING 2013 and OptiModel using the same external validation dataset.

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Construction and Validation of New Nomograms to Predict Risk and Prognostic Factors of Breast Cancer Bone Metastasis in Asian Females: A Population-Based Retrospective Study

Cited by 6 publications

References 35 publications

Risk stratification system and visualized dynamic nomogram constructed for predicting diagnosis and prognosis in rare male breast cancer patients with bone metastases

Risk stratification system and visualized dynamic nomogram constructed for predicting diagnosis and prognosis in rare male breast cancer patients with bone metastases

Development of a nomogram for prediction of central lymph node metastasis of papillary thyroid microcarcinoma

The Prediction of Survival after Surgical Management of Bone Metastases of the Extremities—A Comparison of Prognostic Models

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