Nomogram for predicting the survival of patients with malignant melanoma: A population analysis

Yang, Jin; Pan, Zhenyu; Zhou, Quan; Liu, Qingqing; Zhao, Fanfan; Xue, Feng; Lyu, Jun

doi:10.3892/ol.2019.10720

Cited by 19 publications

(15 citation statements)

References 37 publications

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“…Nomogram has become a reliable and convenient tool in cancer prognosis predictions (11,12). Several prognostic nomograms have been established for predicting the prognosis of melanoma in recent years (13)(14)(15), while global expression pattern based on MRGs has not previously been recognized in melanoma. In this study, we aimed to develop and validate a novel prognostic nomogram based on MRGs signature and clinicopathological factors for ideally predicting the prognosis of melanoma patients.…”

Section: Introductionmentioning

confidence: 99%

Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma

Zeng

Peng

et al. 2020

Front. Oncol.

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Metabolic reprogramming is closely related to melanoma. However, the prognostic role of metabolism-related genes (MRGs) remains to be elucidated. We aimed to establish a nomogram by combining MRGs signature and clinicopathological factors to predict melanoma prognosis. Eighteen prognostic MRGs between melanoma and normal samples were identified using The Cancer Genome Atlas (TCGA) and GSE15605. WARS (HR = 0.881, 95% CI = 0.788-0.984, P = 0.025) and MGST1 (HR = 1.124, 95% CI = 1.007-1.255, P = 0.037) were ultimately identified as independent prognostic MRGs with LASSO regression and multivariate Cox regression. The MRGs signature was established according to these two genes and externally validated in the Gene Expression Omnibus (GEO) dataset. Kaplan-Meier survival analysis indicated that patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group. Furthermore, the MRGs signature was identified as an independent prognostic factor for melanoma survival. An MRGs nomogram based on the MRGs signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Calibration plots showed good consistency between the prediction of nomogram and actual observation. The receiver operating characteristic curve and decision curve analysis indicated that MRGs nomogram had better OS prediction and clinical net benefit than the stage system. To our knowledge, we are the first to develop a prognostic nomogram based on MRGs signature with better predictive power than the current staging system, which could assist individualized prognosis prediction and improve treatment.

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Section: Introductionmentioning

confidence: 99%

Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma

Zeng

Peng

et al. 2020

Front. Oncol.

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“…In recent years, the nomogram has been widely used as a predictive approach across the majority of cancer types ( 20 , 21 ), primarily owing to its ability to meet requirements for an integrated model ( 22 ). The practices of prognosis and risk prediction of diseases via web have contributed to their popularity among clinicians and patients themselves ( 22 , 23 ).…”

Section: Introductionmentioning

confidence: 99%

Development of a Risk Nomogram Model for Identifying Interstitial Lung Disease in Patients With Rheumatoid Arthritis

Xue

et al. 2022

Front. Immunol.

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The clinical features of rheumatoid arthritis (RA)-associated interstitial lung disease (ILD) (RA-ILD) usually manifest to an advanced stage of lung disease, which leads the challenge of early diagnosis and the difficulty in guiding treatments for patients with RA-ILD in clinical settings. The aim of this study was to construct a nomogram for identifying ILD in RA patients. Through the incorporation of the level of matrix metalloproteinase-3 (MMP-3) in plasma, demographics, clinical feature, and laboratory parameters of 223 RA patients (85 RA-ILD) which were grouped as training cohorts and validation cohorts, an identifying nomogram of RA-ILD was built. Candidate variables for the nomogram were screened using univariable analysis and multivariable logistic regression analysis. The accuracy of the diagnostic nomogram was measured via concordance index (C-index), calibration plots, and decision curve analysis (DCA). Results showed that plasma MMP-3 protein was elevated in RA-ILD patients compared with non-ILD RA patients in both training cohorts (p = 0.0475) and validation cohorts (p = 0.0006). Following a final regression analysis, the gender of male, current smoking state, levels of circulating rheumatoid factor (RF), C-reactive protein (CRP), and MMP-3 were identified as risk factors for the construction of the nomogram. The calibration plots further showed a favorable consistency between the identifying nomogram and actual clinical findings. In consistence, the C-index (0.826 for both training cohorts and validation cohorts) indicated the satisfactory discriminative ability of the nomogram. Although the incorporation of MMP-3 failed to significantly improve identified outcomes of the nomogram as determined by DCA, including the level of circulating MMP-3 increased the diagnostic accuracy of the nomogram for ILD in RA patients. Thus, our proposed model can serve as a non-invasive tool to identify ILD in RA patients, which may assist physicians to make treatment decisions for RA patients.

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“…A nomogram integrating multiple prognostic factors can be used to estimate the probability of a particular result. Useful in individualized medicine, it has been applied to a wide range of malignancies [ 8 , 9 ], For patients with rectal cancer, a number of nomograms have been developed to date. However, nomograms for stage II/III rectal cancer patients treated with NCRT followed by surgical resection have rarely been reported.…”

Section: Introductionmentioning

confidence: 99%

A prognostic nomogram for stage II/III rectal cancer patients treated with neoadjuvant chemoradiotherapy followed by surgical resection

Lin

2022

BMC Surg

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Background The purpose of this study was to develop a large population-based nomogram incorporating the log odds of positive nodes (LODDS) for predicting the overall survival (OS) of stage II/III rectal cancer patients treated with neoadjuvant chemoradiotherapy (NCRT) followed by surgical resection. Methods The Surveillance, Epidemiology, and End Results database was used to collect information on patients diagnosed with stage II/III rectal cancer between 2010 and 2015 and treated with NCRT followed by surgical resection. The Cox regression analyses were performed to determine the independent prognostic factors. In this study, LODDS was employed instead of American Joint Committee on Cancer (AJCC) 7th N stage to determine lymph node status. Then a nomogram integrating independent prognostic factors was developed to predict the 24-, 36-, and 60-month overall survival. The receiver operating characteristic (ROC) curves and calibration curves were used to validate the nomogram. Furthermore, patients were stratified into three risk groups (high-, middle-, and low-risk) based on the total points obtained from the nomogram. And Kaplan–Meier curves were plotted to compare the OS of the three groups. Results A total of 3829 patients were included in the study. Race, sex, age, marital status, T stage, tumor grade, tumor size, LODDS, CEA level, and postoperative chemotherapy were identified as independent prognostic factors, based on which the prognostic nomogram was developed. The area under curve values of the nomogram for the 24-, 36-, and 60-month OS in the training cohort were 0.736, 0.720, and 0.688, respectively; and 0.691, 0.696, and 0.694 in the validation cohort, respectively. In both the validation and training cohorts, the calibration curves showed a high degree of consistency between actual and nomogram-predicted survival rates. The Kaplan–Meier curves showed that the three risk groups had significant differences in overall survival (P < 0.001). Conclusion A large population-based nomogram incorporating LODDS was developed to assist in evaluating the prognosis of stage II/III rectal cancer patients treated with NCRT followed by surgical resection. The nomogram showed a satisfactorily discriminative and stable ability to predict the OS for those patients.

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Nomogram for predicting the survival of patients with malignant melanoma: A population analysis

Cited by 19 publications

References 37 publications

Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma

Prognostic Implications of Metabolism Related Gene Signature in Cutaneous Melanoma

Development of a Risk Nomogram Model for Identifying Interstitial Lung Disease in Patients With Rheumatoid Arthritis

A prognostic nomogram for stage II/III rectal cancer patients treated with neoadjuvant chemoradiotherapy followed by surgical resection

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