Factors Affecting Sentinel Node Metastasis in Thin (T1) Cutaneous Melanomas: Development and External Validation of a Predictive Nomogram

Maurichi, Andrea; Miceli, Rosalba; Eriksson, Hanna; Newton-Bishop, Julia; Nsengimana, Jérémie; Chan, May P.; Hayes, Andrew; Heelan, Kara; Adams, David J.; Patuzzo, Roberto; Barretta, Francesco; Gallino, Gianfrancesco; Harwood, Catherine A.; Bergamaschi, Daniele; Bennett, Dorothy C.; Lasithiotakis, Konstantinos; Ghiorzo, Paola; Dalmasso, Bruna; Manganoni, Ausilia Maria; Consoli, Francesca; Mattavelli, Ilaria; Barbieri, Consuelo; Leva, Andrea; Cortinovis, Umberto; Espeli, Vittoria; Mangas, Cristina; Quaglino, Pietro; Ribero, Simone; Broganelli, Paolo; Pellacani, Giovanni; Longo, Caterina; Forno, C. Del; Borgognoni, Lorenzo; Sestini, Serena; Pimpinelli, Nicola; Fortunato, Sara; Chiarugi, Alessandra; Nardini, Paolo; Morittu, Elena; Florita, Antonio; Cossa, Mara; Valeri, Barbara; Milione, Massimo; Pruneri, Giancarlo; Zoras, Odysseas; Anichini, Andrea; Mortarini, Roberta; Santinami, Mario

doi:10.1200/jco.19.01902

Cited by 55 publications

(46 citation statements)

References 22 publications

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“…Currently, the prognostic value of nomograms has been identified in various cancer types [ 6 – 8 ]. Adopting nomograms for predicting prognosis and clinical decision-making has compared favorably to the classical staging systems in different cancers [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a survival nomogram for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction based on real-world data

Chen

Xia

et al. 2021

BMC Cancer

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Background The clinical staging systems for adenocarcinoma of the esophagogastric junction (AEG) are controversial. We aimed to propose a prognostic nomogram based on real-world data for predicting survival of Siewert type II/III AEG patients after surgery. Methods A total of 396 patients with Siewert type II/III AEG diagnosed and treated at the Center for Gastrointestinal Surgery, the First Affiliated Hospital, Sun Yat-sen University, from June 2009 to June 2017 were enrolled. The original data of 29 variables were exported from the electronic medical records system. The nomogram was established based on multivariate Cox regression coefficients, and its performance was measured using Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve analysis and calibration curve. Results A nomogram was constructed based on nine variables. The C-index for overall survival (OS) prediction was 0.76 (95% CI, 0.72 to 0.80) in the training cohort, in the validation-1 cohort was 0.79 (95% CI, 0.72 to 0.86), and 0.73 (95% CI, 0.67 to 0.80) in the validation-2 cohort. Time-dependent ROC curves and calibration curves in all three cohorts showed good prognostic predictive accuracy. We further proved the superiority of the nomogram in predictive accuracy for OS to pathological TNM (pTNM) staging system and other independent prognostic factors. Kaplan-Meier survival curves demonstrated the pTNM stage, grade of differentiation, positive lymph node, log odds of positive lymph node and organ invasion were prognostic factors with good discriminative ability. Conclusion The established nomogram demonstrated a more precise prognostic prediction for patients with Siewert type II/III AEG.

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Section: Introductionmentioning

confidence: 99%

Development and validation of a survival nomogram for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction based on real-world data

Chen

Xia

et al. 2021

BMC Cancer

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“…The nomogram is prediction, so the decision curve analysis method (DCA) is to solve the clinical utility problem and solve the clinical practicality of the nomogram. Now it is also widely used in various fields, such as predicting the prognosis of lung cancer [33], sentinel lymph node metastasis of skin melanoma [34], The prognosis of left atrial enlargement in degenerative mitral regurgitation [35]. In this study, after adding the risk score signature, patients benefited more from 1-, 2-, 3-years.…”

Section: Discussionmentioning

confidence: 87%

Identification and Validation of Autophaggen-based Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

Jiang¹,

Xu²,

Zhao³

et al. 2020

Preprint

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Cervical cancer is a common malignancy in women and has a poor prognosis.More and more studies have shown that autophagy disorder is closely related to the occurrence of tumors. However, the prognostic role of autophagy gene in cervical cancer is still unclear. In this study, we constructed the risk signatures of autophagy related genes to predict the prognosis of cervical cancer. The expression profiles and clinical information of autophagy gene sets were downloaded from the TCGA and GES52903 queues as training sets and validation sets. The cervical normal tissue expression profile data from UCSC XENA website is GTEx data as a supplement to TCGA normal cervical tissue. Univariate COX regression analysis of 17 different autophagy genes with the Consensus approach tumor samples from the TCGA is divided into six subtypes, and the clinical traits in the six subtypes have different distribution, with further then absolute shrinkage and selection operator (LASSO) and multiariable COX regression method finally got seven autophagy genetic risk model is constructed, in the training set, the survival rate of high risk group is lower than the low risk group (p < 0.0001), the validation set,The AUC area of the receiver operating characteristic (ROC) curve, the training set is 0.894, and the verification set is 0.736. We find that the high and low risk score is closely related to the TMN stage (All P is less than 0.05).The nomogram shows that the risk score combined with other indicators such as age, G,T,M, and N better predicts 1-year, 2-year, 3-year survival, and the DCA curve shows that the risk model combined with other indicators produces better clinical efficacy.Then immune cells in 28 in the enrichment score, there were statistically significant differences, high and low risk most GSEA enrichment analysis, the main enrichment in G2 / M checkpoint high-risk score, Genes defining epithelial and mesenchymal transition, raised in response to the low oxygen levels (hypoxia) gene, gene is important to the mitotic spindle assembly, these are closely related with the occurrence of tumor . In conclusion, our constructed autophagy risk signature may be a prognostic tool for cervical cancer.

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“…A nomogram uses clinical, pathological, or other features to establish a statistical predictive model that can provide the possibility of a certain clinical event. [13][14][15] In this pioneering study, we incorporated age, clinical symptoms, the assumption that all patients have symptomatic deterioration. Black lines represent the hypothesis that no patients have symptomatic deterioration.…”

Section: Discussionmentioning

confidence: 99%

Individualized model for predicting COVID‐19 deterioration in patients with cancer: A multicenter retrospective study

Song

Yao

et al. 2021

Cancer Science

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Factors Affecting Sentinel Node Metastasis in Thin (T1) Cutaneous Melanomas: Development and External Validation of a Predictive Nomogram

Cited by 55 publications

References 22 publications

Development and validation of a survival nomogram for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction based on real-world data

Development and validation of a survival nomogram for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction based on real-world data

Identification and Validation of Autophaggen-based Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

Individualized model for predicting COVID‐19 deterioration in patients with cancer: A multicenter retrospective study

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