A prognostic nomogram for the cancer-specific survival of white patients with invasive melanoma at BANS sites based on the Surveillance, Epidemiology, and End Results database

Huang, Jia-nan; Yu, Hai; Wan, Yang; Ming, Wai-Kit; Situ, Fangmin; Zhu, Leqing; Jiang, Yuzhen; Wu, U. Tim; Huang, WenHsien Ethan; Chen, Wenhui; Lyu, Jun; Deng, Liehua

doi:10.3389/fmed.2023.1167742

Cited by 4 publications

(3 citation statements)

References 42 publications

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“…Among the factors we analyzed, age emerged as signi cant independent risk factors. In view of the high incidence rates of hypothyroidism and heart failure in the elderly 14,15 , there is a reasonable association with higher mortality among patients. Similar correlations have also been observed in other studies 16 .…”

Section: Discussionmentioning

confidence: 99%

Nomogram Model Establishment for Short-Term Survival Prediction in Hypothyroidism Patients with Heart Failure Based on the MIMIC-IV Database

Lou,

Guo,

et al. 2024

Preprint

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The objective of this study was to develop an efficient nomogram model for predicting short-term survival in hypothyroidism patients with heart failure. Methods: Retrospective data was extracted from the Medical Information Mart for Intensive Care (MIMIC-IV) open-source clinical database. Patients diagnosed with hypothyroidism and heart failure upon admission were randomly assigned to the training and testing sets. Independent prognostic factors were determined through univariate and multivariate Cox regression analysis. The correlation between variables was assessed using the variance inflation factor. A nomogram model was constructed based on the identified prognostic factors, and risk scores were generated. The model's performance was assessed using the C-index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Result: A total of 656 hypothyroidism patients with heart failure were included in the study. Age, Sequential Organ Failure Assessment (SOFA) score, blood glucose (Glu), blood urea nitrogen (BUN), creatinine (Cr), respiratory rate (RR), and Charlson Comorbidity Index (CCI) score were identified as independent risk factors for patient mortality and were incorporated into the final model. The C-index for the training and testing sets was 0.763 and 0.721, respectively, indicating good accuracy of the model. Evaluation of the ROC curve, calibration curve, and decision curve further confirmed the model's robust and reliable predictive performance. Conclusion: In conclusion, our study successfully developed a convenient and effective nomogram model for predicting short-term mortality in hypothyroidism patients with heart failure. We identified several independent risk factors, including age, respiratory rate, serum creatinine, blood glucose levels, etc. These findings have implications for developing individualized therapeutic plans, enhancing patient management and follow-up, and ultimately improving disease outcomes.

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Section: Discussionmentioning

confidence: 99%

Nomogram Model Establishment for Short-Term Survival Prediction in Hypothyroidism Patients with Heart Failure Based on the MIMIC-IV Database

Lou,

Guo,

et al. 2024

Preprint

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“…The reason we choose 3-, 5-, and 8-year mortality is due to previous research. Lower limb melanoma survival may have identified these time points as important for assessing long-term outcomes or for making comparisons with other studies [ 25 , 26 ]. Also, in cancer stat facts of melanoma ( https://seer.cancer.gov/statfacts/html/melan.html ) the 5-year survival is 93.5%.…”

Section: Discussionmentioning

confidence: 99%

Deep-learning-based survival prediction of patients with lower limb melanoma

Zhang,

Yu,

Zheng

et al. 2023

Discov Onc

Self Cite

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Background For the purpose to examine lower limb melanoma (LLM) and its long-term survival rate, we used data from the Surveillance, Epidemiology and End Results (SEER) database. To estimate the prognosis of LLM patients and assess its efficacy, we used a powerful deep learning and neural network approach called DeepSurv. Methods We gathered data on those who had an LLM diagnosis between 2000 and 2019 from the SEER database. We divided the people into training and testing cohorts at a 7:3 ratio using a random selection technique. To assess the likelihood that LLM patients would survive, we compared the results of the DeepSurv model with those of the Cox proportional-hazards (CoxPH) model. Calibration curves, the time-dependent area under the receiver operating characteristic curve (AUC), and the concordance index (C-index) were all used to assess how accurate the predictions were. Results In this study, a total of 26,243 LLM patients were enrolled, with 7873 serving as the testing cohort and 18,370 as the training cohort. Significant correlations with age, gender, AJCC stage, chemotherapy status, surgery status, regional lymph node removal and the survival outcomes of LLM patients were found by the CoxPH model. The CoxPH model’s C-index was 0.766, which signifies a good degree of predicted accuracy. Additionally, we created the DeepSurv model using the training cohort data, which had a higher C-index of 0.852. In addition to calculating the 3-, 5-, and 8-year AUC values, the predictive performance of both models was evaluated. The equivalent AUC values for the CoxPH model were 0.795, 0.767, and 0.847, respectively. The DeepSurv model, in comparison, had better AUC values of 0.872, 0.858, and 0.847. In comparison to the CoxPH model, the DeepSurv model demonstrated greater prediction performance for LLM patients, as shown by the AUC values and the calibration curve. Conclusion We created the DeepSurv model using LLM patient data from the SEER database, which performed better than the CoxPH model in predicting the survival time of LLM patients.

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“…However, their prognostic value is still a matter of debate. Some studies correlated older age and male gender with decreased survival [3][4][5], while others found no association [6,7]. The primary location of the melanoma also has debatable prognostic value, but it appears location on the lower limbs is associated with a more favorable outcome [8] in comparison to an acral location [9] or head and neck location [10].…”

Section: Introductionmentioning

confidence: 99%

Prognostic Value of the Width of Invasion in pT3 Cutaneous Melanomas

Țăpoi,

Gheorghișan-Gălățeanu,

Gosman

et al. 2023

IJTM

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Intermediate-thickness melanomas display highly variable outcomes influenced by both clinical and histopathological characteristics. This study investigates several clinicopathological prognostic factors for pT3 cutaneous melanomas, focusing on a novel parameter, the width of invasion. This is a retrospective study of 49 patients diagnosed with cutaneous melanoma between 2012 and 2018 who were followed up for at least five years. We evaluated the age, gender, tumor location, Breslow depth of invasion, width of invasion, mitotic index, the presence/absence of ulceration, regression, microsatellites, lymphovascular invasion, and perineural invasion for their association with disease progression and survival. Cox univariate analysis revealed that progression-free survival (PFS) was significantly associated with age, depth of invasion, width of invasion, lymphovascular invasion, microsatellites, and perineural invasion. Overall survival (OS) was significantly associated with age, depth of invasion, width of invasion, microsatellites, and perineural invasion. Through multivariate Cox proportional hazards regression, the only factor associated with both PFS and OS was the width of the invasion. This is one of the few studies to assess the width of invasion and we have demonstrated that this parameter could become an important prognostic factor for cutaneous melanomas.

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A prognostic nomogram for the cancer-specific survival of white patients with invasive melanoma at BANS sites based on the Surveillance, Epidemiology, and End Results database

Cited by 4 publications

References 42 publications

Nomogram Model Establishment for Short-Term Survival Prediction in Hypothyroidism Patients with Heart Failure Based on the MIMIC-IV Database

Nomogram Model Establishment for Short-Term Survival Prediction in Hypothyroidism Patients with Heart Failure Based on the MIMIC-IV Database

Deep-learning-based survival prediction of patients with lower limb melanoma

Prognostic Value of the Width of Invasion in pT3 Cutaneous Melanomas

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