Survival and Prognostic Nomogram for Primary Gastrointestinal Melanoma (PGIM): A Population-based Study

Badakhshi, Harun; Wang, Zi-Ming; Li, Renjie; Ismail, Mahmoud; Kaul, David

doi:10.21873/anticanres.14850

Cited by 6 publications

(6 citation statements)

References 26 publications

(32 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, adjuvant treatment did not affect the prognosis of PGIM, consistent with other studies. 8 26 However, these findings must be interpreted with caution for the SEER database does not contain information on somatic mutations and specific treatment regimens, hence, it is difficult to perform further subgroup analysis of the data. Radiotherapy has been proposed as a method to achieve local control, 27 but most studies have also failed to identify an improvement in OS by radiotherapy.…”

Section: Discussionmentioning

confidence: 98%

“…The effects of tumour size (tumour thickness) on prognosis are controversial. Some studies showed that this factor was not significantly related to survival, 8 23 24 while others found tumour thickness to be an independent prognostic factor. 6 These conflicting results may be related to different tumour sites and depths of invasion.…”

Section: Discussionmentioning

confidence: 99%

“…Current studies have found that factors related to the prognosis of PGIM included age, lymph node involvement, tumour stage, presence of non-pigmented melanoma and different treatment modalities 7 8. In a study on bladder cancer, the authors put forward the concept of lymph node (LN) density, which provided a rational basis for treatment and the estimation of the prognosis of cancer.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prognostic models based on lymph node density for primary gastrointestinal melanoma: a SEER population-based analysis

Zeng,

Zhu,

Zhou

et al. 2023

BMJ Open

View full text Add to dashboard Cite

ObjectiveThis study aimed to construct prognostic models to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with primary gastrointestinal melanoma (PGIM).DesignAn observational and retrospective study.SettingData were obtained from the Surveillance, Epidemiology and End Results (SEER) programme database, encompassing a broad geographical and demographic spectrum of patients across the USA.ParticipantsA total of 991 patients diagnosed with PGIM were included in this study.MethodsA total of 991 patients with PGIM were selected from the SEER database. They were further divided into a training cohort and a validation cohort. Independent prognostic factors were identified by Cox regression analysis. Two prognostic models were constructed based on the results of multivariable Cox regression analysis. The concordance index (C-index) and area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were used to evaluate the discriminative ability. Calibration curves were plotted to evaluate the agreement between the probability as predicted by the models and the actual probability. Risk stratification was developed given the model.ResultsBy the multivariable Cox regression analysis, we identified four independent risk factors (age, stage, lymph node density and surgery) for OS, and three independent risk factors (stage, lymph node density and surgery) for CSS, which were used to construct prognostic models. C-index, time-dependent AUC, calibration curves and Kaplan-Meier curves of risk stratification indicated that these two models had good discriminative ability, predictive ability as well as clinical value.ConclusionsThe prognostic models of OS and CSS had satisfactory accuracy and were of clinical value in evaluating the prognosis of patients with PGIM.

show abstract

Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prognostic models based on lymph node density for primary gastrointestinal melanoma: a SEER population-based analysis

Zeng,

Zhu,

Zhou

et al. 2023

BMJ Open

View full text Add to dashboard Cite

show abstract

“…Although some studies have mentioned melanoma, no specific studies have been conducted on trunk melanoma due to its small sample size, single source of sample size, or lack of CSD risk factor assessment. So it is necessary to carry out more studies on trunk melanoma (24)(25)(26). In addition, most existing models focus on the outcome of all-cause death.…”

Section: What Is Known and What Is New?mentioning

confidence: 99%

Establishment and validation of a nomogram for predicting immune-related prognostic features in trunk melanoma-specific death

Chu¹,

Hu²,

Li³

et al. 2022

Ann Transl Med

View full text Add to dashboard Cite

Background: Trunk melanoma is one of the most common and deadly types of melanomas. Multiple factors are associated with the prognosis of patients with trunk melanoma. Currently, direct, and reliable clinical tools for early assessment of individual specific risk of death are limited, and most of them are prediction models for all-cause death. Their accuracy in predicting competitiveness events, which make up a relatively large portion, may be substantially compromised. Hence, we conducted this study to investigate the risk factors of trunk melanoma-specific death to establish a comprehensive prediction model suitable for clinical application.Methods: Patients with trunk melanoma analyzed in this study were from the SEER program [2010][2011][2012][2013][2014][2015].The random sampling method was used to split the included cases into the training and validation cohorts at a ratio of 7:3. Univariate and multivariate competing risk models were used to screen the independent influencing factors of specific death, and then a nomogram covering these independent predictors was constructed. The concordance index (C-index) and a calibration curve were used to evaluate the calibration degree and accuracy of the nomogram. Results:We identified 21,198 patients with trunk melanoma from the SEER database, and 3,814 of them died (17.99%). Among the death cases, deaths from other causes accounted for 66.50%The prognostic nomogram included 8 variables and 16 independent influencing factors. The overall C-index in the training set was 0.89, and the receiver operating characteristic (ROC) curve for predicting 1-, 3-, and 5-year survival was 0.928 [95% confidence interval (CI): 0.911-0.945], 0.907 (95% CI: 0.895-0.918), and 0.891 (95% CI: 0.879-0.902), respectively. The C-index of the model in the validation set was 0.89, and the area under the ROC curve (AUC) for predicting 1-, 3-, and 5-year cancer-specific death (CSD) was 0.927 (95% CI: 0.899-0.955), 0.916 (95% CI: 0.901-0.930), and 0.905 (95% CI: 0.899-0.921). Both the training set and the validation set showed the ideal calibration degree.Conclusions: This model can be used as a potential tool for prognostic risk management of trunk melanoma in the presence of many competing events.

show abstract

“…[12] At present, various nomograms related to melanoma have been published in the literature, such as gastrointestinal melanoma, vulvar melanoma, skin nodular melanoma, etc., but no nomograms specifically designed for SSM have been reported. [13][14][15] Therefore, we used relevant data from the surveillance, epidemiology and end results (SEER) database to build an SSM nomogram to assess patient prognosis.…”

Section: Introductionmentioning

confidence: 99%

Prognostic model for predicting overall and cancer-specific survival among patients with superficial spreading melanoma: A SEER based study

Tang

et al. 2022

Medicine

View full text Add to dashboard Cite

Skin malignant melanoma is one of the most aggressive skin tumors. Superficial spreading melanoma (SSM) is the most common histological type, which can originate from different body skin sites, and some patients can still accumulate regional lymph nodes and even have distant metastasis in some cases. This study used the relevant data from the monitoring, epidemiology and results database of the National Cancer Institute database to study the overall survival (OS) and cancer-specific survival (CSS) of SSM patients and established an SSM nomogram to evaluate the prognosis of patients. A total of 13,922 patients were collected from the monitoring, epidemiology and results database of the National Cancer Institute and randomly divided into a training cohort (8353 cases) and a validation cohort (5569 cases). Univariate and multivariate Cox regression analysis were used to determine prognostic factors, and these factors were used to construct OS and CSS nomograms for patients with SSM. Finally, the discrimination and consistency of the nomogram model were evaluated by the consistency index (C-index), area under the curve (AUC) and calibration curve. Multivariate Cox regression analysis suggested that age, sex, tumor site, the American joint committee on cancer T stage and the first primary melanoma were independent predictors of OS and CSS in patients with SSM and that the American joint committee on cancer N stage was also an independent predictor of CSS in patients with SSM. Based on the above prognostic factors, this study constructed a predictive model. The C -index of the model OS and CSS for this training cohort was 0.805 [95% CI: 0.793–0.817] and 0.896 [95% CI: 0.878–0.913], respectively. The AUC values for 1-, 3-, and 5-year OS were 0.822, 0.820, and 0.821, respectively, and the AUC values for CSS were 0.914, 0.922, and 0.893, respectively. The data indicated that both nomograms showed better predictive accuracy. The calibration curves of the training cohort and the validation cohort were in good agreement. The nomogram has superior predictive performance in predicting 1-, 3-, and 5-year OS and CSS prognosis in patients with SSM and can provide a reference for individualized treatment and clinical counseling of SSM.

show abstract

Survival and Prognostic Nomogram for Primary Gastrointestinal Melanoma (PGIM): A Population-based Study

Cited by 6 publications

References 26 publications

Prognostic models based on lymph node density for primary gastrointestinal melanoma: a SEER population-based analysis

Prognostic models based on lymph node density for primary gastrointestinal melanoma: a SEER population-based analysis

Establishment and validation of a nomogram for predicting immune-related prognostic features in trunk melanoma-specific death

Prognostic model for predicting overall and cancer-specific survival among patients with superficial spreading melanoma: A SEER based study

Contact Info

Product

Resources

About