Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

Ding, Yuxin; Jiang, Runyi; Chen, Yuhong; Jing, Jing; Yang, Xiaoshuang; Wu, Xianjie; Zhang, Xiaoyang; Xu, Jiali; Xu, Piaopiao; LiuHuang, Shu Chen; Zhang, Lu

doi:10.1186/s12885-021-08105-y

Cited by 22 publications

(22 citation statements)

References 44 publications

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“…A study on 70 605 primary invasive melanomas from the Surveillance, Epidemiology and End Results (SEER) database found that head and neck melanoma made up 21.3% of cases compared with body melanoma and contained older patients (mean age 64.6 vs. 57) 16 . This contrasts with the current study, in which the head and neck melanoma cohort made up only 14.0% of primary invasive melanomas.…”

Section: Discussioncontrasting

confidence: 98%

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Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database

et al. 2021

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Background and Objective: Most melanomas (including melanomas in situ), in Australasia, are treated by general practitioners (GPs). Previously undescribed, the characteristics of a series of melanomas treated by multiple GPs are examined.Patients and Methods: Six hundred and thirtyseven melanomas treated by 27 Australasian GPs during 2013 and documented on the Skin Cancer Audit Research Database (SCARD) were analysed by anatomical site, subtype, Breslow thickness, diameter, associated naevi and linked adverse outcomes.Results: Most melanomas (59.7%) were on males, mean age at diagnosis being 62.7 years (range 18-96). Most (65.0%) were in situ, with a high incidence of lentiginous melanoma (LM) (38.8%) and 32% were naevus associated. Most LM (86.4%) were in situ, compared to 55% of superficial spreading melanoma (SSM) (P < 0.0001). There was male predominance on the head, neck and trunk and female predominance on extremities. There was no significant association between Breslow thickness and diameter, with small melanomas as likely to be thick as large melanomas, and melanomas ≤3 mm diameter, on average, more likely to be invasive than larger melanomas. There was a positive correlation between age and both melanoma diameter and Breslow thickness. Seven cases progressed to melanomaspecific death: Five nodular melanoma (NM) and two SSM, one of which was thin (Breslow thickness 0.5 mm).Conclusions: A large series of melanomas treated by Australasian GPs were predominantly in situ, with a high proportion of LM subtype. With implications for GP training, NM linked to death was overrepresented and there was a novel finding that older patients had larger diameter melanomas.

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Section: Discussioncontrasting

confidence: 98%

“…Nodular melanoma cause a disproportionate number of deaths 11 and thin melanomas can also lead to death 16 . Consistent with this, in the current study, five NM and two SSM, one with a Breslow thickness of 0.5 mm and a diameter of 10 mm, were directly linked to patient death.…”

Section: Discussionsupporting

confidence: 87%

Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database

et al. 2021

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“…However, head and neck melanoma showed the greatest improvement in survival rate and the best ICIs efficacy between the two eras. This contradictory result may be explained by the following reasons: According to epidemiological surveys, head and neck melanoma has a worse prognosis than CM from other body areas ( 29 , 30 ). Head and neck have rich vascularization and lymphatic drainage, melanoma is prone to metastases and even more likely to develop brain metastases ( 31 , 32 ).…”

Section: Discussionmentioning

confidence: 99%

Gradient differences of immunotherapy efficacy in metastatic melanoma related to sunlight exposure pattern: A population-based study

Liu

et al. 2023

Front. Oncol.

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BackgroundImmune checkpoint inhibitors (ICIs) have revolutionized metastatic melanoma (MM) treatment in just a few years. Ultraviolet (UV) in sunlight is the most significant environmental cause of melanoma, which is considered to be the main reason for tumor mutation burden (TMB) increase in melanoma. High TMB usually predicts that PD-1 inhibitors are effective. The sunlight exposure pattern of MM might be a clinical feature that matches TMB. The relationship between sunlight exposure patterns and immunotherapy response in MM is unclear. This study aims to investigate the correlation between sunlight exposure patterns and immunotherapy response in MM and establish nomograms that predict 3- and 5-year overall survival (OS) rate.MethodsWe searched the Surveillance, Epidemiology, and End Results (SEER) database and enrolled MM cases from 2005-2016. According to the advent of ICIs in 2011, the era was divided into the non-ICIs era (2005-2010) and the ICIs era (2011-2016). Patients were divided into three cohorts according to the primary site sunlight exposure patterns: head and neck in the first cohort, trunk arms and legs in the second cohort, and acral sites in the third cohort. We compared survival differences for each cohort between the two eras, performed stratified analysis, established nomograms for predicting 3- and 5-year OS rate, and performed internal validation.ResultsComparing the survival difference between the ICIs and non-ICIs era, head and neck melanoma showed the greatest improvement in survival, with 3- and 5-year OS rate increasing by 10.2% and 9.1%, respectively (P=0.00011). In trunk arms and legs melanoma, the 3- and 5-year OS rate increased by 4.6% and 3.9%, respectively (P<0.0001). There is no improvement in survival in acral melanoma (AM) between the two eras (P=0.78). The receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) and calibration graphs show good discrimination and accuracy of nomograms. Decision curve analysis (DCA) suggests good clinical utility of nomograms.ConclusionsBased on the classification of sunlight exposure patterns, there is a gradient difference in immunotherapy efficacy for MM. The degree of sunlight exposure is positively correlated with immunotherapy response. The nomograms are sufficiently accurate to predict 3- and 5-year OS rate for MM, allowing for individualized clinical decisions for future clinical work.

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“…(c) The following methods were used to construct and verify the prediction model, including multiple fractional multivariate models (MFP model), full model, stepwise selected model (stepwise model), bootstrap full (bootstrap resampling 500 times), and bootstrap stepwise (bootstrap resampling 500 Times). (d) The corresponding nomogram was constructed based on the best model described above, and then we used the “DynNom” package to construct a corresponding online dynamic nomogram ( 15 ). (e) The missing value of variables included in our study was very few, so there was no special handling of the missing values during model building.…”

Section: Methodsmentioning

confidence: 99%

Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission

Wang

et al. 2021

Front. Med.

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Introduction: COVID-19 has overloaded worldwide medical facilities, leaving some potentially high-risk patients trapped in outpatient clinics without sufficient treatment. However, there is still a lack of a simple and effective tool to identify these patients early.Methods: A retrospective cohort study was conducted to develop an early warning model for predicting the death risk of COVID-19. Seventy-five percent of the cases were used to construct the prediction model, and the remaining 25% were used to verify the prediction model based on data immediately available on admission.Results: From March 1, 2020, to April 16, 2020, a total of 4,711 COVID-19 patients were included in our study. The average age was 63.37 ± 16.70 years, of which 1,148 (24.37%) died. Finally, age, SpO2, body temperature (T), and mean arterial pressure (MAP) were selected for constructing the model by univariate analysis, multivariate analysis, and a review of the literature. We used five common methods for constructing the model and finally found that the full model had the best specificity and higher accuracy. The area under the ROC curve (AUC), specificity, sensitivity, and accuracy of full model in train cohort were, respectively, 0.798 (0.779, 0.816), 0.804, 0.656, and 0.768, and in the validation cohort were, respectively, 0.783 (0.751, 0.815), 0.800, 0.616, and 0.755. Visualization tools of the prediction model included a nomogram and an online dynamic nomogram (https://wanghai.shinyapps.io/dynnomapp/).Conclusion: We developed a prediction model that might aid in the early identification of COVID-19 patients with a high probability of mortality on admission. However, further research is required to determine whether this tool can be applied for outpatient or home-based COVID-19 patients.

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Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

Cited by 22 publications

References 44 publications

Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database

Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database

Gradient differences of immunotherapy efficacy in metastatic melanoma related to sunlight exposure pattern: A population-based study

Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission

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