Dataset Information

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders.

ABSTRACT:

Purpose

Cutaneous malignant melanoma (CMM) always presents as a complex disease process with poor prognosis. The objective of the present study was to explore the influence of solitary or multiple cancers on the prognosis of patients with CMM to better understand the landscape of CMM.

Methods

We reviewed the records of CMM patients between 2004 and 2015 from the Surveillance, Epidemiology, and End Results Program. The cumulative incidence function was used to represent the probabilities of death. A novel causal inference method was leveraged to explore the risk difference to death between different types of CMM, and nomograms were built based on competing risk models.

Results

The analysis cohort contained 165,043 patients with CMM as the first primary malignancy. Patients with recurrent CMM and multiple primary tumors had similar overall survival status (p = 0.064), while their demographics and cause-specific death demonstrated different characteristics than those of patients with solitary CMM (p < 0.001), whose mean survival times are 75.4 and 77.3 months and 66.2 months, respectively. Causal inference was further applied to unveil the risk difference of solitary and multiple tumors in subgroups, which was significantly different from the total population (p < 0.05), and vulnerable groups with high risk of death were identified. The established competing risk nomograms had a concordance index >0.6 on predicting the probabilities of death of CMM or other cancers individually across types of CMM.

Conclusion

Patients with different types of CMM had different prognostic characteristics and different risk of cause-specific death. The results of this study are of great significance in identifying the high risk of cause-specific death, enabling targeted intervention in the early period at both the population and individual levels.

SUBMITTER: Li Z

PROVIDER: S-EPMC9198425 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders.

Li Zichao Z Li Xinrui X Yi Xiaowei X Li Tian T Huang Xingning X Ren Xiaoya X Ma Tianyuan T Li Kun K Guo Hanfeng H Chen Shengxiu S Ma Yao Y Shang Lei L Song Baoqiang B Hu Dahai D

Frontiers in oncology 20220601

<h4>Purpose</h4>Cutaneous malignant melanoma (CMM) always presents as a complex disease process with poor prognosis. The objective of the present study was to explore the influence of solitary or multiple cancers on the prognosis of patients with CMM to better understand the landscape of CMM.<h4>Methods</h4>We reviewed the records of CMM patients between 2004 and 2015 from the Surveillance, Epidemiology, and End Results Program. The cumulative incidence function was used to represent the probabi ...[more]

PMID: 35719966

Similar Datasets

Project description:Perturbations in microRNA (miRNA) expression profiles has been reported for cutaneous malignant melanoma (CMM). With regards to a rapidly growing number of newly discovered miRNA sequences, the availability of up-to-date miRNA expression profiles for primary cutaneous malignant melanoma (PCMM), cutaneous malignant melanoma metastases (CMMM) and benign melanocytic naevi (BMN) is limited. Patients with PCMM (n=9), CMMM (n=4) and BMN (n=8) were included in the study. Specimens were obtained during surgery from the center of the tumors (lesional). An exploratory microarray analysis was performed by miRNA expression profiling based on miRBase V.16. Additionally, the expression levels of selected miRNA candidates were confirmed by TaqMan real-time quantitative polymerase chain reaction (RT-PCR). New miRNA candidates previously not described to be associated with CMM were found to be potentially dysregulated in CMM. Nine patients with PCMM (PCMM1-PCMM9), four patients with CMMM (CMMM1-CMMM4) and eight patients with BMN (BMN1-BMN8) were enrolled in the present study. All cutaneous specimens were harvested in the operating room, immediately stored in RNAlater (Quiagen, Hilden, Germany) and kept at - 80 °C until RNA isolation. Total RNA including miRNAs was isolated using the miRNeasy Mini Kit (Quiagen, Hilden, Germany) according to the manufacturer’s protocol. RNA concentration and purity was determined by NanoDrop ND-1000 spectral photometer (Peqlab, Erlangen, Germany). RNA integrity control (RIN) was determined by means of capillary electrophoresis with the 2100 Bioanalyzer and the RNA 6000 NanoLabCHip Kits (both Agilent Technologies, Santa Clara, USA). To be further considered for Microarray analysis a RIN ≥ 7.0 indicating medium to good RNA quality was defined as inclusion criteria. For assessment of labeling and hybridization efficiencies total RNA samples were spiked with in-vitro synthesized oligonucleotides by using the MicroRNA Spike-In Kit (Agilent Technologies, Santa Clara, USA). A total of 100 ng total RNA per sample were introduced into a labeling reaction. The spiked total RNA was treated with alkaline calf intestine phosphatase (CIP). The dephosphorylated RNA was labeled with the miRNA Complete Labeling and Hyb Kit (Agilent Technologies, Santa Clara, USA) according to the manufacturer´s instructions using T4 RNA ligase, incorporating Cyanine 3-Cytidine biphosphate (pCp). The Cyanine-3-labeled miRNA samples were prepared for One-Color based hybridization with Complete miRNA Labeling and Hyb Kit (Agilent Technologies, Santa Clara, USA) according to the manufacturer´s instructions. Labeled miRNA samples were hybridized at 55°C for 20 hrs on separate Human miRNA Microarrays Release 16.0 (8x60K format, (Agilent Technologies, Santa Clara, USA). Afterwards, microarrays were washed with increasing stringency using Gene Expression Wash Buffers (Agilent Technologies, Santa Clara, USA) followed by drying with acetonitrile (Sigma-Aldich, St.Louis, USA). Fluorescent signal intensities were detected with Scan Control A.8.4.1 Software (Agilent Technologies, Santa Clara, USA) on the Agilent DNA Microarray Scanner and extracted from the images using Feature Extraction 10.7.3.1 Software (Agilent Technologies, Santa Clara, USA). All the steps described were carried out according to the manufacturer´s instructions.

Dataset Information

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders.

Purpose

Methods

Results

Conclusion

Publications

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders.

Similar Datasets

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