Thin Melanoma with Nodal Involvement: Analysis of Demographic, Pathologic, and Treatment Factors with Regard to Prognosis.
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ABSTRACT:
SUBMITTER: Karakousis G
PROVIDER: S-EPMC5555768 | biostudies-other | 2017 Apr
REPOSITORIES: biostudies-other
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Project description:ImportanceGiven the evolving patterns of lymph node evaluation for cutaneous melanoma, it is unclear whether the current nodal classification system will continue to accurately reflect prognosis in the modern era. Existing nodal staging for cutaneous melanoma was developed primarily for patients undergoing completion lymph node dissection (CLND) for node-positive disease and does not produce groups with continuously increasing mortality.ObjectiveTo develop and validate a modified nodal classification system for cutaneous melanoma.Design, setting, and participantsThis retrospective cohort analysis included 105 785 patients with cutaneous melanoma undergoing surgery and nodal evaluation from January 1, 2004, to December 31, 2015, in the National Cancer Database. Extent of lymph node dissection was available for patients diagnosed in 2012 and onward. Multivariable models were generated with number of positive lymph nodes modeled using restricted cubic splines. A modified nodal classification system was derived using recursive partitioning analysis (RPA). The proposed lymph node classification system was validated in 85 499 patients from the Surveillance, Epidemiology, and End Results (SEER-18) database. Data were analyzed from April 9, 2020, to May 28, 2021.Main outcomes and measuresOverall survival.ResultsAmong the 105 785 patients included in the analysis (62 496 men [59.1%]; mean [SD] age, 59.9 [15.5] years), number of positive lymph nodes (hazard ratio [HR] per lymph node for 0 to 2 positive lymph nodes, 2.48 [95% CI, 2.37-2-61; P < .001]; HR per lymph node for ≥3 positive lymph nodes, 1.10 [95% CI 1.07-1.13; P < .001]), clinically detected metastases (HR, 1.35; 95% CI, 1.27-1.42; P < .001), and in-transit metastases (HR, 1.48; 95% CI, 1.34-1.65; P < .001) were independently associated with mortality. An RPA-derived system using these variables demonstrated continuously increasing mortality for each proposed lymph node classification group, with HRs of 1.83 (95% CI, 1.76-1.91) for N1a, 2.72 (95% CI, 2.58-2.86) for N1b, 3.79 (95% CI, 3.51-4.08) for N2a, 4.56 (95% CI, 4.22-4.92) for N2b, 6.15 (95% CI, 5.59-6.76) for N3a, and 8.25 (95% CI, 7.64-8.91) for N3b in the proposed system (P < .001). By contrast, the current American Joint Committee on Cancer (AJCC) nodal classification system produced a more haphazard mortality profile, with HRs of 1.83 (95% CI, 1.76-1.91) for N1a, 3.81 (95% CI, 3.53-4.12) for N1b, 2.59 (95% CI, 2.30-2.93) for N1c, 2.71 (95% CI, 2.56-2.87) for N2a, 4.51 (95% CI, 4.17-4.87) for N2b, 3.44 (95% CI, 2.60-4.55) for N2c, 6.06 (95% CI, 5.51-6.67) for N3a, 8.15 (95% CI, 7.54-8.81) for N3b, and 6.90 (95% CI, 5.60-8.49) for N3c. As a sensitivity analysis, the proposed system continued to accurately stratify patients when excluding those undergoing CLND for microscopic lymph node metastases. This system was validated for overall survival and cause-specific mortality in SEER-18. Last, a new overall staging system for node-positive patients was developed by RPA and demonstrated improved concordance vs the AJCC, 8th edition system (C statistic, 0.690 [95% CI, 0.689-0.691] vs 0.666 [95% CI, 0.666-0.668]).Conclusions and relevanceThe findings of this cohort study suggest that a modified nodal classification system can accurately stratify mortality risk in cutaneous melanoma in an era of increasing use of sentinel lymph node biopsy without CLND and should be considered for future staging systems.
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Project description:BackgroundA high percentage of patients with thin melanoma (TM), defined as lesions with Breslow thickness ≤1 mm, presents excellent long-term survival, however, some patients develop metastases. Existing prognostic factors cannot reliably differentiate TM patients at risk for metastases.ObjectiveWe aimed at characterizing the clinical-pathologic and mutation profile of metastatic and not-metastatic TM in order to distinguish lesions at risk of metastases.MethodsClinical-pathologic characteristics were recorded for the TM cases analyzed. We used a Next Generation Sequencing (NGS) multi-gene panel to characterize TM for multiple somatic mutations.ResultsA statistically significant association emerged between the presence of metastases and Breslow thickness ≥0.6 mm (p=0.003). None of TM with lymph-node involvement had Breslow thickness <0.6 mm. Somatic mutations were identified in 19 of 21 TM analyzed (90.5%). No mutations were observed in two not-metastatic cases with the lowest Breslow thickness (≤0.4 mm), whereas mutations in more than one gene were detected in one metastatic case with the highest Breslow thickness (1.00 mm).ConclusionOur study indicates Breslow thickness ≥0.6 mm as a valid prognostic factor to distinguish TM at risk for metastases.
| S-EPMC6114949 | biostudies-literature
Project description:The purpose of this review is to outline recent advancements in diagnosis, treatment, and prevention of pediatric melanoma. Despite the recent decline in incidence, it continues to be the deadliest form of skin cancer in children and adolescents. Pediatric melanoma presents differently from adult melanoma; thus, the traditional asymmetry, border irregularity, color variegation, diameter >6 mm, and evolution (ABCDE) criteria have been modified to include features unique to pediatric melanoma (amelanotic, bleeding/bump, color uniformity, de novo/any diameter, evolution of mole). Surgical and medical management of pediatric melanoma continues to derive guidelines from adult melanoma treatment. However, more drug trials are being conducted to determine the specific impact of drug combinations on pediatric patients. Alongside medical and surgical treatment, prevention is a central component of battling the incidence, as ultraviolet (UV)-related mutations play a central role in the vast majority of pediatric melanoma cases. Aggressive prevention measures targeting sun safety and tanning bed usage have shown positive sun-safety behavior trends, as well as the potential to decrease melanomas that manifest later in life. As research into the field of pediatric melanoma continues to expand, a prevention paradigm needs to continue on a community-wide level.
| S-EPMC5774597 | biostudies-literature
Project description:The presence of lymph node positivity (LN+) guides adjuvant treatment for endometrial adenocarcinoma (EAC) patients, but recommendations regarding LN evaluation at the time of primary surgery remain variable. Sociodemographic factors in addition to pathologic tumor characteristics may more accurately predict risk of LN+ in EAC patients. Patients diagnosed between 2004 and 2016 with pathologic T1-T2 EAC who had at least one lymph node sampled at the time of surgery in the National Cancer Data Base were included. Pathologic primary tumor predictors of LN+ were identified using logistic regression. To predict overall, pelvic only, and paraaortic and/or pelvic LN+, nomograms were generated. Among the 35,170 EAC patients included, 2864 were node positive. Using multivariable analysis, younger patient age (OR 0.98, 95% CI 0.98-0.99, p < 0.001), black versus white race (OR 1.19, 95% CI 1.01-1.40, p = 0.04), increasing pathologic tumor stage and grade, increase in tumor size, and presence of lymphovascular invasion were predictive of regional LN+. Both black versus white (OR 1.64, 95% CI 1.27-2.09, p < 0.001) and other versus white race (OR 1.54, 95% CI 1.12-2.07, p = 0.006) strongly predicted paraaortic LN+ in the multivariable analysis. Independent subset analyses of black and white women revealed that tumor grade was a stronger predictor of LN+ among black women. In addition to standard pathologic tumor features, patient age and race were associated with a higher risk of regional LN+ generally and paraaortic LN+ specifically. This information may inform adjuvant treatment decisions and guide future studies.
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Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication. Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. We previously analyzed the distribution of survival times in these samples and identified more favorable and less favorable groups as patients having time from surgery to death from melanoma greater than 4 years with no sign of relapse (n=25) or less than 1 year (n=22), respectively (Mann et al. 2013, PMID: 22931913). Since that publication, survival data have been re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset. The current survival data are considered to be more accurate. MRNA expression profiling and somatic mutation profiling, were performed as previously described in Mann et al. 2013 (PMID: 22931913).
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| S-EPMC9890291 | biostudies-literature
Project description:Patients with palpable melanoma groin metastases have a poor prognosis. There is debate whether a combined superficial and deep groin dissection (CGD) is necessary or if superficial groin dissection (SGD) alone is sufficient.The aim of this study was to analyze risk factors for deep pelvic nodal involvement in a retrospective, multicenter cohort of palpable groin melanoma metastases. This could aid in the development of an algorithm for selective surgery in the future.This study related to 209 therapeutic CGDs from four tertiary centers in The Netherlands (1992-2013), selected based on complete preoperative imaging and pathology reports. Analyzed risk factors included baseline and primary tumor characteristics, total and positive number of inguinal nodes, inguinal lymph node ratio (LNR) and positive deep pelvic nodes on imaging (computed tomography [CT] ± positron emission tomography [PET], or PET - low-dose CT).Median age was 57 years, 54 % of patients were female, and median follow-up was 21 months (interquartile range [IQR] 11-46 months). Median Breslow thickness was 2.10 mm (IQR 1.40-3.40 mm), and 26 % of all primary melanomas were ulcerated. Positive deep pelvic nodes occurred in 35 % of CGDs. Significantly fewer inguinal nodes were positive in case of negative deep pelvic nodes (median 1 [IQR 1-2] vs. 3 [IQR 1-4] for positive deep pelvic nodes; p < 0.001), and LNR was significantly lower for negative versus positive deep pelvic nodes [median 0.15 (IQR 0.10-0.25) vs. 0.33 (IQR 0.14-0.54); p < 0.001]. A combination of negative imaging, low LNR, low number of positive inguinal nodes, and no extracapsular extension (ECE) could accurately predict the absence of pelvic nodal involvement in 84 % of patients.Patients with negative imaging, few positive inguinal nodes, no ECE, and low LNR have a low risk of positive deep pelvic nodes and may safely undergo SGD alone.
| S-EPMC4686555 | biostudies-literature
Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication. Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. We previously analyzed the distribution of survival times in these samples and identified more favorable and less favorable groups as patients having time from surgery to death from melanoma greater than 4 years with no sign of relapse (n=25) or less than 1 year (n=22), respectively (Mann et al. 2013, PMID: 22931913). Since that publication, survival data have been re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset. The current survival data are considered to be more accurate. MRNA expression profiling and somatic mutation profiling, were performed as previously described in Mann et al. 2013 (PMID: 22931913).
2014-08-18 | E-GEOD-54467 | biostudies-arrayexpress
Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication.
2014-08-18 | GSE54467 | GEO