Dataset Information

Increased CYFRA 21-1, CEA and NSE are Prognostic of Poor Outcome for Locally Advanced Squamous Cell Carcinoma in Lung: A Nomogram and Recursive Partitioning Risk Stratification Analysis.

ABSTRACT:

Objectives

This study aimed to: (1) assess the prognostic significance of serum tumor markers in locally advanced squamous cell carcinoma in lung (LA-SCCL); (2) generate a nomogram to predict the overall survival (OS) and (3) identify a prognostic stratification to assist the therapeutic decision-making.

Methods

LA-SCCL patients receiving definitive radiotherapy and baseline tumor marker measurement were eligible for this retrospective study. Cox proportional hazards regression was used to determine independent factors associated with various survival indexes and a nomogram was created to estimate the 5-year OS probability for individual patient. The identified prognostic factors were recruited into a recursive partitioning analysis (RPA) for OS to stratify patients with distinct outcome.

Results

A total of 224 patients were eligible for analysis. Increased cytokeratin-19 fragment (CYFRA 21-1) was independently associated with inferior OS, progression free survival (PFS) and a borderline decreased local-regional progression free survival (LRPFS). Elevated carcino-embryonic antigen (CEA) served as an unfavorable determinant for OS and increased neuron-specific enolase (NSE) was predictive of poor distant metastasis free survival (DMFS). A nomogram integrating KPS, TNM stage, CEA and CYFRA 21-1 was created, resulting in a c-index of 0.62. RPA identified 4 prognostic classifications, with median OS of 27.6, 19.9, 17.3 and 10.9?months for low, intermediate, high and very-high risk groups, respectively.

Conclusions

Baseline tumor marker panel including CYFRA 21-1, CEA and NSE can be prognostic of outcome for LA-SCCL receiving definitive radiotherapy. The RPA identified four prognostic subgroups, which could assist personalized therapy and clinical trial design in LA-SCCL.

SUBMITTER: Wang J

PROVIDER: S-EPMC6040260 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Increased CYFRA 21-1, CEA and NSE are Prognostic of Poor Outcome for Locally Advanced Squamous Cell Carcinoma in Lung: A Nomogram and Recursive Partitioning Risk Stratification Analysis.

Wang Jingbo J Jiang Wei W Zhang Tao T Liu Lipin L Bi Nan N Wang Xiaozhen X Hui Zhouguang Z Liang Jun J Lv Jima J Zhou Zongmei Z Xiao Zefen Z Feng Qinfu Q Chen Dongfu D Yin Weibo W Wang Luhua L

Translational oncology 20180627 4

<h4>Objectives</h4>This study aimed to: (1) assess the prognostic significance of serum tumor markers in locally advanced squamous cell carcinoma in lung (LA-SCCL); (2) generate a nomogram to predict the overall survival (OS) and (3) identify a prognostic stratification to assist the therapeutic decision-making.<h4>Methods</h4>LA-SCCL patients receiving definitive radiotherapy and baseline tumor marker measurement were eligible for this retrospective study. Cox proportional hazards regression wa ...[more]

PMID: 29958123

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Project description:The HapMap (haplotype map) projects have produced valuable genetic resources in life science research communities, allowing researchers to investigate sequence variations and conduct genome-wide association study (GWAS) analyses. A typical HapMap project may require sequencing hundreds, even thousands, of individual lines or accessions within a species. Due to limitations in current sequencing technology, the genotype values for some accessions cannot be clearly called. Additionally, allelic heterozygosity can be very high in some lines, causing genetic and sometimes phenotypic segregation in their descendants. Genetic and phenotypic segregation degrades the original accession's specificity and makes it difficult to distinguish one accession from another. Therefore, it is vitally important to determine and validate HapMap accessions before one conducts a GWAS analysis. However, to the best of our knowledge, there are no prior methodologies or tools that can readily distinguish or validate multiple accessions in a HapMap population. We devised a bioinformatics approach to distinguish multiple HapMap accessions using only a minimum number of genetic markers. First, we assign each candidate marker with a distinguishing score (DS), which measures its capability in distinguishing accessions. The DS score prioritizes those markers with higher percentages of homozygous genotypes (allele combinations), as they can be stably passed on to offspring. Next, we apply the "set-partitioning" concept to select optimal markers by recursively partitioning accession sets. Subsequently, we build a hierarchical decision tree in which a specific path represents the selected markers and the homogenous genotypes that can be used to distinguish one accession from others in the HapMap population. Based on these algorithms, we developed a web tool named MAD-HiDTree (Multiple Accession Distinguishment-Hierarchical Decision Tree), designed to analyze a user-input genotype matrix and construct a hierarchical decision tree. Using genetic marker data extracted from the Medicago truncatula HapMap population, we successfully constructed hierarchical decision trees by which the original 262 M. truncatula accessions could be efficiently distinguished. PCR experiments verified our proposed method, confirming that MAD-HiDTree can be used for the identification of a specific accession. MAD-HiDTree was developed in C/C++ in Linux. Both the source code and test data are publicly available at https://bioinfo.noble.org/MAD-HiDTree/.

Project description:PURPOSE: Among diverse tumor markers, pretreatment evaluation and follow-up detection of recurrence in colorectal cancer are generally evaluated by serum carcinoembryonic antigen (CEA) levels. However, there have been some reports about the low accuracy and high false-positive results of CEA in colorectal cancer. We investigated the clinical utilities of CYFRA 21-1 by comparing CEA and cancer antigen 19-9 (CA 19-9) in pretreatment and recurrent colorectal cancer. METHODS: Using a solid-phase immunoradiometric assay, serum levels of CYFRA 21-1, CEA and CA 19-9 were analyzed in 132 patients with primary colorectal cancer, 124 healthy controls, 104 patients with benign colorectal disease and 19 patients with recurrent colorectal cancer. We determined three different cutoff values to evaluate the sensitivity of diagnostic performance in pretreatment and recurrent colorectal cancer. RESULTS: CYFRA 21-1 (? 1.13 ng/ml) had a sensitivity of 47 %, compared with 37 % for CEA (? 3.05 ng/ml) and 32.6 % for CA 19-9 (? 23.1 ng/ml) in the initial staging of primary colorectal cancer. Using different cutoff values, CYFRA 21-1 showed higher sensitivity for pretreatment colorectal cancer than CEA and CA 19-9 in adenocarcinoma and adenosquamous carcinoma of this study. A mildly significant correlative relationship was noted between Dukes' stages and three tumor markers (p?<?0.01). The areas under the receiver operating characteristic curves of CYFRA 21-1, CEA and CA 19-9 were 0.81?±?0.03, 0.74?±?0.03 and 0.62?±?0.04, respectively, for discriminating colorectal cancer patients from patients with benign colorectal disease. In addition, CYFRA 21-1 was determined as the most sensitive tumor marker for evaluating recurrent colorectal cancer for all cutoff values. CONCLUSION: This study showed that CYFRA 21-1 could be a useful and dependable tumor marker for pretreatment and recurrent colorectal cancer. Further prospective studies on its usefulness with respect to the prognosis and utility of combined tumor markers are needed.

Dataset Information

Increased CYFRA 21-1, CEA and NSE are Prognostic of Poor Outcome for Locally Advanced Squamous Cell Carcinoma in Lung: A Nomogram and Recursive Partitioning Risk Stratification Analysis.

Objectives

Methods

Results

Conclusions

Publications

Increased CYFRA 21-1, CEA and NSE are Prognostic of Poor Outcome for Locally Advanced Squamous Cell Carcinoma in Lung: A Nomogram and Recursive Partitioning Risk Stratification Analysis.

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