Dataset Information

A nomogram improves AJCC stages for colorectal cancers by introducing CEA, modified lymph node ratio and negative lymph node count.

ABSTRACT: Lymph node stages (pN stages) are primary contributors to survival heterogeneity of the 7^th AJCC staging system for colorectal cancer (CRC), indicating spaces for modifications. To implement the modifications, we selected eligible CRC patients from the Surveillance Epidemiology and End Results (SEER) database as participants in a training (n?=?6675) and a test cohort (n?=?6760), and verified tumor deposits to be metastatic lymph nodes to derive modified lymph node count (mLNC), lymph node ratio (mLNR), and positive lymph node count (mPLNC). After multivariate Cox regression analyses with forward stepwise elimination of the mLNC and mPLNC for the training cohort, a nomogram was constructed to predict overall survival (OS) via incorporating preoperative carcinoembryonic antigen, pT stages, negative lymph node count, mLNR and metastasis. Internal validations of the nomogram showed concordance indexes (c-index) of 0.750 (95% CI, 0.736-0.764) and 0.749 before and after corrections for overfitting. Serial performance evaluations indicated that the nomogram outperformed the AJCC stages (c-index?=?0.725) with increased accuracy, net benefits, risk assessment ability, but comparable complexity and clinical validity. All the results were reproducible in the test cohort. In summary, the proposed nomogram may serve as an alternative to the AJCC stages. However, validations with longer follow-up periods are required.

SUBMITTER: Zhang ZY

PROVIDER: S-EPMC5150581 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A nomogram improves AJCC stages for colorectal cancers by introducing CEA, modified lymph node ratio and negative lymph node count.

Zhang Zhen-Yu ZY Gao Wei W Luo Qi-Feng QF Yin Xiao-Wei XW Basnet Shiva S Dai Zhen-Ling ZL Ge Hai-Yan HY

Scientific reports 20161212

Lymph node stages (pN stages) are primary contributors to survival heterogeneity of the 7<sup>th</sup> AJCC staging system for colorectal cancer (CRC), indicating spaces for modifications. To implement the modifications, we selected eligible CRC patients from the Surveillance Epidemiology and End Results (SEER) database as participants in a training (n = 6675) and a test cohort (n = 6760), and verified tumor deposits to be metastatic lymph nodes to derive modified lymph node count (mLNC), lymph ...[more]

PMID: 27941905

Similar Datasets

Project description:BackgroundThe prognosis of pancreatic carcinoma (PC) remains poor and the American Joint Committee on Cancer (AJCC) 8th staging system for survival prediction in PC patients after curative resection is still limited. Thus, the aim of this study is to refine a valuable prognostic model and novel staging system for PC with curative resection.MethodsThe data of 3,458 patients used in this study were retrieved from the Surveillance, Epidemiology, and End Results database registry of National Cancer Institute. The prognostic value of lymph node ratio (LNR) was analyzed in the primary cohort and prognostic nomogram based on the LNR was established to create a novel staging system. Then, analyses were conducted to evaluate the application of the formulated nomogram staging system and the AJCC 8th staging system. The predictive performance of model was further validated in the internal validation cohort.ResultsSignificant positive correlations were found between LNR and all factors except for surgical procedures. The results of univariate and multivariate analyses showed that LNR was identified as an independent prognostic indicator for overall survival (OS) in both primary and validation cohorts (all P < 0.001). A prognostic nomogram based on the LNR was formulated to obtain superior discriminatory abilities. Compared with the AJCC 8th staging system, the formulated nomogram staging system showed higher hazard ratios of stage II, III, and IV disease (reference to stage I disease) that were 1.637, 2.300, and 3.521, respectively, by univariate analyses in the primary cohort and the distinction between stage I, II, and III disease at the beginning or end of the survival curves was more apparent. All these results were further verified in the validation cohort.ConclusionLNR can be considered as a useful independent prognostic indicator for PC patients after curative resection regardless of the surgical procedures. Compared with the AJCC 8th staging system, the formulated nomogram showed superior predictive accuracy for OS and its novel staging system revealed better risk stratification.

Project description:Radiomics studies to predict lymph node (LN) metastasis has only focused on either primary tumor or LN alone. However, combining radiomics features from multiple sources may reflect multiple characteristic of the lesion thereby increasing the discriminative performance of the radiomic model. Therefore, the present study intends to evaluate the efficiency of integrative nomogram, created by combining clinical parameters and radiomics features extracted from gross tumor volume (GTV), peritumoral volume (PTV) and LN, for the preoperative prediction of LN metastasis in clinical cT1N0M0 adenocarcinoma. A primary cohort of 163 patients (training cohort, 113; and internal validation cohort, 50) and an external validation cohort of 53 patients with clinical stage cT1N0M0 were retrospectively included. Features were extracted from three regions of interests (ROIs): GTV; PTV (5.0 mm around the tumor) and LN on pre-operative contrast enhanced computed tomography (CT). LASSO logistic regression method was used to build radiomic signatures. Multivariable regression analysis was used to build a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The discriminative performance of nomogram was validated both internally and externally. The radiomic signatures using the features of GTV, PTV and LN showed a good ability in predicting LN metastasis with an area under the curve (AUC) of 0.74 (95% CI 0.60-0.88), 0.72 (95% CI 0.57-0.87) and 0.64 (95% CI 0.48-0.80) respectively in external validation cohort. The integration of different signature together further increases the discriminatory ability: GTV + PTV (GPTV): AUC 0.75 (95% CI 0.61-0.89) and GPTV + LN: AUC 0.76 (95% CI 0.61-0.91) in external validation cohort. An integrative nomogram of clinical parameters and radiomic features demonstrated further increase in discriminatory ability with AUC of 0.79 (95% CI 0.66-0.93) in external validation cohort. The nomogram showed good calibration. Decision curve analysis demonstrated that the radiomic nomogram was clinically useful. The integration of information from clinical parameters along with CT radiomics information from GTV, PTV and LN was feasible and increases the predictive performance of the nomogram in predicting LN status in cT1N0M0 adenocarcinoma patients suggesting merit of information integration from multiple sources in building prediction model.

Dataset Information

A nomogram improves AJCC stages for colorectal cancers by introducing CEA, modified lymph node ratio and negative lymph node count.

Publications

A nomogram improves AJCC stages for colorectal cancers by introducing CEA, modified lymph node ratio and negative lymph node count.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets