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Nomogram prediction of overall survival for patients with non-small-cell lung cancer incorporating pretreatment peripheral blood markers.

ABSTRACT: OBJECTIVES:The objective of this study is to build a novel prognostic nomogram in non-small-cell lung cancer (NSCLC) incorporating pre-treatment peripheral blood markers beyond known pathoclinical predictors. METHODS:We analysed 7158 patients with NSCLC diagnosed between 1 January 1997 and 31 December 2012 from a single institution with a uniform medical record and routine follow-up information. Besides common clinicopathological factors, we investigated the prognostic value of the neutrophil to lymphocyte ratio, monocytes and haemoglobin level in peripheral blood before treatment. Patients were randomly assigned to training (4772 patients, 66.7%) or validation cohorts (2386 patients, 33.3%). Cox proportional hazards models determined the effects of multiple factors on overall survival (OS). A nomogram was developed to predict median survival and 1-, 3-, 5- and 10-year OS for NSCLC. The performance of the nomogram was assessed by a concordance index and calibration curve. RESULTS:In the training cohort, the multivariate Cox model identified the neutrophil to lymphocyte ratio, monocytes and haemoglobin level before treatment as significant prognostic factors for OS independent of patient age, gender, smoking history of intensity and cessation, performance status, disease stage, tumour cell type and differentiation grade and therapies. All the significant prognostic variables were incorporated into a nomogram. In the validation cohort, the nomogram showed notable accuracy in predicting OS, with a concordance index of 0.81, and was well calibrated for predictions of OS. CONCLUSIONS:The proposed nomogram incorporating peripheral blood markers and known prognostic factors could accurately predict individualized survival probability of patients with NSCLC. It could be used in treatment planning and stratification in clinical trials.

SUBMITTER: Xie D

PROVIDER: S-EPMC5961359 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Nomogram prediction of overall survival for patients with non-small-cell lung cancer incorporating pretreatment peripheral blood markers.

Xie Dong D Allen Mark S MS Marks Randolph R Jiang Gening G Sun Zhifu Z Nichols Frances F Zhang Mingrui M Chen Chang C Aubry Marie-Christine MC Jatoi Aminah A Garces Yolanda I YI Mansfield Aaron A Wigle Dennis D Molina Julian J Deschamps Claude C Yang Ping P

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery 20180601 6

<h4>Objectives</h4>The objective of this study is to build a novel prognostic nomogram in non-small-cell lung cancer (NSCLC) incorporating pre-treatment peripheral blood markers beyond known pathoclinical predictors.<h4>Methods</h4>We analysed 7158 patients with NSCLC diagnosed between 1 January 1997 and 31 December 2012 from a single institution with a uniform medical record and routine follow-up information. Besides common clinicopathological factors, we investigated the prognostic value of th ...[more]

PMID: 29293957

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Project description:Background: Advances in treatment and supportive care have significantly improved the overall survival (OS) of pediatric patients with acute lymphoblastic leukemia (ALL). However, there is a large number of these patients who continue to relapse after receiving standard treatment. Accurate identification of patients at high risk of relapse and targeted therapy may significantly improve their prognosis. Therefore, the aim of this study was to identify significant prognostic factors for pediatric ALL and establish a novel nomogram for the prediction of survival. Methods: The ALL clinical data of Phases I and II of the Therapeutic Applicable Research to Generate Effective Treatments (TARGET) project were merged and randomly divided into training and validation groups. The LASSO regression model was used to select the specific factors related to the OS of the training group and generate prognostic nomograms according to the selected characteristics. The predictive accuracy of the nomogram for OS was verified using the concordance index of the training and validation groups, the area under the receiver operating characteristic curve for prognostic diagnosis, and the calibration curve. Results: A total of 1,000 children with ALL were included in the TARGET project. Of those, 489 patients had complete follow-up data for further analysis. The data were randomly divided into the training group (n = 345) and the validation group (n = 144). Seven clinical characteristics, namely age at diagnosis, peripheral white blood cells, bone marrow and CNS site of relapse, ETV6/RUNX1 fusion, TCF3/PBX1, and BCR/ABL1 status, were selected to construct the nomogram. The concordance indices of the training and validation groups were 0.809 (95% confidence interval: 0.766-0.852) and 0.826 (95% confidence interval: 0.767-0.885), respectively. The areas under the receiver operating characteristic curve of the 3-year, 5-year, and 10-year OS in the training group were 0.804, 0.848, and 0.885, respectively, while that of the validation group were 0.777, 0.825, and 0.863, respectively. Moreover, the calibration curves demonstrated a favorable consistency between the predicted and actual survival probabilities. Conclusions: Independent predictors of OS in children with ALL included age at diagnosis, white blood cells, bone marrow site of relapse, CNS site of relapse, ETV6/RUNX1 fusion, TCF3/PBX1, and BCR/ABL1 status. The nomograms developed using these high-risk factors can more simply, accurately, and quantitatively predict the survival of children, and improve treatment and prognosis.

Project description:BackgroundHepatocellular carcinoma (HCC) is associated with a dismal prognosis, and prediction of the prognosis of HCC can assist in therapeutic decision-makings. An increasing number of studies have shown that the texture parameters of images can reflect the heterogeneity of tumors, and may have the potential to predict the prognosis of patients with HCC after surgical resection. The aim of this study was to investigate the prognostic value of computed tomography (CT) texture parameters in patients with HCC after hepatectomy and to develop a radiomics nomogram by combining clinicopathological factors and the radiomics signature.MethodsIn all, 544 eligible patients were enrolled in this retrospective study and were randomly divided into the training cohort (n = 381) and the validation cohort (n = 163). The tumor regions of interest (ROIs) were delineated, and the corresponding texture parameters were extracted. The texture parameters were selected by using the least absolute shrinkage and selection operator (LASSO) Cox model in the training cohort, and a radiomics signature was established. Then, the radiomics signature was further validated as an independent risk factor for overall survival (OS). The radiomics nomogram was established based on the Cox regression model. The concordance index (C-index), calibration plot and decision curve analysis (DCA) were used to evaluate the performance of the radiomics nomogram.ResultsThe radiomics signature was formulated based on 7 OS-related texture parameters, which were selected in the training cohort. In addition, the radiomics nomogram was developed based on the following five variables: α-fetoprotein (AFP), platelet-to-lymphocyte ratio (PLR), largest tumor size, microvascular invasion (MVI) and radiomics score (Rad-score). The nomogram displayed good accuracy in predicting OS (C-index = 0.747) in the training cohort and was confirmed in the validation cohort (C-index = 0.777). The calibration plots also showed excellent agreement between the actual and predicted survival probabilities. The DCA indicated that the radiomics nomogram showed better clinical utility than the clinicopathologic nomogram.ConclusionThe radiomics signature is a potential prognostic biomarker of HCC after hepatectomy. The radiomics nomogram that integrated the radiomics signature can provide a more accurate estimation of OS than the clinicopathologic nomogram for HCC patients after hepatectomy.

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Nomogram prediction of overall survival for patients with non-small-cell lung cancer incorporating pretreatment peripheral blood markers.

Publications

Nomogram prediction of overall survival for patients with non-small-cell lung cancer incorporating pretreatment peripheral blood markers.

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