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J. Wang



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    MO05 - Prognostic and Predictive Biomarkers II (ID 95)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Medical Oncology
    • Presentations: 1
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      MO05.07 - Nomogram combining clinicopathologic factors and molecular markers for predicting survival in patients with resected non-small cell lung cancer (ID 3317)

      16:55 - 17:00  |  Author(s): J. Wang

      • Abstract
      • Presentation
      • Slides

      Background
      Nomogram is a recognized method for individually predicting prognosis of cancer patients through combining various significant prognostic factors. Although the prognostic value of molecular biomarkers has been well studied, previous published nomograms are basically built based on only clinical factors. We sought to combine the clinicopathologic variables with the molecular markers to develop a more precise nomogram for predicting survival for early stage NSCLC patient who underwent surgery.

      Methods
      Based on data from the China Clinical Trials Consortium (CCTC) that included 1038 patients with resected NSCLC for whom the 14-gene molecular assay (BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, iL11, LCK, RND3, SH3BGR, WNT3A with ESD, TBP and YAP as internal reference) was tested, we conducted multivariate stepwise Cox regression analyses to identify significant factors which were then integrated to establish the nomogram. Nomogram based on clinicopathologic variables only (c-nomogram) or both clinical and molecular factors (cm-nomogram) were established respectively. Eighty percents of randomly sampled data were used to build the nomogram while the remaining data were used to validate it. The predictive accuracy and discriminative ability of the nomogram was determined by concordance index (C-index). Risk group stratification within a certain stage was proposed for the nomograms.

      Results
      We identified 15 independent prognostic factors, including 7 clinicopathologic variables (age, sex, histology, differentiation, tumor location, T and N stage) and 8 genes (with only CDK2AP1, FUT3, iL11, BAG1, CDC6, and RND3 were selected), then incorporated them to build the nomogram (Figure 1). The calibration curves for probability of 1, 3, 5-year overall survival (OS) showed good concordance between prediction by nomograms and actual observation in the validation set. The C-index of the cm-nomogram was statistically higher than that of the 7[th] edition TNM stage for predicting survival (0.72 vs 0.66, P=0.02) whereas the c-nomgram did not show superior performance than TNM stage system (0.69 vs 0.66, P=0.463). The stratification into three risk groups according to cm-nomogram allows significant distinction between Kaplan-Meier curves in each TNM stage respectively (P<0.01 for all stages, Figure 2).Figure 1

      Conclusion
      We developed a novel and validated nomogram that combines clinicopathologic factors and molecular markers, which provided more accurate predictions for OS of resected NSCLC patients compared with the TNM staging system and nomogram considering only clinical variables. This prognostic model lent support to clinicians and patients in decision making. In addition, it indicated that it is feasible and essential to incorporate molecular markers when building a nomogram to obtain more accurate prediction.

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    P1.07 - Poster Session 1 - Surgery (ID 184)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Surgery
    • Presentations: 1
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      P1.07-029 - Nomogram for predicting survival in patients with resected non-small cell lung cancer (ID 2979)

      09:30 - 09:30  |  Author(s): J. Wang

      • Abstract

      Background
      Nomogram is a widely used tool for cancer prognosis due to its improved individual prediction of survival through combining various significant prognostic factors. The objective of this study was to develop a clinical nomogram for predicting survival for patient with resected non-small cell lung cancer (NSCLC).

      Methods
      Based on data from a multi-institutional registry for 6111 patients with resected NSCLC at China between January 2001 and December 2008, we performed univariate and multivariate stepwise Cox regression analyses to identify survival prognostic factors, which were then integrated to build the nomogram. Seventy-five percents of randomly sampled data were used to build the nomogram while the remaining data were used to validate the model. The predictive accuracy and discriminative ability of the nomogram was determined by concordance index (C-index). Risk group stratification within a certain stage was proposed for the nomograms.

      Results
      Among 26 clinical variables, 13 independent prognostic factors finally entered the nomogram (Figure 1), including age, sex, histology, tumor location, operation type, assess to complete video-assisted thoracoscopic surgery (VATS), primary tumor (T) stage, lymph nodes (N) stage, TN stage, number of dissected lymph nodes, blood loss volume, and complications. The calibration curves for probability of 1, 3, 5, 10-year overall survival (OS) represented good agreement between prediction by nomogram and actual observation in the validation set. The C-index of the nomogram was statistically higher than that of the 7[th] edition TNM stage for predicting survival (0.71 vs 0.66, P=0.01). The stratification into different risk groups allows significant distinction between Kaplan-Meier curves for survival outcomes in each TNM stage respectively (P<0.01 for all stages, Figure 2).Figure 1

      Conclusion
      We developed a novel and validated clinical nomogram that could provide individual and more accurate predictions for OS of resected NSCLC patients compared with the TNM staging system. This prognostic model may support clinicians and patients in decision making, such as to identify those with higher risk for poor prognosis.