Clinical Research Papers:

Validation of a rectal cancer outcome prediction model with a cohort of Chinese patients

Lijun Shen _, Johan van Soest, Jiazhou Wang, Jialu Yu, Weigang Hu, Yutao U. T. Gong, Vincenzo Valentini, Ying Xiao, Andre Dekker and Zhen Zhang

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Oncotarget. 2015; 6:38327-38335. https://doi.org/10.18632/oncotarget.5195

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Lijun Shen1, Johan van Soest2, Jiazhou Wang1, Jialu Yu3, Weigang Hu1, Yutao U. T. Gong3, Vincenzo Valentini4, Ying Xiao3, Andre Dekker2, Zhen Zhang1

1Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China

2Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands

3Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA

4Department of Radiation Oncology, Università Cattolica S Cuore, Rome, Italy

Correspondence to:

Zhen Zhang, e-mail: [email protected]

Keywords: rectal cancer, preoperative chemoradiation, external validation, nomogram

Received: May 13, 2015     Accepted: September 07, 2015     Published: September 18, 2015


The risk of local recurrence (LR), distant metastases (DM) and overall survival (OS) of locally advanced rectal cancer after preoperative chemoradiation can be estimated by prediction models and visualized using nomograms, which have been trained and validated in European clinical trial populations. Data of 277 consecutive locally advanced rectal adenocarcinoma patients treated with preoperative chemoradiation and surgery from Shanghai Cancer Center, were retrospectively collected and used for external validation. Concordance index (C-index) and calibration curves were used to assess the performance of the previously developed prediction models in this routine clinical validation population. The C-index for the published prediction models was 0.72 ± 0.079, 0.75 ± 0.043 and 0.72 ± 0.089 in predicting 2-year LR, DM and OS in the Chinese population, respectively. Kaplan-Meier curves indicated good discriminating performance regarding LR, but could not convincingly discriminate a low-risk and medium-risk group for distant control and OS. Calibration curves showed a trend of underestimation of local and distant control, as well as OS in the observed data compared with the estimates predicted by the model.

In conclusion, we externally validated three models for predicting 2-year LR, DM and OS of locally advanced rectal cancer patients who underwent preoperative chemoradiation and curative surgery with good discrimination in a single Chinese cohort. However, the model overestimated the local control rate compared to observations in the clinical cohort. Validation in other clinical cohorts and optimization of the prediction model, perhaps by including additional prognostic factors, may enhance model validity and its applicability for personalized treatment of locally advanced rectal cancer.

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