Clinical Research Papers:
Nomogram basing pre-treatment parameters predicting early response for locally advanced rectal cancer with neoadjuvant chemotherapy alone: a subgroup efficacy analysis of FOWARC study
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Jianwei Zhang1,*, Yue Cai1,*, Huabin Hu1, Ping Lan2, Lei Wang2, Meijin Huang2, Liang Kang2, Xiaojian Wu2, Hui Wang2, Jiayu Ling1, Jian Xiao1, Jianping Wang2 and Yanhong Deng1
1 Department of Medical Oncology, The Sixth Affiliated Hospital of Sun-Yat Sen University, Guangzhou, Guangdong, P.R. China
2 Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun-Yat sen University, Guangzhou, Guangdong, P.R. China
* These authors have contributed equally to this work
Jianping Wang, email:
Yanhong Deng, email:
Keywords: neoadjuvant chemotherapy, nomogram, predictive, rectal cancer
Received: September 01, 2015 Accepted: November 25, 2015 Published: December 04, 2015
Objective: To develop an accurate model with pre-treatment parameters to predict tumor regression and down-staging in locally advanced rectal cancer patients, basing the cohort of preoperative chemotherapy alone in FOWARC study.
Patients and Methods: From Jan 2011 to Feb 2015, complete data was available for 137 out of 165 patients who received preoperative chemotherapy alone. All pre-treatment clinical parameters were collected. Tumor regression grade (TRG) 0-1 was defined as good regression, and pathological TNM stage (ypTNM) 0-I after neoadjuvant treatment was defined as good down-staging. Nomogram was established to predict tumor regression and down-staging. The predictive performance of the model was assessed with concordance index and calibration plots.
Results: Of the 137 patients, 10 had TRG 0 (complete regression); 32 patients, TRG 1; and 95 patients, TRG 2 and 3 (poor regression); 56 (40.9%) patients were classified as good down-staging with ypTNM stage 0-I. The predictive nomograms were developed to predict the probability of TRG 0-1 and good down-staging with a C-index of 0.72 (95% CI: 0.604-0.797) and 0.76 (95% CI: 0.681-0.844). Calibration plots showed good statistical performance on internal validation. Predictive factors in the models included tumor length, tumor circumferential extent, age, and ApoA1.
Conclusions: The model based on available clinical parameters could accurately predict early efficacy with neoadjuvant mFOLFOX6 chemotherapy alone, which might help in patient selection for optimized treatment.
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