Literature DB >> 27142064

Can clinical factors be used as a selection tool for an organ-preserving strategy in rectal cancer?

Ines Joye1,2, Annelies Debucquoy1, Steffen Fieuws3, Albert Wolthuis4, Xavier Sagaert5, André D'Hoore4, Karin Haustermans1,2.   

Abstract

BACKGROUND: Rectal cancer patients who achieve a good response to chemoradiotherapy (CRT), may be offered less invasive surgery or even no surgery at all. Implementation of such a policy, however, requires precise patient selection. This study identifies pretreatment clinical factors that are associated with pathological complete response (pCR) and ypT0-1N0 and evaluates their performance as a selection tool for organ-preserving strategies.
MATERIAL AND METHODS: Patients with rectal cancer treated with CRT and total mesorectal excision between January 2000 and December 2014 were retrospectively included. Following clinical characteristics were extracted from the medical files: age, gender, body mass index, ASA score, cT-stage, cN-stage, distance from the anal verge, pretreatment carcinoembryonic antigen (CEA), pretreatment hemoglobin and distance from the mesorectal fascia. Univariable and multivariable binary logistic regression models were used to predict pCR and ypT0-1N0. The discriminative ability of the prediction models was evaluated by receiver operating characteristic analysis.
RESULTS: A total of 620 patients were included of whom 120 experienced a pCR (19%) and 170 patients achieved ypT0-1N0 response (27%). A low pretreatment CEA, a high pretreatment hemoglobin and a high cN-stage were associated with pCR in multivariable analysis. A low pretreatment CEA, a low cT-stage and a high cN-stage were associated with ypT0-1N0. After cross validation, the area under the curve for the pCR and ypT0-1N0 prediction model equaled 0.609 and 0.632, respectively.
CONCLUSION: Despite their statistical significance, the value of pretreatment clinical variables in the prediction of pCR and ypT0-1N0 is very limited. To safely select patients for organ preservation, other strategies need to be explored.

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Year:  2016        PMID: 27142064     DOI: 10.3109/0284186X.2016.1167954

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  7 in total

1.  DEEP CONVOLUTIONAL NEURAL NETWORKS FOR IMAGING DATA BASED SURVIVAL ANALYSIS OF RECTAL CANCER.

Authors:  Hongming Li; Pamela Boimel; James Janopaul-Naylor; Haoyu Zhong; Ying Xiao; Edgar Ben-Josef; Yong Fan
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2019-07-11

2.  Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

Authors:  Niels W Schurink; Lisa A Min; Maaike Berbee; Wouter van Elmpt; Joost J M van Griethuysen; Frans C H Bakers; Sander Roberti; Simon R van Kranen; Max J Lahaye; Monique Maas; Geerard L Beets; Regina G H Beets-Tan; Doenja M J Lambregts
Journal:  Eur Radiol       Date:  2020-02-07       Impact factor: 5.315

3.  Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis.

Authors:  Hangfan Liu; Hongming Li; Mohamad Habes; Yuemeng Li; Pamela Boimel; James Janopaul-Naylor; Ying Xiao; Edgar Ben-Josef; Yong Fan
Journal:  IEEE Trans Biomed Eng       Date:  2020-01-27       Impact factor: 4.538

4.  COLLABORATIVE CLUSTERING OF SUBJECTS AND RADIOMIC FEATURES FOR PREDICTING CLINICAL OUTCOMES OF RECTAL CANCER PATIENTS.

Authors:  Hangfan Liu; Hongming Li; Pamela Boimel; James Janopaul-Naylor; Haoyu Zhong; Ying Xiao; Edgar Ben-Josef; Yong Fan
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2019-07-11

5.  Morphologic predictors of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Authors:  Chongda Zhang; Feng Ye; Yuan Liu; Han Ouyang; Xinming Zhao; Hongmei Zhang
Journal:  Oncotarget       Date:  2017-12-19

6.  MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer.

Authors:  Maxiaowei Song; Shuai Li; Hongzhi Wang; Ke Hu; Fengwei Wang; Huajing Teng; Zhi Wang; Jin Liu; Angela Y Jia; Yong Cai; Yongheng Li; Xianggao Zhu; Jianhao Geng; Yangzi Zhang; XiangBo Wan; Weihu Wang
Journal:  Br J Cancer       Date:  2022-04-02       Impact factor: 9.075

Review 7.  On a prolonged interval between rectal cancer (chemo)radiotherapy and surgery.

Authors:  Bengt Glimelius
Journal:  Ups J Med Sci       Date:  2017-02-24       Impact factor: 2.384

  7 in total

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