scholarly journals A feasibility trial of acupuncture in cancer patients undergoing radiotherapy treatment

2021 ◽  
Vol 48 ◽  
pp. 102032
Author(s):  
John Hughes ◽  
Lallita Carballo ◽  
Hilary Plant ◽  
Mike Cummings
2021 ◽  
Vol 43 ◽  
pp. 101372
Author(s):  
John Hughes ◽  
Kylie Gyertson ◽  
Lallita Carballo ◽  
Hilary Plant ◽  
Mitch Sharman ◽  
...  

2010 ◽  
Vol 19 (2) ◽  
pp. 251-259 ◽  
Author(s):  
J.A. QUEENAN ◽  
D. FELDMAN-STEWART ◽  
M. BRUNDAGE ◽  
P.A. GROOME

2008 ◽  
Vol 8 (1) ◽  
pp. 70-79 ◽  
Author(s):  
Wendy Demark-Wahnefried ◽  
L. Douglas Case ◽  
Kimberly Blackwell ◽  
P. Kelly Marcom ◽  
William Kraus ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jiazhou Wang ◽  
Lijun Shen ◽  
Haoyu Zhong ◽  
Zhen Zhou ◽  
Panpan Hu ◽  
...  

Abstract This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients’ radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment.


2018 ◽  
Vol 36 ◽  
pp. 16-25 ◽  
Author(s):  
Xiao Bin Lai ◽  
Shirley Siu Yin Ching ◽  
Frances Kam Yuet Wong ◽  
Carenx Wai Yee Leung ◽  
Lai Ha Lee ◽  
...  

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