The development of complete personalized treatment plans for colon cancer patients utilizing three gene prediction models.

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. e14553-e14553
Author(s):  
Jeng-Kai Jiang ◽  
Hung-Shin Lin ◽  
Jen-Kou Lin ◽  
Yu-Chung Wu ◽  
Teh-Ying Chou ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Prediction Models ◽  
Gene Prediction ◽  
Personalized Treatment ◽  
Treatment Plans

scholarly journals Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihao Lv ◽  
Yuqi Liang ◽  
Huaxi Liu ◽  
Delong Mo
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Prediction Models ◽  
Radical Surgery ◽  
Survival Rates ◽  
Stage Ii ◽  
Survival Prediction ◽  
Stage Ii Colon Cancer ◽  
Overall Survival Rates

Abstract Background It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy. Methods Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves. Results A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration. Conclusions Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.

scholarly journals O-0025 Personalized Treatment Planning of Stage II and IIIA Colon Cancer Patients using Genomic Classifiers (ColoPrint/ MSI-Print)

2012 ◽  
Vol 23 ◽  
pp. iv16-iv17
Author(s):  
Ramon Salazar ◽  
Robert Rosenberg ◽  
Jaume Capdevila ◽  
Victor Moreno ◽  
Ulrich Nitsche ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Treatment Planning ◽  
Stage Ii ◽  
Personalized Treatment

scholarly journals Building personalized treatment plans for early-stage colorectal cancer patients

Oncotarget ◽  
2017 ◽  
Vol 8 (8) ◽  
pp. 13805-13817 ◽  
Author(s):  
Hung-Hsin Lin ◽  
Nien-Chih Wei ◽  
Teh-Ying Chou ◽  
Chun-Chi Lin ◽  
Yuan-Tsu Lan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Early Stage ◽  
Personalized Treatment ◽  
Treatment Plans ◽  
Colorectal Cancer Patients

Investigation of Thymidylate synthase gene polymorphism in colon cancer patients

2012 ◽  
Vol 50 (05) ◽  
Author(s):  
A Schöller ◽  
A Kalmár ◽  
VÁ Patai ◽  
Z Nagy ◽  
B Barták ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Gene Polymorphism ◽  
Cancer Patients ◽  
Thymidylate Synthase

Comparative study of Canadian and Hungarian colon cancer patients

2006 ◽  
Vol 44 (05) ◽  
Author(s):  
M Rohánszky ◽  
A Nagy ◽  
G Bodoky ◽  
S Gallinger ◽  
R Gryfe
Keyword(s):  
Colon Cancer ◽  
Comparative Study ◽  
Cancer Patients

Comparison between different boost dose delivery techniques to the tumor bed of right sided breast cancer patients.

2017 ◽  
Vol 13 (1) ◽  
pp. 4605-4617
Author(s):  
Aly Mahmoud El-Hdidy
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Target Location ◽  
Breast Cancer Patients ◽  
Photon Beams ◽  
Lung Dose ◽  
Dose Volume Histograms ◽  
Tumor Bed ◽  
Boost Dose ◽  
Treatment Plans

Comparisons between three different techniques by which the boost dose was delivered to the tumor bed were carried out , aiming to present the best technique of treatment for right breast cancer patients.In this study, ten right sided breast cancer computed tomography (CT) scans were selected for ten early right breast cancer patients. We made three different treatment plans for each patient CT using three different irradiation techniques to deliver a prescribed boost dose of 10 Gy in 5 fractions to the boost PTV. In the first technique, two tangential photon beams were used, in the second technique we, two oblique photon beams were used and in the third technique, a single electron beam was used. The comparative analyses between the three techniques were performed by comparing the boost PTV- dose volume histograms (DVHs), the ipsilateral breast (right breast) DVHs, the ipsilateral lung (right lung) DVHs and the heart DVHs of the three techniques for each patient. Furthermore the dose that covering 100% , 95% of the volume (D100% , D95%) and the volume covered by 95% of the dose (V95%)of  the boost PTV of all techniques, were calculated for each patient to investigate the dose coverage of the target.Results showed that there were variations of the dose received by tumor bed, right breast and OARs depending on the technique used and the target location and size. A decrease of D100% than 90% of the prescribed dose was observed with the 3rd technique for patients 8, 9 and 10, and was observed with the 2nd technique for patient 5. A reduction of right breast dose was observed when the 3rd technique was use in comparison with the 1st and the 2nd techniques for patients 1, 2, 3, 4, 6 and 8.  Also reduction of right breast was observed when the 2nd technique used in comparison with 1st technique. An increase of lung dose was observed with the 3rd technique for patients 1, 2, 5 and 6, also was observed with 2nd technique in patient 3, 5 and 7. A decrease of lung dose was observed with the 1st technique for patients 2, 4, 5, 6, 7, 8 and 9An individualized treatment, several plans using different irradiation techniques should be developed for each patient individually to reach the best boost PTV dose coverage with minimal OARs’ dose. 

ctDNA as a prognostic factor in operable colon cancer patients: a systematic review and meta-analysis

2020 ◽  
Author(s):  
Emre Yekedüz ◽  
Elif Berna Köksoy ◽  
Hakan Akbulut ◽  
Yüksel Ürün ◽  
Güngör Utkan
Keyword(s):  
Colon Cancer ◽  
Prognostic Factor ◽  
Cancer Patients ◽  
Meta Analysis ◽  
Circulating Tumor Dna ◽  
Random Effects Model ◽  
Inverse Variance ◽  
Increased Risk ◽  
Significant Step ◽  
Tumor Dna

Aim: Using circulating tumor DNA (ctDNA) instead of historical clinicopathological factors to select patients for adjuvant chemotherapy (ACT) may reduce inappropriate therapy. Material & methods: MEDLINE was searched on March 31, 2020. Studies, including data related to the prognostic value of ctDNA in the colon cancer patients after surgery and after ACT, were included. The generic inverse-variance method with a random-effects model was used for meta-analysis. Results: Four studies were included for this meta-analysis. ctDNA-positive colon cancer patients after surgery and ACT had a significantly increased risk of recurrence compared with ctDNA-negative patients. Conclusions: ctDNA is an independent prognostic factor, and this meta-analysis is a significant step for using ctDNA instead of historical prognostic factors in the adjuvant setting.

scholarly journals Data Driven Mathematical Model of FOLFIRI Treatment for Colon Cancer

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2632
Author(s):  
Aparajita Budithi ◽  
Sumeyye Su ◽  
Arkadz Kirshtein ◽  
Leili Shahriyari
Keyword(s):  
Mathematical Model ◽  
Colon Cancer ◽  
Cancer Patients ◽  
Immune Cell ◽  
Treatment Options ◽  
Data Driven ◽  
T Helper ◽  
Primary Tumors ◽  
Cell Fractions

Many colon cancer patients show resistance to their treatments. Therefore, it is important to consider unique characteristic of each tumor to find the best treatment options for each patient. In this study, we develop a data driven mathematical model for interaction between the tumor microenvironment and FOLFIRI drug agents in colon cancer. Patients are divided into five distinct clusters based on their estimated immune cell fractions obtained from their primary tumors’ gene expression data. We then analyze the effects of drugs on cancer cells and immune cells in each group, and we observe different responses to the FOLFIRI drugs between patients in different immune groups. For instance, patients in cluster 3 with the highest T-reg/T-helper ratio respond better to the FOLFIRI treatment, while patients in cluster 2 with the lowest T-reg/T-helper ratio resist the treatment. Moreover, we use ROC curve to validate the model using the tumor status of the patients at their follow up, and the model predicts well for the earlier follow up days.

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