508 THE IMPACT OF RESIDENTIAL SEGREGATION ON COLORECTAL CANCER DIAGNOSIS AND TREATMENT

2020 ◽  
Vol 158 (6) ◽  
pp. S-1514
Author(s):  
Michael Poulson ◽  
Andrea M. Madiedo ◽  
Tracey Dechert ◽  
Jason Hall
2020 ◽  
Author(s):  
Michael R. Poulson ◽  
Samuel A. Helrich ◽  
Kelly M. Kenzik ◽  
Tracey A. Dechert ◽  
Teviah E. Sachs ◽  
...  

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 159
Author(s):  
Yao Peng ◽  
Yuqiang Nie ◽  
Jun Yu ◽  
Chi Chun Wong

Colorectal cancer (CRC) is one of the leading cancers that cause cancer-related deaths worldwide. The gut microbiota has been proved to show relevance with colorectal tumorigenesis through microbial metabolites. By decomposing various dietary residues in the intestinal tract, gut microbiota harvest energy and produce a variety of metabolites to affect the host physiology. However, some of these metabolites are oncogenic factors for CRC. With the advent of metabolomics technology, studies profiling microbiota-derived metabolites have greatly accelerated the progress in our understanding of the host-microbiota metabolism interactions in CRC. In this review, we briefly summarize the present metabolomics techniques in microbial metabolites researches and the mechanisms of microbial metabolites in CRC pathogenesis, furthermore, we discuss the potential clinical applications of microbial metabolites in cancer diagnosis and treatment.


2020 ◽  
Vol 255 ◽  
pp. 164-171
Author(s):  
David Weithorn ◽  
Vanessa Arientyl ◽  
Ian Solsky ◽  
Goyal Umadat ◽  
Rebecca Levine ◽  
...  

2009 ◽  
Vol 7 (2) ◽  
pp. 194
Author(s):  
C. Gurkan ◽  
B. Sabit ◽  
U. Unlu ◽  
A. Kurnaz ◽  
K. Kuscu ◽  
...  

2011 ◽  
Vol 31 (4) ◽  
pp. 530-539 ◽  
Author(s):  
Karen M. Kuntz ◽  
Iris Lansdorp-Vogelaar ◽  
Carolyn M. Rutter ◽  
Amy B. Knudsen ◽  
Marjolein van Ballegooijen ◽  
...  

Background. As the complexity of microsimulation models increases, concerns about model transparency are heightened. Methods. The authors conducted model “experiments” to explore the impact of variations in “deep” model parameters using 3 colorectal cancer (CRC) models. All natural history models were calibrated to match observed data on adenoma prevalence and cancer incidence but varied in their underlying specification of the adenocarcinoma process. The authors projected CRC incidence among individuals with an underlying adenoma or preclinical cancer v. those without any underlying condition and examined the impact of removing adenomas. They calculated the percentage of simulated CRC cases arising from adenomas that developed within 10 or 20 years prior to cancer diagnosis and estimated dwell time—defined as the time from the development of an adenoma to symptom-detected cancer in the absence of screening among individuals with a CRC diagnosis. Results. The 20-year CRC incidence among 55-year-old individuals with an adenoma or preclinical cancer was 7 to 75 times greater than in the condition-free group. The removal of all adenomas among the subgroup with an underlying adenoma or cancer resulted in a reduction of 30% to 89% in cumulative incidence. Among CRCs diagnosed at age 65 years, the proportion arising from adenomas formed within 10 years ranged between 4% and 67%. The mean dwell time varied from 10.6 to 25.8 years. Conclusions. Models that all match observed data on adenoma prevalence and cancer incidence can produce quite different dwell times and very different answers with respect to the effectiveness of interventions. When conducting applied analyses to inform policy, using multiple models provides a sensitivity analysis on key (unobserved) “deep” model parameters and can provide guidance about specific areas in need of additional research and validation.


2016 ◽  
Vol 53 (5) ◽  
pp. 727-735 ◽  
Author(s):  
Marjolein M. J. Zanders ◽  
Myrthe P. P. van Herk-Sukel ◽  
Ron M. C. Herings ◽  
Lonneke V. van de Poll-Franse ◽  
Harm R. Haak

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12566-e12566
Author(s):  
Anna Skrzypczyk-Ostaszewicz ◽  
Agnieszka I. Jagiello-Gruszfeld ◽  
Jerzy Giermek ◽  
Zbigniew Nowecki

e12566 Background: This study discusses the analysis of the prospectively collected material on pregnant patients treated for breast cancer at the Department of Breast Cancer and Reconstructive Surgery of the Maria Skłodowska-Curie National Oncology Institute - National Research Institute (until 2020: Oncology Center - Institute) in Warsaw, in the years 1995 - 2020. 84 patients were included into the final analysis and 72 children were assessed simultaneously. Methods: The paper summarizes information on the diagnosis and treatment of breast cancer during pregnancy, the course of pregnancy and childbirth and the birth parameters of children i.e. weight, length and Apgar score, as well as the dependencies between them, mainly the impact of some breast cancer, diagnosis and treatment process features on the newborns. The patietnt’s survavial - DFS ( disease free survival) and OS ( overall survival) - was also analyzed. The course of breast cancer diagnosis and treatment data were obtained from the patients’ medical documentation (medical records) and from information provided by the mothers during follow-up visits and read in the children's health books. In order to answer the research questions, statistical analyzes were conducted using the IBM SPSS Statistics 26 package. Results: In the analyzed period, the disease recurrence was recognized in 34 (40.5%) patients, and 24 (28.6%) patients died. The median disease-free survival (DFS) was 12.3 years (147.5 months), and the median overall survival (OS) was not reached during the follow-up period. The estimated 5-year survival rates for DFS and OS were 57.9% and 74.5% respectively, and for 10-year survival - 51.4% and 64.5%. The study showed a statistically significant relationship between the baseline clinical advancement and DFS. It has been also analyzed how the diagnosis, treatment and method of pregnancy termination changed in two time periods (1995-2012 and 2013-2020). There were no statistically significant differences in survival - both DFS and OS - between the group of patients treated before and after 2012. In the assessment of the impact of some factors on the birth children parameters (weight and length), statistically significant results were obtained for: pregnancy advancement at diagnosis, breast cancer stage at diagnosis, pregnancy advancement at the start of chemotherapy, the chemotherapy regimen (classic or dose-dense), the number of cycles of chemotherapy given during pregnancy, and the number of drugs used in supportive treatment. Conclusions: The entire analysis has become not only an insightful characteristic of the studied group, but also these results may be important in everyday clinical practice and may help to optimize the management of an extremely complex and difficult situation, which is the coexistence of pregnancy with a malignant disease that threatens the mother’s life.


2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Michael Poulson ◽  
Ella Cornell ◽  
Andrea Madiedo ◽  
Kelly Kenzik ◽  
Lisa Allee ◽  
...  

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