Individualized colorectal cancer screening based on the clinical risk factors: beyond family history of colorectal cancer

2018 ◽  
Vol 88 (1) ◽  
pp. 128-135 ◽  
Author(s):  
Chan Hyuk Park ◽  
Nam Hee Kim ◽  
Jung Ho Park ◽  
Dong Il Park ◽  
Chong Il Sohn ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Cancer Screening ◽  
Family History ◽  
Colorectal Cancer Screening ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
History Of

scholarly journals Major clinical risk factors for seizures in febrile children aged 6 to 60 months.

2020 ◽  
Vol 27 (05) ◽  
pp. 891-894
Author(s):  
Shahid Ishaq ◽  
Ejaz Mazari ◽  
Fazal ur Rehman
Keyword(s):  
Risk Factors ◽  
Family History ◽  
Febrile Seizures ◽  
Study Groups ◽  
Clinical Risk Factors ◽  
P Value ◽  
Chi Square ◽  
Clinical Risk ◽  
Significant Difference ◽  
History Of

Objectives: Febrile seizures (FS) are the most common type of seizures and typically transpire in children with ages from 6 to 60 months. This study was planned to find out major clinical risk factors for seizures in febrile children who were aged 6 to 60 months. A total of 100 febrile children aged 6 to 60. Study Design: Analytical Study. Setting: Department of Neurology, Children’s Hospital and the Institute of Child Health, Multan. Period: From 1st April 2018 to 31st December 2018. Material & Methods: Group A had 40 children with febrile seizures while group B had 60 febrile children but without seizures. Demographic features along with family history of (H/O) epilepsy as well as family history of febrile seizure, types of seizure and infection diseases were noted and analyzed using SPSS version 20. Odds ratio was calculated for various risk factors. Chi square test was applied and P value < 0.05 was considered as significant. Results: Out of a total of 100 children, there were 54 (54.0%) male and 46 (46.0%) female. There was no statistical difference in terms of gender between the two groups (p value = 0.566). Overall, mean age of the children was 26.02 months with standard deviation of 13.4 months. There were 28 (70.0%) children who reported with simple seizures while complex seizures were found in 12 (30.0%) cases. Statistically significant difference (p value = 0.001) was seen in terms of types of infections between the two study groups. When risk of seizures for various risk factors was calculated, family H/O FS, family H/O epilepsy, and upper RTI were as 14, 7 and 3 times respectively and turned out to be the major risk factors for seizures in febrile children. Conclusions: Family H/O FS, family H/O epilepsy and upper RTIs are the major risk factors related with seizures in febrile children. Measures to prevent these risk factors can decrease the burden of FS in our population.

Race and Colorectal Cancer Screening Compliance Among Persons With a Family History of Cancer

2015 ◽  
Vol 110 ◽  
pp. S611-S612
Author(s):  
Adeyinka O. Laiyemo ◽  
Nicole Thompson ◽  
Carla Williams ◽  
Kolapo Idowu ◽  
Kathy P. Bull-Henry ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Family History ◽  
Colorectal Cancer Screening ◽  
Family History Of Cancer ◽  
History Of ◽  
History Of Cancer

Practicum in assessing family history of cancer to inform colorectal cancer screening

2003 ◽  
Vol 124 (4) ◽  
pp. A647
Author(s):  
Marijayne Bushey ◽  
Ann Zauber ◽  
Sidney Winawer ◽  
Nathan Ellis ◽  
Emily Glogowski ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Family History ◽  
Colorectal Cancer Screening ◽  
Family History Of Cancer ◽  
History Of ◽  
History Of Cancer

scholarly journals Examining the Relationship between Biopsychosocial History and Clinical Profiles Following Concussion

2019 ◽  
Vol 34 (5) ◽  
pp. 765-765
Author(s):  
K Emami ◽  
A M Sufrinko ◽  
M W Collins ◽  
A P Kontos ◽  
E A Rossi
Keyword(s):  
Risk Factors ◽  
Motion Sickness ◽  
Clinical Profile ◽  
Clinical Risk Factors ◽  
Post Injury ◽  
Chi Square ◽  
Clinical Risk ◽  
History Of ◽  
Concussion History ◽  
Clinical Profiles

Abstract Purpose To determine if clinical risk factors (e.g., migraine history, motion sickness, concussion history) place an individual at risk for specific clinical profiles (e.g., posttraumatic migraine, vestibular) designated by a clinician following concussion. Methods Fifty (22M; 28F) symptomatic, concussed patients (17.02±3.14 years old) were evaluated within 21days post-injury. Demographics and medical history were obtained, including history of migraine, motion sickness, ADHD, learning disability (LD), oculomotor disorder, psychiatric diagnoses, and prior concussion. The presence of each clinical profile was determined by a clinician, based on synthesis of evaluation findings, including neurocognitive testing, symptom report, and vestibular/oculomotor screening results. Chi-square analyses were used to explore associations between risk factors and clinical profile post-injury. Results Chi-square analyses found that female sex was associated with increased odds (OR=5.25,95% CI[1.55, 17.77]) of vestibular clinical profile, X2(1, n=50)=7.55, p=.006. History of concussion was associated with increased odds (OR=7.10,95%CI[1.39,35.87]) of the PTM profile (X2[1, n=50]=6.56, p=.01) and increased odds (OR=9.85,95%CI[1.00,96.67]) of anxiety/mood profile (X2 1, n=50]=5.24, p=.022. Further, history of motion sickness was associated with increased odds OR=10.2,95%CI[1.2,86.69] of the PTM profile (X2[1, n=50]=6.11, p=.013). No other relationships were found. Conclusion Some clinical risk factors were associated with post-injury clinical profiles consistent with prior literature, while others were not. For example, females were more likely to have a vestibular profile. While motion sickness was associated with PTM, history of migraine was not. Concussion history, which has inconsistent findings for re-injury outcomes, was associated with increased likelihood of PTM and anxiety/mood profiles. Findings add to the literature supporting relationships among risk factors and clinical outcomes.

scholarly journals Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients

2020 ◽  
Vol 11 ◽  
Author(s):  
Siqi Dai ◽  
Shuang Xu ◽  
Yao Ye ◽  
Kefeng Ding
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Expression Profiles ◽  
Gene Signature ◽  
Clinical Risk Factors ◽  
Survival Prediction ◽  
Related Gene ◽  
Cancer Management ◽  
Clinical Risk ◽  
Immune Related Gene

BackgroundDespite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient’s prognosis.MethodsIRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another two CRC datasets from the Gene Expression Omnibus (GEO). Gene function enrichment analysis was conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors.ResultsThe three datasets had 487, 579, and 224 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B, and IL20RB) was developed through feature selection that showed good differentiation between the low- and high-risk groups in the training set (p &lt; 0.001), which was later confirmed in the two validation groups (log-rank p &lt; 0.05). The signature outperformed tumor TNM staging for survival prediction. GO and KEGG functional annotation analysis suggested that the signature was significantly enriched in metabolic processes and regulation of immunity (p &lt; 0.05). When combined with clinical risk factors, the model showed robust prediction capability.ConclusionThe immune-related six-gene signature is a reliable prognostic indicator for CRC patients and could provide insight for personalized cancer management.

scholarly journals Clinical risk factors of colorectal cancer in patients with serrated polyposis syndrome: a multicentre cohort analysis

Gut ◽  
2015 ◽  
Vol 66 (2) ◽  
pp. 278-284 ◽  
Author(s):  
J E G IJspeert ◽  
S A Q Rana ◽  
N S S Atkinson ◽  
Y J van Herwaarden ◽  
B A J Bastiaansen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Cohort Analysis ◽  
Clinical Risk Factors ◽  
Polyposis Syndrome ◽  
Clinical Risk ◽  
Multicentre Cohort
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