Dataset Information

Factors Related to Adverse Events in Colorectal Cancer

ABSTRACT: Coordinated multi-center project with several complementary goals in each one of the sub-projects included. Objectives: 1.To determine risk factors of death, or major complications in the short term; 2.To determine risk factors of death, tumor recurrence, major complications, readmission or deterioration of quality of life in the mid term; 3.Evaluation of patient reported outcomes from before the intervention to the end of the follow-up. 4.To study the role of immunohisto-chemistry markers in the prediction of similar adverse results. This sub-project (coordinator) will approach the determination of risk factors of death, tumor recurrence, major complications, readmission and deterioration of quality of medium term life (1-2 years). Methodology. Design: prospective cohort study with 2 years follow-up after the surgical intervention. Participant centers: 18 hospitals of 6 Autonomous Communities of all Spain. Patients diagnosed of colorectal cancer surgically intervened. Variables: pre-intervention, those of the hospital admission, sociodemographic, immunohisto-chemistry and clinical parameters, that could be in relation to the outcomes to study. Statistic analysis: a derivation sample will be created where the possible predicting parameters will be identified, by cancer of colon or rectum. Predictive models will be created with a good discriminative capacity. A validation of those models will be performed in a validation sub-sample. Logistic and Cox regression models will be used. Simulation models for the prediction of discreet events in the long term will be used.

DISEASE(S): Colorectal Cancer,Colorectal Neoplasms

PROVIDER: 2193392 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Similar Datasets

Project description:Sepsis is the most common cause of hospitalization worldwide. Millions of people survive sepsis each year and are at risk for rehospitalization and death. Pulmonary complications such as respiratory failure due to pneumonia and exacerbation of chronic respiratory disease are among the most common reasons for rehospitalization in sepsis survivors. In order to prevent additional morbidity and death in patients surviving sepsis, we must establish biomarkers to identify patients at risk for pulmonary complications and develop treatments. Late complications in sepsis survivors, particularly nosocomial infections, are proposed to occur through persistent immune reprogramming after sepsis known as immunoparalysis. However, pro-inflammatory immune reprogramming in the form of primed or enhanced responses to secondary stimuli has also been described and could directly contribute to tissue injury and death. Primed immune responses and their contribution to long-term sepsis complications remains understudied. We hypothesize that primed immune responses to inflammatory stimuli in the lung after sepsis are associated with pulmonary complications in survivors of sepsis. To this end, we developed a model of antibiotic treated sepsis induced by cecal ligation and puncture followed three weeks later by secondary challenge with intranasal lipopolysaccharide to induce inflammatory lung injury. We find that mice surviving sepsis have enhanced lung injury responses in the setting of an exaggerated proinflammatory immune response, including primed Ly6Chi monocyte Tnf expression. Using RNA sequencing, we identified derangements in lung gene expression after CLP prior to LPS administration which may mediate enhanced lung injury in this model. One potential mediator, S100A8/A9, was also found to be elevated in the circulation of human sepsis survivors for up to 180 days after sepsis. These findings validate our model and identify S100A8/A9 as one of many potential biomarkers and therapeutic targets for patients at risk for long-term pulmonary complications after sepsis. The role of S100A8/A9, monocyte priming, and other factors predisposing to enhanced lung injury responses and pulmonary complications after sepsis warrant further investigation in humans and mice.

Dataset Information

Factors Related to Adverse Events in Colorectal Cancer

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure