Dataset Information

Information With or Without Numbers For Optimizing Reasoning About Medical Decisions

ABSTRACT: Experts believe that increasing the low uptake of screening for colorectal cancer (CRC) requires educating patients about all approved tests and helping them choose one that fits their preferences. As one motto puts it: "The best test is the one that gets done." Screening tests range from more invasive and very sensitive for polyps and cancer (colonoscopy) to less invasive and less sensitive (e.g., fecal immunochemical testing (FIT)). But it is unclear how best to educate patients about the options and the tradeoffs involved. Some guidelines recommend that decision aids, a promising tool in this area, provide patients with detailed quantitative information, including baseline risk, risk reduction, and chance of negative outcomes. But this sort of "comparative effectiveness" data can confuse patients, especially those with limited mathematical ability. Previous studies have not measured the effect of providing quantitative information to patients with varying levels of ability or interest or asked them whether such data is essential for their decision-making. The investigators will conduct a clinical trial to determine the impact on patients who view a decision aid (DA) that includes quantitative information versus a DA without such data. The investigators will also seek to determine whether numeracy moderates the effect of quantitative information.

DISEASE(S): Colorectal Neoplasms,Colorectal Cancer Screening

PROVIDER: 2192578 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Similar Datasets

Project description:Fifty thousand people die from colorectal cancer (CRC) every year, making it the second leading cause of death from cancer in the United States. And although there are multiple screening tests that reduce the morbidity and mortality of this disease, less than 60% of eligible individuals are up to date with recommended screening. One of the challenges to improving screening is helping patients understand the range of approved tests, including colonoscopy, sigmoidoscopy, and stool testing (such as fecal immunochemical testing (FIT)). Patients rarely consider all their options, partly due to the limited time they have to learn about them during busy doctor’s visits. Computer-based presentations, including decision aids, are a promising tool for improving patient understanding in this and other areas, by giving patients significant amounts of information. But there are important questions about how to design such presentations, including whether they should provide quantitative data about the risks and benefits of screening. Some experts feel that these numbers and graphs are necessary for fully informed decision-making, while others are concerned that they may confuse patients or dissuade them from screening. The investigators have created and pilot tested a computer-based presentation of quantitative information about CRC screening. The investigators found that subjects who viewed the program in a non-healthcare setting exhibited significantly increased interest in screening. In addition, the investigators tested a version of the program that includes a "nudge" towards stool testing with FIT, as a way of encouraging individuals who are confused to undergo some form of screening. In our testing, receiving the nudge was associated with a significant increase in interest in FIT. The investigators now seek to conduct a randomized, controlled study of our computer-based presentation with Clarian patients who are due for CRC screening. All subjects will first view a general video about CRC screening and then will be randomly placed into four groups (using a 2x2 design), to receive quantitative information (or not), and a nudge towards FIT (or not). The results will determine whether a presentation of quantitative information can increase patient understanding, quality of decision-making, and uptake of CRC screening. The results will serve as pilot data for a larger, externally funded study of the effect of individualized ("personalized") quantitative information in this area

Project description:About one-third of oestrogen receptor alpha- positive breast cancer patients treated with tamoxifen relapse. Here we identify the nuclear receptor retinoic acid receptor alpha as a marker of tamoxifen resistance. Using quantitative mass spectrometry-based proteomics, we show that retinoic acid receptor alpha protein networks and levels differ in a tamoxifen-sensitive (MCF7) and a tamoxifen-resistant (LCC2) cell line. High intratumoural retinoic acid receptor alpha protein levels also correlate with reduced relapse-free survival in oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen solely. A similar retinoic acid receptor alpha expression pattern is seen in a comparable independent patient cohort. An oestrogen receptor alpha and retinoic acid receptor alpha ligand screening reveals that tamoxifen-resistant LCC2 cells have increased sensitivity to retinoic acid receptor alpha ligands and are less sensitive to oestrogen receptor alpha ligands compared with MCF7 cells. Our data indicate that retinoic acid receptor alpha may be a novel therapeutic target and a predictive factor for oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen. Peptide and protein identification data set 1: Peptide identification from the MALDI-TOF/TOF data was carried out using the Paragon algorithm in the ProteinPilot 2.0 software package (Applied Biosystems) 46. Default settings for a 4800 instrument were used (i.e., no manual settings for mass tolerance was given). The following parameters were selected in the analysis method: iTRAQ 4plex peptide labelled as sample type, MMTS as alkylating agent of cysteine, trypsin as digesting enzyme, 4800 as instrument, gel based ID and Urea denaturation as special factors, biological modifications as ID focus, and thorough ID as search effort. Peptide identification from the Q-TOF data was carried out using the Spectrum Mill Protein Identification software (Agilent). Data was extracted between MH+ 600 and 4000 Da (Agilent's definition). Scans with the same precursor m/z 90 sec, 0.05 m/z matching with a minimum of 20 peaks in MS2 were merged. Peptide and protein identification data set 2: Proteome discoverer 1.3 with sequest-percolator was used for protein identification. Precursor mass tolerance was set to 10 ppm and for fragments 0.8 Da and 0.02 Da were used for detection in the linear iontrap and the orbitrap, respectively. Oxidized methionine and phosphorylation on S,T and Y was set as dynamic modifications, and carbamidomethylation, N-terminal 8plex iTRAQ, and lysyl 8plex iTRAQ as fixed modifications. Spectra were matched to ensembl 68 limited to human protein sequences, and results were filtered to 1% FDR.

Project description:Context : Non Functioning Pituitary Adenomas (NFPAs), although typically benign, may be locally invasive. Few datas are currently available related to the molecular process of invasion in sporadic pituitary adenomas. Markers of invasiveness, important for helping the clinician in the therapeutic strategy particularly in the decision for adjuvant radiotherapy, are currently lacking. Objective: Evaluate if invasive NFPAs display a specific expression profile compared with non invasive tumors. Methods: To address this issue, we selected 40 NFPAs (38 of the gonadotroph type) and classified them as invasive (n=22) or non invasive (n=18) on the basis of MRI and surgical findings. Then we performed pangenomic analysis based on Agilent Human Whole genome Gene Expression oligonucleotide microarray (44k) Expression in order to identify genes differentially expressed between invasive and non invasive NFPA. Experiements are made in dual color with tumor samples labelled in cyanine 5 and a pool of all tumors labelled in cyanine 3.The expressions of some genes identified by microarray screening were confirmed by real-time quantitative RT-PCR. The selection of genes was made on the basis of Ingenuity networks and degree of upregulation between invasive and non invasive tumors. Moreover, some genes of interest already described in the literature were added to the analysis. Results: Prediction class analysis showed that 346 genes discriminated between invasive and non invasive NFPAs (p<0.001); 233 were up- and 113 were down-regulated between the two groups. We then tested On the basis of Ingenuity networks and degree of upregulation between invasive and non invasive tumors, a set of eight genes, including MYO5A, IGFBP5, FLT3, NFE2L1, PTTG, MMP9, NCAM and NR1H3, was tested in quantitative PCR analysis and. Results confirmed those obtained in microarrays results.analysis. At the protein level, Myosin 5A (MYO5A) demonstrated stronger immunostaining in invasive NFPAs compared to non invasive NFPAs. Conclusions: We propose a molecular signature of eight genes of grossly invasive NFPAs as compared with non invasive tumors: The product of one of these genes, MYO5A, may be a useful marker of invasive process in tumoral specimens. The role of these genes in the invasiveness process and as prognostic markers of pituitary adenomas needs to be confirmedinvestigated. Method: Microarray analyses the transcriptome of 22 invasive Non Functional Pituitary Adenomas (NFPAs) and 18 non invasive NFPAs in dual color (each sample labelled in cyanine 5 and a pool of all tumors labelled in cyanine 3).

Dataset Information

Information With or Without Numbers For Optimizing Reasoning About Medical Decisions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets