RESUMO
BACKGROUND: For patients and intimate partners, the challenge of advanced cancer is often compounded by difficulties in effectively communicating about disease treatment. Relevant evidence-based data are limited, in part because of limitations in understanding the dynamics of dyad-based communication. OBJECTIVES: This pilot study targeted development/feasibility testing of a practical model for assessment of these dynamics in a small group of cancer patients and their intimate partners, with a focus on communication before/after cancer diagnoses, including end-of-life discussions. METHODS: A descriptive phenomenological design was based on the Bodenmann systemic-transactional model of dyadic coping and on semistructured interviews with 7 dyads. Qualitative data analysis used the Colaizzi 7-step method for narrated text interpretation and identification of emergent themes. RESULTS: Patients (median age, 59 years; median intimate partner age, 52 years) had been given a diagnosis of cancer 0 to 6 months before enrollment and were receiving active therapy during participation. Of 534 significant statements analyzed, 2 emergent themes were identified: (1) vulnerable communication during advanced cancer is influenced by preexisting dynamics and complicated by balancing hope/positivity and uncertainty/fear, and (2) communications about end-of-life issues are emotional and influenced by dyad member perceptions about death. A study with a broader racial/demographic representation is planned. CONCLUSION: It is feasible to study dyad communication in the advanced cancer setting, and preliminary data suggest the importance of these dynamics in expression of clinical preferences. IMPLICATIONS FOR PRACTICE: Structured interviews with dyads during advanced cancer care can be used to identify specific challenges and inform improved support approaches.
RESUMO
BACKGROUND: The increasing number of genomic sequences of bacteria makes it possible to select unique SNPs of a particular strain/species at the whole genome level and thus design specific primers based on the SNPs. The high similarity of genomic sequences among phylogenetically-related bacteria requires the identification of the few loci in the genome that can serve as unique markers for strain differentiation. PrimerSNP attempts to identify reliable strain-specific markers, on which specific primers are designed for pathogen detection purpose. RESULTS: PrimerSNP is an online tool to design primers based on strain specific SNPs for multiple strains/species of microorganisms at the whole genome level. The allele-specific primers could distinguish query sequences of one strain from other homologous sequences by standard PCR reaction. Additionally, PrimerSNP provides a feature for designing common primers that can amplify all the homologous sequences of multiple strains/species of microorganisms. PrimerSNP is freely available at http://cropdisease.ars.usda.gov/~primer. CONCLUSION: PrimerSNP is a high-throughput specific primer generation tool for the differentiation of phylogenetically-related strains/species. Experimental validation showed that this software had a successful prediction rate of 80.4 - 100% for strain specific primer design.
