Pengaruh Komunikasi Terapeutik Perawat Terhadap Kepuasan Pasien Di Rawat Jalan RSUD Jogja

The Objective of this study is to know influence of nurse therapeutic communication to satisfaction of patients satisfaction in RSUD Yogyakarta. The study was a quantitative research methods such as surveys of descriptive inferential research with cross sectional approach. Number of samples in this research is 285 sample in inpatient and 140 in emergency room. The instrument used a questionnaire. Analysis of data using multiple linear regression. This study show that there is the influence of therapeutic communication nurse to satisfaction of outpatients and Emergency room in RSUD Yogyakarta, and orientation phase is a phase that most influence on patient satisfaction. The most influential to therapeutic communication is termination stage

Clinical Significance of MLH1 Methylation and CpG Island Methylator Phenotype as Prognostic Markers in Patients with Gastric Cancer

<div><p>Background</p><p>To improve the outcome of patients suffering from gastric cancer, a better understanding of underlying genetic and epigenetic events in this malignancy is required. Although CpG island methylator phenotype (CIMP) and microsatellite instability (MSI) have been shown to play pivotal roles in gastric cancer pathogenesis, the clinical significance of these events on survival outcomes in patients with gastric cancer remains unknown.</p><p>Methods</p><p>This study included a patient cohort with pathologically confirmed gastric cancer who had surgical resections. A cohort of 68 gastric cancers was analyzed. CIMP and MSI statuses were determined by analyzing promoter CpG island methylation status of 28 genes/loci, and genomic instability at 10 microsatellite markers, respectively. A Cox’s proportional hazards model was performed for multivariate analysis including age, stage, tumor differentiation, <i>KRAS</i> mutation status, and combined CIMP/<i>MLH1 </i>methylation status in relation to overall survival (OS).</p><p>Results</p><p>By multivariate analysis, longer OS was significantly correlated with lower pathologic stage (<i>P</i> = 0.0088), better tumor differentiation (<i>P</i> = 0.0267) and CIMP-high and <i>MLH1 3'</i> methylated status (<i>P</i> = 0.0312). Stratification of CIMP status with regards to <i>MLH1</i> methylation status further enabled prediction of gastric cancer prognosis.</p><p>Conclusions</p><p>CIMP and/or <i>MLH1</i> methylation status may have a potential to be prognostic biomarkers for patients with gastric cancer.</p></div

Relationship between CIMP and <i>MLH1</i> methylation.

<p><b>a) Tile map showing methylation pattern</b>. Twenty eight loci (<i>APC</i>, <i>CACNA1G</i>, <i>CHFR</i>, <i>COX2</i>, <i>DAPK</i>, <i>DCC</i>, <i>HPP1</i>, <i>MGMT-Mp region</i>, <i>MGMT-Eh region</i>, <i>MINT1</i>, <i>MINT2</i>, <i>MINT31</i>, <i>MLH1 5'</i>, <i>MLH1 3'</i>, <i>p14</i>, <i>p16</i>, <i>RASSF1A</i>, <i>RASSF2A-region1</i>, <i>RASSF2A-region2</i>, <i>RASSF3</i>, <i>RASSF5</i>, <i>RASSF6</i>, <i>RUNX3</i>, <i>SFRP2-region1</i>, <i>SFRP2-region2</i>, <i>UNC5C</i>, <i>3OST2</i>, <i>FOXL2</i>) were analyzed to determine CIMP status. Thirty patients with not less than ten methylated loci were identified as the CIMP-high group. <b>b) Venn diagram showing the overlap of <i>MLH1</i> 3' methylation and CIMP status</b>. The overlapping relationship between <i>MLH1 3'</i> methylation and CIMP status was analyzed. 10 patients were in the combined in the CIMP-high/<i>MLH1 3'</i> methylated (A), 1 patients were in the CIMP-low/<i>MLH1 3'</i> methylated (B), 20 patients were in the CIMP high/<i>MLH1 3'</i> non-methylated (C), and 37 patients were in the CIMP-low/<i>MLH1 3'</i> non-methylated groups (D). <b>c) Kaplan–Meier estimate of OS in patients with <i>MLH1</i> 3' methylated or non-methylated gastric cancers</b>. Kaplan–Meier survival curves were generated according to <i>MLH1 3'</i> methylation status. The 5-year survival rates were analyzed for the <i>MLH1 3'</i> methylated and non-methylated groups. The survival rate was significantly higher in the <i>MLH1 3'</i> methylated group than in the non-methylated group (log-rank <i>P</i> = 0.0257). <b>d) Kaplan–Meier estimate of OS in patients with CIMP-high or CIMP-low gastric cancers</b>. Kaplan–Meier survival curves were generated according to CIMP status. The 5-year survival rate was analyzed for the CIMP-high group and CIMP-low group. The survival rate was slightly higher in the CIMP-high group than in the CIMP-low group, but the difference was not significant (log-rank <i>P</i> = 0.0688). <b>e) Contribution of CIMP and mismatch repair deficiency status to survival rate</b>. Kaplan–Meier survival curves were generated according to CIMP and <i>MLH1</i> methylation status. The patients were classified on the basis of combined CIMP status and <i>MLH1</i> methylation status into the CIMP-high/<i>MLH1 3'</i> methylated (A), CIMP-low/<i>MLH1 3'</i> methylated (B), CIMP high/<i>MLH1 3'</i> non-methylated (C), and CIMP-low/<i>MLH1 3'</i> non-methylated groups (D). Overall survival rates were higher in the combined CIMP-high/<i>MLH1 3'</i> methylated group, compared to the other groups where the differences were not statistically significant (log-rank <i>P</i> = 0.0706).</p

Multivariate analysis of outcome predictors.

<p>* P < 0.05,</p><p>** P < 0.01,</p><p>*** P < 0.001</p><p>Multivariate analysis of outcome predictors.</p

Methylation features according to CIMP status.

<p>* P < 0.05,</p><p>** P < 0.01,</p><p>*** P < 0.001</p><p>Methylation features according to CIMP status.</p

Clinicopathological features of the patients according to CIMP status.

<p>* P < 0.05,</p><p>*** P < 0.001</p><p>Clinicopathological features of the patients according to CIMP status.</p

The relationship between <i>MLH1</i> methylation and MSI.

<p><b>a) Venn diagram showing the overlap of MLH1 5' methylation and 3' methylation status</b>. The overlapping relationship between <i>MLH1 5'</i>—and <i>3'</i> methylation status was analyzed. 10 patients were in the <i>MLH1 5'</i> methylated/<i>3'</i> methylated (A), 8 patients were in the <i>MLH1 5'</i> methylated/<i>3'</i> non-methylated (B), 1 patient was in the <i>MLH1 5'</i> non-methylated/<i>3'</i> methylated (C), and 49 patients were in the <i>5'</i> non-methylated/<i>3'</i> non-methylated groups (D). <b>b) The relationship between <i>MLH1</i> methylation and MSI</b>. In the <i>MLH1 3'</i> methylated group, >80% cases showed MSI. In contrast, in the <i>MLH1 3'</i> non-methylated group, almost all cases showed MSS. <b>c) Kaplan–Meier estimate of OS in patients with <i>MLH1</i> 5' methylated or non-methylated gastric cancer</b>. Kaplan–Meier survival curves were generated according to <i>MLH1 5'</i> methylation status. The 5-year survival rate was analyzed for the <i>MLH1 5'</i> group and non-methylated groups. The survival rate was slightly higher in the <i>MLH1 5'</i> methylated group than in the non-methylated group but the difference was not significant (log-rank <i>P</i> = 0.1009). <b>d) Kaplan–Meier estimate of OS in patients with MSI or MSS gastric cancer</b>. Kaplan–Meier survival curves were generated according to MSI status. The 5-year survival rate was analyzed for the MSI group and MSS group. The survival rate was slightly higher in the MSI group than in the non-methylated group but the difference was not significant (log-rank <i>P</i> = 0.1316).</p

Additional file 4: Figure S3. of Predictive biomarkers for the efficacy of peptide vaccine treatment: based on the results of a phase II study on advanced pancreatic cancer

Frequency of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells. (a), (c) There were no differences in the percentages of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells in the 46 patients before and after treatment. (b), (e) Before and after treatment, there were no differences in the percentages of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells between the patients with a long survival (n = 6) and the patients with a short survival (n = 19) in the HLA-A*2402-matched group. (c), (f) Before and after treatment, there were no differences in the percentages of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells between the patients with a long survival (n = 6) and the patients with a short survival (n = 15) in the HLA-A*2402-unmatched group. (TIF 60 kb

Additional file 2: Table S1. of Predictive biomarkers for the efficacy of peptide vaccine treatment: based on the results of a phase II study on advanced pancreatic cancer

Comparison of prognostic factors according to the numbers of peptide-specific responses (n = 36 HLA-A*2402-matched patients). (DOCX 28 kb