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1.
Cancer Manag Res ; 14: 2933-2944, 2022.
Article in English | MEDLINE | ID: mdl-36200095

ABSTRACT

Background: Previous studies have shown that the levels of serum tumor markers CEA and CA19-9 were related to chemoradiotherapy. Therefore, it has been assumed that dynamic monitoring of these markers could predict the prognosis of stage II/III rectal cancer (RC). Therefore, this study proposed to evaluate the prognostic value of changes in serum tumor biomarkers for stage II/III RC patients undergoing neoadjuvant chemoradiotherapy (NCRT) followed by total mesorectal excision (TME). Methods: A total of 217 patients with stage II/III RC receiving NCRT followed by TME were retrospectively analyzed. Serum CEA and CA199 levels were measured within one week before NCRT and one week before TME. The optimal cut-off points of ∆CEA% and ∆CA199% for prognosis prediction were calculated by receiver operating characteristics (ROC) analysis. Independent prognostic predictors were identified by univariate and multivariate Cox regression analyses. To avoid the efficiency of ∆CEA% and ∆CA199% on serum tumor biomarker change (STBC) score, two models including and excluding ∆CEA% and ∆CA199% were established separately in multivariate analysis. Results: The optimal cut-off point for ∆CEA% and ∆CA199% were -30.29% and 20.30%, respectively. Univariate analysis showed that ∆CEA%, ∆CA199%, STBC score, ypT staging and yN staging could predict OS. ypT staging and STBC score could predict DFS. In multivariate analysis, only ∆CA199% (HR = 0.468, 95% CI: 0.220-0.994, p = 0.048), ypT staging (HR = 0.420, 95% CI: 0.182-0.970, p = 0.042), and STBC score (HR = 0.204, 95% CI: 0.078-0.532, p = 0.001) were independently related to OS; and STBC score (HR = 0.412, 95% CI: 0.216-0.785, p=0.007) and ypT staging (HR = 0.421, 95% CI: 0.224-0.792, p = 0.007) were independently related to DFS. Conclusion: We established a combined STBC score to predict the prognosis of stage II/III RC patients receiving NCRT followed by TME. The predictive value of the combined score was stronger than a single marker alone and even stronger than several pathological indicators.

2.
BMC Public Health ; 15: 277, 2015 Mar 21.
Article in English | MEDLINE | ID: mdl-25881035

ABSTRACT

BACKGROUND: The public reporting of health outcomes has become one of the most popular topics and is accepted as a quality improvement method in the healthcare field. However, little research has been conducted on the transparency mechanism, and results are mixed with regard to the evaluation of the effect of public reporting on quality improvement. The objectives of this trial are to investigate the transparency mechanism and to evaluate the effect of public reporting on prescription at the level of individual participants. METHODS/DESIGN: This study involves a cluster randomized controlled trial conducted in 20 primary-care facilities (clusters). Eligible clusters are those facilities with excellent hospital information systems and that have agreed to participate in the trial. The 20 clusters are matched into 10 pairs according to Technique for Order Preference by Similarity to Ideal Solution score. As the unit of randomization, each pair of facilities is assigned at random to a control or an intervention group through coin flipping. Prescribed ranking information is publicly reported in the intervention group. The public materials include the posters of individuals and of facilities, the ranking lists of general practitioners, and brochures of patients, which are updated monthly. The intervention began on 13th November 2013 and lasted for one year. Specifically, participants are surveyed at five points in time (baseline, quarterly following the intervention) through questionnaires, interviews, and observations. These participants include an average of 600 patients, 300 general practitioners, 15 directors, and 6 health bureau administrators. The primary outcomes are the transparency mechanism model and the changes in medicine-prescribe. Subsequently, the modifications in the transparency mechanism constructs are evaluated. The outcomes are measured at the individual participant level, and the professional who analyzes the data is blind to the randomization status. DISCUSSION: This study protocol outlines a design that aims to examine the transparency mechanism and to evaluate the effect of public reporting on prescription. The research design is significant in the field of public policy. Furthermore, this study intends to fill the gap of the investigation of the transparency mechanism and the evaluation of public reporting on prescription.


Subject(s)
Drug Prescriptions/statistics & numerical data , Population Surveillance/methods , Prescriptions/statistics & numerical data , Quality Improvement/statistics & numerical data , Cluster Analysis , Community Health Services , Humans , Information Dissemination , Quality Assurance, Health Care , Research Design
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