Factors associated with low cure rate of tuberculosis in remote poor areas of Shaanxi Province, China: a case control study

<p>Abstract</p> <p>Background</p> <p>The directly observed therapy-short course (DOTS) strategy was introduced in Shaanxi province, China to improve tuberculosis (TB) control by means of improved case detection (target: > = 70%) and treatment success rates (target: > = 85%) in new smear positive (SS+) TB patients. At a provincial level the targets were both reached in 2005. However in 30 (28%) out of 107 counties of Shaanxi province the cure rate was below 85%. This study aimed to investigate patient and treatment characteristics associated with non-cure after tuberculosis (TB) treatment in these counties.</p> <p>Methods</p> <p>In this case-control study, new smear positive TB cases in 30 counties with a cure rate <85% were included. Cured patients were compared to non-cured patients using logistic regression analysis to assess determinants for non-cure.</p> <p>Results</p> <p>Of the 659 patients included, 153 (23.2%) did not have cure as treatment outcome. Interruption of treatment was most strongly associated with non-cure (OR = 8.7, 95% CI 3.9-18.4). Other independent risk factors were co-morbidity, low education level, lack of appetite as an initial symptom of TB disease, diagnosis of TB outside of the government TB control institutes, missing sputum re-examinations during treatment, and not having a treatment observer. Twenty-six percent of patients did not have a treatment observer. The non-cure rate was better for those with a doctor (odds ratio (OR) 0.38, 95% confidence interval (CI) 0.17-0.88) as treatment observer than for those with a family member (OR 0.62, 95%CI 0.37-1.03). The main reason for interrupted treatment mentioned by patients was presence of adverse effects during treatment (46.5%).</p> <p>Conclusions</p> <p>Interruption of treatment was most strongly associated with non-cure. Although treatment observation by medical staff is preferred, in order to diminish the proportion of patients who do not have a treatment observer and thereby reduce the proportion of patients who interrupt treatment, we suggest making it possible for family members, after sufficient training, to be treatment observers in remote areas where it is logistically difficult to have village doctors observe treatment for all patients.</p

Improving detection and notification of tuberculosis cases in students in Shaanxi province, China: an intervention study

<p>Abstract</p> <p>Background</p> <p>Cooperation between different public and private health institutes involved in tuberculosis (TB) control has proven to enhance TB control in different settings. In China, such a mechanism has not been set up yet between Centers for Disease Control (CDCs) and university hospitals despite an increased TB incidence among students. This study aims to improve arrival of TB suspects identified by universities at the CDCs in order to manage them under standardized, directly observed treatment-short course (DOTS) conditions according to the National Tuberculosis Programme (NTP) guidelines.</p> <p>Methods</p> <p>Five matched pairs of universities were randomly assigned to the control and intervention group. After a baseline survey, a cooperation mechanism between local CDCs and university hospitals was set up in the intervention group. The effects on referral of TB suspects to the local CDC, tracing by the local CDC, and arrival at the local CDCs were assessed. Differences were tested by means of the chi-square test.</p> <p>Results</p> <p>During the baseline survey, the referral, tracing and arrival rates were between 37% and 46%. After implementation of the cooperation mechanism, these rates had not changed in the control group but increased significantly in the intervention group: the referral, tracing and arrival rates were 97%, 95%, and 93%, respectively.</p> <p>Conclusions</p> <p>It is feasible and effective to set up cooperation between CDCs and university hospitals to increase the number of TB suspects examined by CDCs and increase the number of TB patients treated under DOTS conditions. These public-public mix (PPM) activities should be expanded to cover all other university hospitals in China.</p

Resistance prediction in high‐grade serous ovarian carcinoma with neoadjuvant chemotherapy using data‐independent acquisition proteomics and an ovary‐specific spectral library

High‐grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5‐year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced‐stage HGSOC unsuitable for primary debulking surgery (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability. Here, we built a high‐quality ovary‐specific spectral library containing 130 735 peptides and 10 696 proteins on Orbitrap instruments. Compared to a published DIA pan‐human spectral library (DPHL), this spectral library provides 10% more ovary‐specific and 3% more ovary‐enriched proteins. This library was then applied to analyze data‐independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10 070 quantified proteins, which is 9.73% more than that with DPHL. We further established a six‐protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance to additional chemotherapy after IDS (Log‐rank test, P = 0.002). The classifier was validated with 57 patients from an independent clinical center (P = 0.014). Thus, we have developed an ovary‐specific spectral library for targeted proteome analysis, and propose a six‐protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT‐IDS treatment