Association between dietary intake of saturated fatty acid subgroups and breast cancer risk.

The impact of dietary saturated fatty acids (SFAs) on breast cancer risk may vary depending on their carbon chain lengths, attributable to the discrepancy in their dietary sources and biological activities. The associations between SFA subgroups classified by chain length and breast cancer risk remain controversial. In this case-control study, we aimed to investigate the association between the dietary intake of SFA subgroups, classified by chain lengths, and odds of breast cancer in China. This study included 1661 cases of breast cancer (confirmed as primary and histologically) and 1674 frequency-matched controls. Face-to-face interviews were used to collect basic information, while dietary intake information was obtained by a food frequency questionnaire. The unconditional logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (95% CIs). All SFA subgroups were inversely associated with odds of breast cancer. The adjusted ORs (95% CIs) were 0.78 (0.61-0.99) for medium-chain SFAs, 0.50 (0.31-0.83) for long even-chain SFAs, 0.69 (0.54-0.88) for long odd-chain, and 0.67 (0.48-0.95) for very long-chain SFAs, respectively. In the restricted cubic spline (RCS) models, a non-linear M-shaped association was observed between long odd-chain SFAs and odds of breast cancer (Pnon-linearity = 0.007). However, the associations of medium-chain SFAs, long even-chain SFAs, and very long-chain SFAs did not reach statistical significance (Pnon-linearity > 0.05). No significant interactions were observed between all these four subgroups of SFAs and menopausal status or BMI. Our findings emphasize the significance of elucidating the associations of dietary SFAs according to chain lengths, providing insights into the etiology as well as the potential benefits of SFA-rich food intake in reducing the risk of breast cancer. Further prospective cohort studies and intervention studies are warranted to confirm these findings and identify the underlying mechanisms of the association between dietary SFAs and breast cancer.

Modelled Economic Analysis for Dacomitinib-A Cost Effectiveness Analysis in Treating Patients With EGFR-Mutation-Positive Non-Small Cell Lung Cancer in China.

OBJECTIVES: To establish the cost-effectiveness of dacomitinib compared to gefitinib from the Chinese healthcare system perspective. PATIENTS: Advanced non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. METHODS: Partitioned survival analysis was undertaken to examine the cost-effectiveness of dacomitinib utilising individual patient data (IPD) from the pivotal randomised controlled trial (RCT) (ARCHER 1050). The three health states modelled were progression-free, post-progression, and death. Parametric survival distributions were fitted to IPD against the Kaplan-Meier survival curves corresponding to progression-free survival (PFS) and overall survival (OS) outcomes by randomised groups. Costs included drug acquisition and administration, outpatient management (outpatient consultation and examinations), and best supportive care costs. Utility weights were sourced from the pivotal trial and other published literature. The incremental cost-effectiveness ratio (ICER) was calculated with costs and quality-adjusted life years (QALYs) discounted at an annual rate of 5%. Both deterministic and probabilistic sensitivity analyses were undertaken. RESULTS: In the base case, dacomitinib (CNY 265,512 and 1.95 QALY) was associated with higher costs and QALY gains compared to gefitinib (CNY 247,048 and 1.61 QALYs), resulting in an ICER of CNY 58,947/QALY. Using the empirical WTP/QALY threshold, dacomitinib is a cost-effective treatment strategy for patients with EGFR-mutation-positive advanced NSCLC. The probabilistic sensitivity analysis suggested that dacomitinib had a 97% probability of being cost-effective. CONCLUSIONS: Dacomitinib is a cost-effective treatment strategy in treating patients with EGFR-mutation-positive NSCLC from the Chinese healthcare system perspective. The uncertainty around the cost-effectiveness of dacomitinib could be reduced if long-term survival data become available. CLINICAL TRIAL REGISTRATION: NCT01024413.

Identification of microRNAs for the early diagnosis of Parkinson's disease and multiple system atrophy.

MicroRNAs are reportedly involved in the pathogenesis of neurodegenerative diseases, including Parkinson's disease and multiple system atrophy. We previously identified 7 differentially expressed microRNAs in Parkinson's disease patients and control sera (miR-30c, miR-31, miR-141, miR-146b-5p, miR-181c, miR-214, and miR-193a-3p). To investigate the expression levels of the 7 serum microRNAs in Parkinson's disease and multiple system atrophy, 23 early Parkinson's disease patients (who did not take any anti- Parkinson's disease drugs), 23 multiple system atrophy patients, and 24 normal controls were recruited at outpatient visits in this study. The expression levels of the 7 microRNAs in serum were detected using quantitative real-time polymerase chain reaction. A receiver operating characteristic curve was used to evaluate whether microRNAs can differentially diagnose Parkinson's disease and multiple system atrophy. Clinical scales were used to analyze the correlations between serum microRNAs and clinical features. The results indicated that miR-214 could distinguish Parkinson's disease from the controls, and another 3 microRNAs could differentiate multiple system atrophy from the controls (miR-141, miR-193a-3p, and miR-30c). The expression of miR-31, miR-141, miR-181c, miR-193a-3p, and miR-214 were lower in multiple system atrophy than in Parkinson's disease (all P < 0.05). Combinations of microRNAs accurately discriminated Parkinson's disease from multiple system atrophy (area under the receiver operating characteristic curve = 0.951). For the correlation analysis, negative correlations were discovered between the expression of miR-214 and the Hamilton Anxiety Scale and Parkinson's Disease Non-Motor Symptom scores (all P < 0.05). Our results demonstrate that the distinctive characteristics of microRNAs differentiate Parkinson's disease and multiple system atrophy patients from healthy controls and may be used for the early diagnosis of Parkinson's disease and multiple system atrophy.