Middle school students in Wenchuan County (N = 354) were assessed 4.5 years after the Wenchuan earthquake to examine the effects of challenges to core beliefs, intrusive rumination, and deliberate rumination on posttraumatic stress disorder (PTSD) and posttraumatic growth (PTG). The results indicated that intrusive rumination partly mediated the relationship between challenges to core beliefs and PTSD, whereas deliberate rumination partly mediated both the relationship between challenges to core beliefs and PTG, as well as the relationship between intrusive rumination and PTG. These findings suggest that challenges to core beliefs had a direct positive impact on both PTSD and PTG. Moreover, such challenges predicted PTSD through intrusive rumination and predicted PTG through deliberate rumination. Furthermore, intrusive rumination might cue individuals to engage in a more purposive deliberate rumination process. These results indicate that PTSD and PTG are influenced by different mechanisms and that PTSD and PTG represent 2 separate dimensions of experience following adversity.

Indians had the highest prevalence of diabetes among Asian countries. The age at which the peak prevalence of diabetes was reached was approximately 10 years younger in Indian compared with Chinese and Japanese subjects. Diabetes and IGR will be underestimated in Asians based on the fasting glucose testing alone.

Young age (≤40 years) use to be considered an independent risk factor for the prognosis of women with early-stage breast cancer. We conducted a retrospective analysis to investigate this claim in a population of young patients who were stratified by molecular subtype. We identified 2,125 women with stage I to III breast cancer from the Fujian Medical University Union Hospital. Multivariable Cox proportional hazards models were used to analyze the relationship between age groups stratified by molecular subtype and 5-year disease-free survival (DFS), 5-year distant metastasis-free survival (DMFS), and 5-year breast cancer-specific survival (BCSS). Median follow-up time was 77 months. Patients ≤40 years of age presented with a significantly worse 5-year DFS and 5-year DMFS. In stratified analyses, young women with luminal A subtype disease were associated with a worse 5-year DFS, 5-year DMFS, and 5-year BCSS. Women with luminal B (Her2−) tumors showed a decrease in 5-year DFS and 5-year DMFS. Our findings support the hypothesis that young age seems to be an independent risk factor for the prognosis for breast cancer patients with the luminal A and luminal B (Her2−) subtypes but not in those with luminal B (Her2+), Her2 over-expression, and triple-negative disease.

The notion of personalized medicine demands proper prognostic biomarkers to guide the optimal therapy for an invasive breast cancer patient. However, various risk prediction models based on conventional clinicopathological factors and emergent molecular assays have been frequently limited by either a low strength of prognosis or restricted applicability to specific types of patients. Therefore, there is a critical need to develop a strong and general prognosticator. Methods: We observed five large-scale tumor-associated collagen signatures (TACS4-8) obtained by multiphoton microscopy at the invasion front of the breast primary tumor, which contrasted with the three tumor-associated collagen signatures (TACS1-3) discovered by Keely and coworkers at a smaller scale. Highly concordant TACS1-8 classifications were obtained by three independent observers. Using the ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8 and established a risk prediction model based on the TACS-score. In a blind fashion, consistent retrospective prognosis was obtained from 995 breast cancer patients in both a training cohort ( n = 431) and an internal validation cohort ( n = 300) collected from one clinical center, and in an external validation cohort ( n = 264) collected from a different clinical center. Results: TACS1-8 model alone competed favorably with all reported models in predicting disease-free survival (AUC: 0.838, [0.800-0.872]; 0.827, [0.779-0.868]; 0.807, [0.754-0.853] in the three cohorts) and stratifying low- and high-risk patients (HR 7.032, [4.869-10.158]; 6.846, [4.370-10.726], 4.423, [2.917-6.708]). The combination of these factors with the TACS-score into a nomogram model further improved the prognosis (AUC: 0.865, [0.829-0.896]; 0.861, [0.816-0.898]; 0.854, [0.805-0.894]; HR 7.882, [5.487-11.323]; 9.176, [5.683-14.816], and 5.548, [3.705-8.307]). The nomogram identified 72 of 357 (~20%) patients with unsuccessful 5-year disease-free survival that might have been undertreated postoperatively. Conclusions: The risk prediction model based on TACS1-8 considerably outperforms the contextual clinical model and may thus convince pathologists to pursue a TACS-based breast cancer prognosis. Our methodology identifies a significant portion of patients susceptible to undertreatment (high-risk patients), in contrast to the multigene assays that often strive to mitigate overtreatment. The compatibility of our methodology with standard histology using traditional (non-tissue-microarray) formalin-fixed paraffin-embedded (FFPE) tissue sections could simplify subsequent clinical translation.

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