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Background: We aimed to systematically summarize the diagnostic and prognostic value of circulating/tissue miR21 in patients with colorectal cancer.Methods: An original study was conducted to explore the potential value of circulating miR21 in colorectal cancer diagnosis and tissue miR21 in colorectal cancer prognosis. PUBMED and EMBASE were searched (to August, 2013) to identify eligible studies. To explore the diagnostic performance of circulating miR21, meta-analysis methods were used to pool sensitivity, specificity, positive and negative likelihood ratio, diagnostic OR and to construct a summary ROC curve. For prognostic meta-analysis, study-specific HRs of tissue miR21 for survival were summarized. Subgroup and sensitivity analyses were applied to explore heterogeneity.Results: Finally, 14 studies (including our study) were included in the meta-analyses. The pooled sensitivity, specificity, and AUC of circulating miR21 were 0.76 [95% confidence interval (CI), 0.59–0.88], 0.81 (95% CI, 0.76–0.85), and 0.81 (95% CI, 0.78–0.85) in diagnosing colorectal cancer. Patients with higher expression of tissue miR21 had significant inferior overall survival (OS; pooled HR, 1.56; 95% CI, 1.16–2.11) and disease-free survival (DFS; pooled HR, 1.35; 95% CI, 1.08–1.69). The individual participant data (IPD) meta-analysis demonstrated that tissue miR21 level was independently associated with worse colorectal cancer OS (HR, 1.69; 95% CI, 1.07–2.67; P = 0.023), whereas this association seems to be confined to males (P = 0.007) but not for females (P = 0.845).Conclusions: Circulating miR21 level has potential value for colorectal cancer early detection, whereas high tissue miR21 level is associated with adverse colorectal cancer prognosis.Impact: miR21 is a promising biomarker for early detection and prognosis of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 23(12); 2783–92. ©2014 AACR.

Supplementary Table 1 Instrument used for the evaluation of the risk of bias and applicability concerns of the included prognostic studies (adapted from QUADAS-2). Supplementary Table 2 Characteristics of studies included in the diagnostic meta-analysis. Supplementary Table 3 Characteristics of studies included in the prognostic meta-analysis. Supplementary Table 4 Quality assessment of the included diagnostic studies according to QUADAS-2. Supplementary Table 5 Risk of bias and applicability concerns of included prognostic studies. Supplementary Table 6 Methodological quality of included prognostic studies according to STROBE criteria. Supplementary Figure 1 Receiver operating characteristic curves of plasma miR-21 for discrimination CRC patients from controls. Supplementary Figure 2 Kaplan–Meier curve of tissue miR-21 expression in relation to the survival of CRC patients in the original study. Supplementary Figure 3 Funnel plots of the meta-analyses (A) Funnel plot of tissue miR-21 and CRC OS (B) Funnel plot of tissue miR-21 and CRC DFS (3) Funnel plot of circulating miR-21 and CRC diagnosis. PRISMA Checklist.

Background Nearly 15% colorectal cancer (CRC) patients received ileostomy, while surgical site infection (SSI) is a common complication after ileostomy wound closure. Purse-string closure was reported to reduce SSI rate in ileostomy wound closure compared with conventional linear closure, but had never been systematically reported in CRC patients. The present study aimed to compare the short-term outcomes between purse-string and conventional closure in Chinese CRC patients. Patients and methods A total of 57 CRC patients underwent ileostomy wounds closure in the Second Affiliated Hospital of Zhejiang University during November, 2015 and October, 2017 were retrospectively reviewed. Twenty-nine received purse-string closure while the others received conventional closure. The short-term outcomes including SSI rate, scar length, pain score and hospital stay were reviewed and analyzed. Results There were no significant differences in the characteristics of the patients between two groups. The SSI rate was similar within two groups (10.3% vs 10.7%, p = 1.000). The purse-string closure group had a significantly short scar length (1.66 cm vs 5.30 cm, p Conclusion The present study did not find superiority of Purse-string closure in SSI rate control. It seemed only had a cosmetic effect according to its shorter scar length.

Background and purpose Ki-67 labeling index (LI) is an important indicator of tumor cell proliferation in glioma, which can only be obtained by postoperative biopsy at present. This study aimed to explore the correlation between Ki-67 LI and apparent diffusion coefficient (ADC) parameters and to predict the level of Ki-67 LI noninvasively before surgery by multiple MRI characteristics. Methods Preoperative MRI data of 166 patients with pathologically confirmed glioma in our hospital from 2016 to 2020 were retrospectively analyzed. The cut-off point of Ki-67 LI for glioma grading was defined. The differences in MRI characteristics were compared between the low and high Ki-67 LI groups. The receiver operating characteristic (ROC) curve was used to estimate the accuracy of each ADC parameter in predicting the Ki-67 level, and finally a multivariate logistic regression model was constructed based on the results of ROC analysis. Results ADCmin, ADCmean, rADCmin, rADCmean and Ki-67 LI showed a negative correlation (r = − 0.478, r = − 0.369, r = − 0.488, r = − 0.388, all P P P Conclusions There was a negative correlation between ADC parameters and Ki-67 LI, and the multivariate logistic regression model combined with peritumoral edema and ADC parameters could improve the prediction ability of Ki-67 LI.

The identification of high recurrence risk stage II colon cancer patients was critical to adjuvant chemotherapy decision. However, current definition of high-risk features remains inadequate. This study aimed to construct a model for predicting recurrence risk based on tumor enhancement ratio (TER) on abdominal contrast-enhanced CT scan.282 stage II colon cancer patients were included and randomly divided into training and validation sets in the ratio of 7:3. TER was calculated using maximum tumor attenuation value in contrast-enhanced CT scan divided by the minimum. Kaplan-Meier survival analyses were adopted to evaluate the prognostic value of variables. A model based on TER was built to predict recurrence risk through the LASSO Cox model. The recurrence risk score of patients was calculated based on this model.The optimal cut-off value of TER was 1.83 derived from the time-dependent ROC (tdROC) curve. Patients with high-TER showed increasingly poorer disease-free survival (DFS) in both training (p 0.001) and validation (p 0.001) sets. A model was built based on TER demonstrated satisfactory performance to recurrence risk prediction (C-index: 0.784 in the training set and 0.725 in the validation set). Patients were regrouped into modified high-risk and non-high risk according to recurrence risk score (cut-off value: 1.75) and a significant DFS difference was observed (training set: p 0.001; validation set: p 0.001).TER can serve as a high-risk feature of stage II colon cancer. And a model based on TER provided a new approach to assess recurrence risk of stage II disease.

Additional file 1: Table S1. Meanings and initial values of parameters in the age-structured SEIR model. Table S2. Outcomes, parameters and their values used in sensitivity analysis. Figure S1. Patterns of parameters (p_E, p_NAAT, and p_t) variation with date. A: Proportion of untraced exposed persons (p_E). B: Proportion of cases found by NAAT/RAT (p_NAAT). C: Proportion of concentrated isolation among positive NAAT cases (p_t). Figure S2. Values and regularity of p_E (A) and p_NAAT (B) used in sensitivity analysis. Figure S3. Cumulative number of cases in different districts of Shanghai. Figure S4. The potential areas of virus had been spread on different date of the epidemics in Shanghai (A) and Wuhan (B) with different mean transmission distance (namely the radius of each circle: 13.4 km in Shanghai and 4.4 km in Wuhan). The cumulative number of cases was same for each column. Figure S5. Estimated contract matrices at different settings over seven periods in Shanghai. Figure S6. Demographic comparison of population (A), cases (B) and standard incidence (C) for Shanghai and Wuhan. Figure S7. Effective reproductive number (Rt) in the epidemic of Shanghai. Rt was estimated from4-day and 7-day moving average respectively. Figure S8. Epidemic curve of cumulative predicted cases and reported cases estimate by the model with different values of parameters. Figure S9. The proportion of unascertained cases under different proportion of asymptomatic cases (A), proportion of untraced cases (B) and proportion of cases detected by NAAT/RAT (C). Figure S10. Comparation of estimated secondary attack rates (SAR) and estimated reported SAR (SARobs). Blue and red dashed line is overall SAR (24.1%) and overall SARobs (17.4%).