Nomogram based on clinical and preoperative CT features for predicting the early recurrence of combined hepatocellular-cholangiocarcinoma: a multicenter study.

PURPOSE: To establish and validate a multiparameter prediction model for early recurrence after radical resection in patients diagnosed with combined hepatocellular-cholangiocarcinoma (cHCC-CC). MATERIALS AND METHODS: This study reviewed the clinical characteristics and preoperative CT images of 143 cHCC-CC patients who underwent radical resection from three institutions. A total of 110 patients from institution 1 were randomly divided into training set (n = 78) and testing set (n = 32) in the ratio of 7-3. Univariate and multivariate logistic regression analysis were used to construct a nomogram prediction model in the training set, which was internally and externally validated in the testing set and the validation set (n = 33) from institutions 2 and 3. The area under the curve (AUC) of receiver operating characteristics (ROC), decision curve analysis (DCA), and calibration analysis were used to evaluate the model's performance. RESULTS: The combined model demonstrated superior predictive performance compared to the clinical model, the CT model, the pathological model and the clinic-CT model in predicting the early postoperative recurrence. The nomogram based on the combined model included AST, ALP, tumor size, tumor margin, arterial phase peritumoral enhancement, and MVI (Microvascular invasion). The model had AUCs of 0.89 (95% CI 0.81-0.96), 0.85 (95% CI 0.70-0.99), and 0.86 (95% CI 0.72-1.00) in the training, testing, and validation sets, respectively, indicating high predictive power. DCA showed that the combined model had good clinical value and correction effect. CONCLUSION: A nomogram incorporating clinical characteristics and preoperative CT features can be utilized to effectively predict the early postoperative recurrence in patients with cHCC-CC.

Peritumoral edema in preoperative magnetic resonance imaging is an independent prognostic factor for hepatocellular carcinoma.

BACKGROUND: Peritumoral edema is an independent prognostic risk factor for malignant tumors. Therefore, assessment of peritumoral edema in preoperative magnetic resonance imaging (MRI) may provide better prognostic information in patients with hepatocellular carcinoma (HCC). AIM: To determine whether peritumoral edema in preoperative MRI is a prognostic factor for HCC. METHODS: A retrospective analysis of 90 patients with HCC confirmed by surgical pathology was performed. All patients' peritumoral edema in preoperative MRI was reviewed by two radiologists. The association of disease recurrence with peritumoral edema and clinicopathological features was assessed using the Cox proportional hazards model. Interobserver agreement for evaluating peritumoral edema was determined using Cohen's κ coefficient. RESULTS: Recurrence and non-recurrence after an average 20.8 month follow-up was 25.6% (23/90) and 74.4% (67/90), respectively. The ratio of peritumoral edema of 90 patients with HCC in preoperative MRI was 35.6% (32/90). In univariate Cox regression analysis, peritumoral edema [hazard ratio (HR) 11.08, P < 0.001], tumor diameter (HR 4.12, P = 0.001), microvascular invasion (HR 2.78, P = 0.020), gender (HR 0.29, P = 0.006), cirrhosis (HR 2.45, P = 0.049), ascites syndrome (HR 2.83, P = 0.022), aspartate aminotransferase(AST)/alanine aminotransferase(ALT) (HR 5.07, P = 0.003) were indicators for HCC recurrence. In multivariate Cox regression analysis, the tumor diameter (HR 2.53, P = 0.032) and peritumoral edema (HR 8.71, P < 0.001) were independent prognostic factors of HCC. The sensitivity, specificity, positive predictive value and negative predictive value of peritumoral edema and tumor diameter were 82.6%&60.9%, 80.6%&77.6%, 59.4%&48.3%, and 93.1%&85.3%, respectively. CONCLUSION: Peritumoral edema in preoperative MRI may be considered as a biomarker of prognostic information for patients with HCC.

GSTT1 and GSTM1 polymorphisms predict treatment outcome for breast cancer: a systematic review and meta-analysis.

Observational studies have reported controversial results on the association between GSTT1 and GSTM1 genotypes and treatment outcome of breast cancer. The purpose of this study is to evaluate the association between GSTT1 and GSTM1 and treatment outcome in breast cancer patients. Eligible studies were searched in PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure databases. A random-effect model or fixed-effect model was used to calculate the overall combined risk estimates. Twenty-one studies with a total of 4990 patients were included in this meta-analysis. The GSTM1 null genotype (odds ratio (OR) = 1.33, 95 % confidence interval (CI) 1.01-1.75, P = 0.046) and GSTT1/GSTM1 double null genotype (OR = 2.22, 95 % CI 1.02-4.84, P = 0.045) were significantly associated with an increased tumor response. A reduced overall survival (hazard ratio (HR) = 0.84, 95 % CI 0.72-0.98, P = 0.024) was observed in GSTM1 null genotype, especially in mixed descent (HR = 0.77, 95 % CI 0.61-0.96, P = 0.018) and large sample size (HR = 0.85, 95 % CI 0.72-0.99, P = 0.033). Evidence of publication bias was observed in GSTM1 genotype rather than in GSTT1 genotype. This meta-analysis suggests that GSTM1 null and GSTT1/GSTM1 double null polymorphisms might be significantly associated with an increased tumor response. However, the GSTM1 null genotype might be significantly associated with a reduced overall survival. Future studies are warranted to confirm these findings.

Diagnostic performance of ADCs in different ROIs for breast lesions.

OBJECTIVE: The purpose of this study was to explore the diagnostic performance of apparent diffusion coefficient (ADC) values for breast lesions by different measuring methods and find out the optimum measuring method. METHODS: ADCW-mean and ADCW-min were obtained by whole-measurement method, while ADCmean and ADCmin were extracted by spot-measurement method. Four ADCs were analyzed by One-way ANOVA and Independent T-test. The diagnostic performances of these four ADCs were calculated by receiver operating characteristics (ROC) curves and the area under the curves (AUC) were compared through Z-test. RESULTS: For the whole-measurement method, there were significant differences between malignant and benign lesions (ADCW-mean=1.014±0.197 for malignant, ADCW-mean=1.650±0.348 for benign, F=37.511, P<0.001; ADCW-min=0.627±0.144 for malignant, ADCW-min=1.245±0.290 for benign, F=41.446, P<0.001), as well as the spot-measurement method (ADCmean=1.010±0.234 for malignant, ADCmean=1.648±0.392 for benign, F=34.580, P<0.001; ADCmin=0.817±0.203 for malignant, ADCmin=1.411±0.357 for benign, F=40.039, P<0.001). The optimal diagnostic threshold of ADCW-mean, ADCW-min, ADCmean, and ADCmin values were 1.223×10(-3) mm(2)/s, 0.897×10(-3) mm(2)/s, 1.315×10(-3) mm(2)/s, and 1.111×10(-3) mm(2)/s, respectively. ROC curves indicated that the AUC for ADCW-min (0.969) was statistically significant higher than the AUC for ADCW-mean (0.940; Z=2.473, p=0.013), ADCmean (0.919; Z=3.691, P=0.000), and ADCmin (0.928; Z=3.634, P=0.000). The AUC for ADCW-mean was also significantly higher than the AUC for ADCmean (Z=2.863, P=0.004). CONCLUSION: The results provided evidence that the most reliable and accurate value in demonstrating the limitation of diffusion may be ADCW-min, and it has the highest diagnostic value in distinguishing breast lesions from malignant to benign.

Meta-analysis of diffusion-weighted magnetic resonance imaging in detecting prostate cancer.

PURPOSE: The objective of this study was to determine the diagnostic performance of quantitative diffusion-weighted magnetic resonance imaging in detection of prostate cancer. METHODS: A comprehensive search was performed for English articles published before May 2012 that fulfilled the following criteria: patients had histopathologically proved prostate cancer; diffusion-weighted imaging (DWI) was performed for the detection of prostate cancer, and data for calculating sensitivity and specificity were included. Methodological quality was assessed by using the quality assessment of diagnostic studies instrument. Publication bias analysis, homogeneity, inconsistency index, and threshold effect were performed by STATA version 12. RESULTS: Of 119 eligible studies, 12 with 1637 malignant and 4803 benign lesions were included. There was notable heterogeneity beyond threshold effect and publication bias. The sensitivity and specificity with 95% confidence interval (CI) estimates of DWI on a per-lesion basis were 77% (CI, 0.76-0.84) and 84% (CI, 0.78-0.89), respectively, and the area under the curve of summary receiver operating characteristic curve was 0.88 (CI, 0.85-0.90). The overall positive and negative likelihood ratios with 95% CI were 4.93 (3.39-7.17) and 0.278 (0.19-0.39), respectively. CONCLUSIONS: Quantitative DWI has a relative sensitivity and specificity to distinguish malignant from benign in prostate lesions. However, large-scale randomized control trials are necessary to assess its clinical value because of nonuniformed diffusion gradient b factor, diagnosis threshold, and small number of studies.