Quality of life and cost-effectiveness of different breast cancer surgery procedures: a Markov decision tree-based approach in the framework of Predictive, Preventive, and Personalized Medicine.

Purpose: Breast cancer is a complex disease with heterogeneous outcomes that may benefit from the implementation of Predictive, Preventive, and Personalized Medicine (PPPM/3PM) strategies. In this study, we aimed to explore the potential of PPPM approaches by investigating the 10-year trends in quality of life (QOL) and the cost-effectiveness of different types of surgeries for patients with breast cancer. Methods: This prospective cohort study recruited 144 patients undergoing breast conserving surgery (BCS), 199 undergoing modified radical mastectomy (MRM), and 44 undergoing total mastectomy with transverse rectus abdominis myocutaneous flap (TRAMF) from three medical centers in Taiwan between June 2007 and June 2010. Results: All patients exhibited a significant decrease in most QOL dimension scores from before surgery to 6 months postoperatively (p < 0.05); however, from postoperative year 1 to 2, improvement in most QOL dimension scores was significantly better in the TRAMF group than in the BCS and MRM groups (p < 0.05). At 2, 5, and 10 years after surgery, the patients' QOL remained stable. In the Markov decision tree model, the TRAMF group had higher total direct medical costs than the MRM and BCS groups (US$ 32,426, US$ 29,487, and US$ 28,561, respectively) and higher average QALYs gained (7.771, 6.773, and 7.385, respectively), with an incremental cost-utility ratio (ICUR) of US$ 2,944.39 and US$ 10,013.86 per QALY gained. Conclusions: TRAMF appeared cost effective compared with BCS and MRM, and it has been proved with considerable QOL improvements in the framework of PPPM. Future studies should continue to explore the potential of PPPM approaches in breast cancer care. By incorporating predictive models, personalized treatment plans, and preventive strategies into routine clinical practice, we can further optimize patient outcomes and reduce healthcare costs associated with breast cancer treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00326-4.

5-year recurrence prediction after hepatocellular carcinoma resection: deep learning vs. Cox regression models.

Deep learning algorithms have yet to be used for predicting clinical prognosis after cancer surgery. Therefore, this study compared performance indices and permutation importance of potential confounders in three models for predicting 5-year recurrence after hepatocellular carcinoma (HCC) resection: a deep-learning deep neural network (DNN) model, a recurrent neural network (RNN) model, and a Cox proportional hazard (CPH) regression model. Data for 725 patients who had received HCC resection at three medical centers in southern Taiwan between April, 2011, and December, 2015, were randomly divided into three datasets: a training dataset containing data for 507 subjects was used for model development, a testing dataset containing data for 109 subjects was used for internal validation, and a validating dataset containing data for 109 subjects was used for external validation. Feature importance analysis was also performed to identify potential predictors of recurrence after HCC resection. Univariate Cox proportional hazards regression analyses were performed to identify potential significant predictors of 5-year recurrence after HCC resection, which were included in the forecasting models (P < 0.05). All performance indices for the DNN model were significantly higher than those for the RNN model and the conventional CPH model (P < 0.001). The most important potential predictor of 5-year recurrence after HCC resection was surgeon volume followed by, in order of importance, hospital volume, preoperative Beck Depression Scale score, preoperative Beck Anxiety Scale score, co-residence with family, tumor stage, and tumor size. The feature importance analysis performed to investigate interpretability in this study elucidated the potential use of deep learning models for predicting recurrence after HCC resection and for identifying predictors of recurrence. Further experiments using the proposed DNN model would clarify its potential uses for developing, promoting, and improving health policies for treating HCC patients after surgery.

Inverse Probability of Treatment Weighting in 5-Year Quality-of-Life Comparison among Three Surgical Procedures for Hepatocellular Carcinoma.

This prospective longitudinal cohort study analyzed long-term changes in individual subscales of quality-of-life (QOL) measures and explored whether these changes were related to effective QOL predictors after hepatocellular carcinoma (HCC) surgery. All 520 HCC patients in this study had completed QOL surveys before surgery and at 6 months, 2 years, and 5 years after surgery. Generalized estimating equation models were used to compare the 5-year QOL among the three HCC surgical procedures. The QOL was significantly (p < 0.05) improved at 6 months after HCC surgery but plateaued at 2−5 years after surgery. In postoperative surveys, the effect size was largest in the nausea and vomiting subscales in patients who had received robotic surgery, and the effect size was smallest in the dyspnea subscale in patients who had received open surgery. It revealed the following explanatory variables for postoperative QOL: surgical procedure type, gender, age, hepatitis C, smoking, tumor stage, postoperative recurrence, and preoperative QOL. The comparisons revealed that, when evaluating QOL after HCC surgery, several factors other than the surgery itself should be considered. The analysis results also implied that postoperative quality of life might depend not only on the success of the surgical procedure, but also on preoperative quality of life.

Breast Cancer Surgery 10-Year Survival Prediction by Machine Learning: A Large Prospective Cohort Study.

Machine learning algorithms have proven to be effective for predicting survival after surgery, but their use for predicting 10-year survival after breast cancer surgery has not yet been discussed. This study compares the accuracy of predicting 10-year survival after breast cancer surgery in the following five models: a deep neural network (DNN), K nearest neighbor (KNN), support vector machine (SVM), naive Bayes classifier (NBC) and Cox regression (COX), and to optimize the weighting of significant predictors. The subjects recruited for this study were breast cancer patients who had received breast cancer surgery (ICD-9 cm 174-174.9) at one of three southern Taiwan medical centers during the 3-year period from June 2007, to June 2010. The registry data for the patients were randomly allocated to three datasets, one for training (n = 824), one for testing (n = 177), and one for validation (n = 177). Prediction performance comparisons revealed that all performance indices for the DNN model were significantly (p < 0.001) higher than in the other forecasting models. Notably, the best predictor of 10-year survival after breast cancer surgery was the preoperative Physical Component Summary score on the SF-36. The next best predictors were the preoperative Mental Component Summary score on the SF-36, postoperative recurrence, and tumor stage. The deep-learning DNN model is the most clinically useful method to predict and to identify risk factors for 10-year survival after breast cancer surgery. Future research should explore designs for two-level or multi-level models that provide information on the contextual effects of the risk factors on breast cancer survival.

Machine Learning Algorithms to Predict Recurrence within 10 Years after Breast Cancer Surgery: A Prospective Cohort Study.

No studies have discussed machine learning algorithms to predict recurrence within 10 years after breast cancer surgery. This study purposed to compare the accuracy of forecasting models to predict recurrence within 10 years after breast cancer surgery and to identify significant predictors of recurrence. Registry data for breast cancer surgery patients were allocated to a training dataset (n = 798) for model development, a testing dataset (n = 171) for internal validation, and a validating dataset (n = 171) for external validation. Global sensitivity analysis was then performed to evaluate the significance of the selected predictors. Demographic characteristics, clinical characteristics, quality of care, and preoperative quality of life were significantly associated with recurrence within 10 years after breast cancer surgery (p < 0.05). Artificial neural networks had the highest prediction performance indices. Additionally, the surgeon volume was the best predictor of recurrence within 10 years after breast cancer surgery, followed by hospital volume and tumor stage. Accurate recurrence within 10 years prediction by machine learning algorithms may improve precision in managing patients after breast cancer surgery and improve understanding of risk factors for recurrence within 10 years after breast cancer surgery.

Preoperative Health-Related Quality of Life Predicts Minimal Clinically Important Difference and Survival after Surgical Resection of Hepatocellular Carcinoma.

Despite the growing use of minimal clinically important difference (MCID) as a cancer outcome measure, no study has reported clinically significant outcomes in cancer patients. We defined MCID and evaluated the use of preoperative HRQoL for predicting MCID and survival after surgical resection of hepatocellular carcinoma (HCC). In total, 369 patients completed the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep) and the SF-36 at baseline and at two years post-operative at three tertiary academic hospitals. The corresponding MCID values were 3.6 (SF-36 physical component summary), 4.2 (SF-36 mental component summary), 5.4 (FACT-General total score), and 6.7 (FACT-Hep total score). The predictors of achieving postoperative MCID were significantly higher in patients who had low preoperative HRQoL score, advanced age, high education level, and high BMI (p < 0.05). However, patients with a high preoperative HRQoL score, high education level, high BMI, and low Charlson comorbidity index score were significantly associated with survival (p < 0.05). Preoperative HRQoL scores were predictive of MCID and overall survival after surgical resection of HCC. The findings of this study may be useful for managing the preoperative expectations of candidates for HCC resection and for developing shared decision-making procedures for patients undergoing surgical resection of HCC.

Impact of preoperative anxiety and depression on quality of life before and after resection of hepatocellular carcinoma.

OBJECTIVE: The impact of anxiety and depression symptoms (ADS) is often estimated in terms of clinical endpoints such as the risk of complications and probabilities of readmission and survival. The purpose of this study was to provide a benchmark for capturing the negative effects of ADS on quality of life after hepatocellular carcinoma (HCC) surgery and to provide an evidence base for future research and clinical interventions aimed at understanding and remediating these effects. METHODS: This prospective study analyzed 410 HCC patients at three tertiary academic hospitals. The Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), and Functional Assessment of Cancer Therapy- Hepatobiliary (FACT-H) were administered before HCC surgery and at 6 months, 1 year, and 2 years after HCC surgery. Generalized estimating equations were used to estimate differences-in-differences models for examining the effects of ADS. RESULTS: At baseline, 9.0% of the participants had anxiety symptom (BAI > 10), 17.1% had depression symptom (BDI > 13), and 7.1% had ADS. Throughout the study period, anxiety and depression (differences-in-differences value) had significant (P < 0.001) negative net effects on mean scores for all FACT-H dimensions, and the differences gradually increased over time. From baseline through all follow-up years, the two groups significantly (P < 0.001) differed in scores for all FACT-H dimensions, and the differences increased over time. CONCLUSIONS: For healthcare providers, this study highlights the need for continued monitoring for ADS in patients who have undergone hepatic resection and the need for timely and appropriate psychological care for these patients.

Do preoperative depressive symptoms predict quality of life after laparoscopic cholecystectomy: A longitudinal prospective study.

OBJECTIVE: The impact of preoperative depressive symptoms on quality of life (QOL) after laparoscopic cholecystectomy (LC) remains unclear. The purpose of this study was to develop a benchmark for capturing the burden of depressive symptoms on QOL after LC and for supporting evidence-based clinical interventions for remediating these effects. METHODS: Patients diagnosed with depressive symptoms (Beck Depression Inventory score > 13) after LC (n = 336) were classified into a depressive symptoms group. Propensity score matching was then used to match them with 336 patients in a non-depressive symptoms group for all potential confounding factors. All patients completed the 36-item Short Form Health Survey (SF-36) and the Gastrointestinal Quality of Life Index (GIQLI) at baseline and at 2 years postoperatively. The 95% confidence intervals (CIs) for differences in responsiveness estimates were derived by bootstrap estimation. RESULTS: The GIQLI results revealed that the non-depressive symptoms group had relatively stronger responses for emotional impairment (4.10, 95% CI 2.81 to 5.39) and social impairment (4.06, 95% CI 2.65 to 5.46) in comparison with the depressive symptoms group. In the SF-36, the non-depressive symptoms group also had stronger responses for role emotional (12.63, 95% CI 10.73 to 14.54), social functioning (11.25, 95% CI 9.85 to 12.65), vitality (3.81, 95% CI 2.82 to 4.81), mental health (11.97, 95% CI 10.36 to 13.56) and general health (3.84, 95% CI 2.95 to 4.75). CONCLUSIONS: Depressive symptoms complicate the management of LC patients and are associated with poorer outcomes. Because depressive symptoms are very common, further studies are needed to evaluate integrated and comprehensive approaches for assessing and treating these symptoms.

Comparison of Models for Predicting Quality of Life After Surgical Resection of Hepatocellular Carcinoma: a Prospective Study.

BACKGROUND: The essential issue of internal validity has not been adequately addressed in prediction models such as artificial neural network (ANN), support vector machine (SVM), Gaussian process regression (GPR), and multiple linear regression (MLR) models. METHODS: This prospective study compared the accuracy of these four models in predicting quality of life (QOL) after hepatic resection received by 332 patients with hepatocellular carcinoma (HCC) during 2012-2015. An estimation subset was used to train the models, and a validation subset was used to evaluate their performance. Sensitivity score approach was also used to assess the relative significance of input parameters in the system models. RESULTS: The ANN model had significantly higher performance indicators compared to the SVM, GPR, and MLR models (P < 0.05). Additionally, the ANN prediction of QOL at 6 months after hepatic resection significantly correlated with age, gender, marital status, Charlson comorbidity index (CCI) score, chemotherapy, radiotherapy, hospital volume, surgeon volume, and preoperational functional status (P < 0.05). Preoperational functional status was the most influential (sensitive) variable affecting sixth-month QOL followed by surgeon volume, hospital volume, age, and CCI score. CONCLUSIONS: The comparisons showed that, in preoperative and postoperative healthcare consultations with HCC surgery candidates, QOL at 6 months post-surgery should be estimated with an ANN model rather than with SVM, GPR, or MLR models. The best QOL predictors identified in this study can also be used to educate candidates for HCC surgery in the expected course of recovery and other surgical outcomes.

Health-Related Quality of Life before and after Surgical Resection of Hepatocellular Carcinoma: A Prospective Study

Background and Objectives: This large-scale prospective cohort study of a Taiwan population applied generalized estimating equations (GEEs) to evaluate changing trends in health-related quality of life (HRQoL) and to compare predictors of HRQoL before and after surgical resection of hepatocellular carcinoma (HCC) performed during 2011-2014. Materials and Methods: The Short Form-36 Health Survey (SF-36) and Functional Assessment of Cancer Therapy-Hepatobiliary were used in a preoperative assessment and in 3- and 6-month postoperative assessments of 332 HCC patients. Results: The HRQoL was signficantly (p<0.05) improved at 3 months after surgical resection of HCC and plateaued at 6 months after surgery. Scores for both the SF-36 Physical Component Summary (PCS) and Mental Component Summary (MCS) were significantly higher at the third month after surgery (p<0.05) compared to the preoperative period. Both scores also exceeded the norms after hepatic resection of HCC. However, PCS scores were generally higher than MCS scores throughout the study period. After adjusting for time effects and baseline predictors, GEE approaches revealed the following explanatory variables for HRQoL: time of HRQoL assessment, gender, age, education, coresidence with family, chemotherapy, average length of hospital stay, and preoperative functional status. Conclusions: Hepatic resection significantly increased HRQoL in patients with HCC (p<0.05). However, an evaluation of HRQoL after hepatic resection should consider several factors other than outcomes of the surgery itself. Additionally, patients should be advised that their HRQoL improvement after surgery might depend not only on the success of surgery, but also on their preoperative functional status.

miR-105/93-3p promotes chemoresistance and circulating miR-105/93-3p acts as a diagnostic biomarker for triple negative breast cancer.

BACKGROUND: Triple negative breast cancer (TNBC) lacks both early detection biomarkers and viable targeted therapeutics. Moreover, chemotherapy only produces 20-30% pathologic complete response. Because miRNAs are frequently dysregulated in breast cancer and have broad tissue effects, individual or combinations of circulating miRNAs may serve as ideal diagnostic, predictive or prognostic biomarkers, as well as therapeutic targets. Understanding the role and mechanism of dysregulated miRNAs in TNBC may help to develop novel diagnostic and prognostic strategy for TNBC patients. METHODS: The miRNA array profiles of 1299 breast cancer patients were collected from the Metabric database and subjected to analysis of the altered miRNAs between TNBC and non-TNBC. In Student's t-test and Kaplan-Meier analysis, four upregulated miRNAs correlated with poor survival in TNBC but not in non-TNBC. Four miRNAs were manipulated in multiple cell lines to investigate their functional role in carcinogenesis. From these results, we studied miR-105 and miR-93-3p in greater detail. The level of miR-105 and miR-93-3p were evaluated in 25 breast cancer tumor tissues. In addition, the diagnostic utility of circulating miR-105 and miR-93-3p were examined in 12 normal and 118 breast cancer plasma samples by ROC curve construction. RESULTS: miR-105 and miR-93-3p were upregulated and correlated with poor survival in TNBC patients. Both miR-105 and miR-93-3p were found to activate Wnt/ß-catenin signaling by downregulation of SFPR1. By this action, stemness, chemoresistance, and metastasis were promoted. Importantly, the combination of circulating miR-105/93-3p may serve as a powerful biomarker for TNBC, even in early-stage disease. CONCLUSIONS: miR-105/93-3p activates Wnt/ß-catenin signaling by downregulating SFRP1 and thereby promotes stemness, chemoresistance, and metastasis in TNBC cells. Most importantly, combined circulating miR-105/93-3p levels represent a prime candidate for development into a diagnostic biomarker for both early- and late-stage TNBC.

The prognostic impact of lipid biosynthesis-associated markers, HSD17B2 and HMGCS2, in rectal cancer treated with neoadjuvant concurrent chemoradiotherapy.

Neoadjuvant concurrent chemoradiotherapy has been widely used for rectal cancer to improve local tumor control. The varied response of individual tumors encouraged us to search for useful biomarkers to predict the therapeutic response. The study was aimed to evaluate the prognostic impact of lipid biosynthesis-associated biomarkers in rectal cancer patients treated with preoperative chemoradiotherapy. Through analysis of the previously published gene expression profiling database focusing on genes associated with lipid biosynthesis, we found that HSD17B2 and HMGCS2 were the top two significantly upregulated genes in the non-responders. We further evaluated their expression by immunohistochemistry in the pre-treatment tumor specimens from 172 patients with rectal cancer and statistically analyzed the associations between their expression and various clinicopathological factors, as well as survival. High expression of HMGCS2 or HSD17B2 was significantly associated with advanced pre- and post-treatment tumor or nodal status (P < 0.001) and lower tumor regression grade (P < 0.001). More importantly, high expression of either HMGCS2 or HSD17B2 was of prognostic significance, with HMGCS2 overexpression indicating poor prognosis for disease-free survival (P = 0.0003), local recurrence-free survival (P = 0.0115), and metastasis-free survival (P = 0.0119), while HSD17B2 overexpression was associated with poor prognosis for disease-free survival (P <0.0001), local recurrence-free survival (P = 0.0009), and metastasis-free survival (P < 0.0001). In multivariate analysis, only HSD17B2 overexpression remained as an independent prognosticator for shorter disease-free survival (P < 0.001) and metastasis-free survival (P = 0.008). In conclusion, high expression of either HSD17B2 or HMGCS2 predicted poor susceptibility of rectal cancer to preoperative chemoradiotherapy. Both acted as promising prognostic factors, particularly HSD17B2.

Fibroblast growth factor receptor 2 overexpression is predictive of poor prognosis in rectal cancer patients receiving neoadjuvant chemoradiotherapy.

AIMS: Neoadjuvant concurrent chemoradiotherapy (CCRT) followed by surgery is an increasingly used therapeutic strategy for advanced rectal cancer, but risk stratification and final outcomes remain suboptimal. Recently, the oncogenic role of the fibroblast growth factor/fibroblast growth factor receptor (FGFR) signalling pathway has been recognised; however, its clinical significance in rectal cancer has not been elucidated. In this study, we identify and validate targetable drivers associated with the FGFR signalling pathway in rectal cancer patients treated with CCRT. METHODS: Using a published transcriptome of rectal cancers, we found FGFR2 gene significantly predicted response to CCRT. The expression levels of FGFR2, using immunohistochemistry assays, were further evaluated in 172 rectal cancer specimens that had not received any treatment. Expression levels of FGFR2 were statistically correlated with major clinicopathological features and clinical survival in this valid cohort. RESULTS: High expression of FGFR2 was significantly related to advanced pretreatment tumour (p=0.022) and nodal status (p=0.026), post-treatment tumour (p<0.001) and nodal status (p=0.004), and inferior tumour regression grade (p<0.001). In survival analyses, high expression of FGFR2 was significantly associated with shorter local recurrence-free survival (p=0.0001), metastasis-free survival (MeFS; p=0.0003) and disease-specific survival (DSS; p<0.0001). Notably, high expression of FGFR2 was independently predictive of worse outcomes for MeFS (p=0.002, HR=5.387) and DSS (p=0.004, HR=4.997). CONCLUSIONS: High expression of FGFR2 is correlated with advanced tumour stage, poor therapeutic response and worse survival in rectal cancer patients receiving neoadjuvant CCRT. These findings indicate that FGFR2 is a prognostic factor for treating rectal cancer.

[A comparison of convenience sampling and purposive sampling].

Convenience sampling and purposive sampling are two different sampling methods. This article first explains sampling terms such as target population, accessible population, simple random sampling, intended sample, actual sample, and statistical power analysis. These terms are then used to explain the difference between "convenience sampling" and purposive sampling." Convenience sampling is a non-probabilistic sampling technique applicable to qualitative or quantitative studies, although it is most frequently used in quantitative studies. In convenience samples, subjects more readily accessible to the researcher are more likely to be included. Thus, in quantitative studies, opportunity to participate is not equal for all qualified individuals in the target population and study results are not necessarily generalizable to this population. As in all quantitative studies, increasing the sample size increases the statistical power of the convenience sample. In contrast, purposive sampling is typically used in qualitative studies. Researchers who use this technique carefully select subjects based on study purpose with the expectation that each participant will provide unique and rich information of value to the study. As a result, members of the accessible population are not interchangeable and sample size is determined by data saturation not by statistical power analysis.

Celecoxib plus chemoradiotherapy for locally advanced rectal cancer: a phase II TCOG study.

BACKGROUND: To report the results of a phase II trial combining celecoxib and preoperative chemoradiotherapy (CRT) for locally advanced rectal cancer. PATIENTS AND METHODS: Patients with clinical stage II or III rectal cancer were treated with radiotherapy of 44 Gy in 22 fractions. Concurrent chemotherapy consisted of oral tegafur-uracil and folinate on days 1-30 and 38-65. Celecoxib (400 mg/day) given from days 1 to 65. Surgery was done on day 70. The expression of cyclooxygenase 2 (COX-2) in tumor tissues was evaluated microscopically as a prognostic factor. RESULTS: From 2008 to 2011, 53 patients completed CRT+ celecoxib therapy and 47 received radical surgery. Grade 3 diarrhea developed in 5 (9%). Grade 4 anemia was seen in 2 (4%). Pathological complete response (pCR) was seen in 6 (13%). T or N downstaging found in 38 (81%). Sphincter preservation was achieved in 77% of low-positioned tumors. Patients with tumors expressing high-level COX-2 after CRT + celecoxib treatment had inferior pelvic control (P = 0.01), disease-free survival (P = 0.04), and overall survival (P = 0.03) than those with low-level expression. CONCLUSIONS: Celecoxib can be safely combined with preoperative CRT for rectal cancer. More intensified adjuvant therapy may be considered for tumors expressing high-level COX-2 after CRT and surgery.

Life-sustaining treatment: a comparison of the preferences of Taiwanese older adults and their family caregiver.

BACKGROUND: Written advance directives are not common practice in Taiwan; thus, when older adults are critically ill, family members are usually the ones to make decisions regarding life-sustaining treatment. PURPOSE: This study determined how well the preferences of the family members for the older adults match the preferences of the older adults themselves with regard to life-sustaining treatment. METHODS: A cross-sectional comparative descriptive research design was used in this study. Ninety-five pairs of older adults and their families were included in the final analysis. The Life Support Preferences Questionnaire was used to measure life-sustaining preferences. Paired- sample t tests were performed to compare the mean differences between the older adults' preferences and the family members' preferences for these older adults. FINDING: Family members scored higher on life-sustaining treatment preferences than the older adults for all 32 examined items, with 23 (72%) of these items showing statistical significance. CONCLUSION/IMPLICATIONS FOR PRACTICE: Communication between older adults and their family members regarding life-sustaining treatment may help prevent older adults from receiving unwanted treatments.

Clinicopathological significance of HuR expression in gallbladder carcinoma: with special emphasis on the implications of its nuclear and cytoplasmic expression.

Gallbladder carcinoma (GBC) is a relatively rare disease which pathogenesis is less clarified. Human antigen R (HuR), a RNA-binding protein, modulates the expressions of various cancer-related proteins by stabilizing or regulating the transcription of the corresponding messenger RNA. The significance of HuR expression in a large cohort with GBCs is yet to be evaluated. In total, 164 cases of GBC were selected, and immunostaining for HuR was performed. HuR nuclear (HuR-N) expression and HuR cytoplasmic (HuR-C) expression were evaluated by using a histochemical score. The results of HuR expression were correlated with various clinicopathological factors, disease-specific survival (DSS), and disease-free survival (DFS) in 161 patients with follow-up data. HuR-N overexpression was strongly associated with high histological grade (p = 0.001), vascular invasion (p < 0.001), and high Ki-67 labeling index (p < 0.001). HuR-C overexpression was significantly related to higher primary tumor status (p < 0.001), advanced tumor stage (p < 0.001), histological type (p = 0.006), high histological grade (p < 0.001), vascular and perineurial invasion (p < 0.001 and p = 0.002, respectively), tumor necrosis (p = 0.042), and high Ki-67 labeling index (p = 0.002). Besides, HuR-C overexpression also correlates with HuR-N overexpression (p < 0.001) and cyclin A overexpression (p = 0.026). HuR-N overexpression correlated with poor DFS (p = 0.0348) in univariate analysis, but HuR-C overexpression strongly correlated with a worse DSS and DFS in both univariate (both p < 0.0001) and multivariate (DSS, p = 0.006; DFS, p = 0.001) analyses. Subcellular localization of HuR expression correlates with different adverse phenotypes of GBC. Besides, HuR-C overexpression is an independent prognostic factor for dismal DSS and DFS, suggesting its roles in tumorigenesis or carcinogenesis and as a potential prognostic marker of GBC.

The volume-outcome relationship in laparoscopic cholecystectomy: a population-based study using propensity score matching.

BACKGROUND: The volume-outcome relationship has been validated previously for surgical procedures and cancer treatments. However, no studies have longitudinally compared the relationships between volume and outcome, and none have systematically compared laparoscopic cholecystectomy (LC) surgery outcomes in Taiwan. This study purposed to explore the relationship between volume and hospital treatment cost after LC. METHODS: This cohort study retrospectively analyzed 247,751 LCs performed from 1998 to 2009. Hospitals were classified as low-, medium-, and high-volume hospitals if their annual number of LCs were 1-29, 30-84, ≥85, respectively. Surgeons were classified as low-, medium-, and high-volume surgeons if their annual number of LCs were 1-10, 11-24, ≥25, respectively. Hierarchical linear regression model and propensity score were used to assess the relationship between volume and hospital treatment cost. RESULTS: The mean hospital treatment cost was US $2,504.53, and the average hospital costs for high-volume hospitals/surgeons were 33/47% lower than those for low-volume hospitals and surgeons. When analyzed by propensity score, the hospital treatment cost differed significantly between high-volume hospitals/surgeons and low/medium-volume hospitals/surgeons (2,073.70 vs. 2,350.91/2,056.73 vs. 2,553.76, P < 0.001). CONCLUSIONS: Analysis using a hierarchical linear regression model and propensity score found an association between high-volume hospitals and surgeons and hospital treatment cost in LC patients. Moreover, the significant factors associated with hospital resource utilization for this procedure include age, gender, comorbidity, hospital type, hospital volume, and surgeon volume. Additionally, analysis of the treatment strategies adopted at high-volume hospitals or by high-volume surgeons may improve overall hospital treatment cost.

Therapeutic effect of C-phycocyanin extracted from blue green algae in a rat model of acute lung injury induced by lipopolysaccharide.

C-Phycocyanin (CPC), extracted from blue green algae, is a dietary nutritional supplement due to its several beneficial pharmacological effects. This study was conducted to evaluate whether CPC protects against lipopolysaccharide- (LPS-) induced acute lung injury (ALI) in rats. Rats were challenged with LPS (5 mg/kg body weight) intratracheally to induce ALI. After 3 h LPS instillation, rats were administrated with CPC (50 mg/kg body weight, i.p.) for another 3 h. Our results showed that posttreatment with CPC significantly inhibited LPS-induced elevation of protein concentration, nitrite/nitrate level, release of proinflammatory cytokines, the number of total polymorphonuclear cells in bronchoalveolar lavage fluid, and lung edema evidenced by decrease of lung wet/dry weight ratio accompanied by a remarkable improvement of lung histopathological alterations. Furthermore, CPC significantly attenuated LPS-induced myeloperoxidase activity, O2 (-) formation, expression of inducible nitric oxide synthase, and cyclooxygenase-2 as well as nuclear factor-kappa B (NF- κ B) activation in lungs. Additionally, CPC significantly downregulated proapoptotic proteins such as caspase-3 and Bax, but upregulated antiapoptotic proteins such as Bcl-2 and Bcl-XL in lungs exposed to LPS. These findings indicate that CPC could be potentially useful for treatment of LPS-related ALI by inhibiting inflammatory responses and apoptosis in lung tissues.

SKP2 overexpression is associated with a poor prognosis of rectal cancer treated with chemoradiotherapy and represents a therapeutic target with high potential.

The S-phase kinase-associated protein 2 (SKP2) oncoprotein is an E3 ubiquitin ligase. Overexpression of SKP2 was found in various human cancers, including colorectal cancers, but its potential role as a prognostic marker after neoadjuvant chemoradiotherapy (CRT) and for therapeutic intervention in rectal cancers is unknown. This study examined the correlation of SKP2 expression in the prognosis of rectal cancer patients and the viability of colorectal cancer cells treated with CRT. SKP2 immunoexpression was retrospectively assessed in pretreatment biopsies of 172 rectal cancer patients treated with neoadjuvant CRT followed by surgery. Results were correlated with clinicopathological features, therapeutic responses, and patient survival. Pharmacologic assays were used to evaluate the therapeutic relevance of Bortezomib in two colorectal cancer cell lines (HT-29 and SW480). High expression of SKP2 was correlated with the advanced Post-Tx nodal status (p = 0.002), Post-Tx International Union for Cancer Control stage (p = 0.002), and a lower-degree tumor regression grade (p < 0.001). Moreover, high expression of SKP2 (p = 0.027, hazard ratio 3.21) was an independent prognostic factor for local recurrence-free survival. In vitro, Bortezomib downregulated SKP2 expression, induced caspase activation, and decreased the viability of colorectal cancer cells with or without a combination with fluorouracil. Bortezomib also promoted caspase activation and gamma-H2AX formation in colorectal cancer cells concurrently treated with CRT. High expression of SKP2 was associated with a poor therapeutic response and adverse outcomes in rectal cancer patients treated with neoadjuvant CRT. In the presence of chemotherapy with or without radiotherapy, the promoted sensitivity of colorectal cancer cells to Bortezomib with an SKP2-repressing effect indicated that it is a potential therapeutic target.