Circulating tumor DNA as prognostic markers of relapsed breast cancer: a systematic review and meta-analysis.

Objective: Circulating tumor DNA (ctDNA) is increasingly being used as a potential prognosis biomarker in patients of breast cancer. This review aims to assess the clinical value of ctDNA in outcome prediction in breast cancer patients throughout the whole treatment cycle. Methods: PubMed, Web of Science, Embase, Cochrane Library, Scopus, and clinical trials.gov were searched from January 2016 to May 2022. Conference abstracts published in last three years were also included. The following search terms were used: ctDNA OR circulating tumor DNA AND breast cancer OR breast carcinoma. Only studies written in English languages were included. The following pre-specified criteria should be met for inclusion: (1) observational studies (prospective or retrospective), randomized control trials, case-control studies and case series studies; (2) patients with breast cancer; (3) ctDNA measurement; (4) clinical outcome data such as objective response rate (ORR), pathological complete response (pCR), relapse-free survival (RFS), overall survival (OS), and so on. The random-effect model was preferred considering the potential heterogeneity across studies. The primary outcomes included postoperative short-term outcomes (ORR and pCR) and postoperative long-term outcomes (RFS, OS, and relapse). Secondary outcomes focused on ctDNA detection rate. Results: A total of 30 studies, comprising of 19 cohort studies, 2 case-control studies and 9 case series studies were included. The baseline ctDNA was significantly negatively associated with ORR outcome (Relative Risk [RR] = 0.65, 95% confidence interval [CI]: 0.50-0.83), with lower ORR in the ctDNA-positive group than ctDNA-negative group. ctDNA during neoadjuvant therapy (NAT) treatment was significantly associated with pCR outcomes (Odds Ratio [OR] = 0.15, 95% CI: 0.04-0.54). The strong association between ctDNA and RFS or relapse outcome was significant across the whole treatment period, especially after the surgery (RFS: Hazard Ratio [HR] = 6.74, 95% CI: 3.73-12.17; relapse outcome: RR = 7.11, 95% CI: 3.05-16.53), although there was heterogeneity in these results. Pre-operative and post-operative ctDNA measurements were significantly associated with OS outcomes (pre-operative: HR = 2.03, 95% CI: 1.12-3.70; post-operative: HR = 6.03, 95% CI: 1.31-27.78). Conclusions: In this review, ctDNA measurements at different timepoints are correlated with evaluation indexes at different periods after treatment. The ctDNA can be used as an early potential postoperative prognosis biomarker in breast cancer, and also as a reference index to evaluate the therapeutic effect at different stages.

Radioresistance or/and radiosensitivity of head and neck squamous cell carcinoma: biological angle.

OBJECTIVE: This narrative review aimed to compile and summarize clinically relevant literature in radiation therapy and to discuss the potential in radioresistant and radiosensitive head and neck squamous cell carcinoma (HNSCC). METHODS AND MATERIALS: Google Scholar, PubMed, and the Cochrane Library were retrieved using combined key words such as "radiotherapy" and "head and neck cancer." Search strings additionally queried were "radioresistant," "radiosensitive," "head and neck region," "squamous cell carcinoma," in combination with Boolean operators 'AND' and 'OR.' Subsequently, the resulting publications were included for review of the full text. RESULTS: Radiotherapeutic responses currently in clinical observation referred to HNSCC scoping were selected into this review. The compiled mechanisms were then detailed concerning on the clinical significance, biological characteristics, and molecular function. CONCLUSIONS: Brachytherapy or/and external-beam radiotherapy are crucial for treating HNSCC especially the early stage patients, but in some patients with locally advanced tumors, their outcome with radiation therapy is poor due to obvious radioresistance. The curative effects mainly depend on the response to radiation therapy so an updated review is needed to optimize further applications in HNSCC radiotherapy.

Attention-based generative adversarial networks improve prognostic outcome prediction of cancer from multimodal data.

The prediction of prognostic outcome is critical for the development of efficient cancer therapeutics and potential personalized medicine. However, due to the heterogeneity and diversity of multimodal data of cancer, data integration and feature selection remain a challenge for prognostic outcome prediction. We proposed a deep learning method with generative adversarial network based on sequential channel-spatial attention modules (CSAM-GAN), a multimodal data integration and feature selection approach, for accomplishing prognostic stratification tasks in cancer. Sequential channel-spatial attention modules equipped with an encoder-decoder are applied for the input features of multimodal data to accurately refine selected features. A discriminator network was proposed to make the generator and discriminator learning in an adversarial way to accurately describe the complex heterogeneous information of multiple modal data. We conducted extensive experiments with various feature selection and classification methods and confirmed that the CSAM-GAN via the multilayer deep neural network (DNN) classifier outperformed these baseline methods on two different multimodal data sets with miRNA expression, mRNA expression and histopathological image data: lower-grade glioma and kidney renal clear cell carcinoma. The CSAM-GAN via the multilayer DNN classifier bridges the gap between heterogenous multimodal data and prognostic outcome prediction.

Prediction of prognosis in COVID-19 patients using machine learning: A systematic review and meta-analysis.

BACKGROUND: Accurate prediction of prognostic outcomes in patients with COVID-19 could facilitate clinical decision-making and medical resource allocation. However, little is known about the ability of machine learning (ML) to predict prognosis in COVID-19 patients. OBJECTIVE: This study aimed to systematically examine the prognostic value of ML in patients with COVID-19. METHODS: A systematic search was conducted in PubMed, Web of Science, Embase, Cochrane Library, and IEEE Xplore up to December 15, 2021. Studies predicting the prognostic outcomes of COVID-19 patients using ML were eligible for inclusion. Risk of bias was evaluated by a tailored checklist based on Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pooled sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated to evaluate model performance. RESULTS: A total of 33 studies that described 35 models were eligible for inclusion, with 27 models presenting mortality, four intensive care unit (ICU) admission, and four use of ventilation. For predicting mortality, ML gave a pooled sensitivity of 0.86 (95% CI, 0.79-0.90), a specificity of 0.87 (95% CI, 0.80-0.92), and an AUC of 0.93 (95% CI, 0.90-0.95). For the prediction of ICU admission, ML had a sensitivity of 0.86 (95% CI, 0.78-0.92), a specificity of 0.81 (95% CI, 0.66-0.91), and an AUC of 0.91 (95% CI, 0.88-0.93). For the prediction of ventilation, ML had a sensitivity of 0.81 (95% CI, 0.68-0.90), a specificity of 0.78 (95% CI, 0.66-0.87), and an AUC of 0.87 (95% CI, 0.83-0.89). Meta-regression analyses indicated that algorithm, population, study design, and source of dataset influenced the pooled estimate. CONCLUSION: This meta-analysis demonstrated the satisfactory performance of ML in predicting prognostic outcomes in patients with COVID-19, suggesting the potential value of ML to support clinical decision-making. However, improvements to methodology and validation are still necessary before its application in routine clinical practice.

MARCO is a potential prognostic and immunotherapy biomarker.

BACKGROUND: Macrophage receptor with collagenous structure (MARCO), a novel immune checkpoint expressed on tumor-associated macrophages, has antitumor therapeutic properties. However, the association between MARCO and patient prognosis, immune infiltration, and ICI immunotherapy needs to be studied urgently. METHODS: MARCO distribution in cancer tissues was investigated using the TCGA and GTEx databases. The PrognoScan and KM Plotter databases was used to assess the MARCO prognosis. TIMER2.0, GEPIA, cBioPortal, and GSEA all confirmed the link between MARCO and immune infiltration, mutation profile, and enrichment pathway analysis. Data visualization was implemented by R language. RESULTS: In general, MARCO had a substantial impact on the prognosis of cancer patients and was expressed differently in cancer and adjacent normal tissues. High expression of MARCO was associated with poorer OS in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), lung squamous cell carcinoma (LUSC), colon adenocarcinoma (COAD), and prostate adenocarcinoma (PRAD). However, high expression of MARCO had a better PFI in brain lower-grade glioma (LGG) and skin cutaneous melanoma (SKCM). We discovered that MARCO expression was lowest in pancreatic adenocarcinoma (PAAD) and rectum adenocarcinoma (READ) stage 1, BLCA stage 2, LUSC and stomach adenocarcinoma (STAD) stage 3, and liver hepatocellular carcinoma (LIHC) stage 4. Subsequently, we analyzed the correlation between MARCO and 47 immune checkpoints and observed that MARCO was positively connected with CD80, CD86, and leukocyte-associated immunoglobulin-like receptor 1(LAIR1) in most cancers. In COAD, MARCO has the most microsatellite instability (MSI). In addition, we discovered that high expression of MARCO patients had a better prognosis after immune checkpoint inhibitor (ICI) treatment in SKCM. Finally, GSEA revealed a significant correlation between MARCO and TNF/NFκB signaling, KRAS signaling, PI3K/AKT/mTOR pathway, IL-6-STAT3 signaling, TGFß pathway, and p53 pathway. CONCLUSION: This study comprehensively investigated the relationship between MARCO and clinical prognosis, immune infiltration, and ICI immunotherapy in various cancers. We demonstrated the potential of MARCO as an emerging biomarker, exploring new avenues for future tumor immunotherapy.

Comprehensive assessments of immuno-oncology drug-based combination therapies as first-line treatment for advanced renal cell carcinoma.

Over the last decade, there have been substantial progress in the field of systemic therapy for advanced renal cell carcinoma. Through the transition from treatment with cytokines to molecular-targeted agents, and currently to immuno-oncology drugs, the prognostic outcomes of patients with advanced renal cell carcinoma have been markedly improved. In particular, based on the promising outcomes of recently conducted pivotal randomized clinical trials, immuno-oncology drug-based combination therapy by either dual immune checkpoint inhibition or combined inhibition of an immune checkpoint and tyrosine kinase, is currently regarded as a standard of care for treatment-naïve advanced renal cell carcinoma patients. However, insufficient data are available with respect to the selection of optimal systemic therapies for advanced renal cell carcinoma in the first-line setting due to the lack of a head-to-head comparison between approved immuno-oncology drug-based combination therapies. In this review, therefore, we summarize interesting findings associated with first-line combination therapies for advanced renal cell carcinoma obtained from both randomized clinical trials and real-world clinical practices, in order to present useful guidance to help make treatment decisions for patients with treatment-naïve advanced renal cell carcinoma.

Treatment with neurohormonal inhibitors and prognostic outcome in pulmonary arterial hypertension with risk factors for left heart disease.

BACKGROUND: Despite major advances in pharmacologic treatment, patients with pulmonary arterial hypertension (PAH) still have a considerably reduced life expectancy. In this context, chronic hyperactivity of the neurohormonal axis has been shown to be detrimental in PAH, thus providing novel insights on the role of neurohormonal blockade as a potential therapeutic target. AIM: To evaluate the application and prognostic effect of neurohormonal inhibitors (NEUi) in a single-center sample of patients with idiopathic PAH and risk factors for left heart disease. METHODS: We analyzed data retrospectively collected from our register of right heart catheterizations performed consecutively from January 1, 2005 to October 31, 2018. Patients on beta-blocker, angiotensin-converting enzyme inhibitor, angiotensin receptor blocker or mineralocorticoid receptor antagonist at the time of right heart catheterization were classified as NEUi users and compared to NEUi non-recipients. RESULTS: Complete data were available for 57 PAH subjects: 27 of those (47.4%) were taking at least one NEUi at the time of right heart catheterization and were compared with the remaining 36 NEUi non-recipients. NEUi users were older and had a higher cardiovascular risk profile compared to non-recipients. Additionally, NEUi non-users had a higher probability of dying during the course of follow-up than NEUi recipients (56.7% vs 25.9%, log-rank P = 0.020). CONCLUSION: The above data highlighted a subgroup of patients with PAH and comorbidities for left heart disease in which NEUi use has shown to be associated with improved survival. Future prospective studies are needed to identify the most appropriate therapeutic strategies in this subset population.

Comprehensive risk score of the E-PASS as a prognostic indicator for patients after elective and emergency curative colorectal cancer surgery: A multicenter retrospective study.

OBJECTIVE: To evaluate the prognostic value of the comprehensive risk score (CRS) of the Estimation of Physiologic Ability and Surgical Stress for managing patients with colorectal cancer (CRC) who underwent elective and emergency colorectal cancer surgery with curative intent. SUMMARY BACKGROUND DATA: CRS, which is calculated based on both clinical and surgical factors, is a good predictor of postoperative complications and mortality. However, the impact of CRS in CRC prognosis remains unclear. METHODS: Patients with CRC who underwent curative resection between 2010 and 2019 were retrospectively enrolled in this study. The cohort was divided into the low and high CRS groups. The prognostic value of CRS was evaluated via Cox regression and Kaplan-Meier analyses. The CRS cutoff value was obtained using the Youden index applied to OS curves and have not been validated by any validation cohorts. RESULTS: In total, 2407 patients, including 1359 and 1048 patients with low and high CRS, respectively, were enrolled in this study. Multivariate analysis revealed that a CRS was an independent prognostic factor of overall and recurrence-free survival regardless of disease stage. Furthermore, adjuvant chemotherapy was beneficial for the survival of patients with stage III CRC in both high and low CRS groups; however, the survival benefit was limited in elderly high CRS patients. CONCLUSIONS: CRS was a strong prognostic factor for CRC regardless of disease stage and might be considered as a biomarker for selecting elderly patients who are eligible for adjuvant chemotherapy.

Effect of macrotroponin on the utility of cardiac troponin I as a prognostic biomarker for long term total and cardiovascular disease mortality.

Macrotroponin is a complex formed between endogenous cardiac troponin autoantibodies and circulating cardiac troponin (cTn). It is a recognised cause of discrepancy between current high sensitivity troponin (hs-cTn) assays; and immunoglobulin-bound (macrotroponin) and unbound cTn can coexist in varying proportions in the acute setting. Increasingly it is considered when laboratory cTn results do not match a patient's clinical picture. However, despite the better understanding of macrotroponin as an analytical interference, its clinical significance remains unclear. The aim of this study was to determine the potential impact of macrotroponin on the use of cTn as a long-term prognostic marker. We repeated cTnI testing after polyethylene glycol (PEG) precipitation on consecutive participants (n=159) with a first elevated cTn above 0.2 µg/L during their hospital admission episode. Because this paper is looking at outcomes in years, the initial data were generated at a time when non-hs-cTn assays were in use. We divided the cohort into two groups based on an exploratory PEG recovery cut-off of <34.6% to indicate the presence of possible macrotroponin and compared the overall and cardiovascular related mortality. The median follow-up time for the overall cohort was 8.35 years (8.32-8.40 interquartile range) with no difference between the two groups. The overall median survival was 8.1 years. Our findings indicate a hazard ratio of 0.54 (0.32-0.91 95% CI) for all-cause mortality and 0.48 (0.24-0.95) for cardiovascular mortality in patients with possible macrotroponin compared to those patients with troponin elevation without evidence of macrotroponin, after adjustment for common cardiovascular disease risk factors. Furthermore, an association was observed between PEG% recovery and all-cause mortality (p<0.05). This study showed that patients with macrotroponin have comparatively favourable long-term all-cause and cardiovascular mortality in a cohort of patients with elevated troponin. We illustrate the importance of recognising cTn results as being a summation of heterogeneous components, including those bound to antibodies, and the potential role of macrotroponin to further improve our interpretation and use of cTn as a biomarker.

Identification of differentially expressed genes-related prognostic risk model for survival prediction in breast carcinoma patients.

Since the imbalance of gene expression has been demonstrated to tightly related to breast cancer (BRCA) genesis and growth, common genes expressed of BRCA were screened to explore the essence in-between. In current work, most common differentially expressed genes (DEGs) in various subtypes of BRCA were identified. Functional enrichment analysis illustrated the driving factor of deactivation of the cell cycle and the oocyte meiosis, which critically triggers the development of BRCA. Herein, we constructed a 12-gene prognostic risk model relative to differential gene expression. Subsequently, the K-M curves, analysis on time-ROC curve and Cox regression were performed to assess this risk model by determining the respective prognostic value, and the prediction performance were ascertained for both training and validation cohorts. In addition, multivariate Cox regression was analysed to reveal the independence between risk score and prognostic stage, and the accuracy and sensitivity of prognosis are particularly improved after clinical indicators are included into the analysis. In summary, this study offers novel insights into the imbalance of gene expression within BRCA, and highlights 12 selected genes associated with patient prognosis. The risk model can help individualize treatment for patients at different risks, and propose precise strategies and treatments for BRCA therapy.

Prognostic outcome prediction by semi-supervised least squares classification.

Although great progress has been made in prognostic outcome prediction, small sample size remains a challenge in obtaining accurate and robust classifiers. We proposed the Rescaled linear square Regression based Least Squares Learning (RRLSL), a jointly developed semi-supervised feature selection and classifier, for predicting prognostic outcome of cancer patients. RRLSL used the least square regression to identify the scale factors and then rank the features in available multiple types of molecular data. We applied the unlabeled multiple molecular data in conjunction with the labeled data to develop a similarity graph. RRLSL produced the constraint with kernel functions to bridge the gap between label information and geometry information from messenger RNA and microRNA expression profiling. Importantly, this semi-supervised model proposed the least squares learning with L2 regularization to develop a semi-supervised classifier. RRLSL suggested the performance improvement in the prognostic outcome prediction and successfully discriminated between the recurrent patients and non-recurrent ones. We also demonstrated that RRLSL improved the accuracy and Area Under the Precision Recall Curve (AUPRC) as compared to the baseline semi-supervised methods. RRLSL is available for a stand-alone software package (https://github.com/ShiMGLab/RRLSL). A short abstract We proposed the Rescaled linear square Regression based Least Squares Learning (RRLSL), a jointly developed semi-supervised feature selection and classifier, for predicting prognostic outcome of cancer patients. RRLSL used the least square regression to identify the scale factors to rank the features in available multiple types of molecular data. RRLSL produced the constraint with kernel functions to bridge the gap between label information and geometry information from messenger RNA and microRNA expression profiling. Importantly, this semi-supervised model proposed the least squares learning with L2 regularization to develop the semi-supervised classifier. RRLSL suggested the performance improvement in the prognostic outcome prediction and successfully discriminated between the recurrent patients and non-recurrent ones.

Intratumoral Translocation Positive Heterogeneity in Pediatric Alveolar Rhabdomyosarcoma Tumors Correlates to Patient Survival Prognosis.

Alveolar rhabdomyosarcoma (ARMS) is characterized by one of three translocation states: t(2;13) (q35;q14) producing PAX3-FOXO1, t(1;13) (p36;q14) producing PAX7-FOXO1, or translocation-negative. Tumors with t(2;13) are associated with greater disease severity and mortality than t(1;13) positive or translocation negative patients. Consistent with this fact, previous work concluded that a molecular analysis of RMS translocation status is essential for the accurate determination of prognosis and diagnosis. However, despite this knowledge, most diagnoses rely on histology and in some cases utilize fluorescence in situ hybridization (FISH) probes unable to differentiate between translocation products. Along these same lines, diagnostic RT-PCR analysis, which can differentiate translocation status, is unable to determine intratumoral translocation heterogeneity, making it difficult to determine if heterogeneity exists and whether correlations exist between this heterogeneity and patient outcomes. Using newly developed FISH probes, we demonstrate that intratumoral heterogeneity exists in ARMS tumors with respect to the presence or absence of the translocation product. We found between 3 and 98% of cells within individual tumor samples contained a translocation event with a significant inverse correlation (R 2 = 0.66, p = 0.001) between the extent of intratumoral translocation heterogeneity and failure-free survival of patients. Taken together, these results provide additional support for the inclusion of the molecular analysis of these tumors and expand on this idea to support determining the extent of intratumoral translocation heterogeneity in the diagnosis of ARMS to improve diagnostic and prognostic indicators for patients with these tumors.

Losing Regulation of the Extracellular Matrix is Strongly Predictive of Unfavorable Prognostic Outcome after Acute Myocardial Infarction.

This study tested the hypothesis that MMP-9-/-tPA-/- double knock out (i.e., MTDKO) plays a crucial role in the prognostic outcome after acute myocardial infarction (AMI by ligation of left-coronary-artery) in MTDKO mouse. Animals were categorized into sham-operated controls in MTDKO animals (group 1) and in wild type (B6: group 2), AMI-MTDKO (group 3) and AMI-B6 (group 4) animals. They were euthanized, and the ischemic myocardium was harvested, by day 60 post AMI. The mortality rate was significantly higher in group 3 than in other groups and significantly higher in group 4 than in groups 1/2, but it showed no difference in the latter two groups (all p < 0.01). By day 28, the left-ventricular (LV) ejection fraction displayed an opposite pattern, whereas by day 60, the gross anatomic infarct size displayed an identical pattern of mortality among the four groups (all p < 0.001). The ratio of heart weight to tibial length and the lung injury score exhibited an identical pattern of mortality (p < 0.01). The protein expressions of apoptosis (mitochondrial-Bax/cleaved-caspase3/cleaved-PARP), fibrosis (Smad3/T-GF-ß), oxidative stress (NOX-1/NOX-2/oxidized-protein), inflammation (MMPs2,9/TNF-α/p-NF-κB), heart failure/pressure overload (BNP/ß-MHC) and mitochondrial/DNA damage (cytosolic-cytochrome-C/γ-H2AX) biomarkers displayed identical patterns, whereas the angiogenesis markers (small vessel number/CD31+cells in LV myocardium) displayed opposite patterns of mortality among the groups (all p < 0.0001). The microscopic findings of fibrotic/collagen deposition/infarct areas and inflammatory cell infiltration of LV myocardium were similar to the mortality among the four groups (all p < 0.0001). MTDKO strongly predicted unfavorable prognostic outcome after AMI.

Construction and Validation of an Autophagy-Related Prognostic Risk Signature for Survival Predicting in Clear Cell Renal Cell Carcinoma Patients.

Background: Clear cell renal cell carcinoma (ccRCC) is a common type of malignant tumors in urinary system. Evaluating the prognostic outcome at the time of initial diagnosis is essential for patients. Autophagy is known to play a significant role in tumors. Here, we attempted to construct an autophagy-related prognostic risk signature based on the expression profile of autophagy-related genes (ARGs) for predicting the long-term outcome and effect of precise treatments for ccRCC patients. Methods: We obtained the expression profile of ccRCC from the cancer genome atlas (TCGA) database and extract the portion of ARGs. We conducted differentially expressed analysis on ARGs and then performed enrichment analyses to confirm the anomalous autophagy-related biological functions. Then, we performed univariate Cox regression to screen out overall survival (OS)-related ARGs. With these genes, we established an autophagy-related risk signature by least absolute shrinkage and selection operator (LASSO) Cox regression. We validated the reliability of the risk signature with receiver operating characteristic (ROC) analysis, survival analysis, clinic correlation analysis, and Cox regression. Then we analyzed the function of each gene in the signature by single-gene gene set enrichment analysis (GSEA). Finally, we analyzed the correlation between our risk score and expression level of several targets of immunotherapy and targeted therapy. Results: We established a seven-gene prognostic risk signature, according to which we could divide patients into high or low risk groups and predict their outcomes. ROC analysis and survival analysis validated the reliability of the signature. Clinic correlation analysis found that the risk group is significantly correlated with severity of ccRCC. Multivariate Cox regression revealed that the risk score could act as an independent predictor for the prognosis of ccRCC patients. Correlation analysis between risk score and targets of precise treatments showed that our risk signature could predict the effects of precise treatment powerfully. Conclusion: Our study provided a brand new autophagy-related seven-gene prognostic risk signature, which could perform as a prognostic indicator for ccRCC. Meanwhile, our study provides a novel sight to understand the role of autophagy and suggest therapeutic strategies in the category of precise treatment in ccRCC.

No correlation between body mass index and 30-day prognostic outcome in Asians with acute ST-elevation myocardial infarction undergoing primary coronary intervention.

BACKGROUND: This study investigated whether body mass index (BMI) was a risk factor predictive of 30-day prognostic outcome in Asians with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI). MATERIAL AND METHODS: Data regarding the impact of BMI on the prognostic outcome in Asian populations after acute STEMI is scarce. A number of 925 STEMI patients were divided into three groups according to the BMI: normal weight (<25 kg/m2), overweight (≥25.0 to <30.0 kg/m2) and obese (≥30.0 kg/m2). RESULTS: The obese group was significantly younger with significantly higher incidences of smoking and diabetes mellitus. The incidences of multi-vessel disease, final thrombolysis in myocardial infarction (TIMI)-3 flow, advanced Killip score, advance congestive heart failure, 30-day mortality and combined 30-day major adverse clinical outcome (MACO) did not differ among the three groups. Multiple regression analysis showed the age, unsuccessful reperfusion and lower left ventricular ejection fraction were most significant and independent predictor of 30-day mortality. CONCLUSION: BMI is not a predictor of 30-day prognostic outcome in Asians with STEMI undergoing primary PCI.

Prognostic influence of witness/victim experiences and PTSD-specific symptoms on working and educational capacity: a comparison between two groups of individuals post-trauma.

BACKGROUND: Trauma exposure depends of the type of trauma and can result in the development of posttraumatic stress disorder (PTSD). The type of traumatization (such as Holocaust experiences and other sources of trauma) and specific symptoms of PTSD have influences on the outcome, and specific symptoms of PTSD influence personal and professional outcomes. Another factor is the role of the victim in their traumatization. Some patients are actively traumatized through being victims of torture, while others are passively traumatized by witnessing the traumatization of others. METHODS: We compared two groups of victim/witness trauma sufferers (PTSD vs. Holocaust-experience PTSD (HE-PTSD)) with regard to PTSD symptoms, educational and working capacity, and functional outcome parameters. RESULTS: HE-PTSD survivors with victim/witness trauma experience showed substantially more specific PTSD symptoms and higher symptom-specific intensities but had high social function and education levels. The intensity and type of intrusive memories and sociodemographic factors do not seem to have a prognostic influence on working or educational outcomes. CONCLUSIONS: Identifying the combined victim/witness experience seems to play an important prognostic role in the assessment of PTSD victims. Further studies should consider these findings within other specific traumatization groups.

Diagnostic and prognostic impact of peritumoral stromal remodeling in patients with surgically treated invasive penile squamous cell cancer.

Stromal remodeling (SR), characterized by focal loss of CD34(+) fibrocytes paralleled by a gain of α-smooth muscle actin (α-SMA)-positive myofibroblasts, has been reported in several cancer types. However, the role of SR in invasive penile squamous cell cancer (PSC) has not been investigated so far. We compared 90 surgically treated PSCs (study group) and 55 control specimens (33 foreskins and 22 differentiated penile intraepithelial neoplasias) for the presence of stromal CD34(+) fibrocytes and α-SMA-positive myofibroblasts scored by independent raters. Multivariate proportional hazards regression analysis was used to assess the impact of staining profiles on cancer-specific mortality of the 90 PSCs (median follow-up, 32 months; interquartile range, 6-64). The incidence of SR differed significantly between study and control group specimens (51.1% versus 9.1%; P < .001). Five years postsurgically, 24% and 46% of the study patients without and with SR had succumbed to their PSC (P = .010). After adjusting for the age at the time of surgery, type of surgery, tumor size, Broders' grade, pT stage, and nodal status, study patients with SR showed 3.76-fold increased cancer-specific mortality (95% confidence interval, 1.3-10.5; P = .012). Our findings suggest that SR might have prognostic as well as some limited differential diagnostic value in terms of delineating invasive PSC from preinvasive lesions. However, our preliminary data clearly need to be validated by larger advanced studies in the future.

The meaning of the prognostic factors in ruptured middle cerebral artery aneurysm with intracerebral hemorrhage.

OBJECTIVE: This study analyzed the relationship between prognosis and multiple clinical factors of ruptured middle cerebral artery (MCA) aneurysm with intracerebral hemorrhage (ICH), to aid in predicting the results of surgical treatment. METHODS: Enrolled subjects were 41 patients with ruptured MCA aneurysm with ICH who were treated with surgical clipping. Clinical factors such as gender, age, and initial Glasgow coma scale were assessed while radiological factors such as the volume and location of hematoma, the degree of a midline shift, and aneurysm size were considered retrospectively. Prognosis was evaluated postoperatively by Glasgow outcome scale. RESULTS: Age and prognosis were correlated only in the groups with ICH over 31 mL or ICH at the frontal lobe or sylvian fissure. When initial mental status was good, only patients with ICH on the temporal lobe had a better prognosis. If the midline shift was less than 4.5 mm, the probability of better prognosis was 95.5% (21 of 22). If the midline shift was more than 4.5 mm, the probability of poor prognosis was 42.1% (8 of 19). Patients with ICH less than 31 mL had higher survival rates, whereas if the ICH was more than 31 mL, 41.2% (7 of 17) had a poor clinical pathway. CONCLUSION: Even if the initial clinical condition of the patient was not promising, by carefully examining and taking into account all factors, neurosurgeons can confidently recommend surgical treatment for these patients.