988 resultados para Prognostic Models


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Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.

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The FLEX study demonstrated that the addition of cetuximab to chemotherapy significantly improved overall survival in the first-line treatment of patients with advanced non-small cell lung cancer (NSCLC). In the FLEX intention to treat (ITT) population, we investigated the prognostic significance of particular baseline characteristics. Individual patient data from the treatment arms of the ITT population of the FLEX study were combined. Univariable and multivariable Cox regression models were used to investigate variables with potential prognostic value. The ITT population comprised 1125 patients. In the univariable analysis, longer median survival times were apparent for females compared with males (12.7 vs 9.3 months); patients with an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0 compared with 1 compared with 2 (13.5 vs 10.6 vs 5.9 months); never smokers compared with former smokers compared with current smokers (14.6 vs 11.1 vs 9.0); Asians compared with Caucasians (19.5 vs 9.6 months); patients with adenocarcinoma compared with squamous cell carcinoma (12.4 vs 9.3 months) and those with metastases to one site compared with two sites compared with three or more sites (12.4 months vs 9.8 months vs 6.4 months). Age (<65 vs ≥65 years), tumor stage (IIIB with pleural effusion vs IV) and percentage of tumor cells expressing EGFR (<40% vs ≥40%) were not identified as possible prognostic factors in relation to survival time. In multivariable analysis, a stepwise selection procedure identified age (<65 vs ≥65 years), gender, ECOG PS, smoking status, region, tumor histology, and number of organs involved as independent factors of prognostic value. In summary, in patients with advanced NSCLC enrolled in the FLEX study, and consistent with previous analyses, particular patient and disease characteristics at baseline were shown to be independent factors of prognostic value. The FLEX study is registered with ClinicalTrials.gov, number NCT00148798. © 2012 Elsevier Ireland Ltd.

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Non-small cell lung carcinoma remains by far the leading cause of cancer-related deaths worldwide. Overexpression of FLIP, which blocks the extrinsic apoptotic pathway by inhibiting caspase-8 activation, has been identified in various cancers. We investigated FLIP and procaspase-8 expression in NSCLC and the effect of HDAC inhibitors on FLIP expression, activation of caspase-8 and drug resistance in NSCLC and normal lung cell line models. Immunohistochemical analysis of cytoplasmic and nuclear FLIP and procaspase-8 protein expression was carried out using a novel digital pathology approach. Both FLIP and procaspase-8 were found to be significantly overexpressed in tumours, and importantly, high cytoplasmic expression of FLIP significantly correlated with shorter overall survival. Treatment with HDAC inhibitors targeting HDAC1-3 downregulated FLIP expression predominantly via post-transcriptional mechanisms, and this resulted in death receptor- and caspase-8-dependent apoptosis in NSCLC cells, but not normal lung cells. In addition, HDAC inhibitors synergized with TRAIL and cisplatin in NSCLC cells in a FLIP- and caspase-8-dependent manner. Thus, FLIP and procaspase-8 are overexpressed in NSCLC, and high cytoplasmic FLIP expression is indicative of poor prognosis. Targeting high FLIP expression using HDAC1-3 selective inhibitors such as entinostat to exploit high procaspase-8 expression in NSCLC has promising therapeutic potential, particularly when used in combination with TRAIL receptor-targeted agents.

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Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

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Background and aims: Low stage and curative surgery are established factors for improved survival in gastric cancer. However, not all low-stage patients have a good prognosis. Cyclooxygenase-2 (COX-2) is known to associate with reduced survival in several cancers, and has been shown to play an important role in gastric carcinogenesis. Since new and better prognostic markers are needed for gastric cancer, we studied the prognostic significance of COX-2 and of markers that associate with COX-2 expression. We also studied markers reflecting proliferation and apoptosis, and evaluated their association with COX-2. Our purpose was to construct an accurate prognostic model by combining tissue markers and clinicopathogical factors. Materials and methods: Of 342 consecutive patients who underwent surgery for gastric cancer at Meilahti Hospital, Helsinki University Central Hospital, 337 were included in this study. Low stages I to II were represented by 141 (42%) patients, and high stages III to IV by 196 (58%). Curative surgery was performed on 176 (52%) patients. Survival data were obtained from the national registers. Slides from archive tissue blocks were prepared for immunohistochemistry by use of COX-2, human antigen R (HuR), cyclin A, matrix metalloproteinases 2 and 9 (MMP-2, MMP-9), and Ki-67 antibodies. Immunostainings were scored by microscopy, and scores were entered into a database. Associations of tumor markers with clinicopathological factors were calculated, as well as associations with p53, p21, and results of flow cytometry from earlier studies. Survival analysis was performed by the Kaplan-Meier method, and Cox multivariate models were reconstructed. Cell culture experiments were performed to explore the effect of small interfering (si)RNA of HuR on COX-2 expression in a TMK-1 gastric cancer cell line. Results: Overall 5-year survival was 35.1%. Study I showed that COX-2 was an independent prognostic factor, and that the prognostic impact of COX-2 was more pronounced in low-stage patients. Cytoplasmic HuR expression also associated with reduced survival in gastric cancer patients in a non-independent manner. Cell culture experiments showed that HuR can regulate COX-2 expression in TMK-1 cells in vitro, with an association also between COX-2 and HuR tissue expression in a clinical material. In Study II, cyclin A was an independent prognostic factor and was associated with HuR expression in the gastric cancer material. The results of Study III showed that epithelial MMP-2 associated with survival in univariate, but not in multivariate analysis. However, MMP-9 showed no prognostic value. MMP-2 expression was associated with COX-2 expression. In Study IV, the prognostic power of COX-2 was compared with that of all tested markers associated with survival in Studies I to III, as well as with p21, p53, and flow cytometry results. COX-2 and p53 were independent prognostic factors, and COX-2 expression was associated with that of p53 and Ki-67 and also with aneuploidy. Conclusions: COX-2 is an independent prognostic factor in gastric cancer, and its prognostic power emerges especially in low stage cancer. COX-2 is regulated by HuR, and is associated with factors reflecting invasion, proliferation, and apoptosis. In an extended multivariate model, COX-2 retained its position as an independent prognosticator. COX-2 can be considered a promising new prognostic marker in gastric cancer.

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This paper describes a prognostic method which combines the physics of failure models with probability reasoning algorithm. The measured real time data (temperature vs. time) was used as the loading profile for the PoF simulations. The response surface equation of the accumulated plastic strain in the solder interconnect in terms of two variables (average temperature, and temperature amplitude) was constructed. This response surface equation was incorporated into the lifetime model of solder interconnect, and therefore the remaining life time of the solder component under current loading condition was predicted. The predictions from PoF models were also used to calculate the conditional probability table for a Bayesian Network, which was used to take into account of the impacts of the health observations of each product in lifetime prediction. The prognostic prediction in the end was expressed as the probability for the product to survive the expected future usage. As a demonstration, this method was applied to an IGBT power module used for aircraft applications.

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The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or

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PURPOSE The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. PATIENTS AND METHODS Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and WBC. Two different models of prognostic scores for 90-day mortality were generated by using these factors, including or excluding PS; both achieved specificities of more than 85% and sensitivities of approximately 50% when using a score cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. CONCLUSION Patient selection using any of these prognostic scores will reduce non-drug-related 90-day mortality among patients enrolled in phase I trials by 50%. However, this can be achieved only by an overall reduction in recruitment to phase I studies of 20%, more than half of whom would in fact have survived beyond 90 days.

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Metastasis accounts largely for the high mortality rate of colorectal cancer (CRC) patients. In this study, we performed comparative proteome analysis of primary CRC cell lines HCT-116 and its metastatic derivative E1 using 2-D DIGE. We identified 74 differentially expressed proteins, many of which function in transcription, translation, angiogenesis signal transduction, or cytoskeletal remodeling pathways, which are indispensable cellular processes involved in the metastatic cascade. Among these proteins, stathmin-1 (STMN1) was found to be highly up-regulated in E1 as compared to HCT-116 and was thus selected for further functional studies. Our results showed that perturbations in STMN1 levels resulted in significant changes in cell migration, invasion, adhesion, and colony formation. We further showed that the differential expression of STMN1 correlated with the cells' metastatic potential in other paradigms of CRC models. Using immunohistochemistry, we also showed that STMN1 was highly expressed in colorectal primary tumors and metastatic tissues as compared to the adjacent normal colorectal tissues. Furthermore, we also showed via tissue microarray analyses of 324 CRC tissues and Kaplan-Meier survival plot that CRC patients with higher expression of STMN1 have poorer prognosis.

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Non-small cell lung carcinoma remains by far the leading cause of cancer-related deaths worldwide. Overexpression of FLIP, which blocks the extrinsic apoptotic pathway by inhibiting caspase-8 activation, has been identified in various cancers. We investigated FLIP and procaspase-8 expression in NSCLC and the effect of HDAC inhibitors on FLIP expression, activation of caspase-8 and drug resistance in NSCLC and normal lung cell line models. Immunohistochemical analysis of cytoplasmic and nuclear FLIP and procaspase-8 protein expression was carried out using a novel digital pathology approach. Both FLIP and procaspase-8 were found to be significantly overexpressed in tumours, and importantly, high cytoplasmic expression of FLIP significantly correlated with shorter overall survival. Treatment with HDAC inhibitors targeting HDAC1-3 downregulated FLIP expression predominantly via post-transcriptional mechanisms, and this resulted in death receptor- and caspase-8-dependent apoptosis in NSCLC cells, but not normal lung cells. In addition, HDAC inhibitors synergized with TRAIL and cisplatin in NSCLC cells in a FLIP- and caspase-8-dependent manner. Thus, FLIP and procaspase-8 are overexpressed in NSCLC, and high cytoplasmic FLIP expression is indicative of poor prognosis. Targeting high FLIP expression using HDAC1-3 selective inhibitors such as entinostat to exploit high procaspase-8 expression in NSCLC has promising therapeutic potential, particularly when used in combination with TRAIL receptor-targeted agents.

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Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

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Detection of pretreatment disseminated cells (pre-DTC) reflecting its homing to bone marrow (BM) in prostate cancer (PCa) might improve the current model to predict recurrence or survival in men with nonmetastatic disease despite of primary treatment. Thereby, pre-DTC may serve as an early prognostic biomarker. Post-treatment DTCs (post-DTC) finding may supply the clinician with additional predictive information about the possible course of PCa. To assess the prognostic impact of DTCs in BM aspirates sampled before initiation of primary therapy (pre-DTC) and at least 2 years after (post-DTC) to established prognostic factors and survival in patients with PCa. Available BM of 129 long-term follow-up patients with T1-3N0M0 PCa was assessed in addition to 100 BM of those in whom a pretreatment BM was sampled. Patients received either combined therapy [n = 81 (63%)], radiotherapy (RT) with different duration of hormone treatment (HT) or monotherapy with RT or HT alone [n = 48 (37%)] adapted to the criteria of the SPCG-7 trial. Mononuclear cells were deposited on slides according to the cytospin methodology and DTCs were identified by immunocytochemistry using the pancytokeratin antibodies AE1/AE3. The median age of men at diagnosis was 64.5 years (range 49.5-73.4 years). The median long-term follow-up from first BM sampling to last observation was 11 years. Categorized clinically relevant factors in PCa showed only pre-DTC status as the statistically independent parameter for survival in the multivariate analysis. Pre-DTCs homing to BM are significantly associated with clinically relevant outcome independent to the patient's treatment at diagnosis with nonmetastatic PCa.

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PURPOSE: EphA2, a member of the Eph receptor tyrosine kinases family, is an important regulator of tumor initiation, neovascularization, and metastasis in a wide range of epithelial and mesenchymal cancers; however, its role in colorectal cancer recurrence and progression is unclear.

EXPERIMENTAL DESIGN: EphA2 expression was determined by immunohistochemistry in stage II/III colorectal tumors (N = 338), and findings correlated with clinical outcome. The correlation between EphA2 expression and stem cell markers CD44 and Lgr5 was examined. The role of EphA2 in migration/invasion was assessed using a panel of KRAS wild-type (WT) and mutant (MT) parental and invasive colorectal cancer cell line models.

RESULTS: Colorectal tumors displayed significantly higher expression levels of EphA2 compared with matched normal tissue, which positively correlated with high CD44 and Lgr5 expression levels. Moreover, high EphA2 mRNA and protein expression were found to be associated with poor overall survival in stage II/III colorectal cancer tissues, in both univariate and multivariate analyses. Preclinically, we found that EphA2 was highly expressed in KRASMT colorectal cancer cells and that EphA2 levels are regulated by the KRAS-driven MAPK and RalGDS-RalA pathways. Moreover, EphA2 levels were elevated in several invasive daughter cell lines, and downregulation of EphA2 using RNAi or recombinant EFNA1 suppressed migration and invasion of KRASMT colorectal cancer cells.

CONCLUSIONS: These data show that EpHA2 is a poor prognostic marker in stage II/III colorectal cancer, which may be due to its ability to promote cell migration and invasion, providing support for the further investigation of EphA2 as a novel prognostic biomarker and therapeutic target. Clin Cancer Res; 22(1); 230-42. ©2015 AACR.

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In the development and progression of hepatocellular carcinoma, tumor hypoxia plays an important role, as does activation of the Wnt pathway. The aim of this study was to characterize the expression and interrelationship between hypoxia and Wnt-pathway-associated proteins as prognostic factors for hepatocellular carcinoma. Expression of HIF-1α, CA-IX, E-cadherin, β-catenin, and Ki-67 was assessed by immunohistochemistry in 179 primary hepatocellular carcinoma cases. Univariate and multivariate analyses were performed to assess the relationship between the clinicopathological factors, protein expression, overall survival (OS), and recurrence-free survival (RFS). By univariate analysis, tumor stage, size, satellitosis, and vascular invasion were confirmed as prognostic factors for worse OS and RFS. High expression of HIF-1α, CA-IX, β-catenin, Ki-67, and E-cadherin was observed in 60, 15, 64, 8, and 64 % of tumors, respectively, and this was significantly associated with poor OS. CA-IX, HIF-1α, and E-cadherin were independent predictors of poor prognosis. We stratified 169 patients into four groups according to the expression level of hypoxia and Wnt pathway markers. The group with high expression of both hypoxia and Wnt-pathway-associated proteins showed worst OS. The poor survival of this group was also significant in patients with early stage disease and tumor size of less than 5 cm (p < 0.05). We identified a subgroup of hepatocellular carcinoma patients with high expression of both hypoxia and Wnt pathway proteins and found this predictive of poor survival. The therapeutic options for this group might need to be revisited.

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Background: EpHA2 is a 130 kD transmembrane glycoprotein belonging to ephrin receptor subfamily and involved in angiogenesis/tumour neovascularisation. High EpHA2 mRNA level has recently been implicated in cetuximab resistance. Previously, we found high EpHA2 levels in a panel of invasive colorectal cancer (CRC) cells, which was associated with high levels of stem-cell marker CD44. Our aim was to investigate the prognostic value of EpHA2 and subsequently correlate expression levels to known clinico-pathological variables in early stage CRC. Methods: Tissue samples from 509 CRC patients were analysed. EpHA2 expression was measured using IHC. Kaplan-Meier graphs were used. Univariate and multivariate analyses employed Cox Proportional Hazards Ratio (HR) method. A backward selection method (Akaike’s information criterion) was used to determine a refined multivariate model. Results: EpHA2 was highly expressed in CRC adenocarcinoma compared to matched normal colon tissue. In support of our preclinical invasive models, strong correlation was found between EpHA2 expression and CD44 and Lgr5 staining (p<0.001). In addition, high EpHA2 expression significantly correlated with vascular invasion (p=0.03).HR for OS for stage II/III patients with high EpHA2 expression was 1.69 (95%CI: 1.164-2.439; p=0.003). When stage II/III was broken down into individual stages, there was significant correlation between high EpHA2 expression and poor 5-years OS in stage II patients (HR: 2.18; 95%CI: 1.28-3.71; p=0.005).HR in the stage III group showed a trend to statistical significance (HR: 1.48; 95%CI=0.87-2.51; p=0.05). In both univariate and multivariate analyses of stage II patients, high EpHA2 expression was the only significant factor and was retained in the final multivariate model. Higher levels of EpHA2 were noted in our RAS and BRAF mutant CRC cells, and silencing EpHA2 resulted in significant decreases in migration/invasion in parental and invasive CRC sublines. Correlation between KRAS/NRAS/BRAFmutational status and EpHA2 expression in clinical samples is ongoing. Conclusions: Taken together, our study is the first to indicate that EpHA2 expression is a predictor of poor clinical outcome and a potential novel target in early stage CRC.