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Query: UMLS:C0027651 (tumor)
 685,946 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The main objective of this paper is to present a method of evaluating several tumor markers by using the generalized ROC criterion. This criterion finds the best linear combination of the tumor markers such that the area under the ROC curve is maximized. Confidence intervals for the generalized ROC criteria are also presented. This methodology is applied to 51 patients with advanced colorectal cancer for whom the ACE tumor markers were measured before and during chemotherapy treatment. Two populations were defined according to clinical response to chemotherapy. Each marker taken separately, whether on the raw scale or on the transformed scale, contained 0.5 in the confidence interval and was thus non significant. This was also true for both markers on the raw scale. However, the best linear combination on the logarithms of ACE before and at evaluation gave a significantly better area under the ROC curve. A weighted change in ACE measurements significantly distinguishes between responders and non responders in patients with advanced colorectal cancer. We propose that the methodology presented in this paper be used for the evaluation of several tumor markers.
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PMID:[Generalized ROC criteria in the evaluation of several tumor markers]. 1051 78

In this study, we evaluated the accuracy of a neural network in predicting 5-, 10- and 15-year breast-cancer-specific survival. A series of 951 breast cancer patients was divided into a training set of 651 and a validation set of 300 patients. Eight variables were entered as input to the network: tumor size, axillary nodal status, histological type, mitotic count, nuclear pleomorphism, tubule formation, tumor necrosis and age. The area under the ROC curve (AUC) was used as a measure of accuracy of the prediction models in generating survival estimates for the patients in the independent validation set. The AUC values of the neural network models for 5-, 10- and 15-year breast-cancer-specific survival were 0.909, 0.886 and 0.883, respectively. The corresponding AUC values for logistic regression were 0.897, 0.862 and 0.858. Axillary lymph node status (N0 vs. N+) predicted 5-year survival with a specificity of 71% and a sensitivity of 77%. The sensitivity of the neural network model was 91% at this specificity level. The rate of false predictions at 5 years was 82/300 for nodal status and 40/300 for the neural network. When nodal status was excluded from the neural network model, the rate of false predictions increased only to 49/300 (AUC 0. 877). An artificial neural network is very accurate in the 5-, 10- and 15-year breast-cancer-specific survival prediction. The consistently high accuracy over time and the good predictive performance of a network trained without information on nodal status demonstrate that neural networks can be important tools for cancer survival prediction.
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PMID:Artificial neural networks applied to survival prediction in breast cancer. 1057 12

To compare the incidence of radiographic signs in dogs with rhinitis and primary nasal neoplasia and to assess the performance of observers for distinguishing these conditions, the nasal radiographs of 72 dogs with either rhinitis (n = 42) or primary nasal neoplasia (n = 30) were examined by two independent observers using custom-designed forms to record their interpretations. Rhinitis was associated with a higher incidence of focal or multifocal lesions, localised soft tissue opacities, lucent foci, and a lack of frontal sinus involvement. Neoplasia was associated with soft tissue opacities and loss of turbinate detail that affected the entire ipsilateral nasal cavity, signs of invasion of the bones surrounding the nasal cavity, and soft tissue/fluid opacities within the ipsilateral frontal sinus. The signs with the highest positive predictive value (PPV) for rhinitis were absence of frontal sinus lesions and lucent foci in nasal cavity (PPV of each 82%), and invasion of surrounding bones for neoplasia (PPV 88%). There were no significant differences in the position of the lesion within the nasal cavity, incidence of unilateral versus bilateral lesions, calcified lesions, or absence of teeth. There was moderate agreement between observers about the diagnosis (kappa 0.59). Areas (SE) under ROC curves were 0.94 (0.03) and 0.96 (0.03) for observers A and B, respectively (not significantly different; P = 0.68). These results indicate a high accuracy for radiologists examining dogs with nasal diseases. Differentiation of rhinitis and nasal neoplasia should be based on finding combinations of radiologic signs that together have a high PPV. Differences in interpretation between experienced observers in this study suggest that certain signs are potential sources of error.
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PMID:Distinguishing rhinitis and nasal neoplasia by radiography. 1077 70

We evaluated the degree of tubular differentiation in 172 samples of invasive ductal breast cancer in order to determine numerical thresholds for histological breast cancer grading. The tubular differentiation in each sample was defined as the fraction of fields showing tubular differentiation (FTD). The analysis was based on Kaplan-Meier curves reflecting survival and recurrence of disease, univariate and multivariate analyses of Cox's regression, and maximum efficiencies of ROC analysis. The minimum P-value cut-off for FTD was determined at 59%. The practical interpretation is that tubular differentiation in the neoplasm observed in at least 60% of microscopical fields in the tumour area indicates favourable prognosis of disease. The relative risks for breast cancer death for patients with FTD below 59% as compared with those with FTD above 59% were 6.7--and 6.3-fold (univariate and multivariate analyses respectively). Another threshold could be determined at FTD 23%, although this threshold was associated with clearly lower statistical significancies. The paper introduces two possible solutions for application of the thresholds to the morphometric breast cancer grading system. The study also emphasizes the clinical relevance of the evaluation of tubular differentiation in breast cancer. The consistent morphometric evaluation method was vital in allowing the full weight of the biological significance of tubular differentiation to emerge.
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PMID:Morphometric grading of breast cancer: thresholds for tubular differentiation. 1081

Roentgenographically occult bronchogenic squamous cell carcinomas(ROCs) are very small hilar type lung cancer that grow superficially and localize mainly in the bronchial wall, and these patients are expected to have an excellent prognosis after resection. When a ROC is limited within bronchoscopic visibility and less than 10 mm in longitudinal extension and its bronchoscopic findings are slight thickening and flat or wavelet, the tumor is a good candidate for photodynamic therapy. When a ROC is limited within bronchoscopic visibility, the tumor is a good candidate for segmentectomy with curative intent. The tumor invading beyond bronchial wall and/or nodal involvement should be treated by standard operation.
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PMID:[Strategy of treatment for roentgenographically occult lung cancer]. 1082 58

c-erbB-2 protein levels in tissue extracts and sera were determined in a retrospective analysis of 158 patients who underwent surgical resection of breast carcinoma by means of a sandwich enzyme immunometric assay (EIA) using monoclonal antibodies (MAbs) directed to the extracellular domain of the c-erbB-2 oncogene protein (ErbB-2). In the analysis of tissue extracts, 48 samples (30.3%) showed ErbB-2 levels exceeding 18.0 ng/mg protein (group A), while in 110 samples these levels were below 18.0 ng/mg protein (group B). Immunohistochemical examination of resected tissues using anti-c-erbB-2 antibody revealed positive staining in 93.8% (45/48) in group A and 13.6% (15/110) in group B (p < 0.00001). The proportion of patients who preoperatively showed a serum ErbB-2 value above 5.4 ng/ml was 52.1% (25/48) in group A and 10.0% (11/110) in group B (p < 0.00001). Thus, the level of ErbB-2 in tissue extracts was significantly associated with immunohistochemistry and ErbB-2 levels in preoperative sera. During follow-up, 48 patients (30.3%) developed recurrent disease: 17 in group A (35.4%) and 31 in group B (28.2%). From an ROC analysis based on the postoperative serum ErbB-2 levels in patients either with or without relapse, the cutoff value of serum ErbB-2 for tumor relapse was determined to be 6.5 ng/ml. The sensitivity of serum ErbB-2 in patients with relapsed breast cancer was 58.3% (21/36) overall, 84.6% (11/13) in group A and 43.5% (10/23) in group B. In the analysis of serum samples taken before relapse, 90.9% (10/11) of the subjects in group A and 26.7% (4/15) of those in group B were shown to be positive for serum ErbB-2. Serum ErbB-2 in group A was a more sensitive marker than other tumor markers such as CEA, CA15-3, and NCC-ST-439. Thus, the determination of ErbB-2 in tissue extracts of breast carcinoma may be useful for assessing c-erbB-2 protein expression in the primary tissue and indicates that serum ErbB-2 may be a sensitive marker for monitoring tumor relapse.
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PMID:Combined measurement of the c-erbB-2 protein in breast carcinoma tissues and sera is useful as a sensitive tumor marker for monitoring tumor relapse. 1095 6

The search for markers as potential prognostic factors for different stages of disease is becoming a major task in clinical research. Enormous amounts of information on the effectiveness of tumor markers are being published, and many of these results are conflicting and thus adding confusion to the area. In this paper we discuss the problem of multiplicity that we believe is one of the major statistical reasons for the conflicting results. We further review the ROC curve and the area under it as a popular statistical tool for evaluating the ability of a marker to distinguish between two populations. Finally we provide an extension to the ROC analysis when several markers are available.
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PMID:Methodological issues associated with tumor marker development. Biostatistical aspects. 1097 9

Localization ROC (LROC) observer studies examined whether detector response compensation (DRC) in ordered-subset, expectation-maximization (OSEM) reconstructions helps in the detection and localization of hot tumors. Simulated gallium (Ga-67) images of the thoracic region were used in the study. The projection data modeled the acquisition of attenuated 93- and 185-keV photons with a medium-energy parallel-hole collimator, but scatter was not modeled. Images were reconstructed with five strategies: 1) OSEM with no DRC; 2) OSEM preceded by restoration filtering; 3) OSEM with iterative DRC; 4) OSEM with an ideal DRC; and 5) filtered backprojection (FBP) with no DRC. All strategies included attenuation correction. There were four LROC studies conducted. In a study using a single tumor activity, the ideal DRC offered the best performance, followed by iterative DRC, restoration filtering, OSEM with no DRC, and FBP. Statistical significance at the 5% level was found between all pairs of strategies except for restoration filtering and OSEM with no DRC. A similar ranking was found for a more realistic study using multiple tumor activities. Additional studies considered the effects of OSEM iteration number and tumor activity on the detection improvement that iterative DRC offered with respect to OSEM with no DRC.
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PMID:LROC analysis of detector-response compensation in SPECT. 1102 89

The ligands, receptors and related signaling proteins of the insulin-like growth factor family are involved in the regulation of breast-cancer cell growth. We investigated the expression pattern of insulin-like growth factor-I receptor (IGF-IR), insulin receptor (IR) and insulin receptor substrate-1 (IRS-1), a core downstream signaling protein, in 69 primary breast-cancer specimens of different grades and in 21 control tissues by immunohistochemistry. In addition, cell proliferation (percentage of Ki67(+) nuclei) and estrogen receptor (ER) expression were determined. IGF-IR, IRS-1 and IR were expressed mainly in epithelial cells. IRS-1 and IGF-IR were expressed at high levels in control tissues and in well and moderately differentiated carcinomas but at low levels in poorly differentiated breast cancers. IR expression did not show a significant correlation with the differentiation grade of the tissues investigated. Statistical analysis (ROC analysis for tumor grade) demonstrated that down-regulation of IGF-IR and IRS-1 correlated better with tumor progression than reduction of ER expression or increase in cell proliferation, IGF-IR showing the best correlation, followed by IRS-1 and, less significant, ER and Ki67. Our findings clearly show that progression of breast cancer is accompanied by a reduction of IGF-IR/IRS-1 expression and that IGF-IR/IRS-1 expression inversely correlates with high proliferation rate in dedifferentiated breast cancers. The strong correlation of IGF-IR and IRS-1 down-regulation with tumor progression suggests the use of IGF-IR and IRS-1 as a novel set of marker proteins for tumor grading.
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PMID:Down-regulation of insulin-like growth factor-I receptor and insulin receptor substrate-1 expression in advanced human breast cancer. 1110 95

The RING (really interesting new gene) finger proteins containing a characteristic C3HC4 or C3H2C3 motif appear to act as E3 ubiquitin ligase and play important roles in many processes, including cell-cycle progression, oncogenesis, signal transduction, and development. This review is focused on SAG/ROC/Rbx/Hrt (sensitive to apoptosis gene/regulator of cullins/RING box protein), an evolutionarily conserved RING finger family of proteins that were cloned recently by several independent laboratories through differential display, yeast two-hybrid screening, or biochemical purification. SAG/ROC2/Rbx2/Hrt2 is expressed in multiple mouse adult tissues, as well as early embryos. In humans, both SAG and ROC1 are ubiquitously expressed at a very high level in heart, skeletal muscle, and testis. Expression of both SAG and ROC1 is induced by mitogenic stimulation. SAG is also induced by a redox agent in cultured cells, as well as in in vivo mouse brain upon ischemia/reperfusion. Structurally, SAG consists of four exons and three introns with at least one splicing variant and two pseudogenes. The SAG gene promoter is enriched with multiple transcription factor binding sites. Biochemically, SAG binds to RNA, has metal-ion binding/free radical scavenging activity, and is redox-sensitive. Most importantly, like ROC1, SAG/ROC2 binds to cullins and acts as an essential component of E3 ubiquitin ligase. Biologically, SAG is a growth-essential gene in yeast. In mammalian cells, SAG protects apoptosis mainly through inhibition of cytochrome c release/caspase activation, and promotes growth under serum deprivation at least in part by inhibiting p27 accumulation. Blocking SAG expression via antisense transfection inhibits tumor cell growth. Thus, SAG appears to be a valid drug target for anticancer therapy.
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PMID:SAG/ROC/Rbx/Hrt, a zinc RING finger gene family: molecular cloning, biochemical properties, and biological functions. 1155 50


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