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At least 127 records · Page 7Linked to original sources
PubMed2026

Identification of ultrasound-associated gene candidates in myeloid cells and construction of a prognostic risk model for acute myeloid leukemia.

BACKGROUND: Incorporating ultrasound (US) treatment sensitivity analysis may improve the treatment of acute myeloid leukemia (AML). METHODS: This study integrated single-cell and bulk datasets for analysis. Differential expression analysis between US-treated and control samples was performed using limma package. The AUCell package was used to calculate US-associated scores in the single-cell dataset. Differentially expressed genes (DEGs) between the specific groups were identified, followed by intersection analysis with previously identified DEGs. Univariate regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis (using the glmnet package), and stepwise multivariate regression (using the MASS package) were used to refine the candidate genes and to construct a risk model. The model genes were validated using in vitro experiments. Enrichment analysis was conducted using gene set enrichment analysis (GSEA), and immune infiltration was evaluate by single-sample GSEA (ssGSEA) and ESTIMATE algorithms. The correlations between RiskScores and drug sensitivity were analyzed by oncoPredict package. Finally, tumor mutational burden (TMB) and genomic mutations were compared between the risk groups. RESULTS: Nine prognostic signatures (SPINK2, HNRNPAB, SH3BGRL3, CLEC11A, ITGA4, RPL39L, MX1, HEXIM1, and MAP4K4) were identified. Particularly, low expression of SPINK2 attenuated the activity and invasion of AML cells. High-risk group had higher immune cell infiltration. Eight drugs were predicted to be correlated with the RiskScore model. DNMT3A and RUNX1 showed higher mutation frequencies in the high-risk group, whereas KIT and MUC16 showed higher mutation frequencies in the low-risk group. CONCLUSION: The RiskScore model established in this study provides a theoretical basis for clinically screening responsive populations and optimizing treatment strategies.

Humans↗
PubMed2000

Evaluating the simplified Conjoint Expected Risk model: comparing the use of objective and subjective information

The simplified Conjoint Expected Risk (CER) model by Holtgrave and Weber posits that perceived risk is a linear combination of the subjective judgments of the probabilities of harm, benefit, and status quo, and the expected harm and benefit of an activity. It modifies Luce and Weber's original CER model--that uses objective information to evaluate financial gambles--to accommodate activities such as health/technology activities where values of the model variables are subjective. If the simplified model is a valid modification of the original model, its performance should not be sensitive to the use of subjective information. However, because people may evaluate information differently when objective information is provided to them than when they generate information on their own, the performance of the simplified CER model may not be robust to the source of model-variable information. We compared the use of objective and subjective information, and results indicate that the estimates of the simplified CER model parameters and the proportion of variance in risk judgments accounted for by the model are similar under these two conditions. Thus, the simplified CER model is viable with activities for which harm and benefit information is subjective.

Journal Article↗
PubMed1997

Morbid obesity, absorption, neuroticism, and the high risk model of threat perception.

We studied 70 morbidly obese patients, candidates for gastric exclusion surgery. We found that their mean absorption score was significantly lower and that their mean neuroticism score significantly higher than a matched control group. These results are consistent with predictions from the High Risk Model of Threat Perception (Wickramasekera, 1979, 1986, 1988, 1993a). People high in neuroticism are hypothesized to be hypersensitive to threat and, therefore, at greater risk for stress related psychobiological disorders. But if they are also low in absorption, they are hypothesized to have poor conscious perception of psychosocial threats and, therefore, they develop a very restricted range of psychosocial methods of coping with such threats. Consequently, lows may be mainly restricted to behavioral methods of coping like feeding and drinking to self-soothe unconscious aversive emotions associated with autonomic dysregulation and elevated parasympathetic tone. Their skeptical, rational, pragmatic cognitive style drives them to perceive medical surgical solutions to weight gain as more credible than psychosocial weight reduction programs.

Adult↗
PubMed2000

Short-term breast cancer prediction by random periareolar fine-needle aspiration cytology and the Gail risk model.

BACKGROUND: : Biomarkers are needed to refine short-term breast cancer risk estimates from epidemiologic models and to measure response to prevention interventions. The purpose of our study was to determine whether the cytologic appearance of epithelial cells obtained from breast random periareolar fine-needle aspirates or molecular marker expression in these cells was associated with later breast cancer development. METHODS: : Four hundred eighty women who were eligible on the basis of a family history of breast cancer, prior precancerous biopsy, and/or prior invasive cancer were enrolled in a single-institution, prospective trial. Their risk of breast cancer according to the Gail model was calculated, and random periareolar fine-needle aspiration was performed at study entry. Cells were characterized morphologically and analyzed for DNA aneuploidy by image analysis and for the expression of epidermal growth factor receptor, estrogen receptor, p53 protein, and HER2/NEU protein by immunocytochemistry. All statistical tests are two-sided. RESULTS: : At a median follow-up time of 45 months after initial aspiration, 20 women have developed breast cancer (invasive disease in 13 and ductal carcinoma in situ in seven). With the use of multiple logistic regression and Cox proportional hazards analysis, subsequent cancer was predicted by evidence of hyperplasia with atypia in the initial fine-needle aspirate and a 10-year Gail projected probability of developing breast cancer. Although expression of epidermal growth factor receptor, estrogen receptor, p53, and HER2/NEU was statistically significantly associated with hyperplasia with atypia, it did not predict the development of breast cancer in multivariable analysis. CONCLUSION: : Cytomorphology from breast random periareolar fine-needle aspirates can be used with the Gail risk model to identify a cohort of women at very high short-term risk for developing breast cancer. We recommend that cytomorphology be studied for use as a potential surrogate end point in prevention trials.

Adult↗
PubMedDate not supplied

A risk model for non-small cell lung cancer using clinicopathological variables, angiogenesis and oncoprotein expression.

BACKGROUND: The aim of this study was to investigate new prognostic factors, by using a prognostic model, that could help to identify the patient group with the greatest probability of death. PATIENTS AND METHODS: First, the clinicopathological variables were analyzed. Second, microvessels were immunohistochemically (IHC) stained with factor VIII-related antibody and then counted in the most intense vascularization area or hotspot, using an automatic image analyzer. In addition, biological angiogenesis-related factors such as vascular endothelial growth factor (VEGF) and inducible nitric oxide synthase expression (iNOS) were also studied. Finally, we evaluated the IHC expression of p53 and p21WAF1 tumor supressor proteins. RESULTS: The significant independent predictors were: tumor size (p=0.0063), angiogenesis (p=0.0271) and p21WAF1 (p=0.0478). Thus, the most important factor was tumor size 2.7462 [95% CI=1.3307-5.6673]. Finally, these variables were included in a risk model, in order to identify the group with the highest associated probability of death. CONCLUSION: The analysis of several prognostic factors could establish a more accurate patient risk profile.

Aged↗
PubMed1996

Noninvasive risk modeling after myocardial infarction.

The aim of this study was to extract and combine non-invasive risk parameters from the signal-averaged electrocardiogram (SAECG) and heart rate variability (HRV) based on 24-hour ambulatory electrocardiography to optimize the prognostic value for arrhythmic events after acute myocardial infarction. A prospective series of 553 men < 66 years of age enrolled in the Post-Infarction Late Potential study were analyzed. Within 2 to 4 weeks after acute myocardial infarction, all patients underwent SAECG and 24-hour ambulatory electrocardiography before hospital discharge. During 6 months of followup, 25 patients (4.5%) experienced arrhythmic events (sustained ventricular tachycardia, n = 11; ventricular fibrillation, n = 7; sudden cardiac death, n = 7). The predictive power of SAECG and HRV parameters was assessed using a Cox proportional-hazards model. In HRV analysis, the most significant differences between patients with and without arrhythmic events were observed for the beat-to-beat parameter root-meansquare of successive RR differences [RMSSD]): 25.7 +/- 16.9 ms in patients with arrhythmic events versus 34.1 +/- 18.6 ms in patients free of arrhythmic events (p = 0.004). Time domain analysis of the SAECG showed the QRS duration to be most significantly different in both patient groups: 106.4 +/- 18.7 ms (arrhythmic events) versus 95.3 +/- 18.7 ms (no arrhythmic events) (p = 0.001). Based on the Cox regression model, RMSSD and QRS duration were demonstrated to be independent significant risk factors (regression coefficient for QRS duration: cq = 0.014 +/- 0.006 ms(-1), p = 0.014; for RMSSD: cr = -0.041 +/- 0.016 ms(-1), p = 0.009). Based on the regression coefficients, an analytic risk model was developed describing the arrhythmic risk as a function of QRS duration, RMSSD, and time after infarction. We conclude that the combination of beat-to-beat changes of heart rate measured by RMSSD and QRS duration from the SAECG enhances noninvasive risk stratification after myocardial infarction.

Arrhythmias, Cardiac↗
PubMed2000

Prospective validation of a low-back disorder risk model and assessment of ergonomic interventions associated with manual materials handling tasks.

The evaluation of low-back disorder risk associated with materials handling tasks can be performed using a variety of assessment tools. Most of these tools vary greatly in their underlying logic, yet few have been assessed for their predictive ability. It is important to document how well an assessment tool realistically reflects the job's injury risk, since only valid and accurate tools can reliably determine whether a given ergonomic intervention will result in a future reduction in back injuries. The goal of this study was to evaluate how well a previously reported low-back disorder (LBD) risk assessment model (Marras et al. 1993) could predict changes in LBD injury rates as the physical conditions to which employees are exposed were changed. Thirty-six repetitive materials handling jobs from 16 different companies were included in this prospective cohort study. Of these 36 jobs, 32 underwent an ergonomic intervention during the observation period, and four jobs in which no intervention occurred served as a comparison group. The trunk motions and workplace features of 142 employees performing these jobs were observed both before and after workplace interventions were incorporated. In addition, the jobs' LBD rates were documented for these pre- and post-intervention periods. The results indicated that a statistically significant correlation existed between changes in the jobs' estimated LBD risk values and changes in their actual low-back incidence rates over the observation period. Linear and Poisson regression models also were developed to predict a change in a job's incidence rate and the number of LBD on ajob respectively, as a function of the job's risk change using this assessment model. Finally, this prospective study showed which ergonomic interventions consistently reduced the jobs' mean low-back incidence rates. These results support use of the LBD risk model to assess accurately a job's potential to lead to low-back injuries among its employees.

Adult↗
PubMed2002

Tools from ecology: useful for evaluating infection risk models?

Despite the increasing number of models to predict infection risk for a range of diseases, the assessment of their spatial limits, predictive performance and practical application are not widely undertaken. Using the example of Schistosoma haematobium in Africa, this article illustrates how ecozonation and receiver-operator characteristic analysis can help to assess the usefulness of available models objectively.

Africa↗
PubMed2002

Supplemental value of troponin I combined with a clinical risk model to predict in-hospital events in intermediate and high risk patients with acute coronary syndromes.

To evaluate the supplemental value of serial troponin I (Trp) measurements when combined with a clinical model composed of six clinical parameters in predicting in-hospital adverse event rates, a total of 118 consecutive patients admitted over a 23-month period with intermediate- or high-risk unstable angina or non-Q wave myocardial infarction (MI) as defined by AHCPR criteria who had coronary angiography within 72 hours of hospitalization were studied. Presenting clinical characteristics were graded using a previously validated variation of the Braunwald criteria (RUSH model). The RUSH model clinical score includes six clinical parameters: age, diabetes, intravenous nitroglycerin, pre-admission calcium-channel and beta-blocker, ST depression and post-MI angina (< 2 weeks), and creates an estimated probability of MI or death. The RUSH model was compared to serial Trp levels drawn at 6-hour intervals (0, 6 and 12 hours). An abnormal Trp value was defined as > 2.0 mg/dl. Outcome measures included death, MI, recurrent chest pain and new ST or T changes and enzyme elevation. One death, 23 MIs and 24 other adverse clinical events occurred. The event group had a RUSH score predictive of 12.7 12.4% risk and the no-event group had a score of 13.2 10.2% risk (p = 0.64). The Trp positive group had a clinical score predicting 14.2 13.2% risk and the Trp negative group had a score of 11.7 9.3% risk (p = 0.21). Patients with elevated Trp had an adverse event rate of 32/50 (64%) vs. 21/68 (31%) in patients with normal Trp (p < 0.0004). Elevated Trp had 60.4% sensitivity and 72.3% specificity, odds ratio of 3.97 (1.71 9.33), as well as 64% positive and 69.1% negative predictive values for predicting adverse events. Thus, there was significant incremental value to adding Trp to the clinical score when predicting outcomes in patients with intermediate- and high-risk clinical scores. When Trp was abnormal, it was useful when predicting higher risk; if Trp was normal, it was useful predicting lower but still elevated risk. Consequently, in a population selected for intermediate and high risk, the presence or absence of elevated Trp I is a sensitive and specific additive predictor to clinical score to predict need for revascularization and adverse in-hospital outcomes, as suggested in current guidelines.

Aged↗
PubMed1996

A risk model for ovarian carcinoma patients using CA 125: time to normalization renders second-look laparotomy redundant.

BACKGROUND: We evaluated the incorporation of CA 125 normalization times into a prognostic model based on pretreatment variables in patients with ovarian carcinoma to determine if they could render second-look laparotomy (SLL) redundant. METHODS: A total of 54 consecutive patients with ovarian carcinoma who underwent SLL between 1985 and 1990 were included in this analysis. At diagnosis, all of the patients had abnormal CA-125 serum levels, which fell to within the normal range during chemotherapy. Cox's model was used to select pretreatment variables relevant for prognosis. The influence of the time to normalization of CA 125 (< or = vs. > 1 months) and the capability of SLL results to modify prognostic prediction, were also evaluated. RESULTS: The size of the residual tumor at the beginning of therapy, and Eastern Cooperative Oncology Group (ECOG) performance status (PS) were independently predictive of survival. The time to normalization of CA 125 serum levels (analyzed either as -a continuous or as a two-category variable) also had an independent prognostic role when included in the model. When we examined the inclusion of both CA 125 parameter and SLL into the model together, we found that only CA 125 continued to have an independent prognostic relevance. On the basis of the two pretreatment parameters (PS and tumor size) and of this response parameter (time to normalization of CA 125 values) we selected six subgroups of patients having different outcomes (log rank test of equality over-strata < 0.001). Patients with good prognostic pretreatment variables, and those with intermediate prognosis at the beginning of therapy who showed a quick normalization of CA 125, had an 80% 5-year survival, compared with 16% 5-year survival in the remaining patients. (P < 0.0001). CONCLUSIONS: Our data suggest that the survival of patients with advanced ovarian carcinoma could be accurately predicted by considering some pretreatment variables and time to CA 125 normalization together, without performing SLL. Our risk model, however, needs to be validated by larger prospective trials, to draw any definitive conclusions about the abandonment of surgically defined response.

Biomarkers, Tumor↗
PubMed2001

[Evaluation of coronary heart disease risk model by carotid ultrasonography in the occupational setting--intima-media thickness and coronary heart disease risk].

Recently, because of an increase in aged workers with high risk health conditions in Japan, it is becoming necessary to have a preventive control system for work-related diseases, such as coronary heart disease. We have already built a system by applying the prediction model of Framingham's risk equation for management after an annual check-up since 1999. At that time, we considered the relationship between CHD risk and intimamedia thickness (IMT) as an index of actual atherosclerosis. Correlation coefficients among max IMT, CHD risk and the several health factors in the corporate annual health check-up were obtained by Spearman's method. Significant associations with max IMT were only for CHD risk and systolic blood pressure. Correlation coefficients were 0.30 and 0.21 for CHD risk and systolic blood pressure, respectively. Furthermore, when we divided findings into those for the atherosclerotic and non-atherosclerotic groups defined by a max IMT over 1.1 mm or less, the difference between the two groups in CHD risks was investigated by t-test. The CHD risk for the atherosclerotic group was revealed to be significantly higher than that for the non-atherosclerotic group, with the means +/- SD in the two groups being 21.4 +/- 9.4% and 17.0 +/- 7.7%, respectively. CHD risk was therefore concluded to be important for the objective index of atherosclerosis from the viewpoint of high-risk-strategy in the worksite.

Adult↗
PubMed1991

Multivariate analysis of prognostic factors in stage IV follicular low-grade lymphoma: a risk model.

We analyzed the records of 96 previously untreated patients with stage IV follicular low-grade lymphoma (FLGL) uniformly treated with cyclophosphamide, doxorubicin, vincristine, prednisone, and bleomycin (CHOP-Bleo) chemotherapy from 1972 to 1982. The overall complete remission (CR) rate was 77%. At a median follow-up of 138 months, the 10-year cause-specific survival rate was 42% with a median survival of 100 months. Failure-free survival (FFS) was 15% at 10 years with a median FFS of 30 months. Multivariate analysis showed peripheral lymph node size (LN), degree of marrow involvement, and sex, in that order, to be important for FFS, while the number of extranodal sites (#ENS), LN, sex, and degree of marrow involvement were important for cause-specific survival. We devised a tumor burden (TB) model, incorporating #ENS, LN, and degree of marrow involvement. Three groups were identified with statistically significant differences in cause-specific survival and FFS. Those with low TB (one ENS exclusive of extensive marrow and nodal disease less than 5 cm) had a 10-year cause-specific survival of 73% compared with 24% for patients with high TB (greater than or equal to two ENS and nodal disease greater than or equal to 5 cm) (P less than .001) and 40% for those with intermediate TB (either greater than or equal to 2 ENS, or extensive marrow only, or nodal disease greater than 5 cm) (P = .050). Patients with low TB had a 10-year FFS rate of 32%, while the intermediate and high TB groups had 10% and 9% FFS, respectively (P = .003). Because sex was a very strong prognostic variable, we created a risk model for survival and FFS based on TB and sex. Females with low TB had the best prognosis (92% survival and 50% FFS at 10 years) and males with high TB had the worst outlook (median survival and FFS, 43 and 12 months, respectively). Other TB-sex combinations defined two groups with statistically significant differences in survival but comparable FFS. This model should aid in the design and analysis of future trials.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2006

Estimation of distribution function in bivariate competing risk models.

We consider lifetime data involving pairs of study individuals with more than one possible cause of failure for each individual. Non-parametric estimation of cause-specific distribution functions is considered under independent censoring. Properties of the estimators are discussed and an illustration of their application is given.

Biometry↗
PubMed2006

Application of artificial neural networks to establish a predictive mortality risk model in children admitted to a paediatric intensive care unit.

INTRODUCTION: Paediatric risk of mortality and paediatric index of mortality (PIM) are the commonly-used mortality prediction models (MPM) in children admitted to paediatric intensive care unit (PICU). The current study was undertaken to develop a better MPM using artificial neural network, a domain of artificial intelligence. METHODS: The purpose of this retrospective case series was to compare an artificial neural network (ANN) model and PIM with the observed mortality in a cohort of patients admitted to a five-bed PICU in a Hong Kong non-teaching general hospital. The patients were under the age of 17 years and admitted to our PICU from April 2001 to December 2004. Data were collected from each patient admitted to our PICU. All data were randomly allocated to either the training or validation set. The data from the training set were used to construct a series of ANN models. The data from the validation set were used to validate the ANN and PIM models. The accuracy of ANN models and PIM was assessed by area under the receiver operator characteristics (ROC) curve and calibration. RESULTS: All data were randomly allocated to either the training (n=274) or validation set (n=273). Three ANN models were developed using the data from the training set, namely ANN8 (trained with variables required for PIM), ANN9 (trained with variables required for PIM and pre-ICU intubation) and ANN23 (trained with variables required for ANN9 and 14 principal ICU diagnoses). Three ANN models and PIM were used to predict mortality in the validation set. We found that PIM and ANN9 had a high ROC curve (PIM: 0.808, 95 percent confidence interval 0.552 to 1.000, ANN9: 0.957, 95 percent confidence interval 0.915 to 1.000), whereas ANN8 and ANN23 gave a suboptimal area under the ROC curve. ANN8 required only five variables for the calculation of risk, compared with eight for PIM. CONCLUSION: The current study demonstrated the process of predictive mortality risk model development using ANN. Further multicentre studies are required to produce a representative ANN-based mortality prediction model for use in different PICUs.

Adolescent↗
PubMed1988

Relative risk models for assessing the joint effects of multiple factors.

A goal of analyses of occupational cohort data is the specification of how covariate information relates to age-specific disease risks. In describing this relationship, certain assumptions or models must be defined. For example, the usual standardized mortality ratio assumes a constant multiplicative increase in the age and calendar period disease rates of an exposed cohort over rates in a unexposed referent group. For analyzing several exposures, some of which may be continuous, such as cumulative dose, dose rate, duration of employment, and smoking patterns, or for analyzing complex associations between disease rate and covariates, flexible regression procedures are required. Using a crossclassification of the data and a Poisson probability model, relative risk regression methods are outlined. Breslow and Storer [1985], Guerrero and Johnson [1982], and Thomas [1981] propose general models for the relative risk as alternatives to, but which include, the usual exponential form. We review these models, discuss some limitations (in particular when there is more than one covariate) and present alternatives. Methods and models are illustrated by examining the joint effects of radon exposure and tobacco use on lung cancer mortality among a group of uranium miners.

Adult↗
PubMed1987

Biologically motivated cancer risk models.

A two-stage dose response model is proposed for use in cancer risk assessment. The model assumes that transformation probabilities and cellular dynamics are exposure- and time-dependent.

Animals↗