SEARCH · PubMed Health

Results for “Prognostic model”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47Linked to original sources

PubMed2026

Identification of a necroptosis-related lncRNA prognostic signature and the hub RBP HNRNPK in esophageal squamous cell carcinoma.

ObjectiveEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with poor prognosis. Necroptosis is important for tumor immunity, but its role in ESCC remains unclear. This retrospective bioinformatics study aimed to investigate the prognostic value of necroptosis-related long non-coding RNAs (lncRNAs) and to identify key lncRNA-binding proteins (RBPs) in ESCC patients.MethodsRNA transcriptome and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Necroptosis-related lncRNAs were identified through correlation analysis with necroptosis-related genes, subjected to consensus cluster analysis, and used to construct a prognostic risk model via least absolute shrinkage and selection operator (LASSO) regression. The hub RBP was experimentally validated by quantitative polymerase chain reaction (qPCR) using 30 pairs of ESCC and adjacent normal tissues from patients who underwent surgical resection.ResultsA total of 30 necroptosis-related lncRNAs were significantly correlated with overall survival (OS). The upregulated lncRNAs in the risk model were associated with high immune scores, innate immune cell infiltration, cluster 2 classification, and advanced T-stage disease (p < 0.05). Three hub RBPs (HNRNPA1, HNRNPC, and HNRNPK) were identified through protein-protein interaction network analysis. qPCR confirmed that HNRNPK was significantly overexpressed in ESCC tissues compared to adjacent normal tissues (p < 0.05).ConclusionsThe necroptosis-related lncRNA risk model is an independent prognostic factor for ESCC patients. HNRNPK was identified as a hub RBP significantly overexpressed in ESCC tissues. We hypothesize that HNRNPK may promote tumor progression through regulating proto-oncogene expression or modulating the immune microenvironment, though this requires further mechanistic validation.

Humans↗

PubMed1990

Cryopreservation of skin using a murine model: validation of a prognostic viability assay.

In order to evaluate the many variables that can affect cryopreservation success, a simple, highly reproducible model system is required. We have evaluated the use of tetrazolium reductase activity as a prognostic indicator of skin viability in an inbred murine model. Two inbred hairless mouse strains were characterized in studies on autografting and allografting following different skin-storage protocols. Skin tetrazolium reductase (TR) activity correlated well with oxygen consumption, and with graft success--the ultimate performance criterion--following varying degrees of cryogenic injury. The assay was shown to be highly reproducible. In a series of factorial experiments the only factors affecting TR activity were those concerning the mouse donors, i.e., mouse strain, age, sex, and body area. The effects of these factors on TR activity were fully characterized.

Animals↗

PubMed1997

[Prognosis for medically treated elderly patients with coronary artery disease: analysis by the Cox model].

The prognostic importance of age among well-known prognostic factors such as extent of coronary artery lesions, cardiac function, and myocardial ischemia was evaluated in 147 elderly patients with coronary artery disease aged 65 years or older who underwent dipyridamole perfusion scintigraphy and coronary angiography. After excluding 32 patients who initially underwent percutaneous transluminal coronary angioplasty (PTCA) or coronary artery bypass grafting (CABG), 115 patients who were initially treated medically were analysed by the Cox model for cardiac events during a mean follow-up period of 29 +/- 22 months. Among the 114 patients who were available for follow-up, nine patients (7.9%) had cardiac events, including five cardiac deaths and four non-fatal cardiac events (requiring PTCA or CABG). When the 114 patients were divided into three age-groups; 53 patients aged 65-69 years, 42 aged 70-74 years and 19 aged 75 years or older, the incidence of cardiac death was highest in those aged 75 years or older. Univariate analysis showed that age of 70 years or older (hazards ratio 15.15, p = 0.004), scintigraphic diffuse slow washout (hazards ratio 8.77, p = 0.002), and triple-vessel or left main trunk disease (hazards ratio 6.36, p = 0.05) were important prognostic factors. Multivariate analysis showed that scintigraphic diffuse slow washout (hazards ratio 6.33, p = 0.05), and triple-vessel or left main trunk disease (hazards ratio 11.94, p = 0.05) were statistically significant as independent prognostic factors. However, when age of 70 years or older was included in the analysis, it showed higher hazards ratio (21.21, p = 0.03) than that of scintigraphic diffuse slow washout (7.36) or triple-vessel or left main trunk disease (5.30). Age of 70 years or older may be a significant prognostic factor in elderly patients with coronary artery disease which has an equivalent importance to the extent of coronary lesions.

Aged↗

PubMed2006

Two models for outcome prediction - a comparison of logistic regression and neural networks.

OBJECTIVES: Accurately predicting disease progress from a set of predictive variables is an important aspect of clinical work. For binary outcomes, the classical approach is to develop prognostic logistic regression (LR) models. Alternatively, machine learning algorithms were proposed with artificial neural networks (ANN) having become popular over the last decades. Although some studies have compared predictive accuracies of LR and ANN models, some concerns regarding their methodological quality have been voiced. Our comparison has the advantage of being based on two large independent data sets allowing for elaborate model development and independent validation. METHODS: From the German Stroke Database, a learning data set including 1754 prospectively recruited patients with acute ischemic stroke was used. Utilizing LR and ANN, two prognostic models were developed predicting restitution of functional independence and survival after 100 days. The resulting models were applied to classify 1470 patients with acute ischemic stroke; this test data set was collected independently from the learning data. Error fractions in the test data were determined, and differences in error fractions between the algorithms were calculated with 95% confidence intervals. RESULTS: For most prognostic models, error fractions in the test data were below 40%. There was no difference between the algorithms except for the model predicting completely versus incompletely restituted or deceased patients (difference in error fractions = 4.01% [2.10-5.96%], p = 0.0001). CONCLUSIONS: The conscientiously applied LR remains the gold standard for prognostic modelling; however, ANN can be an alternative automated "quick and easy" multivariate analysis.

Aged↗

PubMed2003

Selection of causal gene sets for lymphoma prognostication from expression profiling and construction of prognostic fuzzy neural network models.

To assess the response of lymphomas to chemotherapy, gene expression profiling data from DNA microarrays were analyzed using the fuzzy neural network (FNN) modeling method. We used the FNN modeling method to produce 10 noninferior models. Using these models, we were able to predict diffuse large B-cell lymphoma (DLBCL) patient outcome with 93% accuracy. Of the 37 genes in the 10 models, 13 genes were repeatedly selected, indicating that these genes are important for prognostication. On Kaplan-Meier plots of overall survival, patients predicted by the FNN model to be cured survived significantly longer than those predicted to be refractory (P<0.0001), indicating that the FNN could successfully identify patients with a relatively poor prognosis among low-clinical-risk patients. The FNN modeling method presented here is able to precisely extract significant biological markers affecting prognosis.

Journal Article↗

PubMed2002

[Prognostic value of a model using restricted left ventricular filling for prediction of developing heart failure after myocardial infarction].

UNLABELLED: The prognostic significance of restrictive pattern (RP) of mitral flow in myocardial infarction (MI) has yet not been defined. The aim of the study was to assess the relationship of a RP in MI patients at discharge with the development of left ventricular (LV) dilatation and clinical symptoms of heart failure (HF) after one year. METHODS: 2D and Doppler Echocardiography was performed on 88 patients (mean age 53.8 +/- 11) at discharge after their first MI and then one year after that MI. Patients were classified according to Doppler examination at discharge into 2 groups: Group I-RP (n = 9) with peak E to A ratio E/A > or = 2 or E/A > or = 1.5 and deceleration time DT < or = 140 ms, Group II--non-restrictive pattern nRP (n = 79). In predicting the development of HF the following variables were analysed using Cox proportional hazard model: MI location and extension (Inf, Ant, non-Q, Q-wave), reperfusion defined by non-invasive features (R/+/, R/-/), Killip-Kimball class (K-K), end-diastolic volume index (EDVI), end-systolic volume index (ESVI), ejection fraction (EF), wall motion score index (WMSI) and restrictive pattern of mitral flow presence (RP). RESULTS: HF developed in 23 patients: 8 pts were in RP-group (89%), while 15 pts were in nRP-group (19%) (rr = 4.68 p < or = 0.001). In the univariate Cox analysis, the following variables were associated with higher incidence of HF: Q-MI (rr = 5.66 p < or = 0.05), R- (rr = 4.96 p < or = 0.001), K-K > or = II (rr = 3.13 p < or = 0.01), EDVI > or = 80 ml/m2 (rr = 5.85 p < or = 0.001), ESVI > or = 40 ml/m2 (rr = 4.07 p < or = 0.001), WMSI > or = 1.4 (rr = 2.79 p < or = 0.01) and RP (rr = 4.6 p < or = 0.001). However, the multivariate Cox analysis revealed only three significant independent predictors of HF: EDVI > or = 80 ml/m2 (rr = 6.27 p < or = 0.001), R- (rr = 4.74 p < or = 0.01) and RP (rr = 3.2 p < or = 0.05). The cumulative predictive power of RP in connection with the selected parameters (RP + K-K > or = II, RP + EF < or = 45%, RP + WMSI > or = 1.4) was higher for RP + K-K > or = II (rr = 4.61 p < or = 0.001) and especially for RP + WMSI > or = 1.4 (rr = 5.06 p < or = 0.001). CONCLUSION: The restrictive pattern of LV filling in MI pts at discharge is an independent predictor of heart failure development. The assessment of both diastolic and systolic LV functions parameters increases prediction power.

Adult↗

PubMed2001

Prognostic assessment of nonmetastatic renal cell carcinoma: a clinically based model.

OBJECTIVES: Determining the recurrence risk in patients treated for renal cell carcinoma (RCC) is important for providing prognostic information and planning potential surveillance strategies. The pathologic stage has been the most widely used single prognostic variable. However, with minimally invasive treatment modalities, the pathologic stage may not be readily available. We developed a biostatistical prognostic model for postoperative RCC that is independent of the pathologic stage. METHODS: The records of 296 patients who underwent open nephrectomy for RCC at Johns Hopkins Hospital between 1990 and 1999 were reviewed. Cox proportional hazards regression analysis was used to generate a prognostic model. RESULTS: The recurrence risk (R(rec)) was determined from this model: R(rec)=1.55 x presentation (0-1)+0.19 x clinical size (in centimeters). Using this equation, 79% of patients were identified as low risk compared with 45% of patients considered low risk by pathologic stage (pT1). Moreover, the separation between the high and low-risk survival curves increased. CONCLUSIONS: This model is the first to our knowledge that uses purely clinical variables to assess the postoperative prognosis in patients with RCC. These results, although not validated, provide substantial evidence that preoperative clinical variables may be used instead of the pathologic stage to determine the risk of recurrence. Uncoupling the reliance on pathologic stage for prognostic information removes a potential barrier to novel minimally invasive treatments for renal malignancy and provides a standard to which observation protocols can be compared. In the future, this model may facilitate selection of appropriate patients for less toxic adjuvant or neoadjuvant therapies.

Aged↗

PubMed1999

Prognostic implications of various models for calculation of S-phase fraction in 259 patients with soft tissue sarcoma.

The S-phase fraction (SPF) in flow cytometric DNA histograms in soft tissue sarcoma (STS) can be calculated in various ways. The traditional planimetric method of Baisch has been shown to be prognostic, but is hampered by a failure rate of around 40%. We therefore tested other models to see if this rate could be decreased with retained prognostic value. In 259 STS of the locomotor system the SPF was calculated according to Baisch and with commercial parametric MultiCycle software using different corrections for background. Using the Baisch model, 159 histograms could be evaluated for SPF. The 5-year metastasis-free survival rate (MFSR) was 0.94 for the low-risk group (defined with SPF), and 0.53 for the high-risk group. In the low-risk group, four of the seven patients who developed metastasis did so after 5 years Using the MultiCycle software, SPF could be calculated in 253 tumours. Depending on type of background correction used, the 5-year MFSR varied between 0.67 and 0.82 for the low-risk group, and between 0.47 and 0.53 for the high-risk group. The late metastasis pattern in the low-risk group was never seen using the MultiCycle software. We conclude that in paraffin archival material, calculation of SPF according to Baisch is preferable in clinical use due to better separation between low-risk and high-risk groups, and also the possibility to identify patients who metastasize late.

Adolescent↗

PubMed2025

Putative function and prognostic molecular marker of mast cells in colorectal cancer.

BACKGROUND: The increased demand for markers for colorectal cancer (CRC) highlights the importance of investigating immune cells involved in CRC progression. This study aims to dissect the mast cells in CRC, characterize the role of mast cells in CRC development, coordinate molecular communication between mast cells and malignant cells, and construct and validate a prognostic classification model based on mast cell markers. METHODS: Single-cell transcriptome data of CRC patients were extracted from GSE146771 for cell classification and annotation. The malignant cells were identified by copykat and the communication between mast cells and malignant cells was analyzed by CellChat. Least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis of mast cell markers were performed in the TCGA-COAD cohort to construct a prognostic classification model. qRT-PCR was performed to detect the mRNA expression of the molecules in the classification model in P815 and MC-9 cells. The co-culture experiment of MC38 and P815 cells were performed in 12-well transwell dish. Wound healing assay and Transwell assay were performed to detect cell migration and invasion. RESULTS: 10,186 high-quality cells in GSE146771 were annotated to 9 cell types. Six markers in mast cells (HDC, GATA2, ASAH1, BTBD19, TIMP1, FAM110A) were selected to construct a classification model. The high-risk score defined showed high infiltration of immunosuppressive cells, including endothelial cells, CAFs, Tregs and high angiogenesis and epithelial-mesenchymal transition (EMT) activities. In the model, HDC were abnormally low expressed in P815 cells, while BTBD19, FAM110A, GATA2, ASAH1 and TIMP1 showed excessive expression in P815 cells. Knockdown of GATA2 in the co-culture system of P815 and MC38 cells blocked cell migration and invasion. CONCLUSION: This study identified the cell types within CRC, elaborated the cellular functions of mast cells in CRC development and their molecular communication to coordinate malignant cells, and highlighted the molecular components and biological features that constitute promising prognostic classification model.

Mast Cells↗

PubMed2002

Prognostic factors for local control in non-small-cell lung cancer treated with definitive radiation therapy.

Radiotherapy plays an important role as a treatment for locally advanced non-small-cell lung cancer (NSCLC), but local failure still occurs in 70% to 80% of the patients. A retrospective analysis was carried out to evaluate the local control predictors for non-SCLC. From January 1990 to December 1996, 256 patients with stages I-IIIb NSCLC entered this analysis. All patients received definitive radiotherapy. The significance of prognostic variables on local control was evaluated using univariate analysis and Cox stepwise regression model. The prognostic index was calculated according to the value of each prognostic factor on local control. Median local progression-free survival time of the whole group was 9.7 months, and 1-, 3-, and 5-year actuarial local progression-free survival were 54%, 24%, and 19%, respectively. Univariate and multivariate analyses showed patients with smaller tumor volume, earlier clinical staging, and treated with higher total dose in shortened overall treatment time had better local control. Tumor volume, clinical staging, and radiotherapy methods were independent prognostic factors on local control. The prognostic index model could predict the local control condition of NSCLC treated with radiation therapy more effectively than a single variable such as TNM staging.

Adult↗

PubMed2000

Assessment of the nested grid model estimates for driving regional visibility models in the southwestern United States.

The Nested Grid Model (NGM) is a primitive-equation meteorological model that is routinely exercised over North America for forecasting purposes by the National Meteorological Center. While prognostic meteorological models are being increasingly used to drive air quality models, their use in conducting annual simulations requires significant resources. NGM estimates of wind fields and other meteorological variables provide an attractive alternative since they are typically archived and readily available for an entire year. Preliminary evaluation of NGM winds during the summer of 1992 for application to the region surrounding the Grand Canyon National Park showed serious shortcomings. The NGM winds along the borders between California, Arizona and Mexico tend to be northwesterly with a speed of about 6 m/sec, while the observed flow is predominantly southerly at about 2-5 m/sec. The mesoscale effect of a thermal low pressure area over the highly heated Southern California and western Arizona deserts does not appear to be represented by the NGM because of its coarse resolution and the use of sparse observations in that region. Tracer simulations and statistical evaluation against special high resolution observations of winds in the southwest United States clearly demonstrate the northwest bias in NGM winds and its adverse effect on predictions of an air quality model. The "enhanced" NGM winds, in which selected wind observations are incorporated in the NGM winds using a diagnostic meteorological model provide additional confirmation on the primary cause of the northwest bias. This study has demonstrated that in situations where limited resources prevent the use of prognostic meteorological models, previously archived coarse resolution wind fields in which additional observations are incorporated to correct known biases provide an attractive option.

Aerosols↗

PubMed1992

Multivariate analysis of the histopathologic prognostic factors of cervical cancer in patients undergoing radical hysterectomy.

Three hundred forty-five patients with invasive carcinoma of the uterine cervix, Stages Ib (211 patients) and II (134 patients), underwent radical hysterectomy and pelvic lymphadenectomy. The influence of histologic factors including histologic subtype, maximum depth of cervical stromal invasion, degree of stromal invasion, longitudinal tumor diameter, lymph-vascular space invasion, corpus invasion, parametrial invasion, vaginal invasion, and pelvic lymph node (PLN) metastases on survival were examined by multivariate analysis. Univariate analysis revealed that all the variables except corpus invasion and vaginal invasion were significant in survival (P less than 0.05). Among these variables, however, PLN metastases, histologic subtype, and longitudinal tumor diameter were identified as independent and significant prognostic factors by multivariate analysis using Cox regression models. The prognostic index (PI), defined by the model (an indicator of the patient's place in the prognostic spectrum), was able to divide the patients into three prognostic groups. The key factors in the definition of these groups were (1) squamous cell carcinoma, small tumor diameter, and no PLN metastases for the good prognostic group and (2) PLN metastasis in two or more node groups, adenocarcinoma with one positive PLN group, or squamous cell carcinoma with one PLN group and large diameter for the poor prognostic group. These prognostic findings could predict the prognosis more precisely than that of clinical staging.

Adult↗

PubMed1995

Prognostic trees to aid prognosis in patients with cutaneous malignant melanoma. Scottish Melanoma Group.

OBJECTIVES: To design user friendly guides to prognosis for patients who have had invasive primary cutaneous malignant melanomas surgically excised. DESIGN: Adaptation of the classification tree method was used to derive prognostic trees for four different subgroups of malignant melanoma patients in whom known and possible prognostic variables interacted in different ways. SETTING: Scotland. SUBJECTS: Statistical modelling for prognostic trees was based on 1978 patients whose primary malignant melanoma was first diagnosed in 1979-86 for whom five year follow up and all relevant clinical pathological data were available. The resultant model was validated with 300 patients first diagnosed in 1987 for whom the same information was available. MAIN OUTCOME MEASURES: Actual and predicted rate of survival after diagnosis of primary cutaneous malignant melanoma. RESULTS: The four subgroups of patients were men and women with ulcerated and non-ulcerated cutaneous primary melanomas. Validation of the model showed excellent agreement between actual status of patients in the relevant subgroups and their status as predicted by the model. CONCLUSIONS: The prognostic trees are simple to use and give more accurate prognosis for individual patients than is currently available from tumour thickness alone.

Decision Trees↗

PubMed2002

The prognostic significance of Gail model risk factors for women with breast cancer.

BACKGROUND: Because many risk factors for breast cancer are related to hormonal factors and hormonal factors influence breast cancer prognosis, risk factors may have prognostic value. In order to assess the prognostic value of risk factors for breast cancer we divided patients with breast cancer into those at high risk and low risk using the Gail model. METHODS: Patients with available follow-up and information concerning age, age at menarche, number of children, age at first birth, number of first degree relatives with breast cancer, and number of previous breast biopsies were divided into low and high-risk groups by the average relative risk calculated using the Gail model. Risk factors, clinical presentations, pathologic findings, tumor characteristics, extent of disease, treatment and outcomes for the 106 high-risk women were compared with the 206 low-risk women. Stage IV patients were excluded. RESULTS: The average relative risk of breast cancer was 2.09. The 106 high-risk women were significantly older (58 years versus 53 years; P = 0.001), older at first live birth (30 years versus 23 years; P <0.001), more likely to have a first degree relative with breast cancer (57% versus 0%; P <0.001), and more likely to have previously had a breast biopsy (19% versus 1%; P <0.001). There was no difference in the average age at menarche. Low-risk patients were significantly more frequently nulliparous (40% versus 22%; P = 0.002). Clinical presentation, pathologic findings, extent of disease, and treatment were comparable in high and low-risk patients. Cancers of low-risk patients were more frequently poorly differentiated (39% versus 25%, P = 0.044). Tamoxifen was used more frequently in high-risk patients (56% versus 41%; P = 0.012). High-risk patients exhibited significantly better 5-year (95% versus 88%; P = 0.047) and 10-year distant disease-free survival than low-risk patients (88% versus 79%; P = 0.050). In multivariate analysis only the number of involved lymph nodes was related to local (P = 0.001) and distant (P <0.001) disease-free survival. CONCLUSIONS: Breast cancer patients considered high risk by the Gail model have significantly better disease-free survival than low-risk patients. This study does not support the notion that risk factors for breast cancer are prognostic factors.

Adult↗

PubMed1997

Prognostic factors in meningococcal disease. Development of a bedside predictive model and scoring system. Barcelona Meningococcal Disease Surveillance Group.

CONTEXT: Meningococcal disease is associated with significant morbidity and mortality. Development of a prognostic model based on clinical findings may be useful for identification and management of patients with meningococcal infection. OBJECTIVES: To construct and validate a bedside model and scoring system for prognosis in meningococcal disease. DESIGN: Prospective, population-based study. SETTING: Twenty-four hospitals in the metropolitan area of Barcelona, Spain. PATIENTS: A total of 907 patients with microbiologically proven meningococcal disease. Patients diagnosed with meningococcal disease from 1987 through 1990 were used to develop the prognostic model, and those diagnosed in 1991 and 1992 were used to validate it. OUTCOME MEASURES: Clinical independent prognostic factors for mortality in meningococcal disease. The association between outcome and independent prognostic factors was determined by logistic regression analysis. A scoring system was constructed and tested using receiver operating characteristic curves. RESULTS: Among 624 patients in the derivation set, 287 (46%) were male, the mean age was 12.4 years, and 34 patients (5.4%) died. Among 283 patients in the validation set, 124 (43.8%) were male, the mean age was 12.7 years, and 17 patients (6.0%) died. In multivariate analysis, independent predictors of death were hemorrhagic diathesis (odds ratio [OR], 101; 95% confidence interval [CI], 30-333), focal neurologic signs (OR, 25; 95% CI, 7-83), and age 60 years or older (OR, 10; 95% CI, 3-34), whereas receipt of adequate antibiotic therapy prior to admission was associated with reduced likelihood of death (OR, 0.09; 95% CI, 0.02-0.4). Hemorrhagic diathesis was scored with 2 points, presence of focal neurologic signs with 1 point, age of 60 years or older with 1 point, and preadmission antibiotic therapy was scored as -1. The clinical scores of -1, 0, 1, 2, and 3 or more points were associated with a probability of death of 0%, 2.3%, 27.3%, 73.3%, and 100%, respectively. CONCLUSIONS: Hemorrhagic diathesis, focal neurologic signs, and age of 60 years or older were independent predictors of death in meningococcal disease, whereas receipt of adequate antibiotic therapy was associated with a more favorable prognosis. The scoring system presented is simple, is based on findings readily available at the bedside, and may be useful to help guide aggressive therapy.

Adolescent↗

PubMedDate not supplied

[Prognostic factors and survival model for decompensated hepatic cirrhosis].

A group of 207 consecutive patients admitted for decompensated liver cirrhosis of different etiologies (alcoholic, HBsAg-associated and cryptogenic), was studied in order to assess the independent long-term (up to 5 years) prognostic value of 13 clinical, biochemical and etiological factors. These were analyzed by the Cox Regression Model using a step-wise backward procedure. The final model included bilirubin (p = 0.003), HBsAg (p = 0.006), encephalopathy (p = 0.010) and a factor comprising urea and albumin (p less than 0.001). The model was validated by a split-sample testing technique and may be used to predict survival in decompensated cirrhosis. A comparison with Child-Pugh's score in terms of survival prediction was carried out and was favorable to our model. We conclude that this model can be useful for predicting short and long-term survival in the three most common types of liver cirrhosis and that the additional overhead to calculate it seems justified in view of the large availability of microcomputers where simple programs can be run to perform this task and draw the predicted survival curves.

Follow-Up Studies↗

PubMed2007

An oncogenetic tree model in gastrointestinal stromal tumours (GISTs) identifies different pathways of cytogenetic evolution with prognostic implications.

To model the cytogenetic evolution in gastrointestinal stromal tumour (GIST), an oncogenetic tree model was reconstructed using comparative genomic hybridization data from 203 primary GISTs (116 gastric and 87 intestinal GISTs, including 151 newly analysed cases), with follow-up available in 173 cases (mean 40 months; maximum 133 months). The oncogenetic tree model identified three major cytogenetic pathways: one initiated by -14q, one by -1p, and another by -22q. The -14q pathway mainly characterized gastric tumours with predominantly stable karyotypes and more favourable clinical course. On the other hand, the -1p pathway was more characteristic of intestinal GISTs, with an increased capacity for cytogenetic complexity and more aggressive clinical course. Loss of 22q, more closely associated with -1p than -14q, appeared to initiate the critical transition to an unfavourable cytogenetic subpathway. This -22q pathway included accumulation of +8q, -9p, and -9q, which could all predict disease-free survival in addition to tumour site. Thus, insights into the cytogenetic evolution obtained from oncogenetic tree models may eventually help to gain a better understanding of the heterogeneous site-dependent biological behaviour of GISTs.

Chromosome Aberrations↗

PubMed1996

Development of an atmospheric 222Rn concentration model using a hydrodynamic meteorological model: I. One-dimensional practical model.

A one-dimensional numerical model for 222Rn transport in an atmospheric boundary layer was developed. The model consists of two parts: a prognostic hydrodynamic model including a turbulence closure model and an atmospheric diffusion model for 222Rn. The first part predicts meteorological conditions to provide the second part with vertical turbulence conditions which affects the vertical motion of 222Rn near the Earth's surface. Calculations with the model are compared with 222Rn concentrations measured during a variety of meteorological conditions, from clear days with high radiation and low winds to cloudy days of low radiation with high winds. The model's results represent well the typical diurnal variations of the 222Rn concentrations.

Air Pollutants, Radioactive↗