975 resultados para Ruin probability
Resumo:
Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 familes from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO’s concordance index from 0.758 to 0.762 (p = 0.046), improves its positive predictive value from 35% to 39% (p < 10−6) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability < 10%. Copyright c 2000 John Wiley & Sons, Ltd.
Resumo:
The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytic expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on informative pairs. The asymptotic distribution of the concordance probability estimate is derived using U-statistic theory and the methodology is applied to a predictive model in lung cancer.
Resumo:
Geometrical dependencies are being researched for analytical representation of the probability density function (pdf) for the travel time between a random, and a known or another random point in Tchebyshev’s metric. In the most popular case - a rectangular area of service - the pdf of this random variable depends directly on the position of the server. Two approaches have been introduced for the exact analytical calculation of the pdf: Ad-hoc approach – useful for a ‘manual’ solving of a specific case; by superposition – an algorithmic approach for the general case. The main concept of each approach is explained, and a short comparison is done to prove the faithfulness.
Resumo:
Partial migration, in which a fraction of a population migrate and the rest remain resident, occurs in an extensive range of species and can have powerful ecological consequences. The question of what drives differences in individual migratory tendency is a contentious one. It has been shown that the timing of partial migration is based upon a trade-off between seasonal fluctuations in predation risk and growth potential. Phenotypic variation in either individual predation risk or growth potential should thus mediate the strength of the trade-off and ultimately predict patterns of partial migration at the individual level (i.e. which individuals migrate and which remain resident). We provide cross-population empirical support for the importance of one component of this model—individual predation risk—in predicting partial migration in wild populations of bream Abramis brama, a freshwater fish. Smaller, high-risk individuals migrate with a higher probability than larger, low-risk individuals, and we suggest that predation risk maintains size-dependent partial migration in this system.
Resumo:
BACKGROUND Although well-established for suspected lower limb deep venous thrombosis, an algorithm combining a clinical decision score, d-dimer testing, and ultrasonography has not been evaluated for suspected upper extremity deep venous thrombosis (UEDVT). OBJECTIVE To assess the safety and feasibility of a new diagnostic algorithm in patients with clinically suspected UEDVT. DESIGN Diagnostic management study. (ClinicalTrials.gov: NCT01324037) SETTING: 16 hospitals in Europe and the United States. PATIENTS 406 inpatients and outpatients with suspected UEDVT. MEASUREMENTS The algorithm consisted of the sequential application of a clinical decision score, d-dimer testing, and ultrasonography. Patients were first categorized as likely or unlikely to have UEDVT; in those with an unlikely score and normal d-dimer levels, UEDVT was excluded. All other patients had (repeated) compression ultrasonography. The primary outcome was the 3-month incidence of symptomatic UEDVT and pulmonary embolism in patients with a normal diagnostic work-up. RESULTS The algorithm was feasible and completed in 390 of the 406 patients (96%). In 87 patients (21%), an unlikely score combined with normal d-dimer levels excluded UEDVT. Superficial venous thrombosis and UEDVT were diagnosed in 54 (13%) and 103 (25%) patients, respectively. All 249 patients with a normal diagnostic work-up, including those with protocol violations (n = 16), were followed for 3 months. One patient developed UEDVT during follow-up, for an overall failure rate of 0.4% (95% CI, 0.0% to 2.2%). LIMITATIONS This study was not powered to show the safety of the substrategies. d-Dimer testing was done locally. CONCLUSION The combination of a clinical decision score, d-dimer testing, and ultrasonography can safely and effectively exclude UEDVT. If confirmed by other studies, this algorithm has potential as a standard approach to suspected UEDVT. PRIMARY FUNDING SOURCE None.