968 resultados para Weibull Probability Plot


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OBJECTIVE In patients with a long life expectancy with high-risk (HR) prostate cancer (PCa), the chance to die from PCa is not negligible and may change significantly according to the time elapsed from surgery. The aim of this study was to evaluate long-term survival patterns in young patients treated with radical prostatectomy (RP) for HRPCa. MATERIALS AND METHODS Within a multiinstitutional cohort, 600 young patients (≤59 years) treated with RP between 1987 and 2012 for HRPCa (defined as at least one of the following adverse characteristics: prostate specific antigen>20, cT3 or higher, biopsy Gleason sum 8-10) were identified. Smoothed cumulative incidence plot was performed to assess cancer-specific mortality (CSM) and other cause mortality (OCM) rates at 10, 15, and 20 years after RP. The same analyses were performed to assess the 5-year probability of CSM and OCM in patients who survived 5, 10, and 15 years after RP. A multivariable competing risk regression model was fitted to identify predictors of CSM and OCM. RESULTS The 10-, 15- and 20-year CSM and OCM rates were 11.6% and 5.5% vs. 15.5% and 13.5% vs. 18.4% and 19.3%, respectively. The 5-year probability of CSM and OCM rates among patients who survived at 5, 10, and 15 years after RP, were 6.4% and 2.7% vs. 4.6% and 9.6% vs. 4.2% and 8.2%, respectively. Year of surgery, pathological stage and Gleason score, surgical margin status and lymph node invasion were the major determinants of CSM (all P≤0.03). Conversely, none of the covariates was significantly associated with OCM (all P≥ 0.09). CONCLUSIONS Very long-term cancer control in young high-risk patients after RP is highly satisfactory. The probability of dying from PCa in young patients is the leading cause of death during the first 10 years of survivorship after RP. Thereafter, mortality not related to PCa became the main cause of death. Consequently, surgery should be consider among young patients with high-risk disease and strict PCa follow-up should enforce during the first 10 years of survivorship after RP.

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Although negative density dependence (NDD) can facilitate tree species coexistence in forests, the underlying mechanisms can differ, and rarely are the dynamics of seedlings and saplings studied together. Herein we present and discuss a novel mechanism based on our investigation of NDD predictions for the large, grove-forming ectomycorrhizal mast fruiting tree, Microberlinia bisulcata (Caesalpiniaceae), in an 82.5-ha plot at Korup, Cameroon. We tested whether juvenile density, size, growth and survival decreases with increasing conspecific adult basal area for 3245 ‘new’ seedlings and 540 ‘old’ seedlings (< 75-cm tall) during an approximately 4-year study period (2008–2012) and for 234 ‘saplings’ (≥ 75-cm tall) during an approximately 6-year study period (2008–2014). We found that the respective densities of new seedlings, old seedlings and saplings were positively, not and negatively related to increasing BA. Maximum leaf numbers and heights of old seedlings were negatively correlated with increasing basal areas, as were sapling heights and stem diameters. Whereas survivorship of new seedlings decreased by more than one-half with increasing basal area over its range in 2010–2012, that of old seedlings decreased by almost two-thirds, but only in 2008–2010, and was generally unrelated to conspecific seedling density. In 2010–2012 relative growth rates in new seedlings’ heights decreased with increasing basal area, as well as with increasing seedling density, together with increasing leaf numbers, whereas old seedlings’ growth was unrelated to either conspecific density or basal area. Saplings of below-average height had reduced survivorship with increasing basal area (probability decreasing from approx. 0.4 to 0.05 over the basal area range tested), but only sapling growth in terms of leaf numbers decreased with increasing basal area. These static and dynamic results indicate that NDD is operating within this system, possibly stabilizing the M. bisulcata population. However, these NDD patterns are unlikely to be caused by symmetric competition or by consumers. Instead, an alternative mechanism for conspecific adult–juvenile negative feedback is proposed, one which involves the interaction between tree phenology and ectomycorrhizal linkages.

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This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

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Two cohorts of amyotrophic lateral sclerosis (ALS) patients were identified. One incidence-based cohort from Harris County, Texas with 97 cases, and the other a clinic referral series from an ALS clinic in Houston, Texas with 439 cases were followed-up to evaluate the prognosis of ALS. The overall Kaplan-Meier 3-year survival after diagnosis was similar, 0.287 for the incidence cohort and 0.313 for the referral cohort. However, the 5-year survival was much lower for the incidence cohort than the referral cohort (0.037 vs. 0.206). The large difference in 5-year survival was thought to be the results of a stronger unfavorable effect of the prognostic factors in the incidence cohort than in the referral cohort.^ Cohort-specific Weibull regression models were derived to evaluate the cohort-specific prognostic factors and survival probability with adjustment of certain prognostic factors.^ The major prognostic factors were: age at diagnosis, bulbar onset, black ethnicity, and positive family history of ALS in both cohorts. Female gender, simultaneous upper and lower extremities onset were specifically unfavorable factors in the incidence cohort. In the incidence cohort the prognosis was relatively favorable for cases with duration from onset to diagnosis longer than 4 months, however in the referral cohort the relatively favorable prognosis only occurred in cases with duration from onset to diagnosis 1 year or longer and was strongest in cases with duration 5 years and longer. Age at diagnosis modified the effect of bulbar onset in the incidence cohort but not in the referral cohort. The estimated survival with presence of an unfavorable prognostic factor identified in the incidence cohort was higher for the referral cohort than for the incidence cohort. Future studies are indicated to investigate the disease heterogeneity issue of ALS based on survival distribution of ALS. ^

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Conservative procedures in low-dose risk assessment are used to set safety standards for known or suspected carcinogens. However, the assumptions upon which the methods are based and the effects of these methods are not well understood.^ To minimize the number of false-negatives and to reduce the cost of bioassays, animals are given very high doses of potential carcinogens. Results must then be extrapolated to much smaller doses to set safety standards for risks such as one per million. There are a number of competing methods that add a conservative safety factor into these calculations.^ A method of quantifying the conservatism of these methods was described and tested on eight procedures used in setting low-dose safety standards. The results using these procedures were compared by computer simulation and by the use of data from a large scale animal study.^ The method consisted of determining a "true safe dose" (tsd) according to an assumed underlying model. If one assumed that Y = the probability of cancer = P(d), a known mathematical function of the dose, then by setting Y to some predetermined acceptable risk, one can solve for d, the model's "true safe dose".^ Simulations were generated, assuming a binomial distribution, for an artificial bioassay. The eight procedures were then used to determine a "virtual safe dose" (vsd) that estimates the tsd, assuming a risk of one per million. A ratio R = ((tsd-vsd)/vsd) was calculated for each "experiment" (simulation). The mean R of 500 simulations and the probability R $<$ 0 was used to measure the over and under conservatism of each procedure.^ The eight procedures included Weil's method, Hoel's method, the Mantel-Byran method, the improved Mantel-Byran, Gross's method, fitting a one-hit model, Crump's procedure, and applying Rai and Van Ryzin's method to a Weibull model.^ None of the procedures performed uniformly well for all types of dose-response curves. When the data were linear, the one-hit model, Hoel's method, or the Gross-Mantel method worked reasonably well. However, when the data were non-linear, these same methods were overly conservative. Crump's procedure and the Weibull model performed better in these situations. ^