Parameterized Link Functions in Generalized Linear Random Effect Models: a Case Study on Breast Cancer Treatment

In non-linear random effects some attention has been very recently devoted to the analysis ofsuitable transformation of the response variables separately (Taylor 1996) or not (Oberg and Davidian 2000) from the transformations of the covariates and, as far as we know, no investigation has been carried out on the choice of link function in such models. In our study we consider the use of a random effect model when a parameterized family of links (Aranda-Ordaz 1981, Prentice 1996, Pregibon 1980, Stukel 1988 and Czado 1997) is introduced. We point out the advantages and the drawbacks associated with the choice of this data-driven kind of modeling. Difficulties in the interpretation of regression parameters, and therefore in understanding the influence of covariates, as well as problems related to loss of efficiency of estimates and overfitting, are discussed. A case study on radiotherapy usage in breast cancer treatment is discussed

Validation of serum ferritin values by magnetic susceptometry in predicting iron overload in dialysis patients

Validation of serum ferritin values by magnetic susceptometry in predicting iron overload in dialysis patients.BackgroundGuidelines for treating anemia in dialysis patients accept, as high-end range of serum ferritin useful to optimize erythropoietin therapy, values high as 500 to 900 μg/L, on the hypothesis that ferritin might be not representative of iron overload.MethodsA superconducting quantum interference device (SQUID) was used to make direct noninvasive magnetic measurements of nonheme hepatic iron content in 40 dialysis patients treated with intravenous iron, and liver iron content was compared with biochemical markers of iron status.ResultsOnly 12/40 (30%) patients showed normal hepatic iron content (SQUID <400 μg/g), while 32.5% had mild (400 to 1000 μg/g) and 37.5% severe (>1000 μg/g) iron overload, although 28/40 patients (70%) had serum ferritin below 500 μg/L. Among many parameters, hepatic iron content was only correlated with ferritin (r = 0.324, P = 0.04). The receiver operating characteristic (ROC) analysis showed the best specificity/sensitivity ratio to identify iron overload for ferritin >340 μg/L (W = 0.716). Multivariate logistic regression analysis demonstrated that an increase in serum ferritin of 100 μg/L and female gender were independent variables associated with moderate to severe hepatic iron overload: OR 1.71 (95% CI 1.10 to 2.67) and OR 10.68 (95% CI 1.81 to 63.15), respectively.ConclusionHepatic iron overload is frequent in dialysis patients with ferritin below currently proposed high-end ranges, and the diagnostic power of ferritin in indicating true iron stores is better than presumed. Safety concerns should prompt a reevaluation of acceptable iron parameters, focusing on potential gender-specific differences, to avoid potentially harmful iron overload in a majority of dialysis patients, mainly females

an application of the cox aalen model for breast cancer survival

Semiparametric hazard function regression models are among the well studied risk models in survival analysis. The Cox proportional hazards model has been a popular choice in modelling data from epidemiological settings. The Cox-Aalen model is one of the tools for handling the problem of non-proportional effects in the Cox model. We show an application on Piedmont cancer registry data. We initially fit standard Cox model and with the help of the score process we detect the violation of the proportionality assumption. Covariates and risk factors that, on the basis of clinical reasoning, best model baseline hazard are then moved into the additive part of the Cox-Aalen model. Multiplicative effects results are consistent with those of the Cox model whereas only the Cox-Aalen model fully represents the timevarying effect of tumour size