Confidence scores for prediction models

In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation, then rival strategies can still be compared based on repeated bootstraps of the same data. Often, however, the overall performance of rival strategies is similar and it is thus difficult to decide for one model. Here, we investigate the variability of the prediction models that results when the same modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer studies, also with high-dimensional predictor space.     

A Mixture‐of‐Genotypes Model for the Distribution of Thermostable Phenol Sulfotransferase Activity

A statistical method for parametric density estimation based upon a mixture‐of‐genotypes model is developed for the thermostable phenol sulfotransferase (SULT1A1) activity which has a putative role in modifying risk for colon and prostate cancer/polyps. The EM algorithm for the general mixture model is modified to accommodate the genetic constraints and is used to estimate genotype frequencies from the distribution of the SULT1A1 phenotype. A parametric bootstrap likelihood ratio test is considered as a testing method for the number of mixing components. The size and power of the test is then investigated and compared with the conventional chi‐squared test. The relative risk associated with genotypes defined by this model is also investigated through the generalized linear model. This analysis revealed that a genotype with the highest mean value of SULT1A1 activity has greater impact on cancer risk than others. This result suggests that the phenotype with a higher SULT1A1 activity might be important in studying the association between the cancer risk and SULT1A1 activity. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Applying DNA barcodes for identification of plant species in the family Araliaceae

An effective DNA marker in authentication of the family Araliaceae was screened out of the five DNA regions (matK, rbcL, ITS2, psbA-trnH and ycf5). In the present study, 1113 sequences of 276 species from 23 genera (Araliaceae) were collected from DNA sequencing and GenBank, in which 16 specimens were from 5 provinces in China and Japan. All of the sequences were assessed in the success rates of PCR amplifications, intra- and inter-specific divergence, DNA barcoding gaps and efficiency of identification. Compared with other markers, ITS2 showed superiority in species discrimination with an accurate identification of 85.23% and 97.29% at the species and genus levels, respectively, in plant samples from the 589 sequences derived from Araliaceae. Consequently, as one of the most popular phylogenetic markers, our study indicated that ITS2 was a powerful barcode for Araliaceae identification.