Development and validation of clinical prediction models: marginal differences between logistic regression, penalized maximum likelihood estimation, and genetic programming.

Objective: Many prediction models are developed by multivariable logistic regression. However, there are several alternative methods to develop prediction models. We compared the accuracy of a model that predicts the presence of deep venous thrombosis (DVT) when developed by four different methods.

[Hypoxaemia and bradycardia in children during guillotine adenotonsillectomy without intubation].

Objective: To study the incidence of hypoxaemia and bradycardia in children who undergo guillotine adenotonsillectomy in a sitting position, without intubation and under inhalation anaesthesia.

Design: Retrospective study.

Method: Analysis of age, weight, sex, oxygen saturation, heart rate and subsequent bleeding in all children up to the age of 11 years who underwent guillotine adenotonsillectomy in the period December 1999 to December 2007.

A software application for comparing large numbers of high resolution MALDI-FTICR MS spectra demonstrated by searching candidate biomarkers for glioma blood vessel formation.

Background: A Java application is presented, which compares large numbers (n > 100) of raw FTICR mass spectra from patients and controls. Two peptide profile matrices can be produced simultaneously, one with occurrences of peptide masses in samples and another with the intensity of common peak masses in all the measured samples, using the peak- and background intensities of the raw data. In latter way, more significantly differentially expressed peptides are found between groups than just using the presence or absence in samples of common peak masses.

Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon expression arrays.

Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histologic subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome.

A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls.

Background: Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest.

MALDI-TOF mass spectrometry analysis of cerebrospinal fluid tryptic peptide profiles to diagnose leptomeningeal metastases in patients with breast cancer.

Leptomeningeal metastasis (LM) is a devastating complication that occurs in 5% of patients with breast cancer. Early diagnosis and initiation of treatment are essential to prevent neurological deterioration. However, early diagnosis of LM remains challenging because 25% of cerebrospinal fluid (CSF) samples produce false-negative results at first cytological examination.

A new method to analyze matrix-assisted laser desorption/ionization time-of-flight peptide profiling mass spectra.

In protein and peptide mass spectrometry in which profiling of peaks is involved, their masses and intensities are important characteristics. Because of the relative low reproducibility of peak intensities associated with complex samples in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS), it is difficult to accurately assess the number of peaks and their intensities. In this study we evaluate these two characteristics for tryptic digests of cerebro-spinal fluid.

Genetic programming outperformed multivariable logistic regression in diagnosing pulmonary embolism.

Objective: Genetic programming is a search method that can be used to solve complex associations between large numbers of variables. It has been used, for example, for myoelectrical signal recognition, but its value for medical prediction as in diagnostic and prognostic settings, has not been documented.

Study Design And Setting: We compared genetic programming and the commonly used logistic regression technique in the development of a prediction model using empirical data from a study on diagnosis of pulmonary embolism.

Genomic profiling of gastric cancer predicts lymph node status and survival.

Gastric carcinogenesis is driven by an accumulation of genetic changes that to a large extent occur at the chromosomal level. We analysed the patterns of chromosomal instability in 35 gastric carcinomas and their clinical correlations. With microarray competitive genomic hybridization, genomewide chromosomal copy number changes can be studied with high resolution and sensitivity.