Design and Implementation of a Community Driven Clinical Trial Information Management System for Precision Oncology Settings.

Introduction: Trial recruitment is a crucial factor for precision oncology, potentially improving patient outcomes and generating new scientific evidence. To identify suitable, biomarker-based trials for patients' clinicians need to screen multiple clinical trial registries which lack support for modern trial designs and offer only limited options to filter for in- and exclusion criteria. Several registries provide trial information but are limited regarding factors like timeliness, quality of information and capability for semantic, terminology enhanced searching for aspects like specific inclusion criteria.

Merging Genomics Public Datasets with Clinical Cancer Registry Data - Lessons Learned.

Publicly available datasets - for example via cBioPortal for Cancer Genomics - could be a valuable source for benchmarks and comparisons with local patient records. However, such an approach is only valid if patient cohorts are comparable to each other and if the documentation is complete and sufficient. In this paper, records from exocrine pancreatic cancer patients documented in a local cancer registry are compared with two public datasets to calculate overall survival.

Olaparib.

Olaparib (Lynparza [AstraZeneca, Cambridge, UK], formerly referred to as AZD2281 or KU0059436) is an oral poly(ADP-ribose) polymerase (PARP) inhibitor. It is rationally designed to act as a competitive inhibitor of NAD at the catalytic site of PARP1 and PARP2, both members of the PARP family of enzymes that are central to the repair of DNA single-strand breaks (SSBs) mediated via the base excision repair (BER) pathway. Inhibition of the BER pathway by olaparib leads to the accumulation of unrepaired SSBs, which leads to the formation of deleterious double-strand breaks (DSBs).

Larotrectinib (LOXO-101).

One of the most challenging issues in oncology research and treatment is identifying oncogenic drivers within an individual patient's tumor which can be directly targeted by a clinically available therapeutic drug. In this context, gene fusions as one important example of genetic aberrations leading to carcinogenesis follow the widely accepted concept that cell growth and proliferation are driven by the accomplished fusion (usually involving former proto-oncogenes) and may therefore be successfully inhibited by substances directed against the fusion. This concept has already been established with oncogenic gene fusions like BCR-ABL in chronic myelogenous leukemia (CML) or anaplastic lymphoma kinase (ALK) in lung cancer, including special tyrosine kinase inhibitors (TKIs) which are able to block the activation of the depending downstream proliferation pathways and, consequently, tumor growth.

Clinical Cancer Registries - Are They Up for Health Services Research?

Clinical cancer registries are a valuable data source for health services research (HSR). HSR is in need of high quality routine care data for its evaluations. However, the secondary use of routine data - such as documented cancer cases in a disease registry - poses new challenges in terms of data quality, IT-management, documentation processes and data privacy.

Transition probabilities of HER2-positive and HER2-negative breast cancer patients treated with Trastuzumab obtained from a clinical cancer registry dataset.

Records of female breast cancer patients were selected from a clinical cancer registry and separated into three cohorts according to HER2-status (human epidermal growth factor receptor 2) and treatment with or without Trastuzumab (a humanized monoclonal antibody). Propensity score matching was used to balance the cohorts. Afterwards, documented information about disease events (recurrence of cancer, metastases, remission of local/regional recurrences, remission of metastases and death) found in the dataset was leveraged to calculate the annual transition probabilities for every cohort.

A method for using real world data in breast cancer modeling.

Objectives: Today, hospitals and other health care-related institutions are accumulating a growing bulk of real world clinical data. Such data offer new possibilities for the generation of disease models for the health economic evaluation. In this article, we propose a new approach to leverage cancer registry data for the development of Markov models.

Prediction of 5-Year Survival with Data Mining Algorithms.

Survival time prediction at the time of diagnosis is of great importance to make decisions about treatment and long-term follow-up care. However, predicting the outcome of cancer on the basis of clinical information is a challenging task. We now examined the ability of ten different data mining algorithms (Perceptron, Rule Induction, Support Vector Machine, Linear Regression, Naïve Bayes, Decision Tree, k-nearest Neighbor, Logistic Regression, Neural Network, Random Forest) to predict the dichotomous attribute "5-year-survival" based on seven attributes (sex, UICC-stage, etc.

Personalized treatment for colorectal cancer: novel developments and putative therapeutic strategies.

Background: Colorectal cancer (CRC) is the third most common cancer diagnosed worldwide and continues to be a major healthcare concern. Molecular heterogeneity of CRC is believed to be one of the main factors responsible for the considerable variability in treatment response. With the recent development of powerful genomic technologies, novel insights in tumor biology of CRC have now been provided, facilitating the recognition of new molecular subtypes with prognostic and predictive implications.

Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families.

Background: Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive.

Genomewide scan in families with schizophrenia from the founder population of Afrikaners reveals evidence for linkage and uniparental disomy on chromosome 1.

We report on our initial genetic linkage studies of schizophrenia in the genetically isolated population of the Afrikaners from South Africa. A 10-cM genomewide scan was performed on 143 small families, 34 of which were informative for linkage. Using both nonparametric and parametric linkage analyses, we obtained evidence for a small number of disease loci on chromosomes 1, 9, and 13.

Confirmation of the prostate cancer susceptibility locus HPCX in a set of 104 German prostate cancer families.

Background: Several prostate cancer (PCa) susceptibility loci have been reported, but attempts to confirm them in independent data sets have produced inconsistent results. It is not yet clear, how much of this variation is due to differences between different populations. HPCX was originally identified in a combined data set of PCa families from the USA and Scandinavia.