Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “NEOPLASM STATISTICS”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26Linked to original sources
PubMed1992

Modeling the modification of the risk of radon-induced lung cancer by environmental tobacco smoke.

The presence of environmental tobacco smoke (ETS) in homes has been implicated in the causation of lung cancer. While of interest in its own right, ETS also influences the risk imposed by radon and its decay products. The interaction between radon progeny and ETS alters the exposure, intake, uptake, biokinetics, dosimetry, and radiobiology of those progeny. The present paper details model predictions of the various influences of ETS on these factors in the U.S. population and provides estimates of the resulting change in the risk from average levels of radon progeny. It is predicted that the presence of ETS produces a very small (perhaps unmeasurable) increase in the risk of radiation-induced tracheobronchial cancer in homes with initially very high particle concentrations for both active and never-smokers, but significantly lowers the risk in homes with initially lower particle concentrations for both groups when generation 4 of the lung is considered the target site. For generation 16, the presence of ETS generally increases the radon-induced risk of lung cancer, although the increase should be unmeasurable at high initial particle concentrations. The net effect of ETS on human health is suggested to be a complicated function of the initial housing conditions, the concentration of particles introduced by smoking, the target generation considered, and the smoking status of exposed populations. This situation precludes any simple statements concerning the role of ETS in governing the incidence of lung cancer in a population.

Air Pollution, Indoor↗
PubMed1991

Methodology issues in risk assessment for radon.

The alpha dose per unit radon daughter exposure in mines and homes is comparable at about 5 mGy/WLM. This means that excess lung cancer risk determined in follow-up studies of miners should be valid to extrapolating to environmental populations. There are several models currently used for risk projection to estimate lung cancer in the U.S. from indoor radon exposure. The accuracy of the estimates depends upon the quality of the exposure data and the models. Recent miner epidemiology confirms that excess lung cancer risk decreases with time subsequent to cessation of exposure. The most rigorous ecological study, to date, shows a persistent negative relationship between average measured indoor radon in U.S. counties and lung cancer mortality. A model for lung cancer risk is proposed that includes smoking, urbanization, and radon exposure. The model helps to explain the difficulties in observing the direct effects of indoor radon in the environment.

Dose-Response Relationship, Radiation↗
PubMed2006

A gene expression signature predicts survival of patients with stage I non-small cell lung cancer.

BACKGROUND: Lung cancer is the leading cause of cancer-related death in the United States. Nearly 50% of patients with stages I and II non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection. No reliable clinical or molecular predictors are currently available for identifying those at high risk for developing recurrent disease. As a consequence, it is not possible to select those high-risk patients for more aggressive therapies and assign less aggressive treatments to patients at low risk for recurrence. METHODS AND FINDINGS: In this study, we applied a meta-analysis of datasets from seven different microarray studies on NSCLC for differentially expressed genes related to survival time (under 2 y and over 5 y). A consensus set of 4,905 genes from these studies was selected, and systematic bias adjustment in the datasets was performed by distance-weighted discrimination (DWD). We identified a gene expression signature consisting of 64 genes that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Kaplan-Meier analysis of the overall survival of stage I NSCLC patients with the 64-gene expression signature demonstrated that the high- and low-risk groups are significantly different in their overall survival. Of the 64 genes, 11 are related to cancer metastasis (APC, CDH8, IL8RB, LY6D, PCDHGA12, DSP, NID, ENPP2, CCR2, CASP8, and CASP10) and eight are involved in apoptosis (CASP8, CASP10, PIK3R1, BCL2, SON, INHA, PSEN1, and BIK). CONCLUSIONS: Our results indicate that gene expression signatures from several datasets can be reconciled. The resulting signature is useful in predicting survival of stage I NSCLC and might be useful in informing treatment decisions.

Algorithms↗