Evidence map›Paper›PMID 9435152›Full record

ArticleEnvironmental health perspectives1998

Models of interaction between metabolic genes and environmental exposure in cancer susceptibility.

E Taioli, C Zocchetti, S Garte

Open access · diamondAbstract read
In one paragraph

Article in Environmental health perspectives, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

E TaioliNelson Institute of Environmental Medicine and Kaplan Cancer Center, New York University Medical Center, New York, NY 10010, USA.
C Zocchetti
S Garte
Columbia University Irving Medical Center · US

Funding

RESEARCH IN ENVIRONMENTAL HEALTH SCIENCES (CENTER GRANT)P30ES000260 · NIEHS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ZELIKOFF, JUDITH TERRY · 1985 to 2020
$26.1M
CYP1A1 AS A BIOMARKER OF EXPOSURE AND SUSCEPTIBILITYR01ES008363 · NIEHS · UNIV OF MED/DENT NJ-SCH OF PUBLIC HEALTH · PI GARTE, SEYMOUR J · 1997 to 1999
–
NIEHS NIH HHS ES00260NIEHS NIH HHS ES08363
6 · The paper itself

Abstract

Polymorphic metabolic genes that confer enhanced genetic susceptibility to the carcinogenic effects of certain environmental carcinogens act according to a type 2 interaction between genetic and environmental risk factors. This type of interaction, for which the gene has no effect on disease outcome by itself but only modifies the risk associated with exposure, must be treated differently from other types of gene-environment interaction. We present a method to analyze different dose effects often seen in studies involving these genes. We define a low exposure-gene effect, when a greater degree of gene environment interaction appears at lower doses of exposure (the interaction follows an inverse dose function), and a converse high exposure-gene effect, when the interaction increases as a function of dose. Using a standard logistic regression model, we define a new term, alpha, that can be determined asa function of exposure dose in order to analyze epidemiological studies for the type of exposure-gene effect. These models are illustrated by the use of hypothetical case-control data as well as examples from the literature.

Indexed as

AlgorithmsAmino AcidsCase-Control StudiesCytochrome P-450 CYP1A1Environmental ExposureHumansLung NeoplasmsMetabolismModels, BiologicalNeoplasmsPolymorphism, GeneticRegression AnalysisSmokingAmino AcidsCytochrome P-450 CYP1A1

Identifiers

PMID9435152
PMCPMC1533018
OpenAlexW1987351773

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.