Evidence map›Paper›PMID 23329866›Full record

ArticleJournal of statistical planning and inference2013

Semiparametric inference on the penetrances of rare genetic mutations based on a case-family design.

Hong Zhang, Donglin Zeng, Sylviane Olschwang, Kai Yu

Abstract read
In one paragraph

Article in Journal of statistical planning and inference, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Hong ZhangInstitute of Biostatistics, School of Life Science, Fudan University, P.R.C ; Division of Cancer Epidemiology and Genetics, National Cancer Institute, U.S.A.
Donglin Zeng
Sylviane Olschwang
Kai Yu

Funding

Methods for Epidemiology StudiesZIACP010181 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBERT, PAUL · 2009 to 2025
$34.8M
Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVIDIAN, MARIE, KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
STATISTICAL METHODS IN CURRENT CANCER RESEARCHR01CA082659 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, DANYU · 2000 to 2016
$3.7M
Semiparametric Regression Analysis of Censored DataR37GM047845 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, DANYU · 2005 to 2014
$3.3M
Intramural NIH HHS ZIA CP010181NCI NIH HHS P01 CA142538NCI NIH HHS R01 CA082659NIGMS NIH HHS R37 GM047845
6 · The paper itself

Abstract

A formal semiparametric statistical inference framework is proposed for the evaluation of the age-dependent penetrance of a rare genetic mutation, using family data generated under a case-family design, where phenotype and genotype information are collected from first-degree relatives of case probands carrying the targeted mutation. The proposed approach allows for unobserved risk factors that are correlated among family members. Some rigorous large sample properties are established, which show that the proposed estimators were asymptotically semi-parametric efficient. A simulation study is conducted to evaluate the performance of the new approach, which shows the robustness of the proposed semiparamteric approach and its advantage over the corresponding parametric approach. As an illustration, the proposed approach is applied to estimating the age-dependent cancer risk among carriers of the MSH2 or MLH1 mutation.

Identifiers

PMID23329866
PMCPMC3544474

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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.