Evidence map›Paper›PMID 42470129›Full record

ArticleBiostatistics (Oxford, England)2026

Estimating the heritability of longitudinal rate-of-change: genetic insights into PSA velocity in prostate cancer-free individuals.

Pei Zhang, Xiaoyu Wang, Jianxin Shi, Paul S Albert

Abstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2026. 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.

Pei ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, United States.ORCID 0000-0001-9332-4917
Xiaoyu WangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, United States.ORCID 0009-0005-5143-6909
Jianxin ShiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, United States.ORCID 0000-0001-8606-4707
Paul S AlbertDivision of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, United States.

Funding

NIH HHS
6 · The paper itself

Abstract

Serum prostate-specific antigen (PSA) is widely used for prostate cancer screening. While the genetics of PSA levels have been studied to enhance screening accuracy, the genetic basis of PSA velocity, the rate of PSA change over time, remains unclear. The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, a large, randomized study with longitudinal PSA data (15,260 cancer-free males, averaging 5.34 samples per subject) and genome-wide genotype data, provides a unique opportunity to estimate PSA velocity heritability. We developed a mixed model to jointly estimate the heritability of PSA levels at age 54 and PSA velocity. To accommodate the large dataset, we implemented 2 efficient computational approaches: a partitioning and meta-analysis strategy using average information restricted maximum likelihood (AI-REML) and a fast restricted Haseman-Elston (REHE) regression method. Simulations showed that both methods yield unbiased estimates of both heritability metrics, with AI-REML providing smaller variability in the estimation of velocity heritability than REHE. Applying AI-REML to PLCO data, we estimated heritability at 0.32 (s.e. = 0.07) for baseline PSA and 0.45 (s.e. = 0.18) for PSA velocity. These findings reveal a substantial genetic contribution to PSA velocity, supporting future genome-wide studies to identify variants affecting PSA dynamics and improve PSA-based screening.

Indexed as

Models, StatisticalProstate-Specific AntigenProstatic NeoplasmsHumansLongitudinal StudiesMaleMiddle AgedProstate-Specific AntigenAI-REML algorithmlinear mixed modelmeta-analysisREHE methodtruncation

Identifiers

PMID42470129
PMCPMC13379640

What Socratic 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 Socratic graph.