Penalized regression for interval‐censored times of disease progression: Selection of HLA markers in psoriatic arthritis

Ying Wu and Richard J. Cook

Biometrics, 2015, vol. 71, issue 3, 782-791

Abstract: Times of disease progression are interval‐censored when progression status is only known at a series of assessment times. This situation arises routinely in clinical trials and cohort studies when events of interest are only detectable upon imaging, based on blood tests, or upon careful clinical examination. We consider the problem of selecting important prognostic biomarkers from a large set of candidates when disease progression status is only known at irregularly spaced and individual‐specific assessment times. Penalized regression techniques (e.g., LASSO, adaptive LASSO, and SCAD) are adapted to handle interval‐censored time of disease progression. An expectation–maximization algorithm is described which is empirically shown to perform well. Application to the motivating study of the development of arthritis mutilans in patients with psoriatic arthritis is given and several important human leukocyte antigen (HLA) variables are identified for further investigation.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://doi.org/10.1111/biom.12302

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:biomet:v:71:y:2015:i:3:p:782-791

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0006-341X

Access Statistics for this article

More articles in Biometrics from The International Biometric Society
Bibliographic data for series maintained by Wiley Content Delivery ().