Analysis of multiple-cycle data from couples undergoing in vitro fertilization: Methodologic issues and statistical approaches

Missmer, SA; Pearson, KR; Ryan, LM; Meeker, JD; Cramer, DW; Hauser, R

Analysis of multiple-cycle data from couples undergoing in vitro fertilization: Methodologic issues and statistical approaches

Missmer, SA Pearson, KR Ryan, LM

Meeker, JD Cramer, DW Hauser, R

Permalink

Publication Type:: Journal Article
Citation:: Epidemiology, 2011, 22 (4), pp. 497 - 504
Issue Date:: 2011-07-01

Closed Access

	Filename	Description	Size
	2011008507OK.pdf		325.2 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Missmer, SA	en_US
dc.contributor.author	Pearson, KR	en_US
dc.contributor.author	Ryan, LM https://orcid.org/0000-0001-5957-2490	en_US
dc.contributor.author	Meeker, JD	en_US
dc.contributor.author	Cramer, DW	en_US
dc.contributor.author	Hauser, R	en_US
dc.date.issued	2011-07-01	en_US
dc.identifier.citation	Epidemiology, 2011, 22 (4), pp. 497 - 504	en_US
dc.identifier.issn	1044-3983	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26054
dc.description.abstract	The number of in vitro fertilization (IVF) cycles in the United States increased from fewer than 46,000 in 1995 to more than 120,000 in 2005. IVF and other assisted reproductive technology (ART) data are routinely collected and used to identify outcome predictors. However, researchers do not always make full use of the data due to their complexity. Design approaches have included restriction to first-cycle attempts only, which reduces power and identifies effects only of those factors associated with initial success. Many statistical techniques have been used or proposed for analysis of IVF data, ranging from simple t tests to sophisticated models designed specifically for IVF. We applied several of these methods to data from a prospective cohort of 2687 couples undergoing ART from 1994 through 2003. Results across methods are compared and the appropriateness of the various methods is discussed with the intent to illustrate methodologic validity. We observed a remarkable similarity of coefficient estimates across models. However, each method for dealing with multiple cycle data relies on assumptions that may or may not be expected to hold in a given IVF study. The robustness and reported magnitude of effect for individual predictors of IVF success may be inflated or attenuated due to violation of statistical assumptions, and should always be critically interpreted. Given that risk factors associated with IVF success may also advance our understanding of the physiologic processes underlying conception, implantation, and gestation, the application of valid methods to these complex data is critical. © 2011 by Lippincott Williams & Wilkins.	en_US
dc.relation.ispartof	Epidemiology	en_US
dc.relation.isbasedon	10.1097/EDE.0b013e31821b5351	en_US
dc.subject.classification	Epidemiology	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Fertilization in Vitro	en_US
dc.subject.mesh	Data Interpretation, Statistical	en_US
dc.subject.mesh	Models, Statistical	en_US
dc.subject.mesh	Survival Analysis	en_US
dc.subject.mesh	Cohort Studies	en_US
dc.subject.mesh	Prospective Studies	en_US
dc.subject.mesh	Research Design	en_US
dc.subject.mesh	Adult	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Self Report	en_US
dc.title	Analysis of multiple-cycle data from couples undergoing in vitro fertilization: Methodologic issues and statistical approaches	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	22	en_US
utslib.for	010402 Biostatistics	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1117 Public Health and Health Services	en_US
dc.location.activity	Brunei Darussalam
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	22	en_US

Abstract:

The number of in vitro fertilization (IVF) cycles in the United States increased from fewer than 46,000 in 1995 to more than 120,000 in 2005. IVF and other assisted reproductive technology (ART) data are routinely collected and used to identify outcome predictors. However, researchers do not always make full use of the data due to their complexity. Design approaches have included restriction to first-cycle attempts only, which reduces power and identifies effects only of those factors associated with initial success. Many statistical techniques have been used or proposed for analysis of IVF data, ranging from simple t tests to sophisticated models designed specifically for IVF. We applied several of these methods to data from a prospective cohort of 2687 couples undergoing ART from 1994 through 2003. Results across methods are compared and the appropriateness of the various methods is discussed with the intent to illustrate methodologic validity. We observed a remarkable similarity of coefficient estimates across models. However, each method for dealing with multiple cycle data relies on assumptions that may or may not be expected to hold in a given IVF study. The robustness and reported magnitude of effect for individual predictors of IVF success may be inflated or attenuated due to violation of statistical assumptions, and should always be critically interpreted. Given that risk factors associated with IVF success may also advance our understanding of the physiologic processes underlying conception, implantation, and gestation, the application of valid methods to these complex data is critical. © 2011 by Lippincott Williams & Wilkins.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/26054