Evidence map›Paper›PMID 39552749›Full record

ArticleJournal of the Royal Statistical Society. Series C, Applied statistics2024

Joint modelling of survival and backwards recurrence outcomes: an analysis of factors associated with fertility treatment in the U.S.

Siyuan Guo, Jiajia Zhang, Alexander C McLain

Abstract read
In one paragraph

Article in Journal of the Royal Statistical Society. Series C, Applied statistics, 2024. 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

3 authors.

Siyuan GuoDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, USA.
Jiajia ZhangDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, USA.ORCID https://orcid.org/0000-0003-4566-0822
Alexander C McLainDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, USA.ORCID https://orcid.org/0000-0002-5475-0670

Funding

Estimating population level infertility and fertility treatment ratesR03HD097287 · NICHD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI MCLAIN, ALEXANDER C · 2019 to 2020
$162k
NICHD NIH HHS R03 HD097287
6 · The paper itself

Abstract

The motivation for this paper is to determine factors associated with time-to-fertility treatment (TTFT) among women currently attempting pregnancy in a cross-sectional sample. Challenges arise due to dependence between time-to-pregnancy (TTP) and TTFT. We propose appending a marginal accelerated failure time model to identify risk factors of TTFT with a model for TTP where fertility treatment is included as a time-varying treatment to account for their dependence. The latter requires extending backwards recurrence survival methods to incorporate time-varying covariates with time-varying coefficients. Since backwards recurrence survival methods are a function of mean survival, computational difficulties arise in formulating mean survival when fertility treatment is unobserved, i.e. when TTFT is censored. We address these challenges by developing computationally friendly forms for the double expectation of TTP and TTFT. The performance is validated via comprehensive simulation studies. We apply our approach to the National Survey of Family Growth and explore factors related to prolonged TTFT in the U.S.

Indexed as

censoringcross-sectional datalength-biased datatime-varying coefficientstime-varying treatment

Identifiers

PMID39552749
PMCPMC11561729

What OpenQuestion holds

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Registered trials

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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.