Evidence map›Paper›PMID 41872762›Full record

ArticleBMC medical research methodology2026

Recall bias in population-based case-control studies of ovarian cancer and genital talcum powder use: potential impact and quantitative bias analysis.

Diezhang Wu, Igor Burstyn, William J Thompson, Jing Qian, Kenneth A Mundt

Abstract read
In one paragraph

Article in BMC medical research methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Diezhang WuDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
Igor BurstynDepartment of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Room 733, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA. ib68@drexel.edu.
William J ThompsonIndependent Consultant, Hume, MO, USA.ORCID http://orcid.org/0000-0002-9457-3234
Jing QianDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
Kenneth A MundtDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionQuantitative bias analysis (QBA) methods have been developed, with growing applications to epidemiological studies. Bayesian QBA (BQBA) methods may be superior in effectively using evidence-based priors and study data to displace fixed-value assumptions, and in characterizing distributions of adjusted point estimates and associated uncertainty.

methodsWe applied simple QBA (SQBA) and BQBA methods to population-based case-control studies on ovarian cancer and genital talcum powder use. Our hypothesis was that differential misclassification of self-reported historical talcum powder use led to statistically significant associations in several of these studies. SQBA results covering ranges of published exposure sensitivity and specificity estimates for genital talcum powder use were generated. BQBA models generated posterior means and 95% credible intervals (CrI’s) of bias-adjusted odds ratios (ORs), sensitivities and specificities of controls and cases, respectively, using pooled case-control study data.

resultsThe mean Bayesian posterior OR was 1.08 (95% CrI 0.67–1.77), mean case and control sensitivities were 0.87 and 0.78 and mean case and control specificities were 0.86 and 0.90, respectively. Model diagnostics indicated good fit.

conclusionUpon adjusting only for hypothesized differential exposure misclassification bias, the association between ovarian cancer and genital talcum powder use was attenuated relative to the unadjusted one. While other potential sources of bias may be operating within this body of studies, exposure reporting bias likely accounts for the statistically significant ORs reported in the individual case-control studies.

Indexed as

Ovarian NeoplasmsTalcBayes TheoremBiasCase-Control StudiesFemaleHumansOdds RatioPowdersSensitivity and SpecificityPowdersTalc

Identifiers

PMID41872762
PMCPMC13130445

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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.