ArticleAmerican journal of epidemiology2010
Invited commentary: Human papillomavirus infection and risk of cervical precancer--using the right methods to answer the right questions.
Article in American journal of epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Commentary: Quantifying the impact of bias to inform quality assessments in systematic reviews: The case of perchloroethylene and Non-Hodgkin's lymphoma.Global epidemiology · 2022Article
- The road ahead for cervical cancer prevention and control.Current oncology (Toronto, Ont.) · 2014Article
- Turning disciplinary knowledge into solutions.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2013Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Epidemiologists are well aware of the negative consequences of measurement error in exposure and outcome variables to their ability to detect putative causal associations. However, empirical proof that remedying the misclassification problem improves estimates of epidemiologic effect is seldom examined in detail. Of all areas in cancer epidemiology, perhaps the best example of the consequences of misclassification and of the steps taken to circumvent them was the pursuit, beginning in the mid-1980s, of the human papillomavirus (HPV) infection-cervical cancer association. The stakes were high: Had the wrong conclusions been reached epidemiologists would have been led astray in the search for competing hypotheses for the sexually transmissible agent causing cervical cancer or in ascribing to HPV infection a mere ancillary role among many lifestyle, hormonal, and environmental factors. The article by Castle et al. in this issue of the Journal (Am J Epidemiol. 2010;171(2):155-163) provides a detailed account of the joint influences of improved HPV and cervical precancer measurements in gradually unveiling the strong magnitude of the underlying association between viral exposure and cervical lesion risk. In this commentary, the authors extend the findings of Castle et al. by providing additional empirical evidence in support of their arguments.
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Registered trials
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.