Evidence map›Paper›PMID 35872590›Full record

ArticleAmerican journal of epidemiology2022

Ascertainment of Incident Cancer by US Population-Based Cancer Registries Versus Self-Reports and Death Certificates in a Nationwide Cohort Study, the US Radiologic Technologists Study.

Danping Liu, Martha S Linet, Paul S Albert, Annelie M Landgren, Cari M Kitahara, Allison Iwan, Castine Clerkin, Betsy Kohler, Bruce H Alexander, Lynne Penberthy

Abstract read
In one paragraph

Article in American journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

10 authors.

Danping Liu
Martha S Linet
Paul S Albert
Annelie M Landgren
Cari M Kitahara
Allison Iwan
Castine Clerkin
Betsy Kohler
Bruce H Alexander
Lynne Penberthy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Follow-up of US cohort members for incident cancer is time-consuming, is costly, and often results in underascertainment when the traditional methods of self-reporting and/or medical record validation are used. We conducted one of the first large-scale investigations to assess the feasibility, methods, and benefits of linking participants in the US Radiologic Technologists (USRT) Study (n = 146,022) with the majority of US state or regional cancer registries. Follow-up of this cohort has relied primarily on questionnaires (mailed approximately every 10 years) and linkage with the National Death Index. We compared the level of agreement and completeness of questionnaire/death-certificate-based information with that of registry-based (43 registries) incident cancer follow-up in the USRT cohort. Using registry-identified first primary cancers from 1999-2012 as the gold standard, the overall sensitivity was 46.5% for self-reports only and 63.0% for both self-reports and death certificates. Among the 37.0% false-negative reports, 27.8% were due to dropout, while 9.2% were due to misreporting. The USRT cancer reporting patterns differed by cancer type. Our study indicates that linkage to state cancer registries would greatly improve completeness and accuracy of cancer follow-up in comparison with questionnaire self-reporting. These findings support ongoing development of a national US virtual pooled registry with which to streamline cohort linkages.

Indexed as

Death CertificatesNeoplasmsCohort StudiesHumansIncidenceRegistriesSelf Reportcancer ascertainmentdeath certificatesincident cancerlongitudinal cohort studiespopulation-based cancer registriesself-reportsUnited States

Identifiers

PMID35872590
PMCPMC10144614

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.