Evidence map›Paper›PMID 8279612›Full record

ArticleAmerican journal of public health1994

Using census and mortality data to target small areas for breast, colorectal, and cervical cancer screening.

H F Andrews, J F Kerner, A G Zauber, J Mandelblatt, J Pittman, E Struening

Abstract read
In one paragraph

Article in American journal of public health, 1994. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

6 authors.

H F AndrewsMemorial Sloan-Kettering Cancer Center, New York, NY.
J F Kerner
A G Zauber
J Mandelblatt
J Pittman
E Struening

Funding

DATA-BASED INTERVENTIONS IN CANCER CONTROLR01CA046586 · NCI · NEW YORK STATE DEPT OF HEALTH · PI NASCA, PHILIP C · 1987 to 1991
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NCI NIH HHS NCI J1 R01 CA 46586
6 · The paper itself

Abstract

objectivesThe goal of this study was to develop and validate quantitative models for estimating cancer incidence in small areas.

methodsThe outcome for each cancer site was the incidence of disease that had reached a late stage at the time of diagnosis. Two sets of predictors were used: (1) census-based demographic variables and (2) census-based demographic variables together with the cancer-specific mortality rate.

resultsThe best models accounted for a substantial percentage of between area variability in late-stage rates for cancer of the breast (46%), cervix (61%), and colon/rectum (58%). A validation procedure indicated that correct identification of small areas with high rates of late-stage disease was two to three times more likely when model-based estimates were used than when areas were selected at random.

conclusionsAdditional testing is needed to establish the generality of the geographic targeting methodology developed in this paper. However, there are strong indications that small-area estimation models will be useful in many regions where planners wish to target cancer screening programs on a geographic basis.

Indexed as

Small-Area AnalysisBreast NeoplasmsColorectal NeoplasmsDemographyFemaleHumansIncidenceMaleMass ScreeningModels, StatisticalNew York CityRegression AnalysisUterine Cervical Neoplasms

Identifiers

PMID8279612
PMCPMC1614917

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.