Evidence map›Paper›PMID 24433346›Full record

ArticleBMC public health2014

Effect size and cost-effectiveness estimates of breast and cervical cancer screening reminders by population size through complete enumeration of Japanese local municipalities.

Shigekazu Komoto, Yuji Nishiwaki, Tomonori Okamura, Hideo Tanaka, Toru Takebayashi

Abstract read
In one paragraph

Article in BMC public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Cancer control programs in East Asia: evidence from the international literature.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2014
    Review
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

5 authors.

Shigekazu KomotoDepartment of Preventive Medicine and Public Health, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan. komoto97@yahoo.co.jp.
Yuji Nishiwaki
Tomonori Okamura
Hideo Tanaka
Toru Takebayashi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClient reminders are known to increase cancer screening attendance rates. However, there are significant costs associated with them, and their effect by population size is unknown.

methodsIn 2007 and 2008, the Japanese Government surveyed breast and cervical cancer screening in every municipality in Japan. From the results, we selected all 1,464 municipalities that carried out both screening types. We examined whether changes in screening attendance rates between 2007 and 2008 were associated with client reminders, number of public health nurses per 100,000 population, financial strength index, and 2007 attendance rates for different population sizes. We then calculated cost-effectiveness estimates of client reminders by population size and screening type.

resultsClient reminders were associated with increased attendance rates in populations <100,000. For populations of 50,000-100,000, there was a 2.76% increase in breast cancer screening (95% CI: 0.41, 5.11), and a 2.25% increase in cervical cancer screening (95% CI: 0.89, 3.61). The incremental cost per additional attendance was higher in populations <50,000 than in populations of 50,000-100,000 (breast, $100 versus $54; cervical, $149 versus $67 respectively).

conclusionsClient reminders for breast and cervical cancer screening increased attendance rates in smaller municipalities in Japan.

Indexed as

Early Detection of CancerAdultBreast NeoplasmsCitiesCost-Benefit AnalysisFemaleHumansJapanPopulation DensityReminder SystemsUterine Cervical Neoplasms

Identifiers

PMID24433346
PMCPMC3904010

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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.