Evidence map›Paper›PMID 23251495›Full record

ArticlePloS one2012

Breast cancer attributable costs in Germany: a top-down approach based on sickness funds data.

Emil Victor Gruber, Stephanie Stock, Björn Stollenwerk

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Healthcare costs associated with breast cancer in Germany: a claims data analysis.The European journal of health economics : HEPAC : health economics in prevention and care · 2020
    Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Cost-of-illness studies based on massive data: a prevalence-based, top-down regression approach.The European journal of health economics : HEPAC : health economics in prevention and care · 2016
    Article
  11. Article
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

3 authors.

Emil Victor GruberInstitute of Health Economics and Health Care Management, Helmholtz Zentrum München, Neuherberg, Germany.
Stephanie Stock
Björn Stollenwerk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is the leading cause of death from cancer among women in Germany. Despite its clinical and economic relevance, no attributable costs for breast cancer have been reported for Germany so far. The objective of this study is to estimate age-specific breast cancer attributable health expenditures for Germany.

methodsSickness fund data from 1999 representing about 26 million insured (i.e. 32% of the total German population) have been analysed using generalized additive models and the error propagation law. Costs have been inflated to 2010.

resultsBreast cancer attributable costs decreased with age. Among breast cancer patients aged 30-45 years, about 90% of all health expenditures were due to breast cancer, whereas in breast cancer patients aged 80-90 years, about 50% were due to breast cancer. Breast cancer attributable costs amounted to about €9,000 annually for patients below 55 years of age and declined to about €3,000 in 90-year-old breast cancer patients.

conclusionThis analysis provides estimates of attributable breast cancer costs in Germany. Compared with the international literature, the estimates were plausible but had a tendency to underestimate breast cancer attributable costs.

Indexed as

Cost of IllnessBreast NeoplasmsFemaleGermanyHumans

Identifiers

PMID23251495
PMCPMC3519543

What OpenQuestion holds

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LicenceCC BY
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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.