Evidence map›Paper›PMID 33362274›Full record

ArticlePloS one2020

Evaluation of productivity losses due to premature mortality from colorectal cancer.

Josep Darbà, Alicia Marsà

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 11% of its field
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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  5. 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

2 authors at 1 institution in 1 country.

Josep DarbàDepartment of Economics, Universitat de Barcelona, Barcelona, Spain.ORCID 0000-0003-2371-0999
Alicia MarsàDepartment of Health Economics, BCN Health Economics & Outcomes Research S.L., Barcelona, Spain.
Universitat de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is responsible annually for around 27% of all deaths in Spain, 15% of which are caused by colorectal cancer. This malignancy has increased its incidence considerably over the past years, which surely impacts global productivity losses. The evaluation of lost productivity due to premature mortality provides valuable information that guides healthcare policies into the establishment of prevention and screening programs. The purpose of this study was to assess the productivity losses from premature deaths due to colorectal cancer over a ten year period (2008-2017). The costs derived from premature mortality due to this highly prevalent cancer were estimated using data on mortality, age- and sex-specific reference salaries and unemployment rates in Spain via the human capital approach. Between 2008 and 2017, 15,103 persons died per year from colorectal cancer, representing almost 15% of all cancer-related deaths. Annually, 25,333 years of potential productive life were estimated to be lost on average, 14,992 in males and 10,341 in females. Productivity losses summed €510.8 million in in 2017, and the cancers of the colon and rectum accounted for 9.6% of cancer-related productivity losses in 2017 in Spain. Colorectal cancer has an important weight in terms of productivity losses within the Spanish population, consequently, prevention and early detection programmes should be promoted and implemented to achieve significant reductions in mortality and productivity losses.

Indexed as

AdolescentAdultColorectal NeoplasmsEfficiencyFemaleHumansIncidenceLife ExpectancyMaleMiddle AgedMortality, PrematureSex CharacteristicsSpainUnemploymentYoung Adult

Identifiers

PMID33362274
PMCPMC7757866
OpenAlexW3116326314

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.