Evidence map›Paper›PMID 22423250›Full record

ArticleEcancermedicalscience2012

Cancer in older patients: an analysis of elderly oncology.

V Swaminathan, Ra Audisio

Abstract read
In one paragraph

Article in Ecancermedicalscience, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
  2. The Influence of Muscle Morphology on Oncological Outcomes: A Review.Journal of frailty, sarcopenia and falls · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Choices in surgery for older women with breast cancer.Breast care (Basel, Switzerland) · 2012
    Review
  9. 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.

V SwaminathanMersey Deanery, FY1 Southport DGH, Town Lane, Kew, Southport, PR8 6PN, UK.
Ra Audisio

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Is it possible to define when someone is elderly? The worldwide population is growing not only in number but also in age; it is estimated that the population will increase to around 750 million by 2021. Two thirds of cancer occurs in the over 65 age groups. With an increasing elderly population, it can be derived that cancer will become a more prevalent condition. The burden of cancer on the medical profession will be even more apparent than before. In addition the elderly age group has different needs compared with younger oncology patients; there can be no 'rule of thumb' with the management of elderly illness. Factors such as frailty are significant when treating cancer in the older patients. The assessment of quality of life in older patients with cancer is also an important factor. Is it best for a patient to enjoy life as it is with cancer or aim for increased life expectancy by undertaking treatment with the threat of morbidity however severe during that period? The volume of scientific evidence currently available to support all the issues in geriatric oncology is greatly limited; almost all treatments designed for oncology are being tested in randomized clinical trials preferentially using younger cohorts of patients. Changes need to be made in order to further this field of medicine. Geriatric oncology is no longer a palliative field, as a healthy active life can now be expected by some older patients. The burden of oncology in the elderly will need to take a modern approach regarding the management of these patients.

Identifiers

PMID22423250
PMCPMC3298408

What OpenQuestion holds

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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.