Evidence map›Paper›PMID 38254286›Full record

ReviewCancer science2024

Progressive, multi-organ, and multi-layered nature of cancer cachexia.

Yuki Nakamura, Don Pietro Saldajeno, Kosuke Kawaguchi, Shinpei Kawaoka

Abstract readReview
In one paragraph

Review in Cancer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. 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

4 authors.

Yuki NakamuraInter-Organ Communication Research Team, Institute for Life and Medical Sciences, Kyoto, Japan.
Don Pietro SaldajenoInter-Organ Communication Research Team, Institute for Life and Medical Sciences, Kyoto, Japan.
Kosuke KawaguchiDepartment of Breast Surgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Shinpei KawaokaInter-Organ Communication Research Team, Institute for Life and Medical Sciences, Kyoto, Japan.ORCID https://orcid.org/0000-0003-4064-6781

Funding

JSPS KAKENHI 19K16770JSPS KAKENHI 20H03451JSPS KAKENHI 21K15530JST FOREST 20351876
6 · The paper itself

Abstract

Cancer cachexia is a complex, multifaceted condition that negatively impacts the health, treatment efficacy, and economic status of cancer patients. The management of cancer cachexia is an essential clinical need. Cancer cachexia is currently defined mainly according to the severity of weight loss and sarcopenia (i.e., macrosymptoms). However, such macrosymptoms may be insufficient to give clinicians clues on how to manage this condition as these symptoms appear at the late stage of cancer. We need to understand earlier events during the progression of cancer cachexia so as not to miss a clinical opportunity to control this complex syndrome. Recent research indicates that cancer-induced changes in the host are much wider than previously recognized, including disruption of liver function and the immune system. Furthermore, such changes are observed before the occurrence of visible distant metastases (i.e., in early, localized cancers). In light of these findings, we propose to expand the definition of cancer cachexia to include all cancer-induced changes to host physiology, including changes caused by early, localized cancers. This new definition of cancer cachexia can provide a new perspective on this topic, which can stimulate the research and development of novel cancer cachexia therapies.

Indexed as

NeoplasmsSarcopeniaCachexiaHumansTreatment OutcomeWeight Losscancer cachexiaimmunosuppressionlivermetabolismmultiomics

Identifiers

PMID38254286
PMCPMC10921013

What OpenQuestion holds

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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.