Evidence map›Paper›PMID 31652685›Full record

ArticleCancers2019

Theoretical and Practical Implications of Treating Cachexia in Advanced Lung Cancer Patients.

Philip Bonomi, Mary Jo Fidler, Palmi Shah, Jeffrey Borgia

Abstract read
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
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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.

Philip BonomiDivision of Hematology/Oncology, Rush University Medical Center, Chicago, IL 60612, USA. pbonomi@rush.edu.
Mary Jo FidlerDivision of Hematology/Oncology, Rush University Medical Center, Chicago, IL 60612, USA. Mary_fidler@rush.edu.
Palmi ShahDepartment of Radiology, Rush University Medical Center, Chicago, IL 60612, USA. Palmi_shah@rush.edu.
Jeffrey BorgiaDepartment of Cell & Molecular Medicine, Rush University Medical Center, Chicago, IL 60612, USA. Jeffrey_A_Borgia@rush.edu.ORCID 0000-0002-1520-7966

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer continues to be a major worldwide health issue, with more than 50% of patients having incurable metastatic disease at diagnosis. Fortunately, the advanced lung cancer treatment landscape is changing rapidly as a result of the positive impact of effective inhibitors of tumor driver mutations, and the more recent discovery that immune modulation with anti-PD-1/PD-L1 monoclonal antibodies results in tumor regression and prolonged survival. While a relatively small subset of lung cancer patients are candidates for inhibitors of driver mutations, the majority of advanced lung cancer patients are candidates for an immunotherapy regimen. Many of these patients have cachexia, which is associated with increased cancer therapy toxicity and possibly reduced responsiveness to immunotherapy. Two ongoing cachexia trials, one testing a ghrelin analogue and the other testing a multimodal strategy, have endpoints which assess clinical benefit-weight gain and relief of anorexia/cachexia symptoms. Provided that the trial objectives are achieved, these treatment strategies will provide a way to relieve suffering and distress for cachectic cancer patients. While awaiting the results of these trials, it would be reasonable to consider designing studies testing cachexia treatments combined with first-line immunotherapy and chemotherapy-immunotherapy in stage IV lung cancer patients, with enhanced overall survival being one of the endpoints.

Indexed as

cachexiaimmunotherapylung cancertrial endpoints

Identifiers

PMID31652685
PMCPMC6893632

What OpenQuestion holds

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LicenceCC BY
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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.