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Record W4396862035 · doi:10.1002/jcsm.13478

Body weight and composition endpoints in cancer cachexia clinical trials: Systematic Review 4 of the cachexia endpoints series

2024· review· en· W4396862035 on OpenAlex
Leo R. Brown, Mariana S. Sousa, Michael S. Yule, Vickie E. Baracos, Donald C. McMillan, Jann Arends, Trude R. Balstad, Asta Bye, Olav Dajani, Ross D. Dolan, Marie Fallon, Christine Greil, Marianne Jensen Hjermstad, Gunnhild Jakobsen, Matthew Maddocks, James McDonald, Inger Ottestad, I. Phillips, Judith Sayers, Melanie Rae Simpson, Ola Magne Vagnildhaug, Tora S. Solheim, Barry Laird, Richard J.E. Skipworth

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2024
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
FundersNational Institute for Health and Care Research
KeywordsCancer cachexiaCachexiaMedicineCancerClinical trialOncologyInternal medicine

Abstract

fetched live from OpenAlex

Significant variation exists in the outcomes used in cancer cachexia trials, including measures of body composition, which are often selected as primary or secondary endpoints. To date, there has been no review of the most commonly selected measures or their potential sensitivity to detect changes resulting from the interventions being examined. The aim of this systematic review is to assess the frequency and diversity of body composition measures that have been used in cancer cachexia trials. MEDLINE, Embase and Cochrane Library databases were systematically searched between January 1990 and June 2021. Eligible trials examined adults (≥18 years) who had received an intervention aiming to treat or attenuate the effects of cancer cachexia for >14 days. Trials were also of a prospective controlled design and included body weight or at least one anthropometric, bioelectrical or radiological endpoint pertaining to body composition, irrespective of the modality of intervention (e.g., pharmacological, nutritional, physical exercise and behavioural) or comparator. Trials with a sample size of <40 patients were excluded. Data extraction used Covidence software, and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. This review was prospectively registered (PROSPERO: CRD42022276710). A total of 84 clinical trials, comprising 13 016 patients, were eligible for inclusion. Non-small-cell lung cancer and pancreatic cancer were studied most frequently. The majority of trial interventions were pharmacological (52%) or nutritional (34%) in nature. The most frequently reported endpoints were assessments of body weight (68 trials, n = 11 561) followed by bioimpedance analysis (BIA)-based estimates (23 trials, n = 3140). Sixteen trials (n = 3052) included dual-energy X-ray absorptiometry (DEXA)-based endpoints, and computed tomography (CT) body composition was included in eight trials (n = 841). Discrepancies were evident when comparing the efficacy of interventions using BIA-based estimates of lean tissue mass against radiological assessment modalities. Body weight, BIA and DEXA-based endpoints have been most frequently used in cancer cachexia trials. Although the optimal endpoints cannot be determined from this review, body weight, alongside measurements from radiological body composition analysis, would seem appropriate. The choice of radiological modality is likely to be dependent on the trial setting, population and intervention in question. CT and magnetic resonance imaging, which have the ability to accurately discriminate tissue types, are likely to be more sensitive and provide greater detail. Endpoints are of particular importance when aligned with the intervention's mechanism of action and/or intended patient benefit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.211
GPT teacher head0.524
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it