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Record W4391751182 · doi:10.1002/jcsm.13434

Appetite and dietary intake endpoints in cancer cachexia clinical trials: Systematic Review 2 of the cachexia endpoints series

2024· review· en· W4391751182 on OpenAlexaff
Ola Magne Vagnildhaug, Trude R. Balstad, Inger Ottestad, Asta Bye, Christine Greil, Jann Arends, Vickie E. Baracos, Leo R. Brown, Olav Dajani, Ross D. Dolan, Marie Fallon, Eilidh Fraser, Aleksandra Grzyb, Marianne Jensen Hjermstad, Gunnhild Jakobsen, Stein Kaasa, James McDonald, Iain Philips, Judith Sayers, Melanie Rae Simpson, Mariana S. Sousa, Richard J. E. Skipworth, Barry Laird, Tora S. Solheim

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2024
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCachexiaAppetiteClinical endpointClinical trialCancerInternal medicine

Abstract

fetched live from OpenAlex

There is no consensus on the optimal endpoint(s) in cancer cachexia trials. Endpoint variation is an obstacle when comparing interventions and their clinical value. The aim of this systematic review was to summarize and evaluate endpoints used to assess appetite and dietary intake in cancer cachexia clinical trials. A search for studies published from 1 January 1990 until 2 June 2021 was conducted using MEDLINE, Embase and Cochrane Central Register of Controlled Trials. Eligible studies examined cancer cachexia treatment versus a comparator in adults with assessments of appetite and/or dietary intake as study endpoints, a sample size ≥40 and an intervention lasting ≥14 days. Reporting was in line with PRISMA guidance, and a protocol was published in PROSPERO (2022 CRD42022276710). This review is part of a series of systematic reviews examining cachexia endpoints. Of the 5975 articles identified, 116 were eligible for the wider review series and 80 specifically examined endpoints of appetite (65 studies) and/or dietary intake (21 studies). Six trials assessed both appetite and dietary intake. Appetite was the primary outcome in 15 trials and dietary intake in 7 trials. Median sample size was 101 patients (range 40-628). Forty-nine studies included multiple primary tumour sites, while 31 studies involved single primary tumour sites (15 gastrointestinal, 7 lung, 7 head and neck and 2 female reproductive organs). The most frequently reported appetite endpoints were visual analogue scale (VAS) and numerical rating scale (NRS) (40%). The appetite item from the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ) C30/C15 PAL (38%) and the appetite question from North Central Cancer Treatment Group anorexia questionnaire (17%) were also frequently applied. Of the studies that assessed dietary intake, 13 (62%) used food records (prospective registrations) and 10 (48%) used retrospective methods (24-h recall or dietary history). For VAS/NRS, a mean change of 1.3 corresponded to Hedge's g of 0.5 and can be considered a moderate change. For food records, a mean change of 231 kcal/day or 11 g of protein/day corresponded to a moderate change. Choice of endpoint in cachexia trials will depend on factors pertinent to the trial to be conducted. Nevertheless, from trials assessed and available literature, NRS or EORTC QLQ C30/C15 PAL seems suitable for appetite assessments. Appetite and dietary intake endpoints are rarely used as primary outcomes in cancer cachexia. Dietary intake assessments were used mainly to monitor compliance and are not validated in cachexia populations. Given the importance to cachexia studies, dietary intake endpoints must be validated before they are used as endpoints in clinical trials.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.122
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.035
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.122
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0130.014
Bibliometrics0.0170.016
Science and technology studies0.0010.002
Scholarly communication0.0060.004
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.295
GPT teacher head0.532
Teacher spread0.237 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2024
Admission routes1
Has abstractyes

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