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Record W4386466547 · doi:10.1002/jcsm.13321

Physical function endpoints in cancer cachexia clinical trials: Systematic Review 1 of the cachexia endpoints series

2023· review· en· W4386466547 on OpenAlexaff
James McDonald, Judith Sayers, Stefan D. Anker, Jann Arends, Trude R. Balstad, Vickie E. Baracos, Leo R. Brown, Asta Bye, Olav Dajani, Ross D. Dolan, Marie Fallon, Eilidh Fraser, Christine Griel, Aleksandra Grzyb, Marianne Jensen Hjermstad, Mariam Jamal‐Hanjani, Gunnhild Jakobsen, Stein Kaasa, Donald C. McMillan, Matthew Maddocks, Iain Philips, Inger Ottestad, Kieran F. Reid, Mariana S. Sousa, Melanie Rae Simpson, Ola Magne Vagnildhaug, Richard J.E. Skipworth, Tora S. Solheim, Barry Laird

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2023
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
FundersRosetrees TrustNational Institute for Health and Care ResearchCancer Research UK
KeywordsMedicineCachexiaPhysical therapyClinical trialQuality of life (healthcare)Clinical endpointRandomized controlled trialGrip strengthCancerCancer cachexiaPsychological interventionPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

In cancer cachexia trials, measures of physical function are commonly used as endpoints. For drug trials to obtain regulatory approval, efficacy in physical function endpoints may be needed alongside other measures. However, it is not clear which physical function endpoints should be used. The aim of this systematic review was to assess the frequency and diversity of physical function endpoints in cancer cachexia trials. Following a comprehensive electronic literature search of MEDLINE, Embase and Cochrane (1990-2021), records were retrieved. Eligible trials met the following criteria: adults (≥18 years), controlled design, more than 40 participants, use of a cachexia intervention for more than 14 days and use of a physical function endpoint. Physical function measures were classified as an objective measure (hand grip strength [HGS], stair climb power [SCP], timed up and go [TUG] test, 6-min walking test [6MWT] and short physical performance battery [SPPB]), clinician assessment of function (Karnofsky Performance Status [KPS] or Eastern Cooperative Oncology Group-Performance Status [ECOG-PS]) or patient-reported outcomes (physical function subscale of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaires [EORTC QLQ-C30 or C15]). Data extraction was performed using Covidence and followed PRISMA guidance (PROSPERO registration: CRD42022276710). A total of 5975 potential studies were examined and 71 were eligible. Pharmacological interventions were assessed in 38 trials (54%). Of these, 11 (29%, n = 1184) examined megestrol and 5 (13%, n = 1928) examined anamorelin; nutritional interventions were assessed in 21 trials (30%); and exercise-based interventions were assessed in 6 trials (8%). The remaining six trials (8%) assessed multimodal interventions. Among the objective measures of physical function (assessed as primary or secondary endpoints), HGS was most commonly examined (33 trials, n = 5081) and demonstrated a statistically significant finding in 12 (36%) trials (n = 2091). The 6MWT was assessed in 12 trials (n = 1074) and was statistically significant in 4 (33%) trials (n = 403), whereas SCP, TUG and SPPB were each assessed in 3 trials. KPS was more commonly assessed than the newer ECOG-PS (16 vs. 9 trials), and patient-reported EORTC QLQ-C30 physical function was reported in 25 trials. HGS is the most commonly used physical function endpoint in cancer cachexia clinical trials. However, heterogeneity in study design, populations, intervention and endpoint selection make it difficult to comment on the optimal endpoint and how to measure this. We offer several recommendations/considerations to improve the design of future clinical trials in cancer cachexia.

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)0.020
metaresearch head score (Gemma)0.079
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 score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.079
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0140.009
Bibliometrics0.0140.016
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.352
GPT teacher head0.543
Teacher spread0.191 · 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

Citations49
Published2023
Admission routes1
Has abstractyes

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