Biomarker endpoints in cancer cachexia clinical trials: Systematic Review 5 of the cachexia endpoint series.
Yule, MS
Thompson, J
Leesahatsawat, K
Sousa, MS
Anker, SD
Arends, J
Balstad, TR
Brown, LR
Bye, A
Dajani, O
Fallon, M
Hjermstad, MJ
Jakobsen, G
McDonald, J
McGovern, J
Roeland, EJ
Sayers, J
Skipworth, RJE
Ottestad, IO
Philips, I
Simpson, MR
Solheim, TS
Vagnildhaug, OM
McMillan, D
Laird, BJA
Dolan, RD
Cancer Cachexia Endpoints Working Group,
- Publisher:
- WILEY
- Publication Type:
- Journal Article
- Citation:
- J Cachexia Sarcopenia Muscle, 2024, 15, (3), pp. 853-867
- Issue Date:
- 2024-06
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Yule, MS | |
dc.contributor.author | Thompson, J | |
dc.contributor.author | Leesahatsawat, K | |
dc.contributor.author | Sousa, MS | |
dc.contributor.author | Anker, SD | |
dc.contributor.author | Arends, J | |
dc.contributor.author | Balstad, TR | |
dc.contributor.author | Brown, LR | |
dc.contributor.author | Bye, A | |
dc.contributor.author | Dajani, O | |
dc.contributor.author | Fallon, M | |
dc.contributor.author | Hjermstad, MJ | |
dc.contributor.author | Jakobsen, G | |
dc.contributor.author | McDonald, J | |
dc.contributor.author | McGovern, J | |
dc.contributor.author | Roeland, EJ | |
dc.contributor.author | Sayers, J | |
dc.contributor.author | Skipworth, RJE | |
dc.contributor.author | Ottestad, IO | |
dc.contributor.author | Philips, I | |
dc.contributor.author | Simpson, MR | |
dc.contributor.author | Solheim, TS | |
dc.contributor.author | Vagnildhaug, OM | |
dc.contributor.author | McMillan, D | |
dc.contributor.author | Laird, BJA | |
dc.contributor.author | Dolan, RD | |
dc.contributor.author | Cancer Cachexia Endpoints Working Group, | |
dc.date.accessioned | 2024-08-06T01:42:33Z | |
dc.date.available | 2024-05-06 | |
dc.date.available | 2024-08-06T01:42:33Z | |
dc.date.issued | 2024-06 | |
dc.identifier.citation | J Cachexia Sarcopenia Muscle, 2024, 15, (3), pp. 853-867 | |
dc.identifier.issn | 2190-5991 | |
dc.identifier.issn | 2190-6009 | |
dc.identifier.uri | http://hdl.handle.net/10453/180050 | |
dc.description.abstract | Regulatory agencies require evidence that endpoints correlate with clinical benefit before they can be used to approve drugs. Biomarkers are often considered surrogate endpoints. In cancer cachexia trials, the measurement of biomarkers features frequently. The aim of this systematic review was to assess the frequency and diversity of biomarker endpoints in cancer cachexia trials. A comprehensive electronic literature search of MEDLINE, Embase and Cochrane (1990-2023) was completed. Eligible trials met the following criteria: adults (≥18 years), prospective design, more than 40 participants, use of a cachexia intervention for more than 14 days and use of a biomarker(s) as an endpoint. Biomarkers were defined as any objective measure that was assayed from a body fluid, including scoring systems based on these assays. Routine haematology and biochemistry to monitor intervention toxicity were not considered. Data extraction was performed using Covidence, and reporting followed PRISMA guidance (PROSPERO: CRD42022276710). A total of 5975 studies were assessed, of which 52 trials (total participants = 6522) included biomarkers as endpoints. Most studies (n = 29, 55.7%) included a variety of cancer types. Pharmacological interventions (n = 27, 51.9%) were most evaluated, followed by nutritional interventions (n = 20, 38.4%). Ninety-nine different biomarkers were used across the trials, and of these, 96 were assayed from blood. Albumin (n = 29, 55.8%) was assessed most often, followed by C-reactive protein (n = 22, 42.3%), interleukin-6 (n = 16, 30.8%) and tumour necrosis factor-α (n = 14, 26.9%), the latter being the only biomarker that was used to guide sample size calculations. Biomarkers were explicitly listed as a primary outcome in six trials. In total, 12 biomarkers (12.1% of 99) were used in six trials or more. Insulin-like growth factor binding protein 3 (IGFBP-3) and insulin-like growth factor 1 (IGF-1) levels both increased significantly in all three trials in which they were both used. This corresponded with a primary outcome, lean body mass, and was related to the pharmacological mechanism. Biomarkers were predominately used as exploratory rather than primary endpoints. The most commonly used biomarker, albumin, was limited by its lack of responsiveness to nutritional intervention. For a biomarker to be responsive to change, it must be related to the mechanism of action of the intervention and/or the underlying cachexia process that is modified by the intervention, as seen with IGFBP-3, IGF-1 and anamorelin. To reach regulatory approval as an endpoint, the relationship between the biomarker and clinical benefit must be clarified. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | WILEY | |
dc.relation.ispartof | J Cachexia Sarcopenia Muscle | |
dc.relation.isbasedon | 10.1002/jcsm.13491 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 0606 Physiology, 1103 Clinical Sciences, 1106 Human Movement and Sports Sciences | |
dc.subject.classification | 3202 Clinical sciences | |
dc.subject.classification | 4201 Allied health and rehabilitation science | |
dc.subject.classification | 4207 Sports science and exercise | |
dc.subject.mesh | Cachexia | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Neoplasms | |
dc.subject.mesh | Biomarkers | |
dc.subject.mesh | Clinical Trials as Topic | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Neoplasms | |
dc.subject.mesh | Cachexia | |
dc.subject.mesh | Clinical Trials as Topic | |
dc.subject.mesh | Biomarkers | |
dc.title | Biomarker endpoints in cancer cachexia clinical trials: Systematic Review 5 of the cachexia endpoint series. | |
dc.type | Journal Article | |
utslib.citation.volume | 15 | |
utslib.location.activity | Germany | |
utslib.for | 0606 Physiology | |
utslib.for | 1103 Clinical Sciences | |
utslib.for | 1106 Human Movement and Sports Sciences | |
pubs.organisational-group | University of Technology Sydney | |
pubs.organisational-group | University of Technology Sydney/Faculty of Health | |
pubs.organisational-group | University of Technology Sydney/Faculty of Health/IMPACCT | |
pubs.organisational-group | University of Technology Sydney/All Manual Groups | |
pubs.organisational-group | University of Technology Sydney/All Manual Groups/Improving Palliative, Aged and Chronic Care through Clinical Research and Translation (IMPACCT) | |
utslib.copyright.status | open_access | * |
dc.rights.license | This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/ | |
dc.date.updated | 2024-08-06T01:42:30Z | |
pubs.issue | 3 | |
pubs.publication-status | Published | |
pubs.volume | 15 | |
utslib.citation.issue | 3 |
Abstract:
Regulatory agencies require evidence that endpoints correlate with clinical benefit before they can be used to approve drugs. Biomarkers are often considered surrogate endpoints. In cancer cachexia trials, the measurement of biomarkers features frequently. The aim of this systematic review was to assess the frequency and diversity of biomarker endpoints in cancer cachexia trials. A comprehensive electronic literature search of MEDLINE, Embase and Cochrane (1990-2023) was completed. Eligible trials met the following criteria: adults (≥18 years), prospective design, more than 40 participants, use of a cachexia intervention for more than 14 days and use of a biomarker(s) as an endpoint. Biomarkers were defined as any objective measure that was assayed from a body fluid, including scoring systems based on these assays. Routine haematology and biochemistry to monitor intervention toxicity were not considered. Data extraction was performed using Covidence, and reporting followed PRISMA guidance (PROSPERO: CRD42022276710). A total of 5975 studies were assessed, of which 52 trials (total participants = 6522) included biomarkers as endpoints. Most studies (n = 29, 55.7%) included a variety of cancer types. Pharmacological interventions (n = 27, 51.9%) were most evaluated, followed by nutritional interventions (n = 20, 38.4%). Ninety-nine different biomarkers were used across the trials, and of these, 96 were assayed from blood. Albumin (n = 29, 55.8%) was assessed most often, followed by C-reactive protein (n = 22, 42.3%), interleukin-6 (n = 16, 30.8%) and tumour necrosis factor-α (n = 14, 26.9%), the latter being the only biomarker that was used to guide sample size calculations. Biomarkers were explicitly listed as a primary outcome in six trials. In total, 12 biomarkers (12.1% of 99) were used in six trials or more. Insulin-like growth factor binding protein 3 (IGFBP-3) and insulin-like growth factor 1 (IGF-1) levels both increased significantly in all three trials in which they were both used. This corresponded with a primary outcome, lean body mass, and was related to the pharmacological mechanism. Biomarkers were predominately used as exploratory rather than primary endpoints. The most commonly used biomarker, albumin, was limited by its lack of responsiveness to nutritional intervention. For a biomarker to be responsive to change, it must be related to the mechanism of action of the intervention and/or the underlying cachexia process that is modified by the intervention, as seen with IGFBP-3, IGF-1 and anamorelin. To reach regulatory approval as an endpoint, the relationship between the biomarker and clinical benefit must be clarified.
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