A novel method to address the association between received dose intensity and survival outcome: benefits of approaching treatment intensification at a more individualised level in a trial of the European Osteosarcoma Intergroup.


Journal

Cancer chemotherapy and pharmacology
ISSN: 1432-0843
Titre abrégé: Cancer Chemother Pharmacol
Pays: Germany
ID NLM: 7806519

Informations de publication

Date de publication:
05 2019
Historique:
received: 08 11 2018
accepted: 08 02 2019
pubmed: 18 3 2019
medline: 13 2 2020
entrez: 18 3 2019
Statut: ppublish

Résumé

There is lack of consensus on the prognostic value of received high dose intensity in osteosarcoma survivorship. Many studies have not shown a clear survival benefit when dose intensity is increased. The aim of this study is to go beyond chemotherapy intensification by arm-wide escalation of intended dose and/or compression of treatment schedule, while conversely addressing the relationship between treatment intensity and survival at the patient level. The study focusses on the difference in outcome results, based on a novel, progressively more individualised approach to dose intensity. A retrospective analysis of data from MRC BO06/EORTC 80931 randomised controlled trial for treatment of osteosarcoma was conducted. Three types of post hoc patient groups are formed using the intended regimen: the individually achieved cumulative dose and time on treatment, and the increase of individual cumulative dose over time. Event-free survival is investigated and compared in these three stratifications. The strata of intended regimen and achieved treatment yields equivalent results. Received cumulative dose over time produces groups with evident different survivorship characteristics. In particular, it highlights a group of patients with an estimated 3-year event-free survival much larger (more than 10%) than other patient groups. This group mostly contains patients randomised to an intensified regimen. In addition, adverse events reported by that group show the presence of increased preoperative myelotoxicity. The manuscript shows the benefits of analyzing studies by using longitudinal data, e.g. recorded per cycle. This has impact on the drafting of future trials by showing why such a level of detail is needed for both treatment and adverse event data. The novel method proposed, based on cumulative dose received over time, shows that longitudinal treatment data might be used to link survival outcome with drug metabolism. This is particularly valuable when pharmacogenetics data for metabolism of cytotoxic agents are not collected. ISRCTN86294690.

Identifiants

pubmed: 30879111
doi: 10.1007/s00280-019-03797-3
pii: 10.1007/s00280-019-03797-3
pmc: PMC6458990
doi:

Banques de données

ISRCTN
['ISRCTN86294690']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

951-962

Subventions

Organisme : Medical Research Council
ID : MC_U122861384
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_12023/21
Pays : United Kingdom

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Auteurs

Carlo Lancia (C)

Mathematical Institute Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands. c.lancia@math.leidenuniv.nl.

Jakob K Anninga (JK)

Department Paediatric Oncology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.

Matthew R Sydes (MR)

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL and MRC London Hub for Trials Methodology Research, 90 High Holborn, London, WC1V 6LJ, UK.

Cristian Spitoni (C)

Mathematical Institute Utrecht University, Budapestlaan 6, 3584 CD, Utrecht, The Netherlands. c.spitoni@uu.nl.
Department of Epidemiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands. c.spitoni@uu.nl.

Jeremy Whelan (J)

Department of Oncology, University College London Hospital, 235 Euston Rd, Fitzrovia, London, NW1 2BU, UK.

Pancras C W Hogendoorn (PCW)

Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.

Hans Gelderblom (H)

Department of Medical Oncology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.

Marta Fiocco (M)

Mathematical Institute Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands.
Department of Biomedical Data Science, Section Medical Statistics, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.

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Classifications MeSH