A Non-Parametric Approach for Jointly Combining Evidence on Progression Free and Overall Survival Time in Network Meta-Analysis

Autor/inn/en	Daly, Caitlin H.; Maconachie, Ross; Ades, A. E.; Welton, Nicky J.
Titel	A Non-Parametric Approach for Jointly Combining Evidence on Progression Free and Overall Survival Time in Network Meta-Analysis
Quelle	In: Research Synthesis Methods, 13 (2022) 5, S.573-584 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Daly, Caitlin H.) ORCID (Ades, A. E.) ORCID (Welton, Nicky J.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1759-2879
DOI	10.1002/jrsm.1539
Schlagwörter	Nonparametric Statistics; Randomized Controlled Trials; Evidence; Networks; Meta Analysis; Cancer; Synthesis; Correlation; Models; Health + Suchen Sie Ihr Suchwort? Evidenz; Meta-analysis; Metaanalyse; Carcinoma; Karzinom; Krebs (med); Krebserkrankung; Korrelation; Analogiemodell; Gesundheit
Abstract	Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and treatments. Furthermore, PFS and OS are not independent; OS is the sum of PFS and post-progression survival (PPS). Our aim was to develop a non-parametric approach for jointly synthesising evidence from published Kaplan-Meier survival curves of PFS and OS without assuming proportional hazards. Restricted mean survival times (RMST) are estimated by the area under the survival curves (AUCs) up to a restricted follow-up time. The correlation between AUCs due to the constraint that OS > PFS is estimated using bootstrap re-sampling. Network meta-analysis models are given for RMST for PFS and PPS and ensure that OS = PFS + PPS. Both additive and multiplicative network meta-analysis models are presented to obtain relative treatment effects as either differences or ratios of RMST. The methods are illustrated with a network meta-analysis of treatments for stage IIIA-N2 non-small cell lung cancer. The approach has implications for health economic models of cancer treatments, which require estimates of the mean time spent in the PFS and PPS health-states. The methods can be applied to a single time-to-event outcome, and so have wide applicability in any field where time-to-event outcomes are reported, the proportional hazards assumption is in doubt, and survival curve shapes differ across studies and interventions. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01