Joint modeling of longitudinal health-related quality of life (HRQoL) data and survival.

Authors

null

Divine Ewane Ediebah

European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium

Divine Ewane Ediebah , Francisca Galindo-Garre , Bernard M.J. Uitdehaag , Jolie Ringash , Jaap C. Reijneveld , Linda Dirven , Efstathios Zikos , Corneel Coens , Martin J. Van Den Bent , Andrew Bottomley , Martin J.B. Taphoorn

Organizations

European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium, VU University Medical Center, Amsterdam, Netherlands, Princess Margaret Cancer Center, Toronto, ON, Canada, VU University Medical Center/Department of Neurology, Academic Medical Center, The Hague, Netherlands, Erasmus University Medical Center, Rotterdam, Netherlands, Medical Center Haaglanden, The Hague, Netherlands

Research Funding

NIH

Background: In cancer clinical trials, several outcome measures may co-vary. Both treatment itself and treatment-related impairment of health-related quality of life (HRQoL) may affect survival. When these effects are analyzed separately, bias may arise. Therefore, our aim is to investigate the combined effect of treatment and longitudinally measured HRQoL on survival. Methods: We analyzed data from an EORTC randomized clinical trial (RCT) of 288 patients with anaplastic oligodendrogliomas who received radiotherapy (RT) alone or RT plus procarbazine, lomustine and vincristine (PCV) chemotherapy. HRQoL was assessed with the EORTC QLQ-C30 and Brain Cancer Module, at baseline, at the end of RT, and then every 3 to 6 months until progression. The appetite loss (AP) scale was pre-selected as the primary HRQoL endpoint, because this scale was previously found to be significantly different between the two treatment arms. Joint modeling was used to assess the combined effect of treatment and treatment-related AP on survival. The hazard ratios (HRs) for treatment effect were calculated using three different modeling strategies: Cox model with treatment only (model 1 [M1]), Cox model with treatment and time-dependent AP score (model 2 [M2]) and the joint model (model 3 [M3]). Results: In general, treatment with RT plus PCV chemotherapy resulted in decreased risk of death compared to RT alone. Estimated HR for treatment was 0.76 (95% CI 0.58–1.00) for M1, 0.72 (0.55–0.96) for M2 and 0.69 (0.52–0.92) for M3. This corresponds to a lower risk of death of 24% in M1, 28% in M2 and 31% in M3, for patients treated with RT plus PCV chemotherapy. Treatment-related AP resulted in increased risk of death, with estimated HR of 1.06 (1.01–1.12) for M2 and 1.13 (1.03–1.23) for M3. This translates to a 13% increased risk of death in M3 as compared to 6% increased risk of death in M2 for every 10-points increase of AP. Conclusions: Our findings suggest that part of the survival benefit of treatment with RT plus PCV chemotherapy can be masked by the negative effect that this treatment has on patients’ HRQoL. In our study, up to 7% of the theoretical treatment efficacy was lost through increased AP affecting survival. Clinical trial information: NCT00002840.

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Abstract Details

Meeting

2014 ASCO Annual Meeting

Session Type

Poster Highlights Session

Session Title

Central Nervous System Tumors

Track

Central Nervous System Tumors

Sub Track

Central Nervous System Tumors

Clinical Trial Registration Number

NCT00002840

Citation

J Clin Oncol 32:5s, 2014 (suppl; abstr 2034)

DOI

10.1200/jco.2014.32.15_suppl.2034

Abstract #

2034

Poster Bd #

25

Abstract Disclosures