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Updated: Mar 19, 2026

Modeling Chemotherapy Resistant Leukemia In Vitro
Published on: February 9, 2016
Cost-Effectiveness Model for Chemoimmunotherapy Options in Patients with Previously Untreated Chronic Lymphocytic
Ursula Becker1, Andrew H Briggs2, Santiago G Moreno1
1F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Objectives:
To evaluate the cost-effectiveness of treatment with anti-CD20 monoclonal antibody obinutuzumab plus chlorambucil (GClb) in untreated patients with chronic lymphocytic leukemia unsuitable for full-dose fludarabine-based therapy.
Methods:
A Markov model was used to assess the cost-effectiveness of GClb versus other chemoimmunotherapy options. The model comprised three mutually exclusive health states: "progression-free survival (with/without therapy)", "progression (refractory/relapsed lines)", and "death". Each state was assigned a health utility value representing patients' quality of life and a specific cost value. Comparisons between GClb and rituximab plus chlorambucil or only chlorambucil were performed using patient-level clinical trial data; other comparisons were performed via a network meta-analysis using information gathered in a systematic literature review. To support the model, a utility elicitation study was conducted from the perspective of the UK National Health Service.
Results:
There was good agreement between the model-predicted progression-free and overall survival and that from the CLL11 trial. On incorporating data from the indirect treatment comparisons, it was found that GClb was cost-effective with a range of incremental cost-effectiveness ratios below a threshold of £30,000 per quality-adjusted life-year gained, and remained so during deterministic and probabilistic sensitivity analyses under various scenarios.
Conclusions:
GClb was estimated to increase both quality-adjusted life expectancy and treatment costs compared with several commonly used therapies, with incremental cost-effectiveness ratios below commonly referenced UK thresholds. This article offers a real example of how to combine direct and indirect evidence in a cost-effectiveness analysis of oncology drugs.
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