Evidence map›Paper›PMID 26783469›Full record

ArticleLeukemia research and treatment2015

Effectiveness and Cost-Effectiveness of Sequential Treatment of Patients with Chronic Myeloid Leukemia in the United States: A Decision Analysis.

Ursula Rochau, Martina Kluibenschaedl, David Stenehjem, Kuo Kuan-Ling, Jerald Radich, Gary Oderda, Diana Brixner, Uwe Siebert

Open access · hybridAbstract read
In one paragraph

Article in Leukemia research and treatment, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.

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  11. Balancing patient value and payer cost in hematologic malignancies: can it be done?Expert review of pharmacoeconomics & outcomes research · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Ursula RochauInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, 6060 Hall in Tirol, Austria; Area Health Technology Assessment, ONCOTYROL-Center for Personalized Cancer Medicine, Karl-Kapferer-Straße 5, 6020 Innsbruck, Austria.
Martina KluibenschaedlInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, 6060 Hall in Tirol, Austria.
David StenehjemDepartment of Pharmacotherapy, University of Utah, 30 South 2000, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah Hospitals & Clinics, 2000 Circle of Hope, Salt Lake City, UT 84112, USA.
Kuo Kuan-LingDepartment of Pharmacotherapy, University of Utah, 30 South 2000, Salt Lake City, UT 84112, USA.
Jerald RadichClinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N, Seattle, WA 98104, USA.
Gary OderdaDepartment of Pharmacotherapy, University of Utah, 30 South 2000, Salt Lake City, UT 84112, USA.
Diana BrixnerInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, 6060 Hall in Tirol, Austria; Area Health Technology Assessment, ONCOTYROL-Center for Personalized Cancer Medicine, Karl-Kapferer-Straße 5, 6020 Innsbruck, Austria; Department of Pharmacotherapy, University of Utah, 30 South 2000, Salt Lake City, UT 84112, USA; Program in Personalized Health, University of Utah, 15 North 2030 East, Room 2110, Salt Lake City, UT 84112, USA.
Uwe SiebertInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, 6060 Hall in Tirol, Austria; Area Health Technology Assessment, ONCOTYROL-Center for Personalized Cancer Medicine, Karl-Kapferer-Straße 5, 6020 Innsbruck, Austria; Center for Health Decision Science, Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, 718 Huntington Avenue, Boston, MA 02215, USA; Institute for Technology Assessment, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac Street, Boston, MA 02114, USA.
University of Utah · USUMIT - Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik · ATFred Hutch Cancer Center · USHarvard University · USUniversity of Utah Hospital · US

Funding

VIRUS-MEDIATED MYELOSUPPRESSIONP01CA018029 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Geoffrey Roger HILL · 1985 to 2026
$128.4M
NCI NIH HHS P01 CA018029
6 · The paper itself

Abstract

Currently several tyrosine kinase inhibitors (TKIs) are approved for treatment of chronic myeloid leukemia (CML). Our goal was to identify the optimal sequential treatment strategy in terms of effectiveness and cost-effectiveness for CML patients within the US health care context. We evaluated 18 treatment strategies regarding survival, quality-adjusted survival, and costs. For model parameters, the literature data, expert surveys, registry data, and economic databases were used. Evaluated strategies included imatinib, dasatinib, nilotinib, bosutinib, ponatinib, stem-cell transplantation (SCT), and chemotherapy. We developed a Markov state-transition model, which was analyzed as a cohort simulation over a lifelong time horizon with a third-party payer perspective and discount rate of 3%. Remaining life expectancies ranged from 5.4 years (3.9 quality-adjusted life years (QALYs)) for chemotherapy treatment without TKI to 14.4 years (11.1 QALYs) for nilotinib→dasatinib→chemotherapy/SCT. In the economic evaluation, imatinib→chemotherapy/SCT resulted in an incremental cost-utility ratio (ICUR) of $171,700/QALY compared to chemotherapy without TKI. Imatinib→nilotinib→chemotherapy/SCT yielded an ICUR of $253,500/QALY compared to imatinib→chemotherapy/SCT. Nilotinib→dasatinib→chemotherapy/SCT yielded an ICUR of $445,100/QALY compared to imatinib→nilotinib→chemotherapy/SCT. All remaining strategies were excluded due to dominance of the clinically superior strategies. Based on our analysis and current treatment guidelines, imatinib→nilotinib→chemotherapy/SCT and nilotinib→dasatinib→chemotherapy/SCT can be considered cost-effective for patients with CML, depending on willingness-to-pay.

Identifiers

PMID26783469
PMCPMC4689963
OpenAlexW2266168940

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.