Evidence map›Paper›PMID 26304904›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2015

Cost-Effectiveness Analysis of Regorafenib for Metastatic Colorectal Cancer.

Daniel A Goldstein, Bilal B Ahmad, Qiushi Chen, Turgay Ayer, David H Howard, Joseph Lipscomb, Bassel F El-Rayes, Christopher R Flowers

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 2 pooled it
6.3field-weighted citation impact, top 2% 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

49 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.

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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.

Daniel A GoldsteinDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA. dgolds8@emory.edu.
Bilal B AhmadDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.
Qiushi ChenDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.
Turgay AyerDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.
David H HowardDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.
Joseph LipscombDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.
Bassel F El-RayesDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.
Christopher R FlowersDaniel A. Goldstein, Bilal B. Ahmad, David H. Howard, Joseph Lipscomb, Bassel F. El-Rayes, and Christopher R. Flowers, Emory University; and Qiushi Chen and Turgay Ayer, Georgia Institute of Technology, Atlanta, GA.

Funding

Translational Physician-Scientist Training Program in OncologyT32CA160040 · NCI · EMORY UNIVERSITY · PI SHIN, DONG M · 2013 to 2017
$1.2M
NCI NIH HHS T32 CA160040NCI NIH HHS T32CA160040
6 · The paper itself

Abstract

purposeRegorafenib is a standard-care option for treatment-refractory metastatic colorectal cancer that increases median overall survival by 6 weeks compared with placebo. Given this small incremental clinical benefit, we evaluated the cost-effectiveness of regorafenib in the third-line setting for patients with metastatic colorectal cancer from the US payer perspective.

methodsWe developed a Markov model to compare the cost and effectiveness of regorafenib with those of placebo in the third-line treatment of metastatic colorectal cancer. Health outcomes were measured in life-years and quality-adjusted life-years (QALYs). Drug costs were based on Medicare reimbursement rates in 2014. Model robustness was addressed in univariable and probabilistic sensitivity analyses.

resultsRegorafenib provided an additional 0.04 QALYs (0.13 life-years) at a cost of $40,000, resulting in an incremental cost-effectiveness ratio of $900,000 per QALY. The incremental cost-effectiveness ratio for regorafenib was > $550,000 per QALY in all of our univariable and probabilistic sensitivity analyses.

conclusionRegorafenib provides minimal incremental benefit at high incremental cost per QALY in the third-line management of metastatic colorectal cancer. The cost-effectiveness of regorafenib could be improved by the use of value-based pricing.

Indexed as

AdultAgedAntineoplastic AgentsColorectal NeoplasmsControlled Clinical Trials as TopicCost-Benefit AnalysisDrug CostsFemaleHumansMaleMarkov ChainsMedicareMiddle AgedPhenylurea CompoundsPyridinesQuality-Adjusted Life YearsAntineoplastic AgentsPhenylurea CompoundsPyridinesregorafenib

Identifiers

PMID26304904
PMCPMC4737857
OpenAlexW2113720307

What OpenQuestion holds

Textmetadata
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.